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All right. We're going to get started with our next session. Very pleased to have Patrick Stokes with us for our next fireside chat. Patrick, of course, is President and CMO of Salesforce, has nearly 20 years of experience in product leadership roles. That includes the last 15 or so at Salesforce. Patrick, thanks so much for being here.

Thanks for having me. Really appreciate it.

My pleasure. So just by way of getting everything started, it'd be helpful if you could outline for us your primary responsibilities and focus areas at Salesforce.

Sure. Happy to. Well, I'm exactly who you all want to talk to. I'm the Chief Marketing Officer at Salesforce. I've had a bit of an interesting journey. So I've been at the company for about 15 years, longer than most, not quite as long as some. Most of my career has been on the engineering and product side. I started as an engineer, moved into product kind of 10 years in product at Salesforce. I ran our platform, and then moved over to marketing about 2 years ago, 2.5 years ago, right, when all the AI stuff really kicked off, I didn't quite know it at the time and then the whole world changed, which was difficult. And then about 4 months ago moved into the CMO position.

Fantastic. So you're coming off of a solid Q1 in which Salesforce impressed with Agentforce disclosures, of which there were several, and you reiterated confidence in second half revenue acceleration as well. So maybe just briefly recap for us what you personally viewed as most important or instrumental kind of out of the last quarter.

Yes. Well, certainly, we're very excited about the continued growth in Agentforce. I think $1.2 billion now on the Agentforce side, up from, I believe, $800 million. So we're very, very excited about that. We're starting to see customers reach real scale on that with some pretty sophisticated use cases. I'm also equally excited about the AWU growth. We're certainly seeing our own token consumption from.

And that's agentic work units.

Agentic work units, yes. And this is this idea of tokens in and out, that's effectively a measure of reasoning or a measure of intelligence, but it's not a measure of actual work getting done. And so we thought it was important for the market and really -- and the technology sector as a whole to kind of have a way to measure actual work getting done by these pieces of intelligence. So we introduced that in Q4 and I was very excited to see that continuing to grow alongside token growth, of course. Interesting watching the 2 of them kind of grow at -- each of them kind of picks up pace at certain moments in time.

It's also really interesting looking at the AWUs kind of across different industries and different segments, you can start to see where different usage patterns are emerging. And then lastly, I would say, I was very, very excited about our Headless launch, which we did not that long ago, in March, I think it was at TDX, our developer conference. And I'm very excited about what that means for Salesforce and the reaction to it we're seeing from our customers. So really opened up kind of a new way of thinking about our role in this agentic era.

All right. That's great. I definitely want to dive more into Headless in a few moments. But let's stick with Agentforce because I think it's important to understand what's underpinning the growth that you were just talking about. So there were a lot of announcements around Agentforce, I would say, dating back to Dreamforce last October. Many other improvements have since been unveiled as well. But how would you characterize the agentic capabilities of Agentforce today? And what are the most important enhancements to both the tech and the ecosystem, right, over the last 6 to 9 months that are really enabling your customers to unlock more value?

Yes. I mean I think the 2 biggest advancements in the last, let's call it, 6 months or so on the Agentforce side are one, something that we call Agentforce Script, which is, if you start building an agent, you get very excited early on because you're, like, all I have to do is write human instructions and like I've coded my agent. They're effectively -- if I'm being very reductive, they're effectively just prompts under the covers. And so anybody can write those. But what you realize when you're starting to try to get agents to do multi-step and complex workflows is you have a lot of like do this, but unless this happens, then do this and you start writing it like that and the agent gets very, very, very confused very, very quickly.

And the irony of like programming languages is that's effectively what they are, if this, then that types of flows. And so we pioneered this way to kind of put little micro moments of scripting into the prompt so that you could eliminate some of the probabilistic problems of working with an LLM. You've all seen this, you ask it a question and then you ask it the same question, you get 2 different answers. So it's a probabilistic nondeterministic system. When you're trying to execute workflows, you don't want that, you want deterministic. You want do it the way I've asked you to do it every single time. And so Agentforce helps you with that. And that's been a big unlock for our customers that are trying to either do this at scale or do it in regulated environments, do it with certain policies that they need to make sure the agent is following.

And then the second, I would say, is voice for sure. Voice is very, very exciting for our customers and it was a pretty significant computer science project for us to get that working well. Voice is a tricky thing because there's humans and people have different ways of talking and there's interruptions and latency and all of these things that you kind of don't think of until you actually start trying to build it and you're like, oh, this is actually pretty damn hard.

Yes. And there are, Patrick, several CCaaS incumbents, right, that have had existing solutions for a while. How do you think about where Agentforce voice stacks up at this stage?

Yes. I mean, I think we're in pretty good shape. If you had asked me 3 months ago, I would say we probably have work to do. But I think at the moment, we're now running Salesforce, our 1-800 number on Agentforce voice. You can call it now and you'll talk to Agentforce. And we have other customers doing the same. I think over -- we'll probably be sitting here with our Q2 earnings after talking about the big kind of scaled voice customers, just like we are the kind of chat customers with Agentforce.

Okay. Super interesting. And then one other comment on Agentforce. We started to hear of some forward-thinking customers that, I would say, are deploying multi-cloud Agentforce use cases. So they might extend from Service Cloud to Sales Cloud or you're doing case resolution in Service Cloud and that triggers a campaign in Marketing Cloud. Is this something that you're really kind of seeing as well? And is your go-to-market aligned enough, frankly, to be able to sell more holistically in this way?

Yes, good question. I mean it's funny. The first part of your question is like, we saw that from the very beginning. There really isn't a usage of Salesforce that doesn't cut across. The platform is actually quite a bit more like [indiscernible] together than you think that it is from a pure usage perspective. From a buying perspective, it's maybe a little bit more discrete. You have sales service, et cetera, et cetera. So those -- as soon as you start using Agentforce, you immediately get into scenarios where you're like, okay, I'm going to use it to try to qualify a lead. But then I want to put those leads into a marketing campaign. You just -- you immediate -- or service, I'm going to use it for case resolution, but I need to know if there's an open opportunity because I'm going to handle my case resolution in a different way. So there's tons of those types of use cases.

What we've tried to do is make it easier to buy that. So this is what our kind of top end additions like we call it internally A for X, so Agentforce for sales and commerce service, et cetera, they kind of come with the entirety of the platform. It's like here it all is, go implement your agent and so you're not kind of buying individual piece parts.

Okay. Great. And then maybe just to sort of zoom out a bit, I think what a lot of investors in this room and elsewhere are wondering is like when will the rubber hit the road, right, when it comes to enterprises, meaningfully deploying Agentforce in production and at scale. Certainly, we know that some have gotten to that level, right? But it just comes down to more broad adoption in that capacity.

Yes. I think your second part there kind of got it. I think certainly, we are seeing many, many, many hundreds of customers reach meaningful scale, either scale from a usage perspective, in some cases, simple use cases, but that are being interacted with by hundreds of thousands or millions of individual kind of consumers on the other side, customers like Southwest, who are now kind of doing 20% to 30% of all of their inbound requests from customers with Agentforce. So it's like the curve of sophistication of the interaction and then volume. And so there may be kind of lower on sophistication, but very, very high on volume. And then you have other customers that are very, very high on sophistication and maybe a little bit lower on volume as they experiment.

So we're seeing kind of all ends of that spectrum. But I think the real basis of your question is, okay, Patrick, but like when is everybody going to be doing that? When is [ 187,000 ] of your customers, they're all going to be doing that?

Or at least a very significant percentage.

At least a very significant percentage. I think we're definitely nearing that. It's certainly part of how we think about H2 and accelerating the business. That's kind of all factored into that. So I definitely think you're going to start to see a rapid acceleration as the product gets easier to use, as the CIOs start to kind of trust what we've built and that also means in a way, I have to be careful how I say this, but in a way, given up on what they've tried to DIY, right? It's kind of like the cloud in the early days where everybody went out and tried to build their own cloud. And you could look at it and say, what are you doing? And what they're doing is they're creating intuition of what it takes to do it.

And then that's putting us in a better position because now they come with that intuition and they go, okay, you've actually solved the problems that I ran into and maybe didn't want to solve. And so we're definitely starting to see a lot more kind of openness to the platform from CIOs than maybe we were 6, 12 months ago when everything was so new, they were all just trying to figure it out.

Okay. Yes, super encouraging. And of course, just maybe to sort of stay with this train of thought. I mean the big fear out there remains that AI and specifically the Frontier labs, right, that they will drive significant disruption and deceleration in the Salesforce business. Why is that view incorrect?

Well, I mean, there's the data side of it, and then there's the subjective side. I mean the data side shows that it's not correct at the moment. Our seats are still growing. Our businesses -- our core businesses are still growing, and we're very happy with the growth. But also when you look into the AI labs, this is what's most fascinating to me. And many of these labs are run by -- have people in the go-to-market organization that we know, they're all using Salesforce extensively, in fact, more than some of our biggest customers. And the reason that is, is because these AI labs, what they're doing is they're not using Salesforce the same way customers have for the last 20 years.

They're not using it as a UI. They're not logging into it every day and logging a call and an opportunity. They're using it through their own agentic interface through Claude Enterprise or through Codex. They're hooking it up with MCP. This is how Headless comes into play. And that's how they're using Salesforce. So what we're seeing is there's actually an expansion of usage and expansion of consumption. That's separate from the whole seat conversation is kind of a separate one, which I'm sure you'll hit on. But just if you separate that for a moment, the existing seats this new way of working with Salesforce, we're seeing usage spike up quite a bit. And so that's very, very encouraging for us.

Okay. Terrific. And yes, that was a perfect segue to Headless. So I do think the Headless 360 announcement, Patrick, just seems like a really clever and interesting way to drive stronger connections to your point, with the Frontier AI models, also opening up the Salesforce platform to external AI agents and coding tools via MCP as you also highlighted. One other thing I would add is just also reducing friction, just making Salesforce easier for developers to use. So I guess, is there anything -- is that a fair characterization? Anything else that you would sort of highlight as part of this?

Yes, definitely a fair characterization. I mean the inspiration for Headless came from just watching people use Salesforce in a different way. We have these partnerships with the AI labs and we're watching them use and we can see the API data. We can see that their consumption is through the roof, but like they're using it through Slack, for example, the AI labs are all big giant Slack users or they're using it through their own Claude interface. But we are also seeing it just in the -- this is a very, very hot kind of space right now. So you go to X or you go to Reddit, and it's just like an army or you go to these Discord channels where all these developers hang out. And there's just these constant kind of sets of conversations of people trying to figure this out.

There's something that I think people can sense where they're like, there's a new way to work. I think that's what they're sensing that there's going to be a way to work that all of the friction of going to all of these discrete applications that have been purpose-built for the function that I do, that's going to go away and it's going to be replaced by a new interface that interacts with kind of the underlying capability of those discrete applications.

So the applications aren't going to go away, but the UI is going to be massively disrupted. And so we started to see that pattern emerging, and that was the inspiration. It's just like, okay, well, that's what customers want and many other companies kind of in our space saw it as well and they were like, we don't want that. We're terrified. We don't want to lose our users. We don't want to lose the UI, and we just took the exact opposite approach and said, no, we endorse it. Let's open this up. We're going to have to figure out how to monetize it, which is something that we're talking a lot about, and I'm sure is very relevant for all of you, but the pattern itself is really a no-brainer. And that's why I think it's so exciting.

I think that you saw a very positive sentiment, which we were all very excited about. It's been a couple of months of the SaaS [indiscernible]. And so kind of getting back in front with a message of like, no, no, guys, we see this. We understand what it is you're trying to do and we want to actually enable that and endorse that. We think that, that is the future. I think it was a little bit of a reset moment for us.

Okay. And clearly, it sounds like a mechanism that put Salesforce more directly in the token path.

Absolutely. Well, I mean when you look at these tokens, tokens represent intelligence, as I said earlier, and right now, by far, the single biggest use case for consuming tokens is coding, right? That's -- it's the killer app. One engineer can generate like $100,000 a month bill without much problem. Now you can debate whether that's highly efficient or not. But they're making -- these labs are making a lot of money on these tokens.

There will probably be some sort of normalization or reckoning of that. Right now, everybody is just like everybody code. And so people are -- you hear these stories of people taking their -- blah, blah, blah. So there's going to be a normalization. But what the AI labs are -- we think that they're looking for is, well, what's the next killer app? What's the next killer use case? And that's where we think Salesforce is perfectly positioned because we think it's knowledge work. We think it's people like you every day that are showing up and having meetings and analyzing things and making decisions, you have to access information and you want to be able to access information in a way that's low friction, and then you want to be able to connect that to the intelligence of the AI, and that's effectively what we can provide.

Okay. Terrific. And then you alluded to this, Patrick, we know there has not been an official decision on Headless 360 pricing, but maybe you could just sort of speak to some of the early considerations and how that monetization might present itself for Salesforce.

Yes. I mean, so there's kind of 2 arms to the puzzle. One, there's actually quite a few very important technology decisions that we need to make in terms of how do we ask people that are building agents outside of our platform to identify those agents to us in the same way that they identify a user to us, and that's important to solve because that provides the layer of kind of governance and licensing and permissioning that we need to put for the agent to exist and consume from Salesforce in the first place.

So there's a number of technology decisions there, many of which will almost certainly result in some sort of agent user license showing up. So just like we have human licenses, we'll likely have agent licenses as well where you have to self identify the agents that you run on top of Salesforce.

Now that sounds like if you're in Salesforce at least where we have this 25-year legacy of seat-based pricing that sounds like the answer. Okay, great. So we're going to charge for the agent licenses, that's possible, but we're trying to be as thoughtful as we can on this and make sure that our own kind of legacy bias on that doesn't come in too much. We're trying to be very kind of forward in the way that we think about it. But really, what we're doing is we're talking to our customers and our partners. And we're going to them right now and we're saying, look, blank slate, here's your contract. Imagine that you could just rewrite your contract right now and have whatever unlimited usage of Headless that you want for the environment that you're trying to create. You tell us what that contract would look like. And that's -- those are the conversations we're having with our customers right now to make sure that we can do it thoughtfully.

What we don't want to do what you can feel in the room, I feel it in every room and especially rooms like this is you all want to know the pricing model so you can model our future growth. And we want you to be able to do that as well, but we want to make sure that we don't give you something that turns out to be wrong and then we have the wrong model. So that's why we're being careful here.

Yes, it makes perfect sense. And the other thing, which I don't know how much of this you guys have thought through, right? But if I think back to the early instantiations of Agentforce pricing, right, where -- and this is a very different world, right, because everyone was trying to figure it out.

Like 6 months ago.

Everything is [indiscernible]. So -- but initially, it's per conversation pricing and then it was per action. And then we got to the point of having sort of discrete subscriptions, right, then we have the Agentforce 1 Editions and then you had AELA, right, where you have Agentforce ELAs for customers that are willing to make very, very big commits. So I guess the question here is, is the bias from your perspective, and I won't hold you to it, I realize it's early stages, but to sort of give customers some choice, but maybe to not make it overly complicated, which some may argue was maybe an initial impediment to Agentforce adoption, again, in the very early innings before you kind of were able to work through all that.

I think that's a very fair characterization or criticism, whatever you want to call it. Yes, I think there's like a Goldilocks type of scenario that we haven't totally found yet. When we first started with Agentforce, it was something that was brand new, and customers didn't know what to expect. So they wanted a consumption model. And so we gave them a consumption model, but it turns out that is a very complicated consumption model. And so it's very, very difficult to kind of predict. It was hard enough to predict their own usage because they didn't really know how they were going to use it at the time.

And then even if they could predict their own usage, it was hard to turn that usage into to understand the commercials of it because our consumption side was so difficult. So we made it easier. We're like, okay, what if you just bought the AELA and then you don't worry about it, like use as much as you want and don't worry about it. And customers like that as well because it's simple, but it's also very expensive. It's more expensive than -- so it's -- you kind of have to pick your [ evil ] but that's not what we want. We don't want the customer to have to pick their [ evil ]. We want to get them to something that they can really trust and believe in. And I think we're seeing other models emerge outside of Salesforce that are interesting. And I think what this comes down to is it's not really about what benefits us. It's we want to find a model that benefits our customer. And so we're going to experiment with as many models as we can. The downside to that is it looks like we're confusing the market, which I get, like how many pricing models do you have? And how do we measure this? But we're -- our approach is like, yes, that's a moment in time, and we kind of just need you to trust us on this. We're going to figure it out. We're going to do it with our customers, and we're going to find the right thing to do.

Okay. Very helpful. Yes. Thanks, Patrick. And while we're on the topic, so last week, Salesforce announced the acquisition of Contentful, which has a CMS content management system. Can you expand on kind of what this IP will help Salesforce accomplish?

Yes. Well, first of all, so the interesting thing about Contentful is that it's effectively a headless-first platform. So they didn't spend a great deal of time worrying about what the UI for content could look like. Because if you think about content, it's really just like a feature of a campaign, which is a feature of marketing. So the SaaS era has created just like this massive sprawl of these purpose-built applications, and that's especially true in marketing. If you look at the LUMAscape for marketing, it's like there's so much. So they were like -- we don't think that's where the world is going. We think the world is going into a world where there's some sort of intelligence that's orchestrating campaigns in real time and doing one-to-one personalization. And so what it would need to do that is it would need a headless CMS. It would need to be able to pull the content out when it needs it. The CMS would have enough metadata, enough context in it so that, that intelligence on the other hand can go grab that when it needs it.

So part of the attractiveness of the acquisition was certainly that just bringing a little bit more Headless DNA into our product organization. But also, this has been a little bit of a gap in our Marketing Cloud Strategy for many years, and so it certainly had some attractiveness in terms of kind of shoring up our Marketing Cloud.

All right, terrific. I'll ask one more question, and then we'll pause for any of you folks that may have a question to ask Patrick. So I want to just talk about Slack for a moment. So a lot of investors, quite frankly, believe that Salesforce overpaid for Slack all those years ago. Now my opinion is that view has some merit, but I will also say that Slack has quietly become a more integral technology in an agentic world and many people don't really seem, from my investor conversations, really seem to be aware of that to the extent that it's actually occurring. And going forward, it also seems that because of Slackbot that this can really become more of a center of gravity for Salesforce. That's the opportunity that we see, but it will be helpful to hear your vision on where you think all this is heading.

Well, it's pretty similar to your characterization there. Slack for us, I think the market in general kind of see Slack as a collaboration tool and they kind of put it in the same [ bar ] as Teams. And I think that's just a really kind of unsophisticated view of what Slack really is, which is where Slack started was it was a platform for developers. So developers needed a way to work together to build projects and so Slack emerged as a solution for that. And it wasn't just because you could create channels and invite your friends into the channels, it was because of its openness. It's connectivity to things like GitHub and Jira.

It built this ecosystem of connectivity. So it became very, very sticky for developers in the way that they work.

We're seeing that same thing now happen to all sorts of different functions. Certainly, this is true in Salesforce. I mean we only work in Slack. It's unbelievable how much we get done in Slack. But we're seeing it with our customers as well and especially the small -- the new logos, the small customers and even the AI labs, which we say small, they're like $1 trillion companies, but they only have like 2,000 people in them, right? So on the scale of employees, they look like they're small, but like they run their whole business on Slack, and it's because of that connectivity. So that's kind of one side of it.

But the other side of it, that's very exciting is that it is already a conversational interface. So it's already really well prepared for an agentic future for when you have teams of humans working side by side with agents. But it's even more than that because you could say, well, Patrick, we kind of already have that with Claude and with ChatGPT, that's a human working with an agent. And it is, but it's one human working with one agent. It's a single player environment. And that single player environment, it's useful. It's nice to be able to work like off on the side and just talk to Claude, but most of us work within teams.

Slack is inherently a multiplayer environment. And once you start putting agents into a multiplayer environment, all sorts of interesting kind of usage patterns start to emerge. So one person can ask a question and the agent answers and then a second person can ask a question and it becomes this very interactive multiplayer type of experience. Imagine using Claude Code, which is also a single player environment in a multiplayer experience. These are things that the labs are kind of very interested in doing with us at the moment. And it also adds an element of trust.

How many of you have ever had your boss and your managers send you something that you can tell was just done in Claude and they're like, look, here's my analysis. And like you instantly know it was done in Claude just by the way it's written. We all have a spidey-sense for this now or OpenAI as well. But what you also are probably developing a spidey-sense for is that your manager is [ full of shit ] and whatever they prompted to get that answer was full of bias. And so of course, it's very convenient that the analysis that the AI did matches what the person on the other side is asking for because that's just human nature in the way we prompt it.

Well, when you move that into a multiplayer environment, all of a sudden this kind of new paradigm of trust evolves because now you can see the prompt, right? And you understand how it arrived at the answer. And in fact, multiple people can kind of prompt it at the same time. And so you're getting a much richer answer that's much more based in multiple viewpoints, which is a much more trusted answer. And that's something that I don't think anybody has really demonstrated yet, but we're on the path to do.

I have to say that's a fascinating point. I hadn't thought through that in that degree of depth, that may be something again that really enables you to kind of drive some more separation, right? As Slackbot continues to -- and Slack more broadly continues to get adopted. So that's -- yes...

And even Slackbot, amazing tool, incredible capability, but even Slackbot right now at this moment in time is a single player, right? So you ask it a question, it answers for you. You can share the answer. But imagine, instead of that, you're just in a channel and you have 15 members in the channel, but 2 of them are agents. And you just ask a question in the channel and the agent responds to them. So that user interaction model or paradigm hasn't been fully explored yet, but that's where we're going with Slack and it's super exciting.

Okay. Tremendous. So fascinating conversation. So that took quite a bit of time, but it was important, I think. Any questions for Patrick.

Patrick, thanks for sharing the insights. Multiplayer was [indiscernible] as you think for multiplayer environment, essentially sort of like [indiscernible] system [indiscernible] use all that stuff. How do you think about that?

Well, I think what we have at Salesforce, whenever we're building product and trying to bring product out into the world, what we're trying to do is identify what's the thing that's scarce. Right now, the intelligence is not really scarce. I mean there's limits on how much energy we can provide in the world to kind of deliver the inference through the GPUs. But the thing that Salesforce delivers that scarce is context and trust. And so if you're building anything with AI right now, it's very, very easy to just start talking to an LLM and you get excited about how intelligent the answer sound, but then you realize it doesn't know anything about your business. And so then you start trying to figure out ways to dump information into it, so it understands your business, but that runs into all sorts of complexity and limitations in how much you're putting into the context window.

You can get about 1 million tokens into a context window right now. But if you put 1 million tokens in your context window, that's going to be an insanely expensive call that one question is going to generate a ton of tokens and the more you put in there, the more confused your LLM will get. So you have to engineer this way to get the exact context that it needs in the moment, pick the right model and then deliver an answer. And that's what Salesforce can kind of do behind the scenes in that moment. And what gets really interesting in that multiplayer environment and inside of Slack is the one piece of context that nobody is really truly thinking about, well, there are some us and others that we're working with. But the really interesting piece of context is the institutional knowledge of the people in your organization, which is encoded as those conversations inside of Slack.

So we bring that in as well. It's not just your data and your metadata, it's the conversational data as well, which adds all that additional context, and then we engineer a way to bring that all in at the moment that a question is asked, optimize the token spend, and that's really where we think our value is going to be in the future. Hopefully, that answers your question.

30 seconds if someone has a quick one for Patrick. If not, I'll just ask one more. So I just wanted to bring up a recent podcast with Marc Benioff. He mentioned that Salesforce is on track to spend $300 million on tokens from Anthropic this year, a pretty massive amount. Tell us just briefly what that will do for Salesforce in terms of productivity and innovation and maybe even inclusive of the cost implications.

Do you want to see our leaderboards? I can pull them up on Slack right now. We can go through team by team and see who's really using. Yes. I mean it's just been -- honestly, it's been insane in our engineering organization, watching the pace of innovation right now is unbelievable. And there are pockets where it's even more unbelievable. Slack, for example, is just fascinating to watch that team now.

I show up with ideas. And like on Monday, the ideas are in production, which is really -- it's just astounding to watch. But it's going much deeper than that as well because a lot of that -- most of that spend right now is coding, but not all of it. There is a very -- this is what I don't think the market has totally caught up to yet. A very material amount of that spend is just knowledge workers. It's my team in marketing. It's Val's team. It's people in sales. It's people like Miguel that are using it to do their forecasting. They're not coding. They are hooking up the MCP servers and consuming tokens from Anthropic to do their knowledge work. And we think that, that's where the kind of next big wave is going to come from.

Super insightful conversation. Patrick, thanks so much.

Thank you.

Thanks, everybody. I assume we'll have some folks filtering in after lunch finishes up. But I'm super excited to have Parker Harris with us, Co-Founder and Chief Technology Officer of Salesforce. Just a couple of English majors talking about headless technology, should be good.

So really excited to have you here. So much going on in the industry around agentic, AI, you've been through so many of these cycles. So it will be fun conversations.

Never been through a cycle like this one, but I've seen the cycles.

No. No, I don't think anyone has in terms of the pace and [indiscernible] and just sort of size of it. It's pretty amazing. So why don't we just jump into it. And if you have a question, raise your hand, we try to keep this as interactive as possible.

But -- to your point on cycles, you've been through a bunch. Why -- and we've seen a lot from Salesforce over the last month or so on Headless. Why are you all as a company sort of excited about that as part of the broader AI strategy?

Yes. I think we were surprised that we didn't make it the headline of Dreamforce last year. It was kind of a more recent idea, and we launched it at one of our world tours. And the feedback was just phenomenal, like everyone in the press and then on social and our customers are like, well, this is a brilliant strategy.

And I think what we're most excited about is just meeting customers where they are. We've had APIs to our service forever. But with the rise of -- and it's also kind of related to Claude Code that really hit that tipping point in February, that the first place we thought is Salesforce should just be easier to configure, to implement, to diagnose and why not vibe code it. So that's like the first step. Like let's open everything up Headless, and you can hit it with that. But then if you look at. And Salesforce always follows consumer trends. Like when we started the company, it was about Amazon, the bookseller, when we launched Chatter, was looking at Facebook. And right now, you look at the model companies and commerce, and there's UI coming into these products.

And so part of Headless was also, let's rethink our experience layer, the experience is actually in the Headless layer because you define the user experience and metadata. And we interpret it and we play it out in what we call Lightning. Now that can come to you, but you're not saying what I told you, you should see, you're just telling AI, this is what I want. And so give me my top deals for the quarter. Tell me what trouble tickets or cases that Kirk might ask me about at Evercore, and it paid in that response, beautiful UI, not just a bunch of text. And so it's really the new experience layer. We're seeing customers use it from things like Claude Cowork with OpenAI, ChatGPT, but also from Slack, which I've been spending a lot of time with the past couple of years being a great engagement layer for kind of everything Headless, not just Salesforce but everything in the enterprise.

Okay. We'll definitely talk more about Slack. I guess when you think about the Headless strategy, what does success look like? Is it opening up the TAM again for you in terms of just these people that might not have come through Salesforce traditionally through, say, more of the app layer? Is it -- when you think about where you'd want to be in a year on this strategy, what would you guys think about as success?

I think first and foremost, it's about adoption. So users are moving and they're looking at these new services -- surfaces. Success would be massive adoption of Headless. And I haven't seen the stats of MCPs on the Agentforce side been more close to Slack. But the Slack business unit MCP interface just spiked, we just released it, I don't know, a couple of months ago, and it is just spiked. So the number of people wanting access to that corpus of information is just like. So we're seeing the adoption.

And we're talking a lot internally about what are the monetization strategies for this because I think part of the success is also there is our current monetization like let's just get more license revenue and agent may be talking to Salesforce agentically through Headless, but it's talking as a named user because it needs to get the right data with the right security protocols, the right context for that agentic response. So it's a lot of named users. But there's also opportunities for usage-based pricing. And we're talking to our customers and saying, well, where do they want us to go.

Yes. That makes tons of sense. You mentioned Slack. Let's double-click on that a little bit. Probably one of the products when you think about Salesforce that has perhaps the most network effect to it within your customer organizations. How does that feed into sort of the broader headless strategy? Why is that such a great engagement layer for the agentic enterprise? Can you talk to us about that a little bit?

Well, take Slack where it was most successful when it started before we ever acquired it, was it with engineering. The engineers would take it real great. I'm going to hook it to get for source code control and Jira for my bug tracking and planning and connect it to my monitoring. Give me all the tools, but don't make me leave what they call the flow of work and just work there in context. And what is amazing about Slack is that expanded from engineering groups to all knowledge workers where they're working together and humans all humans at the time before AI, it's like, great, I can work in Slack. And we're just getting more work done. It wasn't just about communications. It was really about work.

Now it's about AI. It's about getting work done with AI, both as my assistant there. So Slackbot being a native one, but also third parties Claude Cowork in there or my Linear agent, if I'm coding, they're all in Slack because -- and they all want to be in Slack. And it's basically where AI-assisted or more and more AI autonomous work is getting done, but it's where humans are working together with AI with each other. And so Slack calls it multiplayer. When I use like a Codex or a Claude Code, that single player. I'm just working myself with it. And then -- but if I wanted to work with other people, Slack is really the best place for that. And so you'll see more things coming where we're opening up more surfaces where when people want to work together, whether they're coding or they're doing knowledge work, they're in Slack.

And by the way, in both Anthropic and OpenAI, like that's all they use, Slack. They have Slack, they have Salesforce. They don't really log into Salesforce because they're sitting in Slack using their models and stuff they've built, sometimes our stuff and working with all of these headless APIs to get their work done.

Has AI given you an opportunity to go back into those customers that might have bought Sales Cloud 10 years ago and say, look, like financial services is a good industry as an example. I guess, it's never been a great Slack industry forever reason. Maybe people are in Bloomberg.

Would you like to buy some Slack?

Our CIO is here. You can pitch them. But I think the idea would be you should rethink this in concert with AI? Is that kind of the message your salespeople are trying to reintroduce it to sort of, again, expand the surface area where you've been? And I guess, have you seen early success on that and maybe financial tough one, but other industries.

Well, let's take sales, for example. So we always try to like use everything ourselves first of all, call it [ dog footing. ] And so the sales manager agent, as an example, is this agent that is built on Agentforce that we have all these leads. We have a lead database, all these prospect leads. And there's a lot that we think aren't valuable, like to call them because you're too expensive as an employee to call them, call these because we think [ these are close ].

But we've taken all the leads. We think or lower value, and we've put them on this -- the sales manager agent, which agentically is having conversations with our customers over Vimo, WhatsApp voice is coming where they maybe call you. But it's not a one-way batch and blast like market automation like, hey, you're interested in Salesforce automation. And see if they clicked and then somebody calls it, it's a multiparty conversation back and forth. So that's an example where we can go back into a customer and say, would you like to close more business without adding more humans we can help you do that. Or the qualified great acquisition, ex Salesforce team came back in recently come to the website and just engaging with the customer on the website as an agent to get that prospect to the right place where maybe they'll even buy or they'll hand off to a human.

And so there's huge opportunities that we have just to go back on the customer base and say, are you in agentic enterprise? Have you found more productivity with AI or not? And if you've not done any of that, we can help you get there.

And you mentioned sort of monetization around the Headless list concept. I mean you guys had the app exchange for a long time, right, for API-based sort of revenue stream. I mean, should we sort of think about that in a similar vein, whereas you can still buy agents directly from Salesforce, you can build within Lightning? Or look, you might be able to build agents on Claude, hit, hit, come in through the MCP server and get data that way. Is that sort of the way we should think about it? And I guess, from your perspective, again, you're just trying to meet the customers where they are. Is that kind of idea?

Yes, so we have an agent exchange and agents can be built an Agentforce, a third parties. They can -- if it's built on an Agentforce, it's not going through MCP. It's just native or third parties can go through the MCP interfaces. Customers are building some themselves, which is totally cool. We're just trying to solve what is that use case they're trying to solve. And is it more sales? Is it happier customers in the service department? Is it lead gen and market automation whatever it is.

And we're going to do our best to provide services that I guess just you can do it, but it's going to be easier or better with us. But we have been true ever since we started the company. When we started the company, -- we call it Salesforce.com. When we started the company, we like we we're probably going to do more than Salesforce Automation, should we pick a different name, didn't pick a different name and people have told us like change your name. But we had Salesforce Automation and then you have customer service with [ Siebel ] or whatever, like, great, we will integrate. And so we always want to where they are and whatever they're doing. But we'll still pitch in these customers, the integrated platform and just all from us, it's going to be easier and probably cheaper for you long term and just cost to maintain and run.

Okay. Agentforce has been out there now for maybe 18 months. And what have you all learned in terms of adoption, sort of removing the friction, what if companies that are seeing real success with it done correctly? And how do you sort of expand that out to the rest of the year....

Who many times the people use the word for deployed engineer exactly...

Plenty.

Plenty. It's a new term and a number of other companies kind of coined that phrase. I think one of the things we learned which is kind of obvious is agentic AI is nondeterministic which we know. And so but you don't want in your call center, like it could do multiple things. We can't tell you exactly what it will do, but we'd like it to -- that's not a great answer is like how is my portfolio doing? Like do you want to give the right answer. You wanted to have the right context.

So what we found is being in the customer, and it's no longer about being in the customer in the sales process and saying, here's a demonstration of what we can do for you is we're like, why don't we build it with you. We have agentic coding now, we can mitigate the entire platform really, really fast. And we want to show you how it's working. And then we want to work with you to make it successful. So that's one thing.

Another thing is that determinism a non-determinism, in the harness of agent force, we started out just saying, well, the models are going to keep getting better. And so when I say do these 10 things in this order, that's great. It will do that. It turns out 9 times out of 10, it does. I want it at 10 times out a 10. And a lot of companies are doing this, we've pulled out some of what is really deterministic logic, which is workflow basically. And we built Agent Script, which is essentially a way and an ICI to basically script out what do you want the agent to do like coming into the website, ask them who they are or have a pilot claim for insurance is a series of steps you need to do. And in each of those steps, some of those could be nondeterministic AI through a LLM, something that kind of interaction, so mixing the 2 together. And that's been really successful is -- and it's actually faster and cheaper because you're not hitting tokens to do some of those things that you really don't need to model for.

And so what we found is, these things are brilliant brains, but you don't use them for everything. And I think what we first did is like, well, great, let's just have to do everything and turns out they're not graded everything.

Yes. And you all have obviously invested in Anthropic and a number of these native AI companies.

Yes. Yes.

Yes. So that's good was a good one.

That's a good one. Yes. Well, we like to sell [ John Somers ], but not enough. You didn't see where it was going enough.

Always too little after...

Too little, too little, yes.

but one of the questions you bring up around this sort of harness and orchestration concept is that where the value has to accrue longer term for companies that want to participate in this genic world, meaning to your point, the base level of intelligence for models will continue to get better over time. So when you think about how you differentiate, how you deliver value to customers, does it need to be your sort of ability to take that brain and then deliver sort of customer value on top of it? And is that -- do you -- and I guess the second part of the question would be like, is that durable? Meaning is that the delta between what of intelligent models, the intelligence, again, will keep get better. Is it durable? Is that sort of value-add at the orchestration level, durable.

Well, I don't think it's just orchestration. It is the -- like everything we're doing is the Headless. Because we're not building the models. We're using multiple models, mixing them for the right use cases, some for performance for cost. And when we say Headless like agent force, the entire ad bores, you can call it, harness because it's basically using these models to do customer service to do sales. We've got orchestration in there. We have telemetry for monitoring. We've got e-vals or testing the output of it can then get used to update the whole configuration the prompts and everything. And so that's hugely defensible. We've always been a CRM company. That's our wire ticker CRM. We will stay in that lane. And we're not trying to be a multipurpose like -- just like use us for any sort of AI. We're going to be CRM enhanced with AI autonomous.

And yes, I do think that's defensible. And we can also take 27 years of our customer base, the implementations, the business logic, the metadata, all of that's already out there. And they're asking us our massive Salesforce are like, hey, take us to the future because we have those trusted relationships. So I think that's also a huge advantage we have. And then we're taking them there. And we keep using these better and better models, but the models don't have the context. And they don't have the context that is secure, like we don't put all the data in the model. It doesn't have the exact right context for the question because if you put too much data to the model, it has a hard time or you spend a ton of money or both. And so all of that I think is kind of a differentiated...

And you mentioned data, obviously, bought Informatica, you had data cloud before that. How important has that been for you all to build a data platform in the back to complement Agentforce?

I mean we can call it context now because it's a cool word. Yes, we built our Data Cloud, which is really 2 things. One is the data platform for collecting data, but also a data activation platform that connects all the other data platforms out there. MuleSoft for API management, Informatica has been an incredible acquisition. It's exceeded our expectations in the first full quarter, yes. So it's been great for the business.

But I think we have too many brands right now, people know these brands, so it's fine. But we were doing customer mastering that's very important. We weren't doing product mastering. So our customers, our financial instrument would be a product, or a car from for whoever. Informatica has an amazing MDM solution for things like product mastering. And if you're an agent and you want to talk to get the right context, you want to get the right context on I'm going to the car website, and I want to buy a car, which car, you want the context, all the contacts for that product. And so mastering that is super important.

And our vision is not that all the data is there is going to take to make that work. It's a logical semantic onto logic, maybe is better where these days layer that combines the metadata of the history of sales force with metadata from Informatica, it hears all these other data sources with metadata from MuleSoft, of -- here's all these other API-connected data sources with Tableau, which is a semantic layer to understand what is the semantic meaning of all this data. All of that comes together and gives us that rich context layer that AI can then use. So it's a huge event. I'm so happy we're able to get Informatica.

Yes. Is connecting data to the agents still the biggest challenge for a lot of your customers in terms of sort of the promise, and the reality right now.

It's not connecting the data, it's the AI shows them where the data is not clean, it's not right. They haven't mastered it. we even found that when we -- I think we were perfect, but [indiscernible], when we stood up our help.salesforce.com Agentforce agent's, they started showing us where -- in our data sources wasn't it wasn't clean, was it quite right. So we had to go and fix that. And we had all the tools, obviously, with our products to do that. And so getting your data right is definitely that first step for any success with AI.

Any questions? I have a bunch more, I'll open it up. Okay. I'll keep going. I think the next one -- trying to think next one. Verticalization for you all and bringing sort of more -- it seems to me like in an AI world, the ability to bring an agent that not only understands the sort of domain and in terms of being a salesperson understands the context and then actually maybe even the nomenclature that goes into a different industry something that might become more valuable over time. I think through AppExchange, you all let some of your -- like Aviva went out and sort of originally did that in pharma.

How do you think about that going forward for you all because I could see having sales agents that are tuned for retail might be different than insurance that might be different from financial services. So I know [ David Schmaier ] spent a lot of time on this topic, and I talk to him a lot about this topic.

I mean shootout to [indiscernible] earlier, former co-CEO he really started the motion to go industry vertical, which originally, our sales engineers would just go and say, sure, I can take Salesforce and I'll just configure it for banking, retail banking or investment banking. But then we realize it's more than just the data model. And so like when you -- everybody is talking about vibe coding your CRM is like, yes, you can create a data model, but it's far more than that. And so I think we have a huge advantage as you go deeper into our product line and you look at our industry verticals, we have a lot of industry vertical business processes built out. We are building out industry vertical Agentforce agent's. And Agentforce skills and topics that you can use in your industry that understand an insurance claim, understand, I know your customer motion in banking, understand like I'm trying to think of other examples, but just to understand all of those.

And instead of handing you a horizontal here you go, it's a toolkit, go at it, we can hit out of the box, and it keeps getting better. And we're exploring with our research group. How do we -- how could we -- might we fine-tune some smaller models that are industry-specific that really underban the business process that industry to make them even smarter.

And that sort of relates to my next question, I think I know the answer will be. But I expect you all believe that this is going to be a multi-model world where you're going to be using the right model for the right action for the -- in the right, again, context. Is that happening already underneath Agentforce, meaning if someone ask a fairly simple question. You don't necessarily need a frontier model, or you might just want an open source model or some -- to your point, a small language model. Is that already going on? And how, I guess, instantaneous is that when you put in a prompt as Agentforce is smart enough to know the context of the question, so I can go to the right model, get the right answer? Or is that still a little bit...

Exactly like that. It's more like the core reasoning loop, the large foundation models are really useful like to reason what you want. To then voice has its own models to do checking on ethics or violations that could be a simpler model. Just understanding the question of what did they -- were they asking and parsing it out in the right way, can be a smaller model. And so we're -- the first step is not like a cost optimization. It's like let's choose the right model for the use case because often, it's a performance thing like I don't need to run through 1 trillion parameter model due to the simple use case and by the way, it can be expensive and it's going to take too long.

And so quality is the first step, but then performance and cost will be the next to you. And so we're mixing models all over. And we can do it at run time. We can mix and match. I think we will head in the future, we will look at should we have fine-tuned models per customer for some of those use cases that maybe we're dynamically updating the models from each customer, like we wouldn't mix the data. So that's another idea.

And finally, like we're always looking at, well, what's the next frontier model that what can it give me? And will the next Anthropic model or OpenAI, 2 biggest ones, but -- we also look at companies like Mistral that we're invested in and Cohere and other model companies who look at what do they have. We've shied away from the Chinese model for various reasons, a lot of which are -- we sell a lot to the U.S. government.

Right. Maybe you could help me with the question I get a lot, which is there's obviously going to be some workflows that are deterministic, meaning if you have a policy around CPQ, you can't just model come up with sort of guest. It can't be -- how does that get integrated? You mentioned maybe it's the agent script point you made earlier about like how do you start mixing in the benefits of both probabilistic models, but also within sort of the parameters of having deterministic outcomes to some degree. You can't have salespeople being like, all right, like close enough on discount...

Yes. I think one of the best examples is a company called Regrello that we launched, which I thing is called Agentforce Operations?

Operations.

Yes. We never changed the names of our products but it at design time uses AI heavily. So trying to understand the business process of a corporation that's not written down. It's like, well, oh, you want to give a discount on professional services. That's actually an internal example where -- we wanted to -- for a customer, I want to give them highly discounted professional services in the deal for the implementation.

Oh, well, to do that, you need approval from these 3 humans. You need to go on these 4 systems. And it can look at all the data you could draw a diagram, you can parse it or you can look at some of the e-mails that are going around. And it's using AI to understand, well, what is the real human business process, but then it takes that and it turns it into workflow because at run time, it doesn't need to be the AI running that process. It's like, first, I'm going to ask Kirk for an approval to be an e-mail and then when he really says, yes, but I'm going to go to this person to make sure the system -- and it's obvious what it is, but figuring that out, we acquired in an agenetic process.

And so I think more and more, you're going to see that. And so like companies like Dell are like, well, we're saving a ton of money. We used to call it supply chain was the first here we use because they use it in their supply chain area, but it was just simplifying their internal business processes significantly.

We obviously talk a lot about agentic. And I feel like we're sometimes in a little bit of a bubble when we talk about this in the industry. When you go out and talk to CIOs or you're talking to some of your bigger partners, I mean, how early are we? I feel like everybody wants the agentic enterprise tomorrow, but when you go out and talk to customers.

I think we're really early. I mean, we're still super early. Right now, the hot area that's getting automated, it's customer service. That's where you see a lot of little start-ups. That's where we're playing. And then in collaboration with Slack and Slackbot and see Claude Cowork as an example, obviously, coding is a huge area. But yes, I mean those are the areas that we see right now.

Okay. And any industry you think that's farther ahead, the ones that are more regulated, seem to be obvious, that will take a little while longer in certain functions.

I think it's more like the CIO. It's more of the leadership of the company, are they leaning in or not? I was just in France. I was meeting with the [ Adecco ] which is a big recruiter. And they're going all in, they source temporary labor contractors to corporations of all sizes. And I went out to one of their recruiting offices because I wanted to see our software and use. And so they were using Einstein for sales. So that's machine learning. So just like just help me understand the score some leads and score the this candidate and is this a good candidate, matched this candidate with the right thing. So that's machine learning. Then it was using Agentforce to that outbound to have an interaction with a candidate. But it was because Pierre Matuchet, the CIO is an amazing CIO, and he's forward leaning and he's going all in, and he's figuring it out.

And so I think it's -- and then it's about like are you taking the right problem to solve and there's a lot of DIY out there that some has worked a lot has failed. I mean that's selfishly saying, let us help you. So that's another thing we're seeing. But it's still super early. And I think with AI, the demonstrations are so compelling, we think everyone is doing it, and we all have this fomo, well, I got to do it. And that's why a year ago, every CEO said, everybody do AI. And everybody bought various tools and do stuff. And now we're seeing more consolidation and more use case by use case success.

One thing I forgot to ask when we're talking a Headless earlier in the conversation is, it seemed to be that Headless in a market that's moving this fast lets the customer understand that they have optionality with you, meaning you're not boxing them in, and I'd imagine at a time where a lot of CIOs frankly, aren't sure in which way they might want to go 2 or 3 years from now that's actually a benefit, meaning I can count on you all to be flexible with me because every organization is going to have to be somewhat flexible in an AI world.

It's resounded incredibly well, and we just want to meet people where they are and where they are is moving. And we have built user experiences for 27 years. We think -- and you can customize them, but we think this is the first version that makes the most sense for you for sales, service. And maybe the future is not that at all and how I interact with enterprise solutions is going to be personalized just for me. And maybe it's not me, it's my agent or agents. I mean, you look at how people are coding, they're managers of agents now, like, rate the spec and test it and do.

I think every job function will move in that direction. And we want to meet the customer where they are. So what surface do you want to do that? And what user experience do you want? If you want to vibe code a new UI for part of Salesforce, go for it. And you can use parts of what you've already configured and you can build your own. If that's valuable to you, great. If you want to use it and have it surface in these other tools, great. if you want to be multiplayer and have multiple [indiscernible] working together, we still think Slack is the best. If you want to use Teams, many people have Teams, obviously, I think Slack is way better. we will help you use Teams as a service. And I think the world is moving so fast, we can't predict where it's going to be -- we all have to be super flexible and super fast and move with the same pace.

You've obviously been at Salesforce since the beginning. Are you pleased with the agility. I mean it's a big company. So to move -- I think there's sometimes a view of like inhibitor dilemma or those kind of things with companies. But do you feel good about the level of velocity that's going on...

I credit Marc Benioff. I think he is an incredible entrepreneur. And he's like, he's talked about a inhibitor dilemma, we have to go rethink how we're organized a -- should we when we think about forward deployed engineers, we have sales engineers. Well, what's the different -- if we're not building demos, how should we think about that? Should we deploy them more out into where the business is happening. And so Headless, yes, let's go all in on it. And so I'm very pleased with the rate of change that we're driving. We have an internal process called the V2MOM that helps us stay a line, and we just keep rewriting it because it keeps changing.

But that's how tone from the top, change, try some things, don't be afraid to fail, and that's coming from Marc, and then use that V2MOM process to say like we're changing now. Now everybody we're at, here's how we need to align. But it's never perfect. I just talked to some of the leadership in our technology and product organization, like they're asking how do we take more chances and do more. So we've got to keep hammering on it.

Yes. You're obviously very in the weeds on all the tech. And just out of curiosity, what's the sort of idiosyncratic thing that you guys have broken through on more recently that perhaps only you would find it interesting, but I'm kind of curious what you're spending time on, maybe that's in the bells of the technology, whether it's data, governance model.

A lot of it has been for me personally has been in the Slack business unit. And the breakthroughs I'm seeing is, how do you think about multiplayer Claude Code where multiple people are working together with AI to build something. And that could also be Cowork, or it could be Codex or it could be linear.

So it's a breakthrough of thinking about, well, Slack as the channel-based experience you're doing work together. And it's all human based, and we're bringing agents in and what if that agent is building code or writing an S-1 to go for it. Maybe Anthropic, using Anthropic to rates on that would be interesting. But how do we do that together? And so what is that experience? What's the identity of the agent, who like -- and how do you bring it all in together. And so it's not -- maybe it's not the sexiest answer of like, oh, we've figured out this identic loop for that. But it's really more of the user experience. And I think change happens at the user experience layer.

When Steve Jobs launched the iPhone is like, well, the world has changed because of the experience, the battery didn't last day, the outport may be the best, but it was the experience. And so if you think of the company, we're really leaning in harder on what is the experience of the future, and we're trying a lot of ideas, in Slack how -- what is the experience of many people working together with AI.

And is that pretty much the operating environment at Salesforce now? It's everybody in Slack? Is that...

100%. We all in Slack. We're all using Slackbot. I mean Slackbot as an agentic agent helping people, the adoption rate is the fastest I have ever seen of any feature we built. And it's helping everybody get their jobs done, and it's phenomenal. And so everybody is like, we now have just we had a big -- we have lots of meetings -- we just had a big meeting in Las Vegas -- Los Angeles with our top 500 people. And we launched internally Tableau Analytics in Slack, but implemented for every -- all of our regions and all of our sellers, so they can run their business like instead of going into Tableau or into Salesforce or something they built themselves pulling data out and putting it in Excel got for a bit. They're just living in Slack, running their book of business and what's my pipe for the quarter? What are my top deals, what I have closed so far, who has trouble? That's all happening in Slack with Tableau tied to all the data.

And it's a great use case to go to sell because they could say like, hopefully, they're not showing everything, but Kirk, let me show you how I'm running my business at Salesforce, and here it is. And it's a really compelling way to tell.

Yes. That was my next question, actually, which was, it was a reference selling, software choice but reference, anything in the [indiscernible] is reference selling.

I mean certainly selling Salesforce automation, if you're a salesperson [indiscernible] use our tools. It's very easy.

And do you think that Slack but what you showed to customers kind of changes their perception perhaps about there -- where you can go with your technology?

Yes. [indiscernible] the team shop where they're like that. We don't need another chat tool. And we're like, yes, but can I do this? And they're like, oh, wow, and it's tied to Salesforce. And we have Salesforce channels and Slack, all the data is there and Tableau Analytics, all my work. Everything is there. It changes how they think. But we have more work to do there.

Anything in particular you think you have more work to do?

I think we have more work to do on both enabling with our teams of like telling that story and coexist with Microsoft Teams. Like in Slack, you can now join Teams Meetings, It can -- you can MCP to the team's data Black Box could use that data if you're working -- also working in Teams. But people -- most customers I talk to, they're not working in Teams. They're using Teams for video and they're using Teams for direct messaging, which is a little bit of work, but they're not really working together deeply on something. And so -- but we have more work to do on and getting some IP out there.

Just because I think it gets off a little bit. I mean, I think Marc talked about Slack getting the $10 billion at some point in time. What's the -- is the monetization sort of thought process behind Slack changed at all because of this?

Yes. Yes. So the monetization is still very much license based. We move you up in the additions. And so you want more access and more Slackbot, you move up in addition. So that's a typical motion really successful. It's one of our best executing business units. But we also see opportunities for some additional usage-based pricing to come out, which we haven't been out yet, but we're talking about working on, everyone wants their Slack corpus of data. All our partners want access to the APIs, the [indiscernible] products because now with agentic AI the intelligence you can derive from all of the unstructured data in Slack and the messages, the files, all the collaboration is a huge asset. And that's what you can see in Slackbot, but maybe one of these some other tools. And so we can monetize that as well the access to all that.

Yes, pretty amazing amount of context from a business is in Slack for a lot of them.

It's shocking, yes.

I got one more, unless anybody else has a question. All right. All right. Kind of an open-ended one, sort of maybe a softball to some degree. But yes, what's -- if you guys win in agentic enterprise, right, what would you view as success over the next couple of years? Like, obviously, adoption, you mentioned it earlier. Is it Slack becoming -- from a lot of your customers becoming the operating system for them is that what are the I don't know, KPIs to some degree that you're keeping an eye on to know that you're right track around agentic...

I would like to see Slack become the interface for getting work done for sure. And I think we are well on our way to that. I think success is also that you can clearly see how the enterprise has changed with a combination of human workers and digital workers and that's reflected in our solutions, making that possible, but it's also reflected in our numbers where you're seeing like, okay, that's amazing. This company is so much more productive because 1/3 or half of the workforce is digital labor and AR investors can see and that value is now seen in these mix of license and consumption-based revenue. And I think -- we're still on the evolution to consumption-based revenue. You see it. We've had it. Marketing Cloud has had for years. Agentforce is doing really, really well. Data Cloud is doing, you know.

But I want to see that like really clear in the market, and it's not just our pricing and our revenue there, but what has it done to the customer base? Like how does that show up where, wow, your call centers have the size and those people are now doing other higher-level jobs, and your customers are happy. And by the way, it's also a revenue-generating center because everything is blending now. It's like this was true before with the agents that they don't care if I'm a service agent, but I could also tell you like, I could upsell you on something. So that's kind of the future I see.

Agentic work units, is a something you are keeping an eye on.

Yes, it's -- we really were trying to move away from tokens. I mean, because tokens are not a great measurement of did something really get done...

Not really, token has value.

This is how much we've paid model providers and helps with their like it's kind of like leaderboards for vibe coding and what's your -- are you token maxing and who's using the most tokens to vibe code. And if you read about that, people say, well, that's a terrible metric because people are just going to try to use the most tokens and it's not really a right metric for output. And so AWS is definitely the right metric. We're trying to tie Slack to that metric as well as that drives a lot of agentic work units. And then from agentic work units to outcome also.

Great. Yes, we're right at time. Parker, thanks very much for being with us.

Thanks. Really appreciate it. Thank you for having me.

Thanks a lot. Thanks, everybody.

Thanks very much for coming. I was looking forward for this session today because Miguel and I had a terrific discussion after the company reported numbers, he's convinced I'm wrong with my rating, and he's going to prove me wrong. And I'm very open for the challenge.

So as you know, I'm new to cover software being covering cybersecurity for 20 years and networking for 30 years. And I always say that lately, I'm the garbage person at Bank of America, garbage not from a person of quality, meaning everything -- every time someone leaves, they tell me, okay, you cover it. So I cover everything else basically. That's going to change soon, but software is my focus, networking is my focus.

And I want to start with a few things before we start -- I want to start with outlining the background for the discussion. We have 30 minutes to discuss and we're going to talk strategy. We're not going to talk about the quarter. I don't care about the quarter. I talk about -- I care about where is this company positioned for the next 10 years.

Salesforce today is a much bigger company than it was 7 years ago. And the growth decelerated. The growth in the last quarter with professional services, 7%, 7.1%, without 7.7%, it used to be 30%. It used to be 20%. And that's before AI. We're not talking about AI. AI might be a tailwind, might be a headwind, right? So what I want to understand is the reasons for the deceleration, the risks that we see in AI, the opportunities that we see in AI, and how the company is positioned to basically address the opportunities because the whole discussion of this quarter, by the way, for me, it was the first time I do a quarter call for Salesforce, and the whole discussion was about AI. The whole 1.5 hours was about AI. So I want to understand AI, and that's the purpose of our discussion.

So with that, Miguel, thank you very much for coming, and thank you very much for taking the time to educate me because I need this kind of education.

And I want to start with big strategic positioning. No, I'm not giving you kind of direction with my question. I want to ask you, what do you want to highlight when it comes to the opportunity to accelerate growth over the next few years? What are the initiatives that you think will drive higher growth in the future.

First of all, thank you for having me. I will actually very much looking forward to these conversation, we sort of [indiscernible] the eyes a little bit. Can you hear me? The mic. It doesn't seem to be, if it's working?

No. All done. He's fixing it.

Feel is not working very well. Can you hear me at the back?

He's been something new.

Hello, hello. Okay. So listen, so first of all, I think since earnings is -- I've done like 10 analyst meetings. This is the one conference that I wanted to come to. You have the analysts that I wanted to meet you face to face. I've talked a lot about you. You stated about the company. I actually was very curious to understand when I saw your price target. I mean, I'm the Head of Sales and the Chief Revenue Officer, but I also started finance. I started financial engineering, financial management at MIT. I understand valuations and I was curious to get to know you. And then when I read -- I like. So I have a lot of respect for you. By the way, you are very smart. A lot great experience. You have listen, you haven't eaten a lot [indiscernible] but listen, first of all [indiscernible].

Of course, we have -- we bought a company last year that was like with the inorganic growth and we grew 13% revenue, 14% CRPO, we generated $6.7 billion of cash flow, not bad in 1 quarter. I mean there are companies that you like a lot that in 1 year, they don't generate that cash flow. There are companies that publish results the same day amazing results. We like that company. I think there are a lot of people here in San Francisco. And the whole revenue for the whole year is not even the cash flows of Salesforce. But let me...

But I'll stop it for a second because it's a conversation. In the last 2 weeks, we had a rally and the rally in software you are lagging behind. Your stock went up 3%, the others went up 30%. So something in your message doesn't get across to investors. And the fact is it's not us, that's the stock behavior. So investors are concerned. And the question is, where are they wrong? Meaning, what are the growth opportunities that you see in front of you that could prove...

Let me answer the question, but I also need to address some of the inaccuracies. So we the store went up 8.5% on Friday, it went 9.7% yesterday Monday, basically the same as they [indiscernible] or ServiceNow, et cetera. So I don't know where you get the 2%...

It was since the beginning of the year. So it went down, in the last the last role, right?

So listen, we -- our business is for 2 or 3 years, nobody really knew whether Gen AI first, then AI than Agentic was going to be a tailwind or a headwind for enterprise over companies. The world was divided. We -- I joined the company in 2011, they left for 3 years and then came back 3 years ago to be the President and Section 16 Officer and Head of revenue. And I mean, we were, I would say, cautiously paranoid about what could be happening. Last year, we saw it very clear. AI is a massive win for our business. We were competing in a crowded market where we are the absolute leader in a category, SaaS CRM. We've been doing that for 27 years. And we have amazing growth when we are small. But then when you -- as you grow, as you grow, as you grow, the growth starts being a bit more difficult and it's a multi-hundred billion TAM market.

All of the sudden AI is doing several things for us. So first of all, everybody loves AI. Everybody loves the AI labs. The intelligence utility is incredible. But in the enterprise, to convert that intelligence into proactive work, there are a lot of things that need to happen. You need to have the deterministic workflow. You need to have the right context for the data, you need to have the compliance, the government, the permission sharing. That [indiscernible] infrastructure that we built over 27 years is the big difference between beautiful AI for the consumer and productive AI for the enterprise.

So we are very well positioned. AI is making our products easier to implement, easier to use, easier to enrich and put data into and easier to consume. So it is making our different clouds more valuable for our customers. And then AI is giving us -- is opening a door of a multi-trillion, multitrillion TAM market, which is the digital labor. So today, we had the SaaS market, people continue, by the way, the number of seats, the number of salespeople, the number of service people still continue to grow. We can later talk about what happens if it start declining. We can talk about that because for some companies, in some industries, at some point, the number of seats may decline, okay? But forget about that for 1 second.

In addition to that, which is our traditional business that was decelerating, all of a sudden, you have an opportunity to monetize AI in different ways. First of all, the existing sets, we are upgrading them to our higher-end SKUs, which we call it Agentforce One Edition, Agentforce for Facility, Agentforce for Service. Every time we do that, on average, we do anywhere between 60% and 80% uplift. That's pretty big. And customers are very happily paying because now they have access to all the agentic capabilities of our product.

The second way that we monetize AI is because AI has made our software easy to implement, easy to enrich and easy to consume through conversation, then there are more seats available to us. If you look at our last earnings, 7 of the top 10 deals were customers that found new people, new humans to use our licenses or more licenses. It's the opposite. People think that AI is going to reduce licenses, so far, it's increase in licenses.

And then the third way to monetize, which is probably is 50% of the monetization that we do is what we call Flex Credits. So we basically, for customer-facing use cases of agents, those agents need fuel. So we charge them with fuel. We call them Flex Credits. And we put enough in the time so that they get going. Sometimes they buy for the next 3 years, sometimes they buy for the first 6 months. And then customers come and refill the tank. So we are seeing an explosion of Agentforce, which is one of the main drivers. Our core clouds now are better, so they are growing also, and they're growing healthily.

Then you have products like Slack that is exploding. And then we run a very diversified portfolio of products. And every quarter, there are some products and geographies and industries that they don't perform that well. But when you look at our numbers and the most important thing is, the [indiscernible] is net new bookings. So you sell new bookings, and then the net is because there are customers that are treated. Our attrition levels are decelerating and our bookings level are increasing. The difference, which is the [indiscernible] is accelerating. And we saw that last year after a great Q2, the best Q3 ever, the best Q4 ever, the largest Q1 ever that we just did, then the net NAV is accelerating significantly and is growing more than the AUV. And when the lines crossed and they crossed last year, the cross in H2 last year, they continue to surpass the net NAV growth continues to surpass the AUV growth in H1. That is when AOV accelerates organically. And that's what happened.

That's why we committed a month ago, with less visibility, but with a lot of conviction, we committed that the revenue was going to be accelerated in H2, and it's going to reaccelerate. In parallel, Informatica, the revenue on a on an organic basis is reaccelerating significantly. And then we are many other places that we can monetize, and we can talk about that later.

What is the core value of Agentforce? Meaning what do you bring with AI to customers. And you touched on it at the beginning. Why would they use your offering versus going and trying to develop it on their own. And I'm just talking generically.

Yes. Listen, Probably, I remember when we started, there was a website. I don't use it anymore, but remember, there were like 20 agentic platforms. And then 6 months later, this was 2 years ago, there were 150. Probably today, there is 10,000 agentic platform. There are 10,000 ways, there was 1,000 companies that offer a platform that you can build agents, okay? So why would you build agents with Agentforce and not with all the platforms.

So first of all, Agentforce has a number of advantages. Think of in Agentforce like an opinionated hardness or commercial use cases. So where you have direct access to the context of your CRM because it's surfaced through that harness. You have access to the hundreds, sometimes thousands of flows that customers have developed in their orgs, because when a customer implements Salesforce, what they do is they qualify their standard operating procedures in our software, and they build flows. We have a full -- they build workflows and all the workflows, it's like a library of workflow. They're available in their org. Agentforce has native access to those flows. Agentforce can easily hand over to humans back and forth. Basically, that's one of the biggest differentiators, customer, you cannot do that with other platforms. Agentforce is embedded. Agentforce allows you to choose whatever LLM you want to be on the back end. If you use -- and then Agentforce has many other advantages, and has 29,000 customers, which means that nobody in the world has the amount of customers that we have, which means that we've learned.

Our Agentforce for today, the platform, is 1,000x better than it was 2.5 years ago when we launched it. The same way that some of our competitors have increased improved. But when you have 20,000 customers across many industries, geographies, you learn a lot. By the way, some big CEOs and big personalities in the industry, they would tell you that, that agentic layer is going to be commoditized, okay? The good news is, be my guest, build agents on another platform. I want more agents. Agents are users that use platforms at a high scale. We started saying the world of AI is humans and agents working together. We changed our tag line in the company. now is humans, agents, leveraging platforms working together.

And the beautiful thing is, if you don't build your identic layer or your specific agents typically, companies use several agentic layers to build different agenting use cases in the company. That's okay. Because if you want to attach to customers, you will most likely go through our platforms. And that's other big thing that is happening. This is the one more thing like Steve Jobs. That is our Headless 360 strategy that we just launched. Every part.

Okay. So then you can ask a question.

Go ahead here. Yes. Because for me, probably the most exciting thing that we have and it's on top of what we guided.

Why is Headless different than the regular agentic opportunity? Maybe for the basics for those that don't know the company and don't know the space of Headless, why is headless different? Why is it growing? You spoke about it also on the call on the conference call. Why is headless growing the TAM.

Yes. So growing Headless can significantly or will significantly expand the TAM. We are still not factoring any of that in our H2 revenue reacceleration or in the profitable growth [indiscernible] $63 billion and Rule of 50, which is good news for investors okay? So what is different? It's a fundamental difference, before our software, by the way, most enterprise over where a full stack with the database, the workflows and the permission in everything and then we put the identic layer on top. So customers pretty much if they wanted to build agent workflows on Service Cloud, they need to do it reinforced.

Now we decouple all those layers, and we've exposed everything and we wrap them with MCP servers. So you can access the data. You can access the workflows, you can access even Agentforce, you can access lag through MCP service, which means that anyone, anyone, anywhere in any surface. I mean, many of you may be working on Slack great. You can access our [indiscernible]. Many of you may use Cowork, okay? It's very popular now. I use Cowork myself. Well, you use codec or you use another platform. So now you can use our software. In fact, I like to be controversial like you. And people are saying, okay, but people are going to vibe code this CRM. And we've been saying for a long time, that's not going to happen. People are not going to vibe code this CRM, because then they have to buy operate them and then maintain them. And now I say the opposite. I think people are going to vibe code this CRM. That's the future.

They're going to [indiscernible] because they want, those components that are already secured, they are trusted that the uptime is the right thing that you can respect permissioning, et cetera. So it's humongous. It's so big that we are afraid of we need to -- we are very cautiously we're talking and working with our biggest customers, our biggest partners to find the right monetization strategy because our #1 value remains customer success. We don't want to introduce -- we don't want to either say like our friends from Germany, oh, no, nobody access our platform or other companies that try to really take advantage of the opportunity. We just want to do something that is fair.

If you are using our platform in a way that wasn't meant to be because a human being used to the platform maybe engage with the platform. I mean, if you're in a call center, maybe 50 times a day, if you are a salesperson, maybe is 10 times a week, if all of the sudden, there is an agent doing that on behalf of a person or on behalf of an organization and a success in the platform 1,000x more. Well, first of all, our cost to serve, I mean, we'll go through the roof, so we need to monetize that, and we're working again, and every conversation we're having is incurrent constructive, [indiscernible] understanding, and it's going to be a huge opportunity for the future.

Got it. Agentforce grew like 20% year-over-year this quarter. It grew 50% sequentially. Where are we, two questions. Number one, how do you help customers adopt it? Meaning you spoke about flex spending. Can you talk about the program? What is flex spending and how does it help adoption?

And number two, where are we in the deployment cycle, meaning when you talk to your -- you have so many customers, 20,000 customers, when you talk to your customers, do you need to convinced you need to educate them about Agentforce? Do you see deployment? Or is it really at the beginning? I'm trying to understand where are we not from a technology point of view, but from a market readiness point to deploy Agentforce.

I think that's another piece of good news. I mean I'm very, very, very close to where the agentic action is happening. I'm talking to I'm very curious to intellectually to understand what is this new trend. And I would say that customers overall, forget about Agentforce, across the board, they are in a nascent period in the agentic transformation. We put -- we've done one thing that is very cool, working with external consultants. They are working with our expertise of 83,000 people and 150,000 customers. We've mapped what would be -- how would every customer in every industry. So we -- I think we [indiscernible] 17 different industries. And in every industry, we look at the top workflows and for each workflow, how the workflow will be identified. And then we come up with agentic use cases. And then we map them and then we create a library of agentic use cases with a lot of information what data they need, what do they do permissioning, got rails, et cetera.

So every time that I talk to a customer, I put a slide with anywhere between 120 and 180 use cases of agents. It's overwhelming. I call the eye chart across the workflow. They understand the workflow. I then pick up a few examples on how the process works today and how they would work with agents. But then I tell them, listen, I know the company is not ready to do that because companies need to be ready. You need to have the change management, but also you need to have the data. You need to have the legal checks and balances on any identic use cases. And I always position what we call the hero agents, the 5, 10 use cases that are powerful that I know are easy to implement.

And customers today, they are probably in the first 2, 3, 4 initial use cases of a at least of 100 and 120. So they're in very early stage. Every company, the first thing that they realize is the data is not ready. There is not enough and the quality is not there. is not clean. It's not connected, it's not been leveraged sometimes. And by the way, that's why we invest in Informatica. That's why we created this layer at the bottom, we call the Data 360 layer, or the Data Foundation layer. That is a combination of Informatica, [ Meso ] and Data Cloud is a $7.5 billion business growing double digit. And it's going to be a big differentiator for Salesforce because everything starts with the data.

And then if you have the right data, the right context, agents are not going to do ship. And this is where everybody starts. I think, every time that I tell the story, I get very well prepared for the earnings and go and go to the top 100 use cases of customers. And I get surprised because I have the same names that I talked about 3 months ago, oh, but they only had 1 agent, now they have 5 or they only have 1 million AWEs, now they have 10 million. It's live. It's an exponential acceleration. That's why the AWE use that at the end is a metric that you need to follow very closely. -- because it's real productive work, and I can walk you in a different context exactly at what -- how we measure AWE is because this is real work, it's not just taken.

That is exploding, we grew double the AWU quarter-on-quarter, 7x Q1 versus Q1. And it's -- we are just -- I think in 5 years will be probably 500x more consumption than we are today. It's that big, and we are solely in the game. And it's everyone.

Do customers feel comfortable with pricing? Meaning the whole industry goes from seat-based pricing to consumption-based pricing. How do you help your customers to make the transition?

I love you. Because we -- I have like 10 or 12 questions that your team has told my team that maybe you may be asking, and this is the first one in the list. So Thank you.

Perfect. Perfect. So the question list is just to -- I just want to make sure that I don't run out of questions.

Everything else is actually I was going to tell you at the beginning ask me anything, seriously. There's nothing to hide. So pricing has been fascinating, to see what's happened with pricing. We had listen, no idea. We were probably the least sophisticated company in terms surprising because we were selling by seat. That was our only metric basically on the pricing until 2 years ago. Then we launched a in Agentforce, and we launch it for with -- we thought we were very negative conversations. What is the conversation? Well, we don't know, but it sounds good. And it's -- then we defined it in the contract like the back and forth between a customer and agent over 24 hours, okay?

And then very soon we realized, okay, $2 per conversation, is that too much [indiscernible]. So fast forward 2 years, we are meeting customers where they are in their agentic journey. We are highly sophisticated. I mean what I'm saying is that more customers want predictability. So we have two ways to show predictable pricing. One is for internal use cases for human users of our licenses. We upgrade them to the genic version, which is the higher the premium version, typically with a 60% to 80% uplift and then they have unlimited access. We meter, but for them, we don't have meter. So no matter what they use, they pay the same. They like that a lot. In fact, those SKUs that are now is a multi-hundred probably as or $80 billion business, is growing 60%, okay?

And then the customers that want, okay, but I want to have customer-facing agents, because have a demand plan of agents are going to deploy 20 different customer-facing agents and they're going to be consuming credits and data, et cetera. So we build a demand plan. You're going to need all these credits, all this data. And the customer said, what if it's very successful and well, it's going to be more. Yes. But what if it's not successful, it's going to be less. Okay, I'm going to fluff. So we do the ILS -- unlimited the agentic enterprise license agreement, which essentially is unlimited, we fix the price, we still meter to give the information to the customer, but it's unlimited. And sometimes, customers win. And when customers win, we always win because then the renewal comes and then the customer is -- have deployed 10 agents out of 100. So okay, they want in the first 10. But at the end, we don't want to win or lose. We just want to have a fair business with a fair margin, and that's what customers want from us.

And it's predictable, it's beautiful. There are customers that are putting their toe in the water and they don't -- they just want to say, okay, I don't want to pay anything. I just want to pay when the agents consume perfect, as you go [indiscernible]. And there are other customers that say, Okay, I think I'm going to buy 1 million credits. And then you can use it in 2 years. Okay. So we are meeting customers. They are the last thing, particularly enough because we deploy some out-of-the-box use cases like agents or operations agents. And now we can price per business metric based on value. I'm telling you, I lot of business value. When I've done business value pricing in the past, we've made a lot of money.

And then customers maybe share business value, but then at the end, they say, no, I want something flat. But we are Today, we have like 10 ways to price Agentforce or agentic. But if the customer wants an 11 or 12, we'll do it too because we are all learning together. And at the end, I want the best for the customer.

Got it. We have 2 minutes left, and I don't want to completely dominate the meeting. Is there any question from the audience? Just raise your hand, we have a microphone, sure. Do we have a microphone for the audience?

[indiscernible]

[indiscernible] Yes. Premium, which typically means their pilots. Let me start with the end in Q1 in the top 10 deals, that represented $800 million of bookings and representing 2.5x more than the Q1 last year. In those $800 million, there were 3 deals that were pilots, that were successful pilots, and then went into production with a very large deal. They made out of 90,000 transactions, they may be the top 10. So they were good.

So what -- I think the -- what makes it work is having the data having the legal frameworks in place, legal is important. Legal needs to be part of the whole thing because there is a new thing about liability, share liabilities. It's -- now these agents are doing what humans you to do work many times with customers, which is what from a legal perspective, you need to cover that. And then the business value needs to be there. Then the reason that there is a change management that is very important. Typically, the good successful pilots are those where you are on top of the agent, and you are on a daily basis, understanding that's why an agentic layer, a powerful agentic layer is important to do the right testing, the right monitor and the right observability. You're listening to what the agents are doing and real-time changing and because otherwise, the agents drift.

[indiscernible]

Yes. So for us or for the customer? Both. So I mean one of the beautiful things about this new capability. I mean we -- for 27 years, we've been buying and either organically or organically, we've been adding new capabilities through our Customer 360 Suite, we add in Marketing Cloud, and we are Analytics, and we have it. Every time that we added capability, we were able to monetize the customer another 10% or 20% more, okay? The beautiful thing about these new agentic capabilities when customers start the agentic journey with us. They all of a sudden, they use our software in a step change of how they use our software in a totally different way. And that gives us the opportunity and again, the fair opportunity to monetize them in a also a step change.

So when customers start the journey after the initial pilot, the first bite of the apple, we increased our -- they increase their spend with us by 50% or even 100%, they double. And then we see, on average, those the customers that are fully advanced, there are 3, 4 times the original AOV before they started the agentic journey with us, 3 to 4 times. Again, we started this when we were a $40 billion ARR company, more or less, now we have $46 billion or a little bit less than $40 billion.

So if we get every single one of our customers to start their identic journey with us because every customer is starting their agenting journey. The question is, are they going to do it with us or with somebody else? I think we are very well positioned so that we are the chosen platform for them to become agentic, at least in the front office. And when they do that, their revenue with us goes up 3 or 4x, which is beautiful.

For the customer, the ROI, every use case is different. But Typically, the ROI of an agent is much higher than the ROI of the equivalent human. What you're finding many times is humans and agents, leveraging platforms working together, and they come up with new use cases, new services that they were providing to the end customer that they before didn't do. And customers continue to invest which is a good sign of good ROI with us. And I think there is another discussion, maybe that's what you have in mind, which is the tokens discussion. I'm not an [indiscernible] line provider, so I cannot answer, but our role is to also optimize that for our customers. We are -- we will become a gateway between the agentic use cases and the LLM. The LLMs are utilities. And doing depending on the time of the day or the use case or whatever, there's one that is going to be cheaper than others, and we're going to go to the right one for the right use case of that agent.

I know we're having fun, but we are over the time. I want to thank you, Miguel. This was a terrific session. Thank you so much.

Than you for the opportunity. Thank you everyone.

Good morning, and thank you for joining us. I'm Valmik Desai, Vice President of Investor Relations. This session marks the fifth in our series of quarterly post-earnings webinars aimed at providing you all with a deep dive on our latest product innovation, super excited for today's session. We will deep dive on Headless 360 and Slackbot. And as you heard on our earnings call earlier this week from Mark and the team, we're incredibly excited about the opportunity ahead with Headless 360 bringing together humans, agents, headless platforms. So customers can really use Salesforce with any coding agent across any surface. We're also seeing incredibly strong momentum with Slack and with Slackbot, which we're super excited about, personally my favorite product right now to use. I wake up to it every day. It's rapidly helping our customers become agentic enterprises.

Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties and assumptions, which could change should any of these risks materialize or should our assumptions prove to be incorrect, actual company results or outcomes could differ materially from these forward-looking statements. A description of these risks, uncertainties and assumptions and other factors that could affect our financial results or outcomes is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q and any other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements.

All right. With that out of the way, I'm super excited to have Joe Inzerillo, here with us. He leads our enterprise and AI technology business, also has the coolest background in the business. So thank you for joining us, Joe. We also have Rob Seaman, who runs Slack here. We're going to start with the brief presentation, with Joe kicking us off and then we'll jump straight into your questions. Now I know this is definitely not a shy group, but please do submit your questions in the chat. And with that, over to you, Joe.

Great. Thanks, Val. So back at TDX, which seems like a lifetime ago, but it was only, what, 6, 8 weeks ago, we announced Headless 360 and the response has just been unprecedented. People are super excited about it. But there's been a lot of questions about what it is. And so I thought we'd spend a little bit of time talking about that.

So we go on to the next slide. The thing about the whole concept of Headless 360 is really leveraging the stuff that we already have. So if you think about things like our data layer, the layer of context, the layer of work, where all of our apps sit, the agentic layer between Agentforce, Slack, Tableau that sits at that level. And we have an engagement layer up top, where you could see our new Agentforce Coworker, Slackbot, some of our customer apps, custom apps and things like that, that sit up there. But Headless 360 is really meant to be that glue that gives the customers and actually ourselves internally huge flexibility in how we want to represent all of that goodness that sits in the stack below it.

And so previously, at Salesforce, we and our Salesforce admin, were really talking to the computer to provide instructions in advance to create an interface for humans to use. We're now in a world with agentics where we could actually have the agents create the UI on the fly. And Headless 360 is the way that the agents know how to use the Salesforce platform and leverage that 27 years' worth of goodness and history that's baked into it. And so it's really about liberating folks and the way that they want to do it, but liberating them through agentics. And so that's the part that's so exciting is that unlock -- to get the wheel spinning to get these new types of applications that people have never thought to build working and when it works, it's like magic.

So we're going to dive into that a little bit. So generally, in the Salesforce ecosystem, you have a user who is asking for something directly. And so they may be talking, let's say, Claude. And the agent knows how to then go and hit MCP endpoints inside the Salesforce ecosystem to ask questions. And it knows what questions to ask because these aren't just APIs, they are MCPs. So they describe semantically what they're capable of doing. And that allows humans and agents working together to drive more value. And obviously, this works all over the place. It works in Slackbot under the hood. That's the way Slackbot's working right now today. It works in Codex. It works in Claude. It works in all the major AI platforms. But it really is this work where you want to work with the tool you want to use, but still leverage the capabilities of the Salesforce platform. And what we've seen is when people adopt this pattern, they consume more of the Salesforce platform than they ever have because they're liberated to do so in the way that they want to do it and they can use the agent to really double down on the capability set.

Go to the next slide. So I think one of the things that I love about this is just seeing the utilization. So you could see SaaStr -- I think we skipped one there. like the one forward. Here we go. You can see SaaStr on the next slide here. And I love that example with them because they actually put out a tweet that essentially said, I'm paraphrasing, they've reduced their Salesforce licenses, but they've actually been paying more for Salesforce and it's worth every penny because they were able to use some of the early capabilities of the Salesforce MCP, which is really where Salesforce Headless is going to actually build their own custom interfaces. And that allowed them to just leverage more of the platform than you've ever been able to do before. And that's the kind of creativity that we've seen happening in the community and Headless 360 is really speaking to that.

And so the Headless 360 brings the humans and the agents together in Slack. And so we use this internally when we're building Salesforce experiences in Slack, they come preintegrated. So if you think about, for example, our Slack CRM is really Salesforce power sitting behind the scenes, the trust layer, the application layer, the context, everything that you've always loved on this. And at the same time, it's actually in Slack. Looking native. Nobody would ever know that Salesforce is behind the scenes because the interface is the Headless -- the Headless interface is Slack. And so no better way to actually show you that. So I'm going to bring on Rob, who's actually going to take you through a couple of slides and then show you what this looks like in practice. So with that, I'll hand it over to Rob.

Thank you, Joe. And as you heard on the earnings call, obviously, we're having a ton of traction and success with Slack in the market right now. We're very excited to meet this moment because we think it truly is where AI is going to work moving forward. So if you go to the next slide, one of the things we're seeing is, obviously, there's a ton of money that is being poured into AI by our customers and a myriad of companies around the world these days, but there is a missing piece. And outside of agentic coding, obviously like a true translation of that spend directly to employee productivity. So if you go forward, we think what's missing is something that actually connects all your people. You look at a lot of the traditional communication vehicles, whether they be e-mail or text or whatever it might be, they're siloed in their nature.

And you look at all of the agents that are out there today, like typically, they are a single-player, they are deployed into a web-based interface or embedded in a SaaS app. They don't necessarily allow people to talk to those agents and then share those results back with other people. And then every platform ultimately isn't necessarily talking to each other. So what we think needs to exist is something that connects all of these things, but does so very importantly, into a multiplayer run time.

So if you go to the next slide, we call that a work operating system for this AI age. And if you go to the next slide, that is how we are seeing people start to use Slack within our customer base, where all of their employees, their partners, their contractors, even their customers are working with them in Slack. They've deployed all of their agents from Agentforce and other third parties like Vercel, Claude or OpenAI directly into Slack. And then they have all of their other platforms connected into Slack as well, which can then be used by their agents and by their people.

If you go to the next slide, we're seeing this actually play out at some of the biggest companies in the world. But what's really exciting is the most innovative AI companies in the world have gone all in on Slack. And they've not only used Slack to run their business, but they're actually building their products to be used in Slack because it is that multiplayer AI run time. And a couple of great examples are actually Anthropic and Shopify.

So if you go to the next slide, you may have seen on Lenny's Podcast with Cat here, who's the Head of Product for Cowork and Claude Code at Anthropic, said, "Slack is basically the core operating system of their company." What's really interesting about Anthropic is every single one of their employees has a public thoughts channel. We do this within Slack. We've seen Vercel do it as well. A number of other players do it, where every single employee actually just thinks out loud in Slack. And the default is work happens in public. And so if you think about what that actually does is that raises the collective knowledge of your employees, but it also raises the collective knowledge of the agents that you deploy into Slack.

And if you go to the next slide, you'll see at Shopify, what Tobi says here, Tobi and Shopify built an agent called River. So they want all of their agentic coding to actually be done in public in a multiplayer fashion. So what they've done is they've actually deployed it into Slack. And you can only actually use it in public. And what's fascinating about this is what Tobi says here, "So the risk of today is that AI does the work, and we as humans don't learn from it as a group."

And I think that's the downfall of kind of the single player scenario. But when people work together with their agents in public, the opposite really happens, which is the best prompt pattern spread and the best knowledge spreads. And that's what we're actually seeing in Slack with third-party agents and with Slackbot. And so without further ado, I'm going to show you Slackbot. So I'm actually going to walk you through a series of things that Slackbot can do. And let me share here. Can somebody give me a verbal that you can see?

Yes, looks right.

Cool. All right. So this is Slack. For those of you that don't use Slack, I'll do a little bit of orientation on the left-hand side here is our side bar. In the middle of what I have open is a channel, and this is a Salesforce account channel. So you see at the top here how it's account. This obviously has a message stream on how account managers keep the entire company aligned around that customer success.

But you can see within here, I can see the details of that account from Salesforce right here in Slack. So first great example, I think, of Headless 360 is this is all dynamically rendered interfaces based upon the metadata that exists in Salesforce. But what I'm going to do is open my personal agent, which is Slackbot on the right-hand side here. So if you look over here in this flex pane, what I'm going to do is I'm actually -- a lot of salespeople are out on the road, and they may take chicken scratch notes, either handwritten or in their note-taking tool of choice and may eventually need to put those into CRM.

So what I'm going to do is I'm going to take the chicken scratch notes that I wrote on a cocktail napkin about this contact, Kevin Marshall, and I'm going to ask Slackbot to just log a call, for that contact for the B2B commerce opportunity. And so what's interesting here is you're going to see Slackbot. One could actually read this image, which I think is pretty straightforward these days. Two, has the context of the account because it knows that from the screen that we have the account channel open. So it knows what account it's related to in Salesforce. And three, it's actually going to headlessly interrogate Salesforce, find that account, find that contact, take these notes from this image and actually write it into a task associated with that contact, that account and that opportunity in Salesforce.

So we always put the human in the loop. So in this case, this is giving me a notification that it's going to create a record in Salesforce. I'm going to go ahead and say, "Great, go ahead and do that." So I think that's a first quick example of using Salesforce Headless. Again, think of Slackbot as kind of the first best customer for Headless and using Salesforce Headless to meet users where they are and provide an exceptional and conversational experience. Now what I'm going to do is I'm actually going to ask Slackbot what sales plays and customer stories would be relevant to leverage for this particular opportunity? Now what you're going to see here which is fascinating, is another example of Headless. So this is actually fairly specific and strategic questions being asked here that requires some domain context specific to the sales organization, their content, their copy, et cetera.

So if you look down here, you can see Slackbot's actually asking the sales agent. So this is Slackbot calling and orchestrating directly an Agentforce agent. And it's doing so through an MCP tool call. I could open this and I can see what is asking the sales agent. You can see it's given this specific prompt that is given to the sales agent to go off and find those sales plays and customer stories. And again, it's doing it within the context of this particular account, the opportunity that I mentioned and that contact.

And so here, it's coming back with customer stories. It's denoted those that are shareable with Kevin externally. Those that are internal that I can't share with the customer. And so this is extremely helpful and saves a ton of time for a sales rep.

So now what I'm going to do is I'm actually going to ask it to translate all of these insights and these customer stories into a Word doc that I can share with the customer. So what's really important is all the Slack users typically have their calendar, their productivity suite, whether that's Microsoft or Google already connected into Slack. And Slackbot because of that can then act in those systems on that user's behalf.

So one, this has created or logged the call with Salesforce for me , it's found relevant customer stories; three, it's actually going to write a document. I can go off and share with my customer, but it's going to do it in the productivity tool of my particular choice. So my company, in this case, uses Microsoft OneDrive and Word. So this is actually going to go create a Word document. So it's -- I'll actually in fact, that this is real, it's going to -- you can see it said that it is sending me the Word doc, but it didn't actually send me the link. So here is that Word document. So when I open that, I can see what it has generated.

All right, now I want to keep the team going back to the multiplayer angle, I want to keep the team up-to-date on what's going on. So everything here has been kind of a single player. It's been me working with Slackbot. So now what I'm going to say is, "Hey, Slackbot, has like, well, go ahead and drop the message to the account team that summarizes the customer stories that I mentioned and our next steps for [indiscernible]." So when I do that, Slackbot is going to compose that here, but can actually send a message on my behalf back into this channel, and that is going to take what has been a purely single player experience and make it multiplayer, which is immensely powerful. And I think one of the things that we were able to do in Slack that you can't do it in a single-player environment. Now I'm going to hop over and I'm going to show a few more things that we're very excited about that are a little bit more involved. And so the first thing I'm going to do -- sorry, I actually wasn't ready for this, I apologize. Let me open up like Google Drive real quick. Can you give me just a second? I'm going to open.

Someone at home is pausing every single frame and analyzing what Rob is doing.

Exactly I'm going -- give me just 1 second while I stop sharing here, and I'm going to pull up the spreadsheet real quick that I need for this demo. So if you give me a hot sec.

I think this also emphasizes our commitment to transparency and showing it actually happening as it happens at Salesforce.

Absolutely. So let me share again here. All right. Can you see now?

Yes.

Cool. So what I'm going to do is I'm going to go ahead and get this prompt going because this one is actually going to write some code. So over here on the right, I'm going to basically ask Slackbot to use the S&B Q2 forecast tracker spreadsheet and build the 6-page interactive report for me. And it's a pretty detailed set of instructions. So I'm going to kick that off. This will actually take a few minutes because one of the things that's interesting about it when I show you the spreadsheet that it's going to find and read, it's actually very computational and data intensive. And so it figures out that it needs to use Python and it's actually going to write Python and execute that Python to do the analysis. But I'm going to hop over and actually show you that particular spreadsheet. So -- but I think the first thing to tell you is that I didn't give it a link to the spreadsheet. I just said, "Hey, can you look at that Q2 forecasts that are in a spreadsheet." And it goes off into this case, Google Drive and it finds it.

So what I'm going to do is hop over to Chrome, and I'm going to show you the spreadsheet. So this is kind of dummy data, but it's an actual spreadsheet used by a sales team here at Salesforce. And so I'm going to click through really quick and show you like just the degree of complexity that's in the spreadsheet, the number of tabs, the amount of data. This is just not something that a human being can like genuinely look at and be able to make the most sense of. But Slackbot can do that for me. So it's off executing against that right now. What I'm going to do is I'm going to go pull up a prior version that I executed and show this to you.

So when I hop up here, you'll see what it comes back with. So it came back with, hey, I've actually created that for you. But when I open up the details of what it's done, let me actually just show it too, which is in is a better example. This has actually created a dynamic user interface on the fly that didn't exist before. And this is, I think, the power of Slackbot, but also the power of the Salesforce Headless 360. So this is query Salesforce. It's read that spreadsheet. It's joined the information between the spreadsheet and Salesforce. It's taken my prompt and then dynamically generated this interface. So I can see a risk matrix of my deals where I have gaps to commit.

It can see where we have velocity and coverage issues. I can do some what-if and scenario modeling, if I wanted to, to see what might happen and overall health signals. This is something that probably would have taken a human being a while to take care of before that we're now able to do in a really quick fashion. So I'm going to hop back over.

I'm going to close out of this, and I'm going to show you a different prompt. So when I hop back in here, you'll see the second prompt I gave it is actually saying, okay, we have a QBR later this week. I want you to leverage the presentation design skill and put together an executive summary PowerPoint presentation of the team's performance. So based upon this dashboard that's happening here and what -- this is important to highlight, this actually leverages our skills framework, which is new.

We just turned on for customers this week. So Slackbot Skills are a way for end users to actually define kind of micro agents or tasks or processes, if you will, and then share them with their team. We've got a series that have been built by us. We've got those that have been built internally at Salesforce. We have some that are recommended based on social proof and sharing. But these are really, really powerful.

And so when I hop in back in here, you will see that what Slackbot used is that presentation design skill, which I'll open up here. And this just through natural language gives it some instructions on how to actually build a presentation, and it spit out this PowerPoint presentation, which I'll open here.

So as I scroll through this PowerPoint presentation, you'll see this is a translation of that spreadsheet, what's going on in Salesforce in that dashboard that was created into something that's consumable in a meeting that we can share. So I think this is, again, something that people spend a ton of time actually going through the production of that we can get human beings out of the production work and back into that kind of creative and critical thinking.

So I will stop -- actually, one last thing I'm going to show you on the multiplayer element. I want to show you a real channel in Salesforce called How I Slackbot. This gives you an idea of the kind of social nature and multiplayer nature of AI and Slack. This is not a channel we created. The users created it themselves. It's called How I Slackbot. We now have 4,600 employees that have opted into this. And every single day, these employees are sharing skills that they have built. And any employee can hop in here and add those skills to their Slackbot and releverage them. And it's just become this incredibly vibrant AI community. It is ultimately up to the AI fluency of the Salesforce employee base as a whole. And with that, I will stop.

Awesome. Thank you, Rob. Thank you, Joe. That was awesome. We have a ton of questions coming in. I'm going to start with one here from Gregg Moskowitz at Mizuho. It's focused on kind of the opportunity that we have with Headless. And he says, "While Salesforce's Agentforce disclosures have been very encouraging from an adoption standpoint, it hasn't yet been visible from a revenue standpoint. Given that Headless 360 opens up the Salesforce platform to external AI agents and coding tools via MCP. Do you think this could be the mechanism that puts Salesforce more directly in the token path?" So maybe, Joe, you can start with that one.

Yes. Look, thank you. It's a great question. Thanks for the question. Absolutely. I mean I think Headless 360 is what the market has been asking for us to do with our agentic technology. They saw what the capabilities were with Agentforce and what it could do internally. And I think it's one of those things that have clicked for us and it clicked for the market at around the same time that like "Wow, wouldn't it be great if all the coding agents could take advantage of everything that Salesforce had to offer." And I think the Headless 360 strategy is really about empowering the ecosystem of agents. So there's no question that there's 2 things that we have real high confidence and we have data that gives us this high confidence, which is this is something that people want. And the people that use it consume more.

So it gives them more Slackbot because it takes the things that have been happening in Salesforce historically at human scale and changes it into agent scale. And that agent scale is the humans and the agents working together but the agent scale is just much, much, much larger and freeing it up so that you can just bring the tool of your choice to bear on Salesforce.

In some cases, that's the completely vertically integrated Salesforce stack. In other cases, it may be components like Cowork or some other LLM coding tool or operations tool that you could just basically attach to Salesforce and go for it. So I absolutely think that this is one of those things where every MCP interface that we've turned on at Salesforce immediately gets lit up with traffic. And we see that traffic just continuing to grow because the demand is there because what we have in the core platform is just so valuable.

Awesome. I do think I'll add one thing. The way we're looking at the long-term opportunity here is exactly as Joe described, which is we feel that more people are accessing the platform, the more they're able to actually surface those insights wherever they want to do that work is super valuable for us, right? And it's super valuable for our customers. So when we start to see more usage patterns at more kind of use cases that really start to proliferate, that's where we're going to work with our customers, work with our ecosystem and understand what is the right way to kind of capture value on both sides of the equation for customers for Salesforce. So certainly more to come there, but it's totally the right question to be focused on.

Our next question here comes from Rathin Yagnik, my good friend and our investor at Adage Capital Management. "Is there any initiative to have the UI of Slack itself from purely text and image-based presentation interaction to a more dynamic richer interface. For example, having something like Tableau more closely integrated into Slack, so you can see ad hoc visualization?" And I think Rob showed some of this, but maybe, Rob, you can touch on the future road map here as well.

Absolutely. We did show a few things there, which was we showed specifically the on-demand creation of like a dashboard or a dynamic surface. But I think what's most exciting for Slackbot is 2 things. One is MCP and the MCP UI standard that's emerging. So basically, any MCP tool that Slackbot can call can actually generate MCP UI that can be then rerendered in Slackbot, which inherently makes it more dynamic. But also coming back to Headless 360 is the Salesforce Headless experience layer. So there's so much rich metadata in the Salesforce platform for Salesforce customers like they've expressed the way they work and do business. And in Tableau and the way that they've built their layouts in Lightning. And that could all be transposed basically and shown through MCP UI and Slackbot. So yes, Slack, think by just the nature of consuming MCP and MCP UI with the Headless experience layer from Headless 360 is going to become much more rich visually.

Yes. And maybe just to add on, if people want to see a glimpse of what this looks like, when you turn that dial to maybe not 11 yet, but at least a good solid 8 is take a look at Slack CRM and when you look at it, you are doing deep work that historically, you would have gone to a rich Lightning interface to do, but you're now able to do it in Slack. But to Rob's point, more importantly, the agent is also able to do it with you in Slack and so you see that you could do the deep work on a very rich surface, but you could also have the agent to do that work on your behalf and you can collaborate multiplayer with the agent. And I think that's a big thing. Multiplayer is not just a human thing. It's the humans and the agents collaborating together in a multiplayer scenario.

Awesome, we're going to stay on the Slack and Slackbot subject here with a question from Keith Bachman from BMO. How does Slack compare and compete against Microsoft Copilot and I think it means Slackbot there. It seems like a lot of overlap with Microsoft and yet Microsoft has underlying personal productivity tools. So maybe, Rob, you can start there.

Yes. I mean the way I think about it -- I'm not going to sit here and necessarily talk about our competitor's products or a partner's products. But what I would like to say is like what makes Slackbot magical is the work that we have done to actually -- we call it being a good host within Slack. But the work that we've done to kind of tilt the umbrella and help users on board and help with the AI fluency. So one, I think that is something that you don't see in a lot of like the single player instances of AI tools that are out there today. Two, the other thing that I would say is like there's just a tremendous system of context in Slack.

So if you look at the way people actually use Slack and like the bias towards working in public channels and having these longitudinal channels that the membership changes over time. There's just a significant amount of context where it can like immediately. So I think there's no cold start problem. They can start writing like you. It can start understanding your company's objectives and priorities almost immediately. And then another like ease-of-use thing, frankly, is that it inherits all of the connections you already have into your Slack, right? And so 70% of our customers are Microsoft shops. And so I can use Slackbot to book a meeting through Outlook? I can use Slackbot to write a Word doc as you saw or create a PowerPoint presentation for me. So it's just like -- it's incredibly facile in the sense that it helps you get up to speed on AI. It helps you share AI with your teammates. And it actually helps you connect to other systems and operate in those systems, I think, faster than anything else we've seen.

Yes, absolutely. And just maybe to add to what Rob is saying. I think when we think about the fact that we live in an incredibly heterogeneous environment right now. There are agents everywhere. There's other systems everywhere. I think the big thing is it's the fit and finish and the way that people use the tools that's super important. So I think the sort of software world was really fixated on features, what is the Harvey ball or checkbox chart look like as to what features you have. And those are important, don't get me wrong. But the big thing about Slackbot is how organic it is and how you use it.

You don't have to mention agents in the stream of consciousness that you're talking to Slackbot with. It knows how to use these tools and orchestrate them. And I think that's one of the reasons as a company, we've really been talking about AWUs or these agentic work units because that's really the output side of it. If people are driving these AWUs, we know they're actually getting work done with the tool. And we feel like, again, we need to make it heterogeneous, we need to work with everybody. We really value our partners, but we also believe that it's the best place to get work done is in Slack.

Great. We have another one here that kind of goes into both Slackbot and Headless 360 from Allan Verkhovski from BTIG. "If customers are spending more on Salesforce for leveraging their MCPs, how does that conversation go in terms of how much of an uplift they're willing to pay for Headless 360? And what is your right to win? And why should people gravitate to Slackbot?"

Yes. Well, I think those are 2 separate questions. I'll take the first. Maybe I'll give Rob the Slackbot question. But I think as far as Headless 360, we have not unveiled our total commercial plan for this. And I think the reason is because we really want to work with our customers and make sure that we're getting this right. Like this is an important adjunct to what we've been doing historically, and there's a lot of complexity to it. And so we don't want to do it too quickly and just kind of shotgun something out there. We really want to talk to the customers to understand how they see the value, how we can help with it. But the thing that we believe is there is value. So when we talk about what it might charge or if a customer is going to pay us more or less, the whole point is if the customer is using the platform more, there's a way to come up with that's totally fair and beneficial to both parties to monetize that extra value that's created. And so I think sometimes in the customer service use case, for example, a lot of people talk about savings, but we're really fixated on growth.

So when we think about things like qualified and sales agents and the things that we're putting out now agentically using the platform, it's increasing what a company can do from a revenue standpoint. It's increasing the stickiness of the interactions with that company, and we believe that, that value creation by using these new tools, there's going to be a fair way to split it, but we just don't want to be too overly prescriptive without really socializing it with like our CIO advisory boards and other folks that are out there to make sure that we're really hitting the mark and making sure that we stick the landing on, again, appropriately monetizing that value. But we're confident the value is there, and we're confident it will be very accretive. I don't know, Rob, if you want to take the Slackbot portion of that, though, because I think that's a great question as well.

Yes, absolutely. The first thing I would say is as far as right to win, the most important thing for us is to actually be the home of all AI for employees within enterprises that is used in a multiplayer way. So period. It's actually not Slackbot. The most important thing for us is that Salesforce, all of your other AI tools show up in Slack exceptionally and can be used in this multiplayer run time in a way that like makes a ton of sense for humans and agents to collaborate. And then after that, I think Slackbot is our most important priority. And as far as our right to win, I'm not going to say it's our right to win necessarily a particular category of software, but we do typically have a right to win your use. And the way that we do that through Slack is obsessing over the user experience, and obsessing over how teams work together, right?

And I think that's what you'll see with Slackbot that when you see internally at Salesforce, we've got 70,000 weekly active users of it, 93% week-over-week retention. People are just kind of, as Val said, kind of obsessed with it because it so naturally fits into their workflow. So there's 2 aspects of that. One is proximity. It's right there in Slack, we're already spending a couple of hours a day to work with your colleagues. Two is the context. So it knows what you're working on and it knows what's important for your company. And so I'd just reiterate, the most important thing for us is for the ecosystem to be successful in Slack and then making AI extremely easy to use and share through Slackbot.

Awesome. Great. We have another one here that's along the same thread, a lot of the similar questions around headless economic impact. So Kirk Materne from Evercore asks, "Can you talk about Headless 360 from an economic perspective. It would seem there are different revenue and op margin implications for buying an agent versus building an agent inside Salesforce versus building an agent elsewhere and accessing a CRM agent via an MCP server. Any way to think about the variability across these different scenarios?"

So maybe I'll start with just a high-level view, and then I would love Joe and Rob to chime in on kind of their use cases. Specifically on a Headless use case that you're building on another platform as you heard us say, we're working through that. More to come there on the commercial model. I think where we start to see a differentiation specifically on comparing an Agentforce built agent, which is purpose-built, understands the context, understands what your task you're trying to accomplish and is deeply integrated in the full set of CRM data that we have, that drives a much faster kind of time to value proposition for customers.

It's a higher accuracy outcome for a lot of these customers as well when they're able to use things like Agentforce Script determinism in the flow of that workflow and that agent where they're actually able to not just leverage optimization of which model makes sense for the right step of this process or this task, but how do I make sure I'm actually kind of programming in the standard workflows, the standard if this is the topic that they're asking about, this is the way we should actually react here, and that actually helps you drive leverage on the cost side of how much you're pinging an LLM to get that answer done. So there's a lot of work our team has been doing from an R&D perspective.

There's a lot of work that we even have done from an implementation and deployment perspective, Agentforce testing center. You heard from one of our customers at UCLA Health that talked a lot about the importance of having that testing center to have a high degree of confidence before they went live with a patient-facing agent. Of course, in a world where their goal is to make the patient experience better, to triage faster on those health care requirements that are higher impact and higher priority versus ones that are lower priority that they can just surface with a quick answer, that takes a lot of confidence for a firm like that to actually go live with an agent facing their patients. So the ability to have that level of confidence, all the work we've done around the platform, we think there's a huge advantage there. But Joe, I'd love for you to come in and kind of chime with your perspective of what you've heard from customers as well.

Yes. I mean I talk to customers every day. And we have some customers that, again, love the vertically integrated stack. So for them, Agentforce is just natural. They have that skill set. Their trailblazers know how to use Salesforce. They know what they want to get out of the Salesforce. Agentforce unlocks these new potential applications of it. And so they want to do that. And I also talk to customers that say, "Hey, I have this investment in my coding agent or tools or whatever, and I would like to do it this way."

I think Headless 360 speaks to both of them. And I think the way that I think about it is like cars, right? I'd say the vast majority of us buy a car and then we drive it around. And maybe we hang an air freshener, we certainly play our own music in the car. We do a bunch of things to make that car ourselves, but we don't physically change the car. There are people that mod cars, right? So they change the suspension, they switch out the rims. They do all those sorts of things, and that's the way they want to drive their car. I think with us, we give you a couple of different series of cars that are fit for purpose for those particular industries or size companies, small business, et cetera.

So we give you a bunch of different choices in cars, and you can take the vertically integrated car and not touch it, just customize it in the ways that we talked about or you can go and fully mod that car and you can give them components of it and say, well, look, I want the Salesforce engine transmission and tires, but I'm going to put my own chrome on it. I'm going to do this and that. The other thing to what Val was talking about is if you want to take that Salesforce version of it and you want to do really great things with it, it also comes with a pit crew, right, and a mechanic. And that's really testing center and all those sorts of things. And so when you think about it, we're really trying to provide choice, we would like to win more than our fair share of folks that want to use the vertically integrated stack because it just delivers so much value so much faster.

But we also want a rich environment of people taking components of it that they think are going to make their particular application and my analogy, their car better for them. and we're trying to do both of those things. And Headless 360 is the mechanism by which we're actually able to do both of those at the same time without having randomly different development efforts to try to support that.

Awesome. I think we answered Arjun's from William Blair's question already. So I'm going to skip ahead as he was asking about the vertically integrated stack and how we think about third-party agents versus Agentforce. James Sperling at UBS is asking about data sharing. It's an area that's been an accelerant for Snowflake consumption, can CRM attack that data sharing use case between vendors, partners, customers to drive consumption and stickiness by enhancing the focus on Slack external partner connections or Slack dashboard sharing? And I know we have a massive Slack ecosystem. So maybe, Rob, you can chime in on what you're seeing there.

I think we have a tremendous opportunity to participate in that. And I think what's been really exciting, one, what's been really exciting is the adoption of the MCP standard. I think this one creating an interoperability between agents, but also agentifying the access patterns to APIs. It has pushed us and made us change our APIs across Slack and Salesforce with these new agentic access patterns. But it's nice to have a standard around this, and I think participating in that is incredibly important, and it allows our agents to consume the tools, services and data from other systems and vice versa, and we want to play very nice in that. How it all ends up shaking out from a monetization or balance of trade perspective, I think, remains to be seen. But I think right now, we're obsessing over creating the things that actually help users and companies achieve what they want and figuring out the economics as we do that because the rate of change is just so fast.

I'd just add one thing. I mean specifically because the questioner asked about Snowflake and mentioned data, one of the things that we have is our data foundations layer, data cloud, Informatica, all the -- Tableau, all the stuff that sort of sits in that data foundation side of it, all of those are either are or will be available as Headless 360 as well. And so when you think about a lot of, let's say, Snowflake data or Databrick's data that's sort of landlocked, where it has part of the picture, but it doesn't have a full semantic understanding of the company, you can use data foundations to give it that semantic understanding that semantic grounding, and then you could use that on our agents to make them better. They'll just naturally take advantage of it or you could use headless, you can use data foundations headlessly to power other agentic experiences where Salesforce is just doing that data aggregation part on the semantic layer side of it.

So I think what we really want to do is we want to have a set of LEGO blocks out there, where people can assemble them. But just like LEGO does, you also could buy the kit that tells you exactly how to build the spaceship that you want to build, but if you don't want to build that exact spaceship, you're free to customize it any way you want. But I think sometimes when people think about it is they don't think about all the things like Informatica that are now sort of either inherently or will be available headlessly as part of that LEGO kit that allows you to just compose these things in ways that is vastly easier than trying to get everything consolidated in a single database.

Great. We have another question here from Kirk and Peter at Evercore."How are you managing compute costs in terms of customers' access to the massive Slack context library that continues to build on itself over time, meaning the context change or context library as more tokens on any query of Slackbot are presumably going to be utilizing to fulfill this request?" So Rob, maybe you can talk about that optimization path that we're going through.

Yes, absolutely. What's interesting, you may have heard it on the earnings call yesterday. We actually have -- so we launched our Slack MCP server 9 or 10 weeks ago, and we now have 1.2 million weekly active users of our MCP server that are making around 40 million weekly active tool calls that I think are pulling around 175 billion data tokens a week at this point. So it is a tremendous amount of volume. And so I think it speaks to the value to the second part of your question about the context that sits in Slack. I can't get into too many details, but we're working on a number of things to actually minify the footprint of the infrastructure required to serve that while also still meeting the needs of the use cases.

I think we're also doing as much as we can to I mean this gets into the technical details. We're doing as much as we can to preprocess and make as efficient as possible the consumption of those APIs. We've actually built, as I mentioned earlier, different versions of our APIs with partners for these new agentic access patterns because a lot of the APIs, frankly, that existed before for the traditional Slack app use cases aren't the best fit for these agentic access patterns that are much more chatty and iterative. And so we're actually building entirely new APIs that are agent focused. And I think over time, we'll be figuring out exactly how that fits into our plan structure and monetization structure with partners.

Yes. The only thing I'd add to it is, I think it's a great question. I think it's an astute question. But one of the things that perhaps we don't talk enough about is our transformation as an agentic enterprise using these coding tools. And so just to throw some love towards the Slack engineering team, it's incredible what the team has been able to do. And we now have groups of people that are 20x the productivity they were in the past. And so I think before these coding agents, there was like a real tension with like how much do you drive features versus how much do you drive efficiencies in cost structure and cost to serve.

Because we have these coding tools because it's so entrenched and we're moving so much faster, we can do that optimization more contemporarily to the feature development that we've ever been able to do in the past because of the scale we're getting out of the coding tools. And so we, as a user of agentic coding tools have unlocked capabilities and velocities that like if you would have told us 2, 3 years ago that we would be here, I don't think anybody would have believed it, they would have thought of it as science fiction.

It's a great point there. And I think one request for Joe, I've requested access to Claude Code personally, so I can start to agentify the IR process and help answer questions faster. So hopefully, that access gets approved soon. Our next question here is for -- from Omar Sheikh from Redburn. "Can you give us any examples of how early adopters are using Headless 360 right now?" So maybe, Joe, you can talk about some of the customer examples that are really exciting.

Yes. I mean I think when I look at somebody like Williams-Sonoma as an example, that has aspects of it that are delivered using essentially the Headless 360 APIs and MCPs, even though we didn't really call it that when we demoed it a couple of months before, we actually came out with the name. The underlying technology was the same. And so when you see these like super rich experiences like the shopping experience, Williams-Sonoma is just really incredible where it understands what you bought from them. You can ask for recipes. You can see these rich carousels of things rendered into the Agentic side of it. We're also seeing like really incredible things with like SharkNinja where we can actually drive the website itself, where the agent is interacting with us. And the acquisition we made recently, Qualified, I think, is a great example. In the past, if we bought a company like Qualified, we would be thinking about, okay, well, how do we do these integrations into our platform.

But because the Headless 360, we're actually able to just integrate with them the way that anybody else can integrate with the Salesforce platform. And so Piper, our agent there is now able to do more things with Salesforce than they could pre-acquisition because obviously, we're putting a lot of focus on that. But ultimately, the Headless 360 platform, other people could do that, too. So I think when I look at these agentic experiences, we're just scratching the surface. I mean some of them are really step functions better than what's been in the market before.

A couple of examples that I gave that I personally like, but they're still so early innings as to what's possible when you start thinking about customers' agents talking to our agents, when you think about the whole website essentially being totally dynamically generated by the agent. All of these things are avenues that are going to start coming up that we can take advantage of. And so I think those are just a couple of examples, but it's just so early innings with this about how good you could make it. And that's actually the exciting part of where we're at right now is just seeing people take advantage of things in ways that like we wouldn't have predicted, but we're thrilled to see happen in production.

Our next question here comes from Matt VanVliet at Cantor Fitzgerald and focused a bit on gross margin. So as both Agentforce and Data 360, MCP adoption grows, what is the strategy around gross margin as monetization takes different paths and usage of AWUs becomes the near-term goal.

So I can start with this one. I think with a portfolio of products like we have at Salesforce, of course, we have different kind of gross margin profiles across our core business and that's something that we manage really well. We have best-in-class subscription and support gross margins in the industry. We're going to continue to manage that well, right? With new products, you always expect kind of ramp cycle, a curve of efficiency that will take some time to get through, but we're managing to kind of keeping best-in-class software subscription and support gross margins over the long term. Now what does that mean? I think, first and foremost, customer success is super important, make sure we're optimizing for usage, getting Headless in the hands of more customers, making sure they're understanding how can I use this in my business, that we think actually will expand usage across the entire portfolio, which is super, super exciting.

There's a lot of things from a monetization standpoint that you've heard us talk about over the last few quarters. Agentforce One Edition, Agentforce for Apps, more bundled SKUs, ELAs, driving more of this embedded agentic use cases within the purchasing vehicles that we have is another way for us to capture more value. In the quarter, Agentforce One Edition and Agentforce for Apps actually grew 60% bookings growth year-over-year in Q1. And the ARPU uplift we're seeing there for the premium tier additions is really meaningful, 60%, 70%, 80% ARPU uplift that we're able to achieve. So there's a lot of ways for us to go out there and kind of capture the value from what we're delivering to our customers, but we also manage a portfolio of gross margins and have committed to kind of maintaining that best-in-class level that we're at today.

Yes, Val -- I mean you hit it -- you've nailed it. The only thing I would really add to that is, I think right at the beginning of your response, you embedded perhaps the most important part for this to understand is the fact that it's growth in usage, right, growth and delivering value. And so there will be instances where customers existing licenses like some of what Val talked about, will be all they're paying us. And yes, their utilization will go up. We also believe we can drive efficiencies back to my last answer. But we're also seeing that we have these consumption models. We have those things where customers when they succeed, we succeed from a customer outcome standpoint, and that growth in it sort of inherently brings the gross margin with it because we're highly aligned to our customers. And they are paying us more, but they're happy to pay us more because they're making more money materially. And that's exactly where we want to make sure that when we think about pricing models, we get this right because we want to be equitable to everybody. But I think Val said it very well.

Awesome. The next question here is from Terry Tillman at Truist. "And as you think about Headless 360 longer term, is the bigger opportunity expanding the number of users who interact with Salesforce and increasing the depth and frequency of platform usage or is it opening up new agent-driven use cases that were not practical in the traditional UI-based model?"

Yes, I think it's actually both. I think both of those things, it's a good question. But I think both of those are going to happen at the same time. I mean when you think about it -- when you take a step back and you say, okay, we look at our admins, we look at the folks that were like building these interfaces, like the UI was empowering, but it was also constraining, right? Every admin out there, every UI person, every trailblazer had a backlog of stuff that they wanted to get into the interface that they -- that somebody believed -- maybe they are a business user or a stakeholder that submitted it was going to drive incremental value to them. But there was a finite limit to how much of that you can do.

Now in this world with the agentic coding tools and with Headless 360 and the sort of ephemeral business driven, let me talk to the agent and tell it what I need. Our belief is that people will have more meaningful conversations with the Salesforce platform. And when they have more meaningful conversations, they're going to have more of them. And there's no question that agents are assistive in that, agents are driving it and human beings are also driving it. So I think we see it happening in all vectors. There's definitely a lot of folks that in a company that didn't necessarily interact with Salesforce directly, definitely did not interact with Salesforce Lightning that now, I think, are going to drive increased usage because they're going to talk to an agent that's going to be talking to Headless 360 in the Salesforce platform.

And I think Slack is just the greatest example of that. When people use our products in Slack, they use more of them. And that is because of the fact that they're just so much more dynamic and so much more powerful when we can create this level of both control and just assistiveness to the individual users of it and not constrain it by how much the IT department could actually fulfill those requests. And so as a technologist, I look after the office of our CIO and the internal Salesforce systems, I'm thrilled with this thing and how it's working because it gives me the opportunity when I wear that hat to think about how do I better serve my business users. And part of the way I better serve them is I teach them how to fish and then I give them the fishing rods.

And I think that's what this technology is going to do as it expands to is that this concept of -- it's not even distributed IT, it's AI fluency lifting in the entire company, and therefore, the tooling goes much more horizontal. I think that's going to drive utilization for short.

Awesome. Our next question here is on Agentic Work Units from Jackson Ader at KeyBanc. "Which tasks or outcomes consume more or less AWUs. Do AWUs track closely to token consumption? Or are there some outcomes that are really valuable and high in AWUs, but don't consume a ton of tokens?"

The answer is that AWUs are very token variable, I would say. In some cases, they consume a lot of AWUs. The particular task or a lot of tokens, the particular task that outputs in AWU may be very reasoning intensive. So it's sort of thinking about things and taking a bunch of stuff into consideration. And therefore, the token count is quite high. But I'll give you an example of why we use AWUs as opposed to exclusively token count is if you look at Agent Script inside of Agentforce. It allows you to have a high degree of determinism. Well, the way we're able to ensure that is we're not using LLMs to fulfill those requests. There's an agent -- an agentic LLM upfront that's trying to understand your request. But when you get into that sub agent, that is deterministic, we're running other types of models and other types of procedural code on the back end to guarantee that it will be a deterministic outcome, but it's actually not agentic in that sense.

The front end of it's agentic, but the fulfillment end of it is not. And so that would be an example of that's actually a very low token use case, but still very high value. And I think that that's one of the reasons we think AWUs, at least at this point, are really good measure because it's like what work did you get done with sort of agentics in the loop. And the deterministic nondeterministic deep reasoning, wide reasoning, all of those things have very, very different token profiles, but we believe they all deliver kind of similar amounts of value. So that's the reason we added up the way that we do.

Yes. I totally agree, Joe. The one thing I'd add just for some color on what you saw in our Q1 AWU print, Agentforce Service, the service use cases are still representing the majority of AWU consumption but let me call out some of the fastest-growing areas within that AWU number you saw 1.6 billion in the quarter. That was growing really well quarter-over-quarter. We actually saw a real valuable increase in kind of the sales use case. We launched the sales agents, I want to say 3 quarters ago now, and that, I think, grew above 200% quarter-over-quarter in AWU usage.

We had certain industries that we've been hyper focused on from getting these out-of-the-box agents, more use cases, right, retail consumer goods, high tech, public sector that represented a real large amount of AWU consumption in the quarter and there's a way for us to really look deep into the AWU usage across these different vectors to understand what's working, what's not, where can we go faster, and that's a huge operational advantage for us.

And the last thing I'll mention, Slackbot, absolute amazing AWU usage growth quarter-over-quarter, more than 300% quarter-over-quarter growth in Slack AWUs in just a short period since launch. So a lot of good things happening there, a lot of ways for us to really monitor, optimize, make sure that these AWUs are actually converting real kind of token kind of raw intelligence into work enterprise outcomes. And that's what we're super excited about there.

So the last question here that we have for the webinar today, and thank you to Joe and Rob for hosting. As AI agents increasingly outnumber human users, how does the Slack and Headless 360 product road map evolve? So maybe give us a little bit of a sneak peek, whatever you're comfortable sharing at this point on what can we expect to see out of these products in the future?

Yes. Well, I'll start. Maybe I'll throw it over to Rob for the Slack perspective on it. But I think what I think about agent 360, I'll just go a little deeper than what I was talking about before, there are parts of me that really believe that 2/3 of the capacity of my IT organization is going to be building things that power agentic use cases for business users. So they're very much in the situation where their customer used to be the business owner directly, now it's the business owner's agent or their coding agent or the Cowork agent. And so when we really start to think about that, that's, I think, when you get massive scale because you also get massive customization, right? We -- in the abstract, we always wanted to have the most personalized version of Salesforce that people can have so that it felt natural, they used it, they loved it. It brought them joy, same thing with Slack, but there were limitations based upon how much code you could write, how much you could do for customization. Those limits have now been reset in a very, very major way.

And so I think thinking about as an internal IT provider, internal technology providers thinking about the use case that you're no longer just providing technology for humans, you're actually providing technology for your digital workforce as well to get jobs done. I think this is just a super provocative concept. And I think we're going to get there a lot faster than people think. We think Headless 360 is a pivotal piece of that because that's the things -- the types of things that these agentic digital labor agents are going to have to use, they need that kind of foundation, and we're happy to kind of lead the way by showing people, yes, this is the way that deep work is going to be done in a hybrid workforce.

Just to build on what Joe said from a Slack perspective, I'd say we're very excited and we're tracking towards. I think you'll see as many agents in Slack as users as you will, in humans in Slack as users. And I think that's, again, going back to our priorities, that's where it's exciting to try and nail the problem of becoming that multiplayer AI home for the ecosystem or multiplayer home for the AI ecosystem. And then I think to another point Joe made earlier, I think what you'll see moving forward is there was actually a mention of this on Lenny's Podcast by the CEO of EVRY, the other day. But I think you'll see Slackbot become a super-agent for employees in Slack, and that will ultimately be the primary thing that they talk to that ends up interfacing with and surfacing other agents from -- certainly from Agentforce, but from third parties as well. So excited to see proliferation of agents and Slackbot help with the wayfinding with those agents.

Awesome. Well, that wraps up this webinar. Thank you all for joining so much. We look forward to seeing you over the next few weeks. One quick ask, if you have feedback on what you'd like to hear next quarter, what topic, what product, an area of the business that you'd like to deep dive on please send that over to myself, to Alex Chan, Alex Kingery. We also have a new member on the team that you'll be seeing out at the conferences over the next few weeks, Lauren O'Brien that we're really excited to get out there. So look forward to seeing you on the road, give us feedback, and thank you so much for joining.

Bill, welcome back.

Great to be back.

He has been actually very consistent in supporting our conference. So thank you for being a support. Thank you for always scheduling it the day after our earnings. I'm sorry. I know it's hard. But thanks for making the trip. And for you, I'm going to go off memory. You were joined in 2017, and you were at Microsoft 14 years prior to that.

That's right. Yes.

Okay. So it's ingrained. That memorable. The -- so had a good chat with Robin last night post and talk through things. I think -- I mean the key question that we're -- everyone is asking us today is you have low teen cRPO growth. You've called for an acceleration in the back half of the year. CRPO is accelerating. So everyone is like, well, how do you see an acceleration overall if we're not seeing cRPO accelerate?

Yes. Yes. Well, first off, thank you for having me again. It's always a pleasure to come and speak with you guys about what we're really excited about at Salesforce. And you've always been sort of -- someone that keeps us on our toes. So thanks, and I'm happy to answer kind of what we're seeing in the business at large. When you look -- I think some of the things that you heard in our earnings script yesterday from Mark and Robin and the team, we have a lot of real excitement happening in the business. And the exciting parts that really give us confidence about the back half acceleration, number one, agent force. Agent force is really transforming not just the way that kind of the revenue complexion comes in the sales force, but it's transforming the way our customers are using our software to add value to their business. And this quarter, our focus has really been on accelerating the adoption flywheel, getting customers in this moment from pilot into production and really seeing that production have meaningful returns on the front end of their business. And we've seen in every industry, companies in financial services, health care, high tech, retail, using this platform to finally catch up to the demands of their customer. And that's, I think, been one of the most exciting parts is for the first time, technology is helping companies sort of catch up because the demands of customers have always sort of overwhelmed the service centers, the sales centers, et cetera. So Agent force is really off and running, and I think we're really excited about it's early days. Over the installed base, we're still getting more of those customers sort of through the adoption flywheel. So I think you're starting to see that pick up velocity as we've invested in more forward deployment engineers that really help customers with their adoption and getting their first scenarios live. That's been sort of a big sort of motion this quarter. But when you look at the core businesses, like our Agent Force One addition, which is our premium addition of our Sales Cloud, which allows agents to work with sellers and amplify their productivity, that's also accelerating for us. So this Agentic wave is not just about sort of kind of these functions that are customer-facing functions. It's also about the productivity of the enterprise as well. And both of those are really starting to have dividends on the business. So as these get more adopted and flywheel, that's what gives us that confidence about the second half.

The Sales Cloud did accelerate in the quarter. It was good to see that. We got a few questions. The Service Cloud did decel and everyone was like, is this just an anomaly? Is it because of the agents taking over now in service? Like what happened in terms of why excel in sales and why decel in service?

Right. One of the things I think you have to pay attention to about the Salesforce business is we've changed now our segment-based reporting. So now we used to sort of have reporting based on our cloud, Sales Cloud, Service Cloud, Marketing and Commerce Cloud, et cetera. Now we're sort of shifting that to really our apps, our Edgentech apps and our data and platform kind of business. And the reason for that is you're seeing a little bit of this maybe taxonomy shift from what used to be always in Service Cloud now has gone into the agent force line. So if you added that back into the Service Cloud, you'd actually see it not having the deceleration like you're talking about. What to pay attention to, and I think the root of the question is, are seats going away in sort of the service center because a lot of our Service Cloud has been seat driven. Service Cloud added seats this quarter. So we're adding more seats. We're adding more agents. And I think that the combination of those 2 really become the flywheel of growth acceleration for those core clouds.

When you say it added more seats, were you specific in terms of the growth?

We don't report growth of the seats, but just in a raw sort of net basis, both those clouds are adding seats. So people are still hiring in the service center. They're hiring in the sales centers. And I think as you see what is really exciting, especially with things like Agent Force One and Slack bot, we're actually bringing more people into the Salesforce ecosystem because now Slack is working with our Customer 360 applications in ways that we're inviting more people into the workflow. And I think that's really exciting for the future because now it means that we're not just limited to what sales and service teams do. Now you kind of have a bigger addressable market across the enterprise at large.

You've rightfully nailed the pricing. I mean I think it was a bus tour we came and saw you and you're like, you guys, it's not all capacity. It's going to be seats and capacity. And I think every company here has been saying the same thing, which -- and most of the people I trust in the industry, like CIOs can't just go on and just do pure capacity because they bankrupt the budget. But is it -- any new update? Is that the bill vision of the world still on pricing? Is it --...

You're the only person that's ever told me I've nailed the pricing. So thank you for that. Honestly...

I'm sure Mark doesn't say that.

No. Look, I think in general, it's really -- human labor has always been easy to predict on the basis of a seat. And I think as companies hire and they sort of have software for that human capital, that has been sort of the best way to plan. That's the best way to predict, and that's been the best way to sort of make it easy for enterprises to consume a Software-as-a-Service subscription offering like we have. Agents are different. They're not seats. They're not people, and they don't have limitations of work. And so they work 24 hours a day, not 8 hours a day like humans do. And so paying a seat is just not right for that sort of kind of entity that's working on your platform.

And so that's why the consumables make a lot more sense kind of an agent, just pay for the work that it does. So I think somewhere between that hybrid model is where you'll see this net out, I think, for the industry at large. But I would also pay attention to those consumables themselves because those are also emerging and changing. Today, most of the world is infatuated with the token. And this token sort of explosion that's happening in enterprises, it's asking -- people are starting to ask questions like are these tokens leading to yield? And so we've often heard about token maxing as a sort of strategy. Well, now the counter theory is, is this really output maxing? We know that we're actually getting content, but is that content actually producing business yield. One of the things that we're starting to do some more experimentation on is more value-based and outcome-based pricing of these consumption offerings because, again, where we want to be is the company that doesn't just sort of monetize compute and storage like a hyperscaler does, we want to monetize the outcome that comes off of the software because if companies are getting more growth or getting more savings, that's how we sort of share in that value exchange.

So I do think as our pricing continues to sort of evolve down these spectrums, we're going to have lots of different options for different kinds of companies, big and small. And I think as it sort of nets out in an aggregate sense, seat-based and consumables is the right pattern. What those consumables represent, it's going to be based on the offering that someone is consuming from us. But that's also -- you've asked me this question before, like that's why Flex credits are so important. Flex credits are a new unit of measure, a new unit of currency that companies that subscribe to the Salesforce ecosystem leverage that can work on any of the technologies. They're not buying products, they're buying capacity and output from the offerings that we serve them with. So I do think this will continue to be an evolving conversation. And our strategy when we first talked about this is we just need to meet our customers where they are on this journey, and that's what we're doing is creating offerings for them.

There's a fear right now that Anthropics come in and they're effectively going to create an overlay layer and that they're just going to surround the CRM system and your growth will stop, their growth will build. They won't replace you, but they'll create an overlay right or wrong.

Wrong. Would you like me to elaborate on that? Because I keep getting hammered by our clients on this topic. What -- well -- and I'm glad that Mark came out on the podcast and said you spent $300 million on Anthropic, which is maybe a signal that you guys are going to coexist. And yes, you might be frenemies. You might compete in some areas, but in large part, you can be friends.I think, first off, Anthropic is our customer. what Anthropic uses to transform their go-to-market strategy and accelerate their growth at Salesforce. What we use inside of our organization to drive productivity and write code is cloud. So there is definitely a coexistence sort of in our future that's there.

And look, I'm being a little facetious about like just the kind of hard answer. But if that had been true, wouldn't Slack have already kind of replaced Salesforce because that was an overlay layer for work and workflow. And it didn't replace Salesforce, it amplified Salesforce. It actually made it so that more work and workflow reached more people. And I do think that's truly what we're seeing with this moment of the builder and creator economy with Anthropic and Cloud specifically, which I use every day, it's actually helping me do more in Salesforce, not less. It's actually helping me to sort of analyze my Salesforce data and extrapolate more intelligence around my Salesforce data, but it still is most importantly, using Salesforce data.

And so I do think this is where the market likes to have these sort of binary moments of SaaS versus the token. That's not the reality. A lot of companies are working with multiple tools and multiple systems. And ultimately, that's why we saw this pattern emerge with what we call our headless strategy, which is to allow the Salesforce platform to be accessed by tools like Cloud or OpenAI's tool set or Google's tool set or even the Slack tool set because we want more people participating in the work and workflow that Salesforce represents.

What are we all getting wrong on the outside because we can't smell and breathe the inside. But what are you seeing that you're like, I wish the market would stop talking about this. They just -- maybe they can't stop talking about, but they've got it fundamentally wrong. Is there...

I don't think anyone has it fundamentally wrong. I just don't think everyone has it fundamentally right now. And I think that the questions, like I said, everyone likes to make this about binaries and offsets. -- okay, if you're no longer investing in SaaS, it's because you're investing in the tokens or some other sort of system that's there. The reality is companies come to Salesforce because they want to be better companies. They come to Salesforce because they want better outputs. They want better outcomes for what they use Salesforce for. And I don't think that the world is going to stop trying to make better companies. I think that we are just going to need to sort of utilize Salesforce in ways that powers those transformations that companies are trying to do. So I think that what the market -- where the market wants to think of this offsets in terminal value of things like seats and seat-based labor, the reality is where we're finding ourselves at Salesforce today, more work is getting done, more data is being generated, more sort of interactions are being handled, more campaigns are being executed, more orders are being driven on our commerce platforms. This is not a time of less, it's a time of more. And I think Salesforce becomes this incredible orchestrator for the enterprise to help businesses achieve more.

There's been a few comments from investors. We're at a technology transformation tectonic shift, whatever you want to call it. Everyone says, well, why spend $50 billion on a buyback when I should be leaning into the tech cycle now. We have a lot of companies that are at discount. We have a private market that's dislocated. M&A is in a tail spin right now. Like this is like go time for most of our clients, they would say, and Robin's response to me last night was, Brent, we're doing both. We are doing acquisitions. I mean, I guess you're not doing really big ones, you're doing more tuck-ins. But how do you think about this?

Yes. Look, I mean, I think Robin's answer is right. We are doing both. I mean Informatica is a great sort of signal of that. But one of the things that I think that the market may be -- we were early in sort of our acquisition of Slack a couple of years ago right ahead of the pandemic. And the market really didn't quite understand that, okay, what we're really trying to do at that time is broaden the aperture of users and sort of work and workflows that happens inside the enterprise. That was perceived as maybe a bridge too far at the time because the valuation of Slack was high.

But right now, I can guarantee as hell that we have Slack because it is becoming a modern surface for engaging work into what that's transforming to be. Informatica is another really great example. Informatica is an acquisition we completed last year, which has incredible synergies with our Data Cloud strategy because Data Cloud was really about harnessing this world of customer information. Informatica was this world of noncustomer but customer adjacent information that happens inside the company. The part to the root of the question, we want to only invest in those areas that are on our mission to transform how businesses operate, better data, better workflow, better orchestration, better outcome. Those are the kinds of acquisitions that we look at. And there's a lot of technologies out there that just really good tech, but doesn't really net into better outcomes for companies. And I think that's where we're thoughtful about what we acquire. It's really about making sure that we accelerate our strategy, which is to help companies sort of perform and operate better.

There's been a little concern around some of the departures, and I know your CPO retired, so you go to anthropic. But you have a lot of great talent. But how do you kind of calm the nerves of everyone in this room of, hey, like we're -- we feel like we're keeping the most important people.

Yes. Look, first off, I think technology and there are always sort of these moments where there's an exciting mission for companies to join. What has kept me at Salesforce since 2017 is the mission of making business the greatest platform for change. And I think that people who are still on that mission or still understand that technology's purpose is to help businesses drive sort of better results for their cities, their societies, et cetera. That's what kind of galvanates like our culture to Salesforce. It's not because we're fascinated by the next-generation models. It's not because we think about these incredible new use cases or new apps that can be built. We're committed to sort of that mission.

The talent that -- and it starts with Mark. I mean, Mark is sort of the ultimate leader, champion, spiritual adviser to all of us in the company. And I think that what Mark is really doing is finding the talent that wants to internalize that mission into this next era really to kind of drive business forward in this moment in time. So I think the leaders and leadership that we've amassed in the company and has allowed us to sort of put the right talent in the right places. myself, I started in kind of the software and product management space. I now do monetization strategy. So sometimes it's not always linear talent moves, but we put our talent in the places that drive the best yield for the company. And I think Mark is a great inspiration for getting the right talent in place here at Salesforce to drive those sort of transformations we're trying to go through.

That's great. The Marketing Commerce, Tableau, I mean, there's been some headwinds, right? So there's been -- you got some nice acceleration in sales and service stable when you include the other parts of the transaction. But marketing Commerce and Tableau have been a little bit of a headwind. Is that -- can you recover from that? Is it like what needs to happen?

Yes. Look, first off, the breadth of our portfolio is a strength. And I think that because of the strength of the portfolio, it allows us to sort of have these moments where we see acceleration in sort of some business units while others are going through more secular transformations. I think the world of marketing is going through a secular transformation. I mean it look no further than what Google just announced on the way that search is transforming for businesses today. That's going to fundamentally reshape what the world of digital marketing looks like. And so it's not a secret that a business like marketing may have moments of softness. It's that it is going through more of this transformation state about what does the future of marketing look like in that sense. Same with commerce. It used to be that you would shop online in an online commerce store.

Well, this world of commerce and commerce agents are starting to emerge. So as that market retools, those platforms have to retool as well. The good news is businesses like Sales Cloud, our long-standing sort of bread-and-butter business are having its moment. Slack is having its moment. Agentforce having its moment. So not only are businesses that we've long been in, but acquired entities like Slack and Informatica are accelerating, organic innovation like Agentforce is accelerating and even our legacy business on Sales Cloud is accelerating. So you're going to see these puts and takes, I think, as different moments emerge. But again, the strength of the Salesforce portfolio is not sort of indicative of just one unit cloud. It's really the whole that we care about.

We're getting agent to death at this conference. Don't say. Everyone's got an agent, right? So...

It's like you've driven in San Francisco and see all the boats.

You're the second presenter to bring that up back to back. How do you think this kind of settles out? I mean, right now, in your space, just in the front office, I mean, we've got like 10 vendors that are all claiming the same thing, then you have vertically aligned vendors that are in financial services. We've got -- I mean, we got every flavor of agent, and we've seen this movie before or all the movies show and then a couple of rides at the top. What...

Yes. I was actually with a customer last week, and they said that they made the comment about the San Francisco billboard. So I'm stealing it from them. But it was like literally every e-mail, every day, every call is about try my new agent. And it just can't sustain. And I think that -- so I do think incumbent vendors have an advantage because they have the opportunity to identify processes that are already established. So I think incumbency in many cycles, maybe as seen as like a curse, maybe I want to try and replace that technology. I'm not seeing that pattern. What I'm actually seeing is more companies coming to us and saying, can you identify this workflow that we have because we want to do it off of trusted data and the governance of the Salesforce platform that's long been how we've operationalized our organization.

So I do think incumbents have an advantage more so than even the upstarts at this point because they have to kind of fight for every sort of breadth of oxygen. We have something to prove, which is let's actually modernize some of the workflow that's there. Where I see it netting out, Brent, is candidly not -- we can't see thousands of entities. I think there will be consolidation. I think that as vendors like us that have a breadth of portfolios identify all that workflow, it's not just about maybe identifying each experience. It's also about how they orchestrate with one another. That's going to be, I think, where truly the rubber meets the road in terms of what stays versus what sort of just sort of fades off into the ether. So I think orchestration is sort of the next horizon. First off, everyone is in the horizon right now of taking these pilots moving into production.

Once they're in production, now let's like try and orchestrate and then rationalize. And then what kind of comes out on the end of that is probably fewer bigger agents that sort of represent more fully autonomous functions for businesses. So I think that's the transition that we're starting to see already. And a good example of that, by the way. We have a customer in retail. They just went -- they had an old -- an agent sort of service experience. What they really wanted was that agent service experience to sell digital products. Well, that company didn't have a commerce technology. So they came to Salesforce and said, okay, I'm going to replace that agent experience with Agent force because Agent force serves and sells all at once. So I think that's really this concept we call it a super agent. These super agents could do more than just one function. That's ultimately where I think this will net up to that rationalization moment.

I think maybe not this quarter, I don't know what the number was if you launched it, but the mid-market has been kind of a space that's been strong. I think you've had a good leader there. You've had -- people want to buy everything from you. They don't want to assemble it. Can you maybe just give us a sense of what's happening in the mid-market?

Well, I think you -- the signal you can look into is the packaging strategy we put together for our Agent Force One Edition. And AgentForce One for sales includes sales and Tableau and Slack. -- all in one offering for a business. Well, that means I don't have to buy a sales analytics offering. I don't have to buy a sales collaboration offering. I don't have to buy a Salesforce automation offering. I just get it from Salesforce. And so as sort of certain elements of technology, maybe this is that rationalization moment kind of showing up even in seat-based labor, the seats themselves where people have had best-of-breeds on all these different vendor functions that exist, now they want to actually consolidate a lot of that to sort of one vendor because they actually believe that when all of that information signals together, then it can fuel an agent strategy.

So I actually think they're quite symbiotic. Application consolidation leads to better data that gets unified, that leads to better agents that can perform on the outside. So this is sort of our flywheel of let's get this Agent Force One addition into more of our installed base so that we actually drive more of that data that gets generated on the similar platform that we can fuel agents to perform on behalf of the businesses.

We all do these channel checks and whether it's Atlassian or you or whatever, and a lot of the smaller system integrators are like the vendors are stealing my business. And it seems like it is a sense of maybe we're going to higher-end partners, but maybe it's just, hey, this direct relationship with the customers is becoming easier. But I don't know. It seems like it's happening across a lot of vendors. And so with the actual channel checks we all do, say are very different than actually what you produce. And is that -- it seems like a common pattern we've seen in Atlassian, too. But it seems like is this a signal, hey, it's just easier to implement the software. We don't need as many of these small partners to help.

No, I don't believe that at all. But what I believe is that the vendors have an added responsibility to help companies find value from the offerings that they've created. And because the technology is so new, a lot of technology vendors are investing in these forward deployment engineers not only to get the service sort of up and running, but also to get the key signals of how to sort of tune and optimize our offerings so we can improve the products in this moment in time. So I think one of the signals that we've done with partners like Accenture is start to now invest in not just forward deployment engineers that are Salesforce employees, but forward deployment engineers that work at Accenture that actually can work as an extension of our workforce that's there.

So I don't think it's really about closing off an ecosystem. I think it's really about making sure that -- in the early sort of days of this agentic moment, vendors have an added responsibility. We're investing with our resources. We're teaching these channel providers and service integrators how to do it the way that the software was meant to be designed and kind of retooling, I think, in this moment. So I would actually think it's more of a retool than it is about stealing their business.

Okay. Great.

That was not my quote. We're not stealing their business. We're retooling.

The verticals have been a huge strength of yours when you think about health care, pharma, insurance, maybe kind of walk through what you're most excited about there. And we always get the question about pharma, so maybe.

Well, our Life Sciences Cloud, for example, has been one of the new offerings here at Salesforce that has really had an incredible quarter. And as organizations are sort of retooling their sales forces for the future, they want to do so with modern technology. And this cloud was built from the ground up for this enngentic moment where not only is a great sales orchestration platform, but it's also a great sort of system built with agents that are actually helping kind of qualify leads and do sample management.

And so there's all kinds of great innovation that I think when you rebuild for this ground up that a cloud like life sciences cloud is innovating on that's having sort of kind of huge growth opportunities for us right now. To answer your question at large on verticals and our industry strategy at large, every industry is going through different moments of transformation. And the fact that we have not just horizontal software that is kind of a vanilla one-size-fits all, but acutely with the right compliance and the right certifications and the right workflows and the right sort of data model and the right logic for those industries sets us apart.

And I do think as we continue to see our industry strategy deliver what customers want, it's all about that faster time to value that they can get up and running and then really a software that speaks their language and speak kind of works the way that they need it to because it's been built from the ground up for all the sort of rules and regulations those industries require.

You get one vertical of up and comer for you, like there's massive, just incredible.

Yes, I'm sort of biased because life science cloud is one of our newest ones, but that's...

Life science would be the one.

I'm very excited there. But I would also say public sector has had a lot of strengths for us. Our manufacturing areas have a lot of strengths, financial services, health care, they are all going through degrees of transformation. And I think health care is always the one that in our country anyway, we have a lot -- this is sort of, again, why you work at Salesforce. because we believe that we can transform health care in such a profound way with now digital agents on the front end of those experiences. And I think that's why even yesterday in earnings, we had UCLA Medical online with us talking about how we're fundamentally just changing the business of health care. So that's something we all benefit here from California. But ultimately, as a society, we benefit from because we can really make the health care system more equitable for everybody.

Any questions from the audience?

Could you just talk about the acceleration in the second half? I know it was our first question. But is your visibility because you're giving people free tokens and they have to work through them and then they'll buy more? Or is it just a function of time to deploy, you know they're deploying it and doesn't happen until then...

Yes. I would say very much -- what is giving us confidence is the pilot to production sort of movement, right, that's there. And the signal was the hiring that we did really around our 4 deployment engineers to help with that hiring velocity to take shape. So I think that's really kind of what gives us a lot of that confidence is moving through the deployment kind of side. And this is not like linear deployment where like traditional CRM software, if you deployed it, you would kind of knew how to kind of fit a process, a workflow, et cetera. These agents are very different. They are -- they have different capabilities, and they have different scale. And so a lot of this is more about change management than it is about hands-on keyboard writing code. That's the easy part. The hard part is getting companies to understand many of the processes that you have in your organization today were built with an era of human constraint in mind. Well, now you don't have that same kind of constraint. So how would we just go back to the drawing board and design it altogether?

I feel like 6, 8 months ago, we were saying that there would be acceleration, it was just because of lapping the soft renewals years and then growing faster and now different answer is that now it's about agent force and that adoption, not just the fact that it was going to accelerate regardless of what just based on the core getting better.

Yes. I don't -- I'm not here to kind of comment about what we said last time and what we said this time. I'm just telling you what it is. What it is right now is we have a lot of people that have agent force and a lot of people that are in their deployment of agent force. And that is how we see the kind of the excitement about the second half is just the sheer volume of activity that's out there.

I know you guys haven't talked much about the inference cost side of things other than the other seems like you're trying to successfully growing the inference business and you're using pricing mechanisms as a lever to account for what the costs are going to be. My rough guess would be you guys are looking at a $5 billion inference bill over the next few years. Do you feel like you have any levers to sort of confront the COGS issue of having agents out there doing 1,000x more than human do?

Yes, for sure. I think that, again, as I was sort of mentioning in the last gentleman's question, many of these processes in the past were based on what humans could do. And now with agents sort of having limitless capacity and limitless availability, it opens up a whole new sort of transformation for what businesses are trying to do around kind of how they operate and in an always-on manner. So as you sort of look at what is -- where we see the sort of maybe groundswell of inference and tokens kind of hitting our world, this is where I think we have a smart architecture around how we build Agent force.

I don't need to call an LLM to give you an e-mail address. I can just query our database to give you that. And so our technologies that we've built inside of AgentForce, which we call our Atlas reasoning engine, both has deterministic and nondeterministic sort of scenarios inside of it. And increasingly so, what we find is we can help companies be more efficient in actually using their tokens because honestly, today, if you're just using Claude and you're trying to kind of query a profile, you're burning a lot of tokens for something that was a simple SQL query. So this is allowing us to really be more efficient at the tokenization of the enterprise. And I do think that sort of architecture is allowing us to make it much more economical for customers. And we're not just pushing it on to the customers themselves. We're actually working with them around how to reengineer, reoptimize sort of their work.

Anything else you think the -- I know you mentioned like it's not just, hey, like one takes off and everyone else loses. Any other kind of things you're hearing kind of from our side that you feel need clarification?

No. Look, I think there is -- as you classify sort of different technology companies, obviously, there's the hyperscalers who have a different business model than the SaaS providers do today. The hyperscalers really were built for this moment of just letting the meters turn. And the more the meters that turn, the happier they sort of make their money off of. That's not what we're here to do at Salesforce. We're not trying to be a hyperscaler. What we're really wanting to be is probably the world's first hyper value provider, which is we can provide massive sort of ability for companies to come into this ecosystem but ultimately drive better performance of their business. So we're not -- I don't pay a lot of time or attention thinking about like how many tokens that fulfills our work.

What I care about is that our customers come to us and they perform better as an organization. That's why this signal of more outcome or value-based sort of pricing as a new lever for us puts us into a shared value space for what our clients expect when they come to our platform that they're getting utility from. So that's where I would really kind of think about kind of maybe my ask is taxonomize different companies for really what is the pure function that they're aligning to do. And for us at Salesforce, like I said, the world is going to be made off of companies that perform better with this technology. That's our mission.

We really appreciate your support. And hopefully, we get the new Head of IR down here. We heard a really, really cool guy and I didn't get the call. So I'm feeling a little left out.

I know if you took the call. No, I'm kidding.

Looking forward having, Mark.

Thank you. Thank you. Really appreciate.

To you.

At this time, I would like to welcome you to the Salesforce First Quarter Fiscal 2027 Conference Call. This conference is being recorded. [Operator Instructions] At this time, I would like to turn the call over to Mike Spencer, Executive Vice President of Finance. Sir, you may begin.

Good afternoon, and thanks for joining us today on our fiscal 2027 first quarter results conference call. Our press release, SEC filings and a replay of today's call can be found on our website. Joining me on the call today is Marc Benioff, Chair and CEO; Robin Washington, Chief Operating and Finance Officer. We also have Patrick Stokes, President and Chief Marketing Officer; Miguel Milano, President and Chief Revenue Officer; and Srini Tallapragada, President and Chief Engineering and Success Officer, joining us for the Q&A portion of the call. Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties and assumptions, which could change. Should any of these risks materialize or should our assumptions prove to be incorrect, actual company results or outcomes could differ materially from these forward-looking statements.

A description of these risks, uncertainties and assumptions or other factors that could affect our financial results or outcomes is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q and any other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements. As a reminder, our commentary today will include non-GAAP measures. Reconciliations between our GAAP and non-GAAP results and guidance can be found in our earnings materials and press release. And with that, let me hand the call over to Marc.

All right. Fantastic. Thanks so much, Mike. I'm so excited to be here with everybody and great to do our second video earnings call with you, and it's really great. It's a gorgeous day in San Francisco, and we're going to have a great time here with you. We've even got a couple of customers joining us, which we're really excited about. Well, I think as everybody can see, this was really an outstanding quarter for Salesforce. We have delivered record revenue, record deals and just incredible cash flow. And of course, I think we've also returned record levels to our investors, and we're going to talk about that and how important that is, especially during this unusual time. So we're going to come into that. And also, by the way, we also mentioned we have some record token counts. I think we're going to talk about how we processed 28.6 trillion tokens, up 152% quarter-over-quarter, no greater example of the tremendous adoption of these new Agentic products by our customers and how we've converted those into 3.8 billion Agentic work units.

Agentic AI, well, it's the biggest growth opportunity for our customers, for us at Salesforce. And since we brought CRM into the cloud, we're just seeing tremendous new innovation every single day. And you can see it in our products. You can see it in our customer momentum. You can see it in our results. Salesforce has never been more essential to our customers. We're going to hear from them in just a second. And we're the #1 Agentic CRM, transforming every company into an Agentic enterprise.

Now let me tell you about these amazing Q1 numbers. Revenue was $11.13 billion, up 13% year-over-year nominal and 12% in constant currency. CRPO $33.6 billion, up approximately 14% nominal and 13% in constant currency. And Q1 non-GAAP operating margin of 34.8%, up 250 basis points, again, hitting some record levels. GAAP operating margin of 21.1%, up 130 basis points, pretty awesome, and we delivered $6.7 billion in operating cash flow. Tens of thousands of businesses across every industry are building their Agentic enterprises with Salesforce. We're going to talk about that today. And OpenAI, Anthropic Google companies building the future of AI, all of them Salesforce customers, all of them Slack customers, building these incredible new capabilities with Agentforce. We secured a record 98 Q1 deals with over $1 million in new ACV in the quarter, 98 Q1 deals with over $1 million. Miguel is going to talk about that today.

Organizations like LVMH, Chobani, the U.S. Air Force, which, by the way, just signed a new $72 million ELA with us during the quarter, awesome. And we're seeing incredible demand for Agentforce with ARR now greater than $1 billion. And combined with Data 360 and Informatica Cloud, we've delivered $3.4 billion in AI and data ARR. 50% of Agentforce and Data 360 bookings were from existing customers expanding their commitment. And to date, we processed 28.6 trillion tokens, up 152% quarter-over-quarter and converted them into 3.8 billion, as I mentioned already, Agentic Work Units for our customers, up 11% -- sorry, up 111% quarter-over-quarter. Agentforce now powering every Customer 360 application, and it's changing how organizations operate across service, sales, marketing, commerce and so much more. Nowhere is this more evident than in customer service. Let's just start right there with Agentforce service.

Humans and agents collaborate across every channel from first contact to first resolution across the trinity of channels, voice, website, apps is a great example. You're going to hear in a moment, UCLA Health. If you go to uclahealth.org, you'll see right away, Agentforce is there to help you get your questions answered to connect with their physicians, to connect with their technology at UCLA. It's a great example using our most current version of Agentforce. And since we deployed Agentforce on help.salesforce.com and on 1-800-NO-SOFTWARE, well, only 15 months ago, it's autonomously handled now 4 million inquiries. It's now double what human agents are handling. Every customer can turn this on now. So many customers are seeing incredible results with Agentforce service.

Vivino, the world's largest wine company supporting 74 million users with only 37 reps, kind of hard to believe, but it's possible because its Agent Vivina, autonomously handles order status, lookups, account questions, more autonomously slashing resolution time by 70%. McAfee has selected our new Agentforce ITSM product or what we call Agentforce IT service to replace ServiceNow. They are using it for everything, ticket deflection, hardware provisioning, incident management, really cool. And Florida Prepaid, a college savings plan provider with more than 200,000 accounts is using Agentforce voice to autonomously handle 75% of business hour calls and 100% of after-hour calls. And with Agentforce sales, we're powering the entire revenue life cycle from first lead to close deal.

And as I said before, over 25 years, Salesforce has generated tens of millions of leads. We never called back. In Q1 alone, Agentforce sales worked 220,000 leads autonomously, generating $42 million in pipeline, awesome. So I'm more excited about what our customers are doing in service, in sales, in marketing and Slack and all of these things. Another great example, cybersecurity leader, Fortinet using Agentforce sales to power predictive lead scoring. Financial leader, AgriBank now built an SDR agent that instantly qualifies leads on WhatsApp. You can go to salesforce.com and even see our own qualification system running right on our homepage as well.

Okay. In Q1, we completed the acquisition of the Qualified and Integrated Piper, their SDR agent into Salesforce, brought all those great Salesforce alumni back home. More than 700 customers are already using Piper. It's an incredible success, and we deployed Piper on salesforce.com, as I mentioned. So you're going to be able to use it firsthand. I think that's so great. It's engaging 50% of our traffic and qualifying thousands of leads and delivering 45% more pipeline than traditional web agents. Also very excited about our new Agentforce Coworker, which we announced last week. If you haven't heard about that, every single one of our Salesforce applications now comes with a built-in autonomous agent. No complex configuration. You just turn it on. It becomes your coworker, finding answers, taking action, getting work done fast. To give you an idea of the impact that coworker will have, people search for information inside Salesforce 1 billion times a month.

Coworker turns search into answers and answers into action. And one of our trailblazers, Andrew Russo, you probably saw him respond directly to me on X kind of was a surprise, but he said, there's no way this is real life right now. Agentforce Coworker was able to pull together and navigate our complex sales and ERP data to answer questions that just yesterday would have been 60 minutes of swivel chairing between screens and systems. It was pretty cool to see that. And I'll tell you this quarter, we also announced Headless 360, again, making all of Salesforce accessible through our MCP clients, APIs, CLA prompts, Headless 360 bringing together the human agents and headless platforms so you can use Salesforce with any coding agent across any surface. It's going to speed implementations, drive consumption, more actions, more workflow, more data, more intelligence, all compounding across Salesforce.

We're meeting our customers where they are since launch in April. We've already processed 4.5 million MCP calls into our platform. Q1 alone, we processed nearly 1 trillion API calls, incredible. And with Headless 360, indeed is building and deploying Agentforce agents right from Cursor and Just Eat Takeaway, one of the leading online food delivery platforms in Europe. We just had them speak to our entire management team with such an amazing story, is using Headless 360 already to bring agents into WhatsApp and other channels, engaging with 350,000 partners across 15 countries.

So now let's talk about our favorite Slack, which every AI company in the Bay Area here is using to run their business, including OpenAI and Anthropic transforming our customers into Agentic enterprise. Slack was nearly half of our 1 million-plus wins this quarter, up 80% year-over-year. It is a rocket ship to the moon. All of the AI companies run on Slack. As I mentioned, I don't think there's a start-up or next-gen AI company that doesn't run on Slack, Anthropic calls Slack, it's core operating system, and that's what Slack is becoming for every enterprise. All of our apps are Slack first. So now a service agent can summarize a case, update the record, escalate to a human right in Slack. And Slackbot is also an MCP client, so you can tell it to create a purchase order in NetSuite or update a project in Jira, and it happens, no switching tools.

We've seen 1 million users of Slack MCP in the first 6 weeks, and Slack AWUs grew nearly 350% quarter-over-quarter. In 2 years, there'll be more agents using Slack than people. Every one of those agents needs the context and the data and the insights directly from Slack. Every workflow needs the data. Every action needs the integration and every customer needs to see what's happening across the entire business. We have the largest collection of trusted CRM context ever assembled between Data 360, Informatica, MuleSoft, Tableau, manage and deliver all that context so that any agent can reason, act and deliver real outcomes.

Informatica has an amazing acquisition. It performed incredibly well this quarter. It's doing the heavy lifting and data management that every customer needs to move from pilot to production. All of this is why we're the #1 Agentic CRM, and we provide what every company needs to become an Agentic enterprise. Okay. So now let's keep going. And with Headless 360, the entire platform is accessible. We have some new people joining us at the table. So it's very exciting. Great to see everybody. And we're transforming and more importantly, our customers are transforming too. Okay. All right. Anyway, here we are. Let's move on to what's really important. So welcome. Thank you for being here. We're thrilled that you're here and would you just introduce yourself to everybody because I don't think they know.

James Schenck, President and CEO of PenFed Credit Union, headquartered in Tysons, Virginia.

And is this your first time in San Francisco?

In here a few times, been with Salesforce...

Usually, I see you in D.C. So happy that you're here with us and grateful that you're here. So why don't you tell us a little about -- you've been using Salesforce a while at PenFed. You've had this vision of becoming an Agentic enterprise. Why don't you tell us what's happening? We heard you a little bit on your earnings call. I think everyone should hear you on our earnings call, too.

Let me just tell you the why. So I started in financial services 25 years ago. There was -- I'm sorry, 18,400 banks and credit unions. There's 8,000 today. Think about that. 500 credit unions and banks are either merged or beaten out of existence every year. And so we knew we had to change. We've been around for 91 years and to remain relevant, we realized we need to partner with somebody that can sort of rebuild our tech deck to take us to a new level.

So you are motivated.

Super motivated. You got to be hungry every day. I was 6.5 like you when I started. I'm 5.6 today.

All right. So now tell us a little more about what have you done? What's the vision?

So about 2 years ago, I was actually at World Tour in New York City, and I saw some other partners, their vision of what they thought it can do for the member experience. When we're competing against 8,000 other firms, we got to deliver hyper-personalization and every transaction, we do about 500 transactions a second, 160 million member transactions a year. They have to be right anywhere in the world real time. So we built our entire platform over the last few years. We went from about 400 platforms down to literally 12 strategic partners. Our call center, our mobile, our web and our branches all run on Salesforce.

Every additional partner or tech siloed capability is a tax on innovation, it's a tax on speed and it's a tax on security. So by building it around Salesforce, I really think it's taking me 25 years to realize Jim Collins' Flywheel Effect, we have 76 agents now running across operations, mortgages, IT, HR. All of our areas are adopting it to make our employees be more productive. We like to say they're Bionic employees now. We're not losing employees. We're able to add more volume at scale, industrialized scale with the same number of people, and we're very proud of that.

Well, you've heard the narrative on the SaaSpocalypse. Everybody has heard of this crazy thing that these AI apps are transforming software, which it definitely is true. All of our products are just so much better because of it. But how is it impacting how you're using Salesforce?

Let me just talk about how people make a buying decision because I hear some of these stories. Somebody knocks in your door, are you going to open the door and give them the keys to your safe or the code to your safe to your family's jewels. So every day, a CEO of any firm is going to get 50 calls. Somebody can do it different or better. How is the decision really made? First of all, does the firm, in this case, Salesforce have the product and service that we need? Second, do you have the engineers, the architects, the professionals to work with my team in order to bring that vision to reality? And then lastly, even if another firm had those first 2, who is the firm standing behind it that can be there through good times and bad times that's going to stand behind that product or service. When you line up all 3, that's where a good trusted partnership exists. That's why we went with Salesforce.

So we work with your team literally hand in hand. We said we want to streamline processes. We want to take out latency in the code. We want to do X, Y or Z. Your team was there in the trenches at every level, engineers, architects, building out the vision. But then it's not just pie in the sky on the white [ sheet ], it's implementable. We have 76 agents running side by side with our employees. A good example is in our call centers. We have Agent Wingman. I'm an aviator, so I think they named it because I like Wingman. Agent Wingman is going to save me nearly $1.6 million this year, has decreased our call handle time 10% this year, 50% reduction in after-call work time and 40% reduction in held calls. So better experience for the member. Remember, they can go 8,000 other institutions. I want them to have a great experience each and every time with PenFed. It's got to be right each and every time.

Yet I want my employees to do the knowledge work, building trust in the relationship, not entering what just happened on the phone call. We have agents that listen to the phone call, transcribe it. The human is still in the loop. They approve what was just talked about, but then it's 360, if the transaction occurred in the branch, web, mobile. So the next person that deals with that consumer, that member, they know exactly the relationship. They know what we might want to sell them next or what they need next for their daughter or their graduation. So it's creating a hyper-personalized omnichannel experience without having 400 people I need to meet with. I have 12 strategic partners that are allowing us to power the business.

And you've kind of alluded to this, but obviously, thank you for your service as well and just tell us about your members and how important they are to our country.

We've been serving those. We started out as The War Department Credit Union in 1935. We support the men and women who serve our nation across the national security community and all Americans who support them anywhere in the world. That's why it has to be right, correct, real-time industrial strength, and we're very proud of that.

Well, we're very proud to have you as a Salesforce customer. Before we wrap it up today, is there anything that you think other financial service leaders like yourself or other folks who are thinking about implementing agent technology should know?

It occurs faster than you think. So literally, we had the vision when we saw what was possible 2 years ago. You can build it quickly. The most important thing is having the right partner and not to have too many partners. Too many partners slow things down.

Fantastic. James, we couldn't be more thrilled to have you here today.

Thanks, Marc.

And it's great to have you in San Francisco. And thanks for everything you're doing for the whole country and for everyone. Thank you so much. Great to be with you. All right. We're so happy to have James here, and thank you for coming to San Francisco. Unbelievable, to have him here is so great. And I think that, that's such a critical message. And then we have another customer with us as well, UCLA Health, another great customer. They're using Agentforce to support 450 patients a day. I'm not going to go through all the details. Please welcome our good friends here, Pallavi and also Michael. So guys, welcome, and thanks for coming on the show here with us.

Thanks, Marc.

Thanks for having us.

Well, why don't you tell us your story? You just heard James' story. Why don't we hear your story down at UCLA Health. I already told everyone to go to uclahealth.org and look at Agentforce. But can you tell us a little bit about what you're doing?

Sure. So we've been working with Salesforce for quite a few years. But most recently, we've consolidated into one single instance of Health Cloud, and we've built on top of that with Marketing Cloud, Data 360 and most recently launched our first experiment with Agentforce, and that's a customer-facing chatbot that just -- it's -- right now, it's only scraping our website to act as a little bit of a virtual concierge to direct patients to where they need to go. It's helping with find a provider. It's helping with general inquiries. It's helping with clinical trials. And the way I like to think about it is each of those topics may have been a phone call. They may have been an e-mail. They may have been an onus put upon the patient, but now it's really -- it's a one-stop shop for the patient as opposed to them in a time of need, it's getting them their answers faster.

Well, I'll tell you, it's so exciting to have you with us, and there are so many health care institutions doing so much for you. I actually have a press release here about CVS Health is going to launching something tomorrow with us. And I just want to just say you guys are way ahead of everyone else. There's so many people with a lot of conservatism in the health care industry and deploying agents. What's your message to them in regards to -- I already said you can go right to your website and see it, but what is your message to your peers or to others who are considering deploying Agentic technology?

I would say it took a while for us to sort of dip our toe in the water in the customer-facing space. We're doing a lot on the back end when it comes to research, but this really has an impact on our operations. And we took a lot of precautions. This particular product really helped us from a testing perspective. There were a lot of protocols in place that allowed us to validate every step that we were taking. And that offered a lot of certainty for senior leadership to kind of sign off on the first experiment that we took here.

Outstanding. Pallavi, give us the technical know-how, the detail here. It's in the SaaSpocalypse, as you know. So how do you look at the SaaSpocalypse? You're an expert in this area. You're deploying the technology. Give us your insight.

Yes, absolutely. I think fundamentally, we're looking at this technology with our business problem in mind of health care systems are stretched so thin, how do we help and support our health care workers and how do we help and support our patients get access to care faster. So for us, this is a technology as is anything, how do we best utilize this technology to service and address those pain points operationally, make our staff faster and help our patients. That's really what's driving us and really how we approach this. As Mike mentioned, we're using the same oversight, same policies and procedures that we need to, to deploy these types of technologies.

Well, Pallavi, you deployed our most current version of Agentforce, incredible what you've done with it and the whole multimedia experience, the integration with the call center, every capability, you're connecting your physicians, delivering the technical know-how of UCLA right to your clients. Just give us give us your just biggest surprise deploying this technology. What was it that you just really just hit you with that was like, wow, this is what everybody should know.

I think with any technology implementation, the biggest thing that we take away is how much debt we've built up from a workflow standpoint, how much technical or people debt that we create and then we get mired in this, this is the way that things have to be. So this is really an opportunity for us to open the door and say there's a way we can do things differently. Can we solve the problems of yesterday and start to make a new enterprise for tomorrow. So that's really how we've been approaching it. We were excited that we were able to stand up our first agent use case that Mike led within 8 months. So we're really looking forward to what's next and how can we scale and capitalize on this technology next.

All right. Mike, there's the question. What's next? And how are you going to capitalize on this technology as the next step?

That's actually -- the other great thing about this is there's been a lot of insights that our own patients have led us down and Agentforce has actually been great about sort of consolidating and chunking each of those. So whether it's what systems do we give Agentforce access to, what capabilities do we ask it to do for us. So next, we're looking at potential integrations with MyChart. I think that's probably one that's relatively high on the list. But we also want to start having some assistance with our back-office functions as well. So there's a couple of different things.

Well, I want to just thank both of you for being on the call. We're so thrilled to have you. We're thrilled to have you as a customer, and I hope you'll not only continue to drive us forward, but also inspire our other customers as well. And with that, I'm going to turn it over to Robin Washington.

Thanks a lot, Marc. Well, you've just heard the case for Salesforce as the #1 Agentic CRM. The financials behind it tell the same story. So let me start with the drivers behind the numbers, why our growth is durable and how we're funding it with operational excellence. And I want to update you on our capital allocation strategy, which, as Marc said, is driving long-term shareholder value. One framing note before I walk you through the quarter. This is our first quarter under the new FY '27 revenue disclosure framework. As agents transform how we build, sell and serve customers, our new framework reflects that Agentforce is now deeply embedded across every one of our applications. So please review our earnings deck for additional details on this.

So starting with our durable growth drivers. Sales, Service and Slack are at the core of the #1 Agentic CRM, collectively representing more than 60% of Q1 net new AOV. Agentforce ARR surpassed the $1 billion mark this quarter. Our largest applications, Sales and Service saw year-over-year seat growth with humans and agents both expanding on the platform. Bookings for A1E and A4X, our premium SKUs anchored in sales and service, including the value from our Agentic capabilities, grew nearly 60% year-over-year. As customers adopt Agentforce, they expand across our platform. On average, our top 10 customers by Q1 AWU usage have increased their total Salesforce spend by 1.5x in the last year.

And now with Informatica as part of Data 360, we're already unlocking synergies with revenue growth accelerating since the acquisition. This is the flywheel we laid out at our Investor Day, and it's working. Those signals show up in the headline numbers. Q1 revenue came in at $11.13 billion, up 12% in constant currency, ahead of our guide. The outperformance was driven by Informatica's on-prem business and professional services timing. CRPO ended the quarter at $33.6 billion, up approximately 13% in constant currency, driven by continued momentum in Agentforce, Data360 and Slack. Both metrics were partially offset by softness in commerce and in Tableau. We're driving durable growth through operational excellence. We call our internal playbook Customer Zero. We're our own first customer, leveraging our products to run our business. It's how we're building a lean Agentic Enterprise and driving profitable growth. And it is keeping us on track for our FY '30 Rule of 50 framework.

In Q1, AI coding tools enabled us to double the amount of features and codes shipped year-over-year, while simultaneously reducing incidents and defects. Slackbot, which is embedded directly into the flow of work, is now our fastest adopted AI tool in Salesforce's history, driving 3.8 million hours of annualized productivity gains for our employees. It has become a daily driver of my own productivity as well. And disciplined execution continues to underpin our responsible capital return strategy. Underscoring our confidence in the future, we commenced the largest ever $25 billion accelerated share repurchase, or ASR, representing half of our $50 billion share repurchase authorization. Combined with our buyback program, this reduced Q1 diluted share count 10% year-over-year.

Our ASR alone decreased Q1 share count by 103 million shares, representing 11% of shares outstanding. And it increased our Q1 non-GAAP earnings per share and GAAP earnings per share by $0.23 and $0.14, respectively. Turning to our outlook for the year. Building on the momentum from the second half of last year, we expect first half net new AOV growth to outpace AOV growth and drive organic revenue reacceleration in the second half of FY '27. Before discussing the numbers, a few key assumptions in our guide.

Our Q2 and FY '27 revenue guidance reflect continued momentum in Agentforce, Data 360 and Slack, partially offset by ongoing weakness in Marketing and Commerce and increased softness in Tableau bookings and renewals. We also expect greater license revenue volatility with the addition of Informatica on-prem revenue to our business. Now moving to the numbers. We are raising the midpoint of our FY '27 revenue guidance to $45.9 billion to $46.2 billion. And we continue to expect subscription and support growth of approximately 11% year-over-year in constant currency. We are reiterating our non-GAAP operating margin guidance of 34.3% and adjusting our GAAP operating margin guidance to 20.6%, largely driven by higher restructuring.

Our recent debt issuance tied to the successful initial delivery of our ASR resulted in an approximately 5-point headwind to operating cash flow and free cash flow. As a result, we are updating our guidance for both metrics to grow 4% to 5% year-over-year. We expect Q2 revenue of $11.27 billion to $11.35 billion, growth of approximately 10% in constant currency. Q2 CRPO growth is expected to be approximately 13% year-over-year in constant currency. Our guidance reflects the strength of our balanced portfolio and reinforces our confidence in our second half revenue acceleration, enabling us to achieve our FY '30 framework. And looking ahead, the Headless 360 strategy that Marc walked through expands our addressable market into surfaces we've never previously monetized. That's the next leg of our path to FY '30. Back to you, Mike.

Thank you, Robin. Operator, we'd like to move to questions now. I'll ask each participant to limit to one question in respect for others on the call. With that, operator, we'll take the first question.

[Operator Instructions] Your first question will come from Brent Thill with Jefferies.

Marc, I'm curious to get your thoughts on just the transformation to an AI-led story. The Agentforce numbers are great to see. But what else in terms of what you're most excited about? What are you seeing in the signals from the customer pipeline? And any other metrics that you're excited about that you can share with us that perhaps we can't see?

Well, that's why I thought it's so important that we move to this video concept for the earnings call and also that you get to hear directly from the customers. And I think we're trying to pick out a couple of customers every quarter that can kind of I would say that they are -- kind of represent all of our customers in transformation. And I think that what's exciting is that the technology is really dramatically impacting how these customers are able to deliver their own results, which is why we even saw James bring this to his earnings call. So I'm going to say that what we're going to do is we're going to continue to make that happen. Now let me just give you my personal perspective. We're using it ourselves more than ever before. I kind of mentioned in the quarter, you see the service numbers. If you go to help.salesforce.com that we've delivered more than 4 million autonomous service transactions in a relatively short order, it's kind of hard to believe.

Even if you go to 1-800-NO-SOFTWARE and you press 2 and you get into the service queue and you bypass our sales organization, you'll notice it's all autonomous. You even kind of authenticate in autonomously. The Agentforce will work with you. And then if at some point, Agentforce kind of says it can't answer your question, it goes and then brings a human in directly to help work with it in resolving your problem. Also in the quarter, you saw like we qualified huge numbers of leads autonomously. We've just really never been able to do that before. I think every customer is going to be doing that. You saw we also bought qualified.

And we have this kind of SDR sales agent kind of going outbound as well, helping to kind of understand our own business. We're modeling this for all of our customers so that they can do this as well. Or even in how I'm using Slack every day, I use Slackbot to kind of give me insights into my business to really look at everything that's happening with my core business, I can then get that insight. In every aspect of my business, agents are transforming how I operate my business. As you heard in UCLA Health or in PenFed, it's transforming their business. From a technology perspective, the biggest thing that happened in the quarter from my perspective was that Agentforce is now available and replaces essentially Salesforce search.

So for those of you who are Salesforce users, the millions of people who use Salesforce every day, the search bar is a critical part of how the application operates. Now Agentforce is that search bar. So you can not only search and aggregate and get insights into information throughout every single app we have, but also create agents, and those agents can appear in Slack and Microsoft Teams and other applications, even in an app that's going to run directly on your phone called Salesforce Coworker. That is the biggest exciting technology because that is going to be technology that you're not going to have to implement, you're not going to have to rebuild things.

All of a sudden, this Agentic technology is directly enhancing every single one of our applications from our financial services cloud to our health care cloud, every app we have. So that's what's really exciting. And I just think that the speed of innovation and the speed of change is what's awesome. And then the rate of innovation, it far exceeds the ability for customer adoption. That's why bringing these customers in to help model for other customers what they can do is really mission-critical right now.

With that, it looks like we have Keith up for the next question. Keith?

Excellent. Thank you for the call. And congratulations with all the momentum behind Agentforce and those AWUs accelerating in the quarter. I think the investor debate right now is about the timing and how that translates into strength for the broader business. And the question I wanted to ask was where you guys garner your confidence of a back half organic subscription revenue acceleration because we haven't seen outperformance in CRPO over the last 2 quarters. This quarter was spot in line with your guidance last quarter was as well. And it feels like the bookings trends are lagging a little bit. It feels like Tableau is dragging on the business a little bit, Commerce Cloud dragging on the business. So can you help us put those 2 sides of the debate, like really strong KPIs from agent force, but the bookings not really looking to come through over the past 2 quarters and how you sustain confidence in that back half acceleration?

Yes, Keith, maybe I'll start with the question and have Miguel and others chime in as well. So you're right. Overall, I would say Q1 and our Q2 guide show very strong CRPO. It is a leading indicator for us. But also keep in mind, we raised our overall guidance for the year. And the 2 metrics that we've talked about going all the way back to October is the acceleration of net new AOV greater than AOV. We saw that in the last half of FY '26, and we also are seeing it and have huge confidence in it for the first half of '27. What that will lead to is a reacceleration of our core revenue growth in the second half of the year. And that's what I'd really ask you to kind of hone into. There's a lot of momentum that drives behind that. We've talked about our big deal motion. Miguel can talk about it more.

Clearly, we've seen the success with Agentforce and Data 360. I'd say that over 50% of those bookings came from existing customers refilling the tank. So we're definitely seeing good usage. Our pipeline is very strong. We've also see an opportunity to expand our TAM. So I'll let Miguel maybe go on into a little bit more details. But I think not only about CRPO, I think about our commitment and confidence relative to reacceleration growth is really the driver of how we see our bookings going forward.

Maybe -- thank you, Robin. Maybe to add a few other metrics under the hood a little bit. We feel very comfortable. Obviously, we like the headline numbers. But I also like, in particular, the strength of our core business. You alluded to the net new AOV acceleration. We are confident on the reacceleration of our subscription and support business in constant currency organically. By the way, in the H2, we also have another business we acquired, which is Informatica. Informatica was a business that was growing single digit, both on bookings and revenue. In just 2 quarters, we have significantly reaccelerated that the bookings of the chart beyond anybody's expectation because data is king. Well, my daughter told me "dad says data is king" because I have 3 daughters. It's on the booking front.

But on the revenue front, we've seen a huge acceleration. Now we are -- in last quarter and this quarter, we are -- obviously, it's subject to the timing of some of the on-prem renewals, but we are in double-digit growth. So I like a lot of things about our core business, which is very important. You alluded to big deals. Oh my God, Marc, 98 deals above $1 million of net new AOV in combination, the top 10 deals, focus on the top 10 deals. In combination, the whole booking, the annual incremental booking grew 60%. When you look at the TCV, which goes in the RPO, we added approximately $800 million. That's 2.5x the same 10 deals last year, the top 10 deals. 7 -- this is a beautiful statistic, 7 of the top 10 deals added seats, new seats. This is the new way that we have to monetize AI. We have 3 new ways -- 3 ways and then one more way that coming up, as you alluded to.

The first one is we are upgrading the existing seats of our customers so that they -- the same users, human users can use unlimitedly AI. And this is the A1E that increased 60% in the quarter because there is a big uplift on those seats. Second, we are finding new pockets of seats that now with our transformed clouds, our clouds are not the same. We transform individually every one of our clouds. Our Sales Cloud, I've been using Sales Cloud for 15 years. It's totally different. Our -- I mean now we have Agentic PDR. I can talk to my Sales Cloud. I mean, I don't want to say this because Parker already said it, I log into my Sales Cloud less because I can -- I have access to so many ways to interrogate my Sales Cloud, Commerce Cloud, Marketing Cloud, everything has been transformed. There is a big growth.

So now the ROI of those clouds are higher. So there are pockets of users that before they couldn't afford buying us, now they're buying 7 of the top 10 deals included. And then the biggest way that we have to monetize AI is with customer-facing use cases by selling Flex Credits, by putting fuel in the tank 6 of the top 10 deals, 6 of the top 10 deals were AELAs, unlimited enterprise license agreement, where we threw in a bunch of Flex Credits and customers are deploying use case after use case, channel after channel. They're going deterministic, they're going to voice. So I'm very confident on the reacceleration in H2. And we're very optimistic on the whole overall business.

And maybe the last thing I'd ask on CRPO, Keith, is remember, it's also subject to renewal timing. And the more we get this flywheel growing and think about consumption, it's view as a leading indicator and how it's going to change relative to our revenue is something that's developing over time. So I think we...

It just comes shorter sales cycles. And by the way, the last huge, and you put it like -- and there is one more thing to come. There is one more thing to come, which is the Headless 360. We're going to bring our Agentic -- #1 Agentic CRM to every surface, meeting customers where they are. And we're going to work together with our customers and with our partners to find the right ways to fairly -- in a fair way to monetize those new interactions and those new users that are accessing our platform.

So you've heard it straight from our CRO. We're very confident, right, relative to reacceleration of our bookings as well as our revenue for the second half of FY '27.

Thank you, Keith. Gabriel, welcome. We'll take your question now.

Miguel, you teed me up perfectly on Headless here. Marc and team, I would love to spend a little bit of time on your headless strategy and more specifically, how it intersects with the build versus buy debate. On the one hand, Robin was talking about how it expands the opportunity in the surface area for Salesforce. On the other hand, talk to us about how you protect your downside from potentially enabling value abstraction out of Salesforce, perhaps customers want to build things more in-house or perhaps it enables competitors or value abstraction. So talk to us a little bit about your monetization strategy and how do you protect yourself to the downside?

So you're right. Headless is probably the most exciting announcement of the quarter. And I'd love for Patrick to come in, and Patrick is our Chief Marketing Officer. Patrick Stokes is here. And Patrick, do you want to give us a little bit of an insight into our headless strategy?

Yes, I'd love to. We were just backstage prepping for this, and we said, what did we say about Headless at the last earnings call? And I realized we didn't. We were still getting ready to launch it at TDX, right? Yes. I mean we haven't even used the word yet, and now it's become such a key part of our strategy and our customer strategy and how we're going to grow. It was just at TDX in March when we launched this. And I think what's so exciting about Headless is 2 things. One, it's having a real impact on making it easier to implement with Salesforce. So building out with Salesforce has now become easier than ever because we've seen these coding agents, Claude and Codex from OpenAI. As you use these things, what you realize is you need to be able to connect the underlying APIs, which you do through this layer that's called MCP. And if you can connect those into the coding agents, it makes it faster than ever to implement and deploy Salesforce.

And I think we're seeing that show up in the numbers. Just this quarter alone, Agentforce customers in production grew by 50%. So I think we're starting to see a little bit of that impact as not just our customers, but also our global SIs across the entire platform, absolutely implementing Data 360, implementing Agentforce, implementing a service. All of this, Life sciences, all of this now becomes really just a conversation. So that's one end. But the other end is really what we heard from Miguel, which is this is really changing how people get value and consume Salesforce.

In my experience, we're not seeing people take this capability and the coding agents, for example, and try to build all of this stuff themselves. What they want to do is they want to take this capability and they want to use Salesforce in different ways and get more value out of it. So rather than logging into this discrete application and this application and this application to get an answer to one question that might span multiple applications or multiple kind of sources of information, you can now just take these MCP servers and plug them into any tool that you want. They are inside our application, of course, with Agentforce coworker, as Marc described, right up at that search bar. If you're a Slack customer, you can get to it right with Slackbot. That's really a Headless experience as well. But if you want to plug these into ChatGPT and Claude, you can do that as well. And all of this just results in more and more value being pulled -- being delivered to our customers from the Salesforce platform.

I would just add to that. I think even though we just announced, it's been less than a month, correct? I think Salesforce historically has been very open, and we got more than 1 trillion API calls on our core platform just in this quarter. What we have seen is on Headless MCP tool calls have been more than 1.5 million. So what people are using is they're using it not only in Salesforce, where they do with coworker and our regular sites. They're also able to use it in their flow of work. Similarly, on -- we announced the Headless MCP server for Slack and Slack has done 30 million -- 50 million tool calls. So what we are finding is there is a latent demand where people want to use Salesforce in their flow of work, but they need a trusted infrastructure. They need an operational infrastructure to run it at scale with all the compliance, with all the sharing and security models, with all the permissioning, with all the compliance, so they will use -- continue to use that while getting value.

And like as Miguel said, what we want to do is it's a new way. We want to capture value wherever the work is happening. And that's the conversation we are having with our customers. And as we talk to our customers, ISV partners and all, we'll figure out the right value. So I think it's a new monetization area for us.

All right. Well, let's get down to one more level of detail. This was the quarter where as we used the word Headless for the first time, we used it in -- we talked about it at TrailheaDX. I used it in the tweet. The tweet went really viral. It was a surprise to me, I'll be honest, because, of course, we had always been first on APIs and XML, in SOAP, in REST and now in CLI and MCP, but the system was always built to be API first. It has always done massive amounts of transactions and complex transactions. We've always reported those API figures. And now we even have a new API, which is our whole user interface basically spinning out of the platform as an API with -- so we have that incredible capability. So in all cases, the platform has always been API first. All the applications have been API first.

But when we announced Headless, everybody is like, oh, they've lobbed the top off of it or they've cut the applications off. They kind of got confused in my opinion. They don't understand that all of our apps are rendered dynamically with metadata that they're driven -- it's a metadata-driven platform. So Patrick, you're the marketing officer. Why -- where did that confusion come from for people? Why do they think Headless means that there's no more application or Salesforce app?

Well, probably from the name Headless, which does seem to imply that I can understand. But that term, obviously, if you're in the technology world, that comes from -- it's been a term that's been used in technology for quite some time to imply that the UI is not directly linked to the underlying capabilities or services that are underneath it in this case, APIs. And yes, Salesforce has always been open. I think what people got so excited about here is this idea that Salesforce was endorsing this way of working. We were basically saying, "Hey, we want you to take the value of Salesforce and the value that you get from our apps, from sales, from service, from commerce and marketing, and we want you to be able to work however you want to work, whether that's in Slack or whether that's in Claude or whether that's directly in the app." That's what this capability really enables.

And I think people were really excited about that. And maybe a little inappropriately skeptical that we would have just locked it all down and said, no, it has to be in our app, and that's never been the case for Salesforce. We've always been, I think, year after year, Postman says that Salesforce is the most used set of APIs on the planet. And if you're building today...

People don't know what that means on this call. So will you just explain it, you got it down to the inside baseball.

Sure, sure. So what that means is when you're a builder, when you're out there building something, and this is especially true today because there's now an ocean of builders that have been created as a result of this coding agent boom. When you go to build something for your business, you, at some point, are likely going to want to connect to Salesforce that is what we see. And it doesn't matter what platform you're doing it on. You can be building something on a competitive platform to Salesforce or on Google or AWS or one of our partners.

But at some point, you're going to want to connect into Salesforce. And that's why those APIs have always been hugely, hugely used. But when you are building with an agent, you need a slightly different type of API. That's what we call MCP. And so by really putting those MCP servers out and saying, yes, this is how we want people to build. I think it was a big surprise and a big move in the right direction. And it also creates, I think, a real monetizable opportunity for us.

If I could add one thing because the fact that we announced Headless at TDX it made people think that this was just for builders and that now they can take our CRM apart and which they can now also, by the way. But I think the big breakthrough was not with the builder workers, but with the knowledge workers.

It's more about how you work.

Let me give you 2 concrete examples. I met 100 customers basically face-to-face, one-on-one since the beginning of the year. And let me -- 2 examples, Adecco, great customer across the board. They use pretty much every cloud. They went into Data Cloud and Agentforce last year. They did a big commitment in Q1, at the beginning of Q1. They are basically design and AELA, wall-to-wall. They have amazing recruiter agents going there, millions of transactions. They're moving into voice. When we announced Headless, they called us and they are like, "Wait a minute, this is -- let me try to understand what you're doing." So now because they are also using other platforms to develop other agents. So they have agents with some of the AI labs that they're also trying to access our data. Are you saying that now these agents that we are building outside Agentforce can also leverage Salesforce? And we said, exactly, we did it for that.

So now there's going to be a lot of new agents that are going to be accessing our platform. That's example number one. Example number two is Anthropic. Anthropic is one of our biggest users of CRM of Sales Cloud. And obviously, Slack, their usage through Q1 has exploded fivefold because now they are using Sales Cloud from a Headless perspective, and they are approaching it from Coworker from other applications from Slack, they're hitting Sales Cloud. So Sales Cloud has become more prominent and more strategic for them than ever because of Headless. These are 2 examples, extreme examples, but this is every single conversation that I have with the customer, their smiles are big because of Headless.

Thank you, Gabriela. I hope you felt the energy on that question.

Your next question will come from Brad Zelnick with Deutsche Bank.

Marc, the AWU and token consumption metrics are some of the biggest and fastest growing in software and seems to validate that customers are using and deriving value from the product. Can you help us translate the usage metrics to revenue? Like the Agentforce ARR is impressive, but the usage suggests much faster adoption. And just as a related follow-up, the gross margins show no degradation despite surging token demand. So can you just help us understand how you're able to do that?

Yes. Well, there's a lot of different points there. I'm not sure exactly where I want to go. But I mean our -- talking about the financials of the company, when we talk about the Agentic enterprise, first and foremost, obviously, Salesforce is a large scaled company in software, at the moment, largest, 83,000 employees. For the last couple of years, we have not been loading up a lot more engineers with Srini. So Srini is here at the table. He's got what about 15,000 engineers, and you've had the 15,000 engineers for about 2 years, it's been mostly flat, right? And I would say that the reason it's been mostly flat is because we have been using AI to create more efficiency for our engineers. And especially this year, now with these new coding agents, we're seeing even more dramatic capability.

So that's a key part of our margin story is that we're not hiring more engineers. We're not hiring more GA. We're mostly expanding only in one area. You can see headcount has grown, but it's mostly growing in Miguel's area in sales because I think we all realize the one thing that we're doing here with you selling and communicating that agents are not exactly doing that. They can qualify, okay? They can provide service. But in sales, we still scale because there are so many different parts of the market that we have to get to. So that will be a critical part of expanding our company, but at the same time, expanding our margins.

I think on the other part of that, that's really key is you're right, we're trying to really communicate that level of token usage. Maybe we're one of the first to really get out and talk about, "Hey, not only do we have agents, but we've delivered 28.6 trillion tokens." I listened to some of the other earnings calls, and I don't think that they're at that level of detail. We've even gone down into this 3.8 billion Agentic Work Units where Patrick has really pioneered this idea of how to be able to communicate more effectively the level of depth that's really going on with our customers actually implementing this technology. And that, I think, is also a critical thing that we're only a couple of years into this Agentic revolution, but we see all this adoption and usage.

In every other product that we've rolled out, you've never seen the level of scale and growth of a new product like what we've seen with Agentforce. And you're going to see that, in my opinion, I don't know, but I'm going to give you a vision. I think as we get Agentforce Coworker live for all of our customers, and it's just the ability for the administrator to say now that it's available to these users like that experience that we had with Andrew Russo, this idea that all of a sudden, we're about to add a massive amount of new functionality and capability into all of our apps overnight, you're going to see these token numbers continue to expand and grow.

Are we using more tokens internally? We are for our own operations like in engineering. Are we using them for our customers? We are. And then we're absorbing that into our margin structure. It's not that we're not spending a lot with OpenAI. We are. We're using their platform. We're using Codex, their coding tool. We're using Anthropic. We're using their platform and their coding tool Cowork. We're using both of these platforms. Both of these companies are our customers. We're very excited about how they're using it. We use their products as well. They use our products very aggressively, both of them in Slack and Sales Cloud and Service Cloud across the board. So that is really what's happening. Which part did I not directly address?

I think you have it all. Brad, maybe to add to your monetization point, you're right, AWU is something that we use to measure how work gets done with our customers and also internally as customer zero. But our top 10 AWU customers have spent more than 1.5x over this past year with us. So it is being monetized over time via consumption and just basically getting more value from our core platform.

And I think we should probably just directly address this head on. And look, we're not going to give guidance on attrition and all these things. We never have. But Miguel, you're talking about how attrition is falling in the second quarter. And what's your vision around attrition and heads in accounts and agents and what's happening in these customers?

I mean our focus has been net new AOV. We did a lot of work, to be honest with you, to focus align everyone in the organization from product to back office to front office, to professional services. Everybody is aligned on one metric, which is net new AOV, which is the difference between the new bookings and then the leakage, the attrition. And we managed to redirect and we show at the Investor Day how the curve was negative. At some point, the negative growth.

So Q1 was a very strong net new AOV quarter for you as well, right? So -- what is that -- tell us why is that transformation happening?

The important thing is we are focusing on customer success, which has been always a focus, but our -- some of the incentives were not aligned internally. They've been aligned now pretty much from the second half of the year. We saw net new AOV outpacing AOV growth. We are very confident that in H1, we're going to see continued net new AOV growth outpacing AOV growth. Obviously, that's both levers. We are obviously increasing the new bookings, and we are minimizing the pain of attrition. In some cases, account executives, they swap products to make sure that customers are happy using the product. So we are very confident on the net AOV in H1 also being growing more than AOV and the reacceleration that we committed.

And listen, when you commit something 12 to 18 months in advance, I mean, we're good professional, but we're not magicians. And we don't -- I mean, there was a probability that it could not have happened, but we were very firm, and it's -- I mean, I'm very happy that we're executing as per plan. In fact, a little bit better than planned because you raised the guidance. So thank you so much.

The only other thing I'd bring up to your point, Brad, on margins, again, going back to our FY...

It's such a good question, right? Because it's really getting down into the depth of it, right?

Is that as we marched FY '30 in that Rule of 50, right, our ability to leverage these tools to improve our productivity is a critical component of how we're going to get to Rule of 50, as Miguel said, grow the top line, $63 billion plus with Informatica, but also improve margins and operating profitability. So as I said earlier, customer zero is #1 for us, and it's going to help us reach our framework as a lean Agentic enterprise.

Excellent. Okay. Great. Let's move on to the next question.

Okay. With that, operator, we'll take our last question now, please.

Your last question will come from Kirk Materne with Evercore Partners.

I wanted to follow up on, Miguel, you had made a comment on one of your customers using Sales Cloud through Slack. And I want to dive in on Slack a little bit just as part of the broader Headless strategy. Can you talk about Slack being potentially sort of a gateway for broader Agentic adoption in your customer base, what you're seeing now, how that's sort of stacking up in your pipeline opportunities? It just seems like it's an unbelievable network effect product. And I was curious how that's having an impact, if at all, right now or if you expect it to, on sort of broader Agentic bookings as we go into the back half of the year?

That's such a good question. I think each of these folks should address it. But Miguel, why don't you start?

So first of all, from a top line perspective, and we'll talk about how strategic Slack has become. Slack has become one of the favorite platforms and surfaces for, in this case, very, very specific, both the builders and the knowledge workers found in Slack the way to -- it's a multiplayer collaborative platform to access your applications to is your work operating system. It's incredible what has happened on Slack, how we are leveraging, by the way, a great partnership with one of the labs with Anthropic to launch Slackbot. Slackbot is our personal assistant. It has increased the productivity of the whole company around 3% more or less. So now I do everything. I ask everything to an agent. That agent has access to all my applications, all my approvals, all my sharing models, all my conversations and the business is booming. By the way, the bookings are booming, but also the net new AOV of that business is very impressive.

And the key characteristic is when we talk about the MCP server tools calls on Slack, most of them were done by the builders building applications that needed that rich context that Slack provides. So huge growth, AUV top line growth, bookings growth, net new AOV, very little attrition. So...

Also on Slack, I think, is the best -- when we say agents and humans work together, you experience it in Slack. When you're in a channel and suddenly in a lot of these -- especially I see it now in my engineering channels, like half the time, somebody puts a question or a request on a Slack channel and the agent is listening and answering it, developers do a PR request in Slack. And then suddenly, the agent is picking up and trying to do it. They want status reports. So I think Slack is where people can really understand the manifestation and they're all asking questions as a human and Slackbot is even a better way of articulating that in a packaged way.

So that's like why -- what is driving and the advanced use cases because the developer community tends to try these tools. It's very embedded. They see this manifestation a lot more and which is also the reason why some of our most advanced customers and labs and engineering organizations are using Slack MCP even more than we thought. And I think that's a key interest. And I feel as it goes to the general population in the knowledge worker, Slack will become even more prominent because people will say, this is the way to work. And we always said Slack is the operating system of work. And I think now people can really see it. And once they start using it once, it looks like magic, and that's why they say, "Oh, this is how it all is meant to be."

Patrick, we're going to give you the last word here.

Great. Yes. I mean I think it's all about the experience that Slack delivers. I mean when you get in and you use a product and it just works, that is a moment for you, and you're going to go back to that product. And I think that's exactly what Slack is. And it's more sophisticated really than it's ever been. We started as this collaboration tool, but it's become so much more than that. It's not just a place where all of your institutional knowledge is it now can make calls out to other tools. You can have agents working right in there side-by-side with humans. You look at these coding projects and the incredible coding agents that have surfaced in the last 2 years. But the thing about coding is like that's not a single player job, right? When you code, you're working with a team and Slack is the only place where you can have that coding agent and the full team of all of your engineers and your developers all working...

And even the deals of support channels, it's there and with Slack CRM, this is all we brought back. So I think it's a natural place to work. So I really see that's what is driving...

I think number one is this, which is that when we bought this company, it was doing less than $1 billion in revenue. And it was struggling. It was having problems. The management team was really not clear how they were competing against Microsoft. But I think coupling with our distribution capability, now adding the value of our core applications, and I think this key point that it drove nearly half of our million-dollar wins this quarter, up 80% year-over-year. That means that Slack is really having its absolute moment. And I think the second thing that's really important is here's the Slack AWUs that have grown 350% quarter-over-quarter. That is amazing, 350% quarter-over-quarter AWUs. In 2 years, there's going to be more agents using Slack than people. I mean, this is an incredible example of the future and also how this product is more valuable, being used more, has more data, more capability.

And therefore, it's going to have more intelligence and more value back to all of these customers as well. Plus all of these companies can create Slack communication between each other as well. If you're a Slack customer, you can easily have a secure communication with another customer as well. Miguel, do you want to add?

Because that work graph that will become one of the richest work context in the enterprise is getting richer and richer. So we build -- I mean, the community built 3 million custom apps on Slack in Q1. That's 8x quarter-on-quarter. I mean there is a huge boom. Out of those custom apps, there were 250,000 that were AI agents that were built, third-party AI agents, and that grew more than doubled in quarter-on-quarter, grew eightfold year-on-year. So everybody is working on Slack.

Well, I think that it's safe to say, and I'm not giving guidance by what I'm saying, but sales is a $10 billion cloud already. Service is a $10 billion cloud already. Data is already a $10 billion cloud. I think when we see the growth rate that's happening inside Slack, you saw the ACV was incredible in the first quarter. This is going to be fast track from something we bought with less than $1 billion that I'm sure we'll be talking in short order about Slack being a $10 billion cloud as well. All right. With that, I'm going to turn it back over to you, Michael.

Yes. Thank you, and thank you, everyone, for joining us on the call. Just a quick reminder, we have our quarterly webinar on Friday. And very timely, given the questions today, we're going to talk about Slackbot and our Headless strategy in a deeper way with our product leadership. So please join us for that on Friday. You can find the information on our website. And with that, we'd like to thank everyone for joining us, and we'll be seeing everyone in the coming weeks.

Thank you for joining. This concludes today's call, and you may now disconnect.

Excellent. Thank you, everyone, for joining us this afternoon. My name is Keith Weiss, I run the U.S. equity software equity research franchise here at Morgan Stanley. Taking my software promotion become the overall but -- very pleased to have with us this afternoon from Salesforce, both Robin Washington, Chief Operating and Financial Officer; and Joe Inzerillo President of Enterprise and AI technology. So Joe and Robin, thank you so much for joining us.

Thank you so much for being -- and Keith, we had to be sure that we gave you one of our latest we hear there's a big announcement forthcoming, but also just for or right. You have to be sure to show it.

I never got to join in the club and Francisco because I wear suits all the time. So now I could finally it in with I got a lake

I've got to show everybody it's all about Blackbox.

Yes. Blackbox. Very nice. I like it. Thank you.

You guys recently closed your FY '26 and a transformational year for Salesforce. When it comes to sort of product strategy, which Joe is going to talk to us a lot about, but also the sort of operating model within -- in Salesforce and pricing models. So maybe just start out, Rob, you could tell us a little bit about some of the key accomplishments from a financial perspective. And how this has set you up for FY '27 in terms of what's been going on with Salesforce in the past year?

Yes. Well, thanks for that start. Yes, we had, as you said, a terrific year from an innovation as well as a financial standpoint. We announced our results last Wednesday as you had in like record revenues, record quarter, record cash flows. -- pretty much taking you back to Investor Day, Keith, I think what's important to note, we laid out a framework over the next several years.

We talked about that continued elevation of net new ALD being greater than AOV over time. And we saw those inflection points play out in Q3, in Q4. So it gave us even further conviction to what I said back then of the 12- to 18-month trajectory to return to organic double-digit growth. If you add on to that Informatica you're talking about '27, but we're even thinking broader, amazing integration already, great return. We were able to make that accretive fairly quickly here within 1 year and feel really good about how it's fitting in with our core data component of our platform and really helping our customers, particularly our customers.

So very excited about that. In terms of other things that we've done, we're seeing our investments start to pay off. We invested a lot in AE capacity last year, and it's something we want to continue to do -- we've also invested in FTEs, very focused on deployment of agent force. And as Joe talked about, a way for us to continue to fine-tune our agents to make them easier to install, et cetera. and infrastructure. So all things that really set us up well and on the continuum to meet our objectives over time. There's also just our growth playbook that we've had in place.

In Q4, if you think about our premium SKUs, 300% quarter-on-quarter adoption of those premium SKUs, which really for us shows the value of our stack in general. So that's really important to us. We've also kind of invested in industry playbooks and processes even with some of our new products like Grollo that are really helping customers kind of figure out where do I start? How do I take and become an identic enterprise? And what are some real focused use cases that I can accelerate.

So we feel really good about '27, particularly that second half acceleration that I mentioned and continuing to grow profitably. We have doubled down on investments in FY '27 to meet that FY '30 framework. Ended the year at rule of 44, feeling very good about that trajectory of Rule of 50. So prioritization on growth in revenue and a Gentex as well as as profitable growth that I think you'll get to the capital question at some point.

Hit on that. I want to bring Joe into the conversation. And you mentioned the stack. And I think that's important when we're talking about Salesforce because there's a lot of asset at play here that you guys have built out a very robust sort of underlying data platform. There's a lot of application capabilities on top of that.

Now there's an Agentic layer on top of that slack as part of the equation. And Joe, you've had a really remarkable career in 3 decades. You've had leadership roles at Disney streaming, BAMTech, Chief Technology Officer at SiriusXM. And when I think about your career, it's building big system. And this is a big system that you need to build out here at Salesforce. So can you talk to us about sort of your vision when you come in and you take this role, what's the vision of what sales force could bring to the market in terms of enterprise AI and what that's going to mean for your customers?

Yes. I mean thanks for the question. I think you're right. On one hand, you can look at my career and say, like, I built things of big scale, enormous. -- the other stuff they've done has been pretty big as well. But the other way to look at it is I really spend most of my time in the direct-to-consumer market, and not like a traditional enterprise technologies.

But I think at Gentex is one of those things where it feels much more like direct-to-consumer. And it feels it on a technical basis, like these continuous improvement loops, how do you constantly refine things, how do you get them better? How do they learn? How do you learn -- that's one aspect of it. But I also think it comes down to just the way we interact technology. And so in an enterprise setting, you say, "Oh, okay, well, here's a screen, and I'm going to try to optimize it.

Now every salesperson needs to conform to that screen. But if you go to sales and agent force or in Slack, now all of a sudden, you're having a conversation and knows who you are and knows the questions that you've asked. It's a very personal relationship, not unlike the customization that might be in a Disney Plaza SiriusX upstreaming or Pandora, where it gets to know you. That's now going to become in the forefront, and we're seeing it now becoming in the forefront of how these technologies mesh together to drive better outcomes for our customers.

Got it. So the past 2 like investor debates behind you. And investors obviously have a lot of uncertainty about sort of what the future holds, particularly for the SaaS application layer. But you -- I mean you came to Salesforce, you came into this big system is a big incumbent vendor with full knowledge of what was going on, right? Like the models were already in play. And you saw opportunity here at Salesforce.

So how do you get comfortable with some of the like the investor concerns? Like number 1 is the DIY concern, right? Now with cogeneration tools, it's so much easier to develop software. Why does that not present a more of a threat to Salesforce and what you guys have built and erode some of the moats that people have traditionally thought about within software business.

Yes, look, it's a great question. And I can see how people would think about it that way because they'd say, "Oh, well, look, you have these amazing tools. But I think about it more like a master carpenter right? Like back in the day when you had to cut with a hand off, like you really had a big good carpenter in all parts of it. Now you can cut on a table saw. It's probably going to be a pretty good cut. So the tools are raising the boats for everybody.

So yes, the DIY market is getting more sophisticated but so are we. And we have a backlog of data and features and things we've always wanted to deliver to our customers, but it sort of sits in the queue based upon what capacity you could afford for meaningful and disciplined growth. Now all of a sudden, we're seeing the good engineers and our teams are going 20x, and they can really sprint ahead of this. And so I think it's really, in my career, I've done a lot of DIY. We built a lot of systems from mostly whole clock.

But even I had the like, why would I want to waste time trying to build something that I could buy that's fit for purpose. I'd rather spend my development money to use those tools to do the thing I'm trying to do, whether that's DisneyPlus or another direct-to-consumer product, that's where my value is. And so I just think that like the combination of us continuing to accelerate the rate at which we're delivering meaningful outcomes to our customers as well as them being able to then use those outcomes to really specific on what their core business is, I just can't imagine there's a lot of people that are going to want to go backwards and say like, well, let me build a better Salesforce. Like I don't understand where the ROI is in that.

And there would also be a defense against another investor concern of start-ups, right? -- of AI-native startups being able to kind of move faster. But we think about startups, there's a dynamic between best-of-breed and suites. And if you guys can innovate faster you could close that feature functionality gap between sort of what a start up and focused on the single technology versus what you could bring into a broader suite, it seems to tilt the balance in your favor of like let's put all this solution let garner these new capabilities from our incumbent vendor who's already automating a lot of our business process totally. I mean, everything that you just said -- and then I'll add another one, which is if you think about social media.

So if you set sort of tick tock aside, that's really a state-sponsored company. It's tough to argue that they competed on the even field. But look at the social media companies. they're all the same ones that were social media companies that were at the birth of it years ago. And the reason is it's not just everything that you just said, it's also the data. It's that deep semantic understanding of what your customers are doing and what the processes look like. In case of social media, that sort of identity graph, the social graph that ties all these people together allows them the fuel to continue to innovate on the interfaces and things like that.

And yes, start-ups come, some of them get acquired, some of them are inspiration but they haven't really mounted a real threat against them. And I'm not saying that we think we're in vulnerable. But at the same time, we have all of these assets, and we have 26 years of real data that tells us where people are having problems where they want to go forward. How can we help automate those things with that tool set.

So the data is just as important because it provides continuous inspiration for how we're going to try to solve problems and move the bar up for what our customers are able to achieve.

And I think that's the key differentiation. Like they're not customers just desire to see if I don't just want technology. I want things that ultimately improve my interaction with my customers, my bottom line, my productivity. You can't do that without the data, right? So they're looking for solutions, and we built 26 years of being the trusted number 1 AI CRM vendor as well as being very innovative.

And I think you combine all that together, we have the solutions, we have the technology, but we have the trust and the data.

Right. And it's not just data like we're thinking about data, like the data sitting in the database is also the understanding of your customers, understanding their business problems, that's ultimately where the value is on the business problems. All right.

The second sort of investor concern that I wanted to pass by Jo was the idea of an AI user interface, right? And I think Claude with cowork really and how well that did tool use really spark this fear of that perhaps going forward, we're not going to go into Salesforce to understand what's going on in our customers and then go into maybe work day to understand what's going on with HR, we're going to have this one universal AI user interface that is going to handle all of our quest understand all of our systems understand all of our data and abstracts sort of the user from the end systems and maybe sales force a little bit more of a back-end transactional system.

So one, how do you respond to that concern and two, can Slack play a bit of that role for -- at least for a Salesforce customer, again, sales force type systems.

Yes. No, I think it's a great question. I'll take the second part first. I mean Slack,it's not an if, it is. if you look at the major AI companies out there, they're using Slack. Like it is the way that they get work done internally. So I think that Slack is a natural place for it because it's where people who use Slack get things done.

So why would they not also be getting them done with agents, especially because those interfaces and those interactions tend to be fairly textural. It's like a collaboration tool that she could say like what we found when Slack was founded before we acquired it, that they thought about Agentix, but they thought about people, but it turns out that the agents that people want to work in a very similar way.

But to your other point about the disruption side of it, I think the way I think about it is old enough that I've lived through these technological revolutions. And back in the '90s when you wanted to run a computer program, you went to a very specific computer and clicked a very specific binary and did a very specific thing. And then really, Mark, and Salesforce were the ones who invented "Oh, no, no, you could just do that SaaS, it could be in the cloud. And there was a whole bunch of like, oh, the people who had these binaries were going to be disintermediated. And yes, while Salesforce grew out of that with a new company, Oracle and a lot of these other companies are still around. They adapted to it. Same thing with mobile. Mobile, very similar things like, well, you need a map, and then all of these companies have apps.

AI is going to fundamentally change the way we interact with the computer. And that's cool. But it doesn't just change it in a super narrow way. It changes it in a general case way and slack back to the first answer, Slack is that organic way that people are de facto actually going to Slack because it's really well suited to do that. So yes, I mean, look, if we were a different company, and we didn't have Slack. Maybe I would be worried about it, but I actually think we're leading this transformation with Slack. And people are coming to us, the AI folks, they're building things into it.

And so there won't be a menogamy of interface there's going to be a plurality of interface. So where is the gravity? And I think Slack is a great example of the human collaboration with agents is the gravity and that's where we're pulling people towards.

Got it. Got it. Robin, I want to ask you about a different investor today, but another investor concern, and that's the risk of seat-based models. The idea that we are automating and doing a digital labor replacement of the very units that you price on. So how do you think about that potential disruption risk? Is there risk in terms of not being able to sort of make up for seats with added value that you're bringing with the more consumed developments of what we're doing with agents.

Right. It's a fair question that we get asked a lot. And I will say when we look at the core data, we're not seeing that. We're seeing the great adoption the momentum metrics around our Gentek products, but we haven't seen seats year-over-year on quarter-on-quarter decline.

And I think it goes back to the earlier conversation is as long as we're showing value of our platform and in our way, Gentex make our core apps even more valuable, I think that's what's really critical. Now to sit and say that over time, are you not going to have some type of attrition of seeds that could very well happen. But we really see a hybrid model of seats as well as adoption of our genetic products driving consumption. And I can't tell you exactly how those curves are going to grow.

But overall, we see overall continued value of our core apps and the system, the integration of them and the context is being really critical. It's like you can't have one without the other. -- our overall conversation here.

I totally agree with what Robin's saying. But I'll -- Robin and I are sort of here talking about the company, but we also have a relationship because in addition to overseeing Slack and agent force, I also essentially oversee our office of the CIO and all the things that we're using it. And so Yes. When she and I have questions like about, okay, should we invest in this. We're putting our business ads on as 2 executives that run the 75,000-person plus company, right? And we're looking for value. It's 1 of the reasons that we introduced this like agenetic work unit as a measure because it really matters what the outcome is.

Like you could spend 1 million tokens and that could be good or bad depending on what you're doing with it. As or what you're doing with it. And so when we try to think about investments, we're thinking about it in the same way our customers are -- and we're saying, okay, what is it doing? Like is it delivering the value? How do we get there? How do we measure that impact. And I think the whole industry is evolving, it's super fernetic right now. Nobody has a playbook of exactly how this is going to work.

But in a simplistic sense, if we deliver real value, like we're going to get compensated for that real value. And the higher value we can deliver because of the complexity of the task that the agents can sort of orchestrate across our stack and other stacks, that's going to bode well for what we can do from a pricing standpoint, regardless of the vehicle.

And I think just to take an example like that, and Mark, our CEO uses it a lot, is our helpdesk.com. We have been able to save on reactive call volume. Now we've been able to reallocate those resources to other areas of the business. it's adding incremental value. We're able to measure that and reinvest it or readopt it. And in some ways, it allows our customer service reps to interact more with the technology, the whole idea of humans and agents working together, so they can be more focused on proactive value-add co.

Our call volume is still going up because we're growing, but our ability to reallocate those resources and leverage agents really helps our productivity and allows us to rebalance. And so when I think about it as a user, the value of my users hasn't gone down. It's just allowed them to be more value-additive, more focused on ensuring that they're meeting the needs of my customers, and it gives my customers 24/7 support for things that don't meet human engagement.

Okay. So maybe to kind of sum up this, like investor concern and competitive dynamic and maybe shift the conversation more to constructive of what Salesforce is going to bring to the marketplace or Salesforce's positioning. It's unlikely that your customers are going to try to DIY their own solutions, right? That's what they look to us for. They're looking for solutions. You have strong competitive conditioning against startups. But there is this new white space. This is added capability that large language models and generative bring into the overall system. And there's going to be a competition for who gets at that white space, who is able to create this further automation, further productivity for the end customer.

So Joe, maybe you could talk to us about what sets up sales force well to win in that competition. What gives you guys the right to win in building out that additional capability, those additional workflows against the front office and even broader into going into stuff like ITSM.

Yes. I mean I think when you think about it, the whole paradigm is sort of like upside down from where it was before. So you think about like the way in which you build code was like very like, okay, let's take this thing we want to do, break it down into steps, do all these steps very iteratively figure out how we get there and all sorts of stuff like that. We're now starting to go the other way.

We're now the imagination is sort of starting at like the user level where you can put tools in the hands of users and then observe how you can continue to make them faster and faster and faster. And for us, I can't understate how important it is. It's not just the models. The models themselves are incredible, miraculous frustrating creatures that exist now, and they've completely shifted the paradigm and they keep making improvements, but they're not delivering like a results-based system that you can depend on for a business. you need that data. And it's not just the data like you were saying in a database that sort of sits there at rest. That data is now kinematic because of these models. It's always sort of being introspected and moved and things like that.

So when you look at us, we start with sort of this data layer where we have all of this amalgamated knowledge but we can represent it to the upper layers of the stack. And so you start working your way into the activation layer, the apps themselves, the facilities that the apps provide and then you have the genic sort of orchestrating the whole thing and then back to Slack.

You have this interface layer that then participates in the entire thing. And so does that necessarily assure that we're going to be successful? Of course, not. -- does it sort of show that we have this incredible advantage in vertical integration where we have like a really strong foundation of how these components that need to all exist, need to all interoperate, need to all be observable can work together.

And then because we've worked so much on the finish of how they fit together, you also get into the situation where I can't emphasize enough of these continuous improvement -- so it's not just does it work today. It's like how does it get better tomorrow? How does it react to the change in human behavior. How does it react to more data becoming available. And that's how these things are just going to go. Like there is not going to be steady state done, ship the software we're done. It's always going to be at this frenetic user level as opposed to the sort of architectural level.

And I think we're really well positioned because both through organic build and kind of the DNA of who we are and acquisition, we filled out that layer in vertical integration, and we've seen with hyperscalers and things like that, how much that vertical integration is a huge asset in delivering solutions that actually work and drive value.

Got it. So like we were talking about before, so Joe is bringing solutions to real customer problems. If you guys are bringing a solution to your customer, they're going to pay for it. They're going to value it in some way. And you guys have developed a whole menu of options for agent force pricing. We have Agentic enterprise license agreements. We have consumption-based pricing via per call. We have Flex credits. We have seat-based SKUs like agent force 1 edition. Why is this so important to that so many pricing options? Like why it creates a lot of confusion for us like infusion. Why is this so important to get adoption in the marketplace to have this menu of options.

Yes. It's confusion, but it's also agility. I think what we're finding to Joe's point, this is not a static market. We're competing. Our customers are looking at options. They're trying to scale. And our job is to be sure that we've got solutions that meet customers where they are. Some want to pay per user, particularly if they're looking at other options. Others want certainty. They want to understand what this means. They like the user model.

And so the different menu of options that we have allows us to meet a customer wherever they are on that journey, keep -- and over time, the ELAs are great. If you want to go all in on us, you don't need to worry about whether this agent is going to hit up against the cell too much or that's going to be term. You can really decide what are the right use cases -- do you want customer patients? Do you want employee?So we believe that agility that we have, sorry for the confusion, really helps take off the table for the customer any concerns they might have around cost. -- and it allows us to kind of just double down with them relative to being their platform of choice.

Yes. I mean, to Robin's point, I'd also just add living through the hyperscaler revolution. Was an example of like, it was a very different model. People were used to this CapEx model and I do this, I get a data center and all that kind of stuff. And by the way, like I used to be really good at building data centers. I thought that was an awesome skill set. I have built a data center in 12 years.

And so like that all of a sudden became less interesting to me. But I think when you think about that transition. We think about it as if it was like this square wave transition that just happened. And everybody was like, yes, well, of course, this is how you pay for a cloud. But really, is it took a long time in retrospect, it seemed short, but it took a pretty long time, took a decade really to get that into the full mainstream.

The same thing is happening as far as the pricing models go with the Gentex right now. The only difference is because gentex are moving so quickly from a disruption standpoint, that entire time line is compacted. And so like, to your point of us changing models, we're trying to be reactive to the market, trying to be reactive to our customers, meet them where they are. if that -- if you actually slowed down time and kind of expanded that to a decade thing, it wouldn't seem as frenetic, it's just because there's so much opportunity and so much disruption right now that it feels like they're stacking and it is, and it does confuse customers, but we think the inaction is much worse than that.

So we really want to try to get some stability, really trying to mature it and get to a point where we're meeting everybody where they're at. But I think the time scale is what people don't really appreciate is the fact that this is all just happening really fast for the whole industry.

And I think the receptivity that we've had gives us the ability to monetize in any framework that the customer wants. Over time, it's more predictable for us. It's, again, back to that hybrid model. But our goal is to ensure that our overall platform is sticky, it's retained. And we think this all-in model really helps us with that in our regard.

And to Joe's point, we're iterating with the customer -- it's a very different selling model. It's not users and we go away. We're out there are forward deployed engineers working with them and fine-tuning. And these pricing options, including credits, give them a lot of different options and ways to absorb that based on the success that they see in the iterations that they go through to be successful.

Right. So I mean, what I hear from a lot of investors and what they're looking to me for and want they're looking to view and the IR team probably even more so is clarity. They want absolute certainty of that $1 a seat revenue is going to turn into X amount of agent plus seat revenues. But listening to Joe about the -- how quickly this is evolving, how quickly the capabilities are evolving. -- listening to you about how customers are still trying to figure out how they want to pay for it.

It seems like maybe we're looking for something that would be too limited, right? If you guys narrowed it down to one set of functionality in 1 pricing model, you're going to limit your opportunity -- so with that being said, it's near term maybe maximizing from the stock price long term, limiting -- what should we be looking to? Like what -- is it? Is it the genetic work units we be looking to? And what gives you guys confidence because you call for acceleration into the back half of FY '27, you looking to, to get that certainty to give that forecast? Because I know you you're conservative. Like you're not going to tell us about acceleration until you feel really comfortable with that accelerate.

usually hazard of the job -- but no, I mean, at the end of the day, it really comes down to customer success. And it's really about that partnership. We've used -- we've thrown out the AW -- I should say, to run it out. It's a really good metric for AWs. -- but we're looking at net new A -- so we have a set of metrics that helps us really understand the direction of that customer journey. I think the other thing that is important, keep to your point, what's happening with the customer -- and we also talk about the multiplier effect of being on multiple clouds, leveraging our Agentics, et cetera, we're seeing real acceleration of ARR per customer as both customers go on this journey towards the Agentic enterprise.

So that's another comforting point to us. But you're right, we're definitely in a shift I think trust and customer success is absolutely the most important thing. And as long as we do those things, we're going to be okay and show that value and work to our customers. We see it in the numbers. We see it in our pipeline. We're seeing it with our SDR agents, which are generating more leads. And to your point, I think customers are coming back saying, "I don't want technology. I want solutions. And that's what we've been doing for 26 years.

Now with the Agentics, I think that's the value that we see and that's the direction of growth that we see our customers really leaning into.

Totally. And Robin sort of talks about the growth in ARR and like how we think about it. But I also sort of break it down into customers that I personally interacted with. And so like I was in APAC in November, and I was talking to 1 of our customers that was just sort of starting the Agentic journey in Japan. And that same customer about 2 weeks ago was in New York, and I got to see them again. And it's sort of it's like your friend's kids, right? You see a picture and say, "Oh, wow, they're big.

Now I had that same sort of impact with their Agentics where they had sort of started and then you look at it like, wow, and now they were coming in to talk to us again about what are the next 5 use cases we're going to do. And when you see that kind of like we did something we work together, we partnered, they got results. And now they want to expand that program, it's hard to like summarize those in a number on a spreadsheet, but you feel it when you see it happening. And I think that this particular customer was a great example of I got two snapshot of pictures several months apart, and I could feel the acceleration.

Yes. We see it internally. We call ourselves customer 0, and we started with everybody experimenting, hundred-plus agents -- we've kind of got it down to 4 key categories: employee, customer sales, back-office procurement, what we call them hero agent, and we're starting to see the acceleration. We were just -- they are talking to employees, it's about it's getting us permission to go faster because they now see the value add, and we now know where to invest and where to decelerate, and we see that same journey as Joe said, with our customer.

And I think this is also the part that sometimes I see undervalued in the industry or underestimated in the industry is the fact that like these tools are due to everybody sort of almost instantaneously. And so when they come out, obviously, we have relationships with model folks. We get a little bit of a head start. But people are now starting to really know how to use them to deliver real results. And so when I talk to other CIOs, their second agent is a whole lot easier than the first.

And the third is easier than the second. And that's both because the products are maturing, but it's also because they know what life cycle, a genetic life cycle works for them. They have the data. They know what they need to look at. They know how to make these things better. it's not like there's no appetite to take these things on. So really, what we're now into is the building of the confidence curve about the practitioners understanding that like, yes, I can sign up for a number that I'm trying to either grow or save I know I can do that now because I've got this precedent of these last 3 things that I've done.

And now I really feel like I have mastery of the technology despite the speed that it's going on. And that learning curve of the practitioners really starting to understand how to actually use these things that are advantaged for a business, we see every day with ourselves and also when we talk to customers. And like I said, sometimes it's hard to see that read through into a spreadsheet in a very, very specific precise way, like you all want to see, but you feel it when it's happening, and we definitely feel it.

Right. So you guys take these innovations, you create solutions for your customers. You're starting to get real traction with these solutions. You're feeling it from the marketplace and you come out with Agenetic work units to try to pay to us sort of that inflection that you're seeing in the business and the traction that you're seeing with these agents, why Agenetic work units we come up with a new KPI. Why not tokens? -- like everybody else in the industry is talking about coking -- why do we have to come up with a new KPI for Salesforce in particular?

I'll give you a really perfect example of it is 1 of the things that we've done with agent force in the last -- we announced sort of a Dreamforce last year, tail end of last year was agent script. And this notion of like the real challenge that a lot of people have when they go down the agentic path is, you want a rich understanding of what the human is trying to do -- but often, you want very prescriptive outcomes.

So if you're filling somebody's prescription, you don't want the engine to guess, right? The models themselves are stochastic, right? They're probably ballistic. So like you want that to be very precise. And it's really tough to do that within an LM by itself. So part of Agent script is this deterministic side a bit that we have with our new planning agent, agenticaptive reasoning, we call it, and when you look at it, you start to say, well, if somebody goes to do something and the token use goes down, that would be bad except if they start to use things that actually use this a genic reasoning engine as opposed to the LOM itself, the token count goes down, but the actual efficacy goes way up.

And so we really felt like tokens are a story, like you do need to look at tokens. But at the same time, you really need to figure out like how do you get worked on. And the work unit felt like a very parcelable thing where you can say like we actually did something that helped further the cause of whatever this customer was trying to do. And so that's why we thought that like it never fall in love with these things. They come and go. -- but we felt like we needed something that wasn't just tokens because it wasn't really describing the phenomena.

And ultimately, you want that mix of like efficiency, efficacy and cost to all be concatenated into 1 statistic. And right now, I just think the market is so immature that we don't have the ability to quite do that yet, but AW use we think, is a big step in that direction.

And the benefits to that, to us, it helps our customers better understand the ROI. It also helps us better manage 1 of your other question is what's going to happen with gross margins, right? So the efficiencies of that, that engineering feed internally for us helps our gross margins as well. And again, I can measure Joe's success, our success in customer by looking at our work units. What are we actually getting done. So it's a great metric for a number of different reasons.

Salesforce isn't just a wrapper around tokens. You guys are adding a lot of value back is you get levered exactly again...

And that value is not only with the agents, it's also with the core. that, again, it's this hybrid model of users and agents working together with context of data that's the value proposition that we want.

And back to the absolutely. And you just touched on this. I think it's worth like just really trying to put a fine point on. Again, when we talk about like context and things like that, we're sort of talking about it in a past tense. -- in the sense of like this is the thing that the agent needs to make its decision. That's true. But when it makes its decision. The thing that happened becomes context as well for the next call the agent makes either to that same person, very personal context or sort of thematically across the organization or when we look at it from building the technology stack itself, it winds up being the more that you can do these, the more you get acceleration in people using it, the more exhaust you have from these transactions, which then make the transactions better, which makes people want to use it more, et cetera, et cetera. And that flywheel effect starting in a lot of things.

We saw it internally, we see it with a lot of our customers at this point in time. But that's where it's really going to start to accelerate because each 1 of these things just reinforces the previous action and then predicts the future action better.

Got it. So I want to wrap this all up with the capital allocation question. You guys have talked about the Trinity of capital allocation. You started paying a dividend. You raised at 6% this year. you're going to have strategic focused M&A that is more shareholder-friendly as well as share repurchases. And you guys returned more than $14 billion to shareholders in FY '26.

90% of our free cash flow last year. Yes.

You guys put out a very big number in terms of share authorization. $50 billion at the time it was 27% of market cap. Does that signal a little bit more of a weighting on the share repurchases given where the share faces, given your excitement in the business, versus maybe the other 2 parts of the Trinity.

Yes. I would say the way we -- I mean, look, I said it on the call, if you look at what we see as the value of our products, our innovation in our company, there's a big dislocation -- and so we see no better investment right now than Salesforce. That being said, we're going to do it in a balanced, disciplined fashion that doesn't preclude us from thinking about smart M&A.

Last year, we acquired 10 companies, including Informatica. To your point, we're doing in a disciplined fashion. You should consider dividends or floor -- and we're generating a ton of free cash flow and expect to continue to do. So yes, they're all important. -- we see dislocation with us. We're going to double down and be a little bit more aggressive than we have in the past. But all, to your point, in a Trinity fashion that makes the most sense that drives long-term shareholder value. And at the end of the day, its growth in that top line, the reacceleration of double-digit growth.

We know that's how we're valued. We're not going to do anything around share repurchases that preclude us from doing that. but we see a really opportunistic opportunity to take out a portion of our market cap, and that's what we're going to focus on.

Amazing. Super setting time at Salesforce. Joe, Robin, thank you so much for joining here with us.

Thank you.

Good morning, and thank you all for joining us. I'm Dame Decide. This session marks the fourth in our series of quarterly post-earnings webinars aimed at providing you all with a deep dive on our latest product innovations and strategy. Today, we will deep dive on our Agentic enterprise architecture evolution and innovation. As you heard earlier this week on our earnings call, our force system architecture of engagement, agency work and context it's foundational to how we are helping customers become Agentic enterprises.

Starting with some housekeeping. Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties and assumptions which could change. Should any of these risks materialize or should our assumptions prove to be incorrect, actual company results or outcomes could differ materially from these forward-looking statements. A description of these risks, uncertainties and assumptions and other factors that could affect our financial results or outcomes is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q and other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements.

Today, I'm really excited to host Muralidhar Krishnaprasad or may, our President and Chief CTO of Product Engineering and Madhav Thattai, our Executive Vice President and GM of Agent Force; we're going to start with a brief presentation and a demo, and then we're going to jump straight into your questions. And I know this is not a shy group, but please do submit your questions in the chat. With that, I'll hand it over to you, MK.

All right. Thank you, Ami. As you all know, first of all, good morning, and thank you for joining us. As you know, all know, every company wants to become an Agent tech enterprise. And for us, the definition of an agent enterprise is where humans and agents drive customer success together so that you can get better productivity, higher revenue and, of course, more efficiency in our operations. Next slide. But I think the biggest mistake people do is that they just think simply, all it is, is you just need an LLM to do the work. Because raw intelligence is not enterprise work.

On the left side, you see the frontier models all ready to go tackle the complex intelligent task. On the right side, you have the enterprise outcomes. Unfortunately, 95% of all these enterprise Air pilots fail because they're not crossing the case. Because these LLM can't act their own. They are not deterministic. They don't -- like you can't rely on their outcomes all the time, and they lack business context.

And so next slide, this is really why the agent enterprise needs more than models. And this is not just us just pontificating but really through our experience over the last several years making so many of our customers successful bringing in agent enterprise. And the 4 things that we really need, starting from the bottom is a system of context, which can tell you exactly what your data is, what your customers are, what are they doing, so that you have the business context around the operations you want to do. The next is the system of work where the work actually gets done, whether you're servicing a customer, you're selling to a customer, you're marketing and so on. And then you have a system of agency, which is actually doing that, taking that raw intelligence and being able to orchestrate across the system of work using the context appropriately.

And finally, the system of engagement where you're actually talking to that customer on the right channel, whether it's for employees or for customers. And we believe these 4 is really what takes that crosses the chasm from intelligence to business outcomes through an AI-driven model.

Next slide. Here, in Salesforce, our 4 layers of context work, agency and engagement, we believe we have the industry's only unified stack that can make this possible. Starting from the bottom, of course, we can run on any models, whether it's open in tropic, Gemini, et cetera. Starting from the bottom, our Data 360 provides the foundational system of context. You can bring all your structured data, unstructured data, in many cases, just 0 copy, you can leave the data in their warehouses, but pull them together. And really create that singular customer profile, product profile and others, which can help you give that context of what the users or accounts is doing across your business.

And then we have above that is a system of work. We have the most industry's comprehensive thing related everywhere from marketing, sales, service, operations, analytics and so on. And this is where work gets done. This is where all your business workflows are created as well. And as you know, we recently launched our CCaaS and IDS product line as well to join this. And then you have the system of agency. This is where the agent force customer and employee agents are built. This is the 1 that is taking the context and then bringing all of the business workflows that are there in Customer 360 together using the power of the LLM models.

Finally, the system of engagement is where we have both our channels with all the channels that we support from WhatsApp, SMS, text, e-mail and others, but more premium channel is with slack for our employee experiences particularly with Slack pot and our ability to do enterprise search and really bringing in all of the power of the visualizations also into the system of engagement. So this is how comprehensive our stack is, and they all work together in unison.

Next slide. Now I'll just briefly deep dive with 2 slides on the context itself and hand over to Madhav. So to do that context, you really need data -- and this is really where Data 360 comes into play. You can connect to hundreds and hundreds of different sources that's a new enterprise very easily. You can turn any unstructured data, your call transcripts, your nodes, your design documents, whatever they may be into both structured data as well as vectorize them so that agents can actually understand and reason over them. And you also get memory, all these agents get both short-term and long-term memory so that when you come back after 3 months to talk to your business, it can actually quickly pull back what you have done. And you also want to bring that quality and clarity because data quality becomes important. You're putting the reputation of your business on the line by putting the agents in the front, and this is where the data quality and cleansing comes into play.

Next slide. And so putting this together, the way context works as you see on the left side, you have all of this data and all of these applications sitting there with the power of the Data 360, the MuleSoft, Informatica and Tableau, you can actually create those MDM records, the unified profiles, create the context engineering around it where you tie all of this data with the raw data, with the context about what they're doing with the agents and be able to go analyze it and then link it back into the system of work. So this is how the context layer at the bottom ties in with all your data stores in the enterprise with the system of work that we have across and then feed it to the agent layer. Madhav, over to you.

Thank you so much, I'm glad to be with all of you today. So MK talked about the system of context. I want to now touch on the system of agency and what we built with agent force. I think you all saw Otis in our earnings, we talked about the performance of agent force in the last 15 months, we're now at an $800 million run rate up pretty significantly year-over-year. And we went from about 3,000 customers to now over 23,000 customers across those 29,000 deals that you see. It's been incredibly encouraging to see customers from all over the world. in different industries, using agent force for many different use cases, some of which we're going to talk to you about today.

But a couple of the things that are really, really important as we think about this. First of all, we see agent force uplifting our license products where customers are now using them for premium experiences for employees with our agent force for sales, agent force for service, agent force 1 edition products the customer is getting a lot of value on those employee use cases. And then, of course, there's the consumption business where these are fully autonomous agents that are facing customers. You've obviously seen the great examples with Williams Sonoma and others, where we have these agents that are doing kind of end-to-end life cycle work for our customers. And then also really encouraging to see that some of those customers now are really at a deep stage of maturity. And so they are coming back for more credits and more expansive use cases as they start to drive this across their life cycle. So incredibly exciting performance for the product, and we're really just getting started.

Let's go to the next slide. Now I want to spend a minute on this. We introduced this new metric this week, and I know I've talked to some of you already about what it means. But MK made what I think is the most profound and important statement, which is it is not sufficient to just measure intelligence. And we've been talking about intelligence as measured by tokens for a couple of years now ever since this capability launched. And it's really important to understand what's happening at the infrastructure layer, just like when we talk about the cloud, we want to understand what's happening at the compute layer, at the storage layer, at the networking layer, and we really see tokens as a part of that infrastructure layer. But what we care about and what our customers care about is turning that intelligence into work. So we introduced this new metric a genic work unit, which is really comprising all of the work that is being done on our platform with these agentic systems.

Now that could be a decision made by an agent to respond or make a decision and reason through a particular task. It could be the task of actually performing a record update or triggering a workflow or maybe an API and a third-party system, maybe running a piece of code and so we now systematically measure everything that's happening in agent force, in Slack, in MuleSoft and we say, okay, let's really understand how are customers getting real work done because that real work is what really tells us that the utility of the product is valuable to the customer. The more they use the product, the more we know it's having an impact on their business. And so it's early. We're trying to understand a lot about this metric. We can now look at this metric by product line. We can look at it by customer. We can understand which use case they're using it for.

So really, really exciting. And we think that the moment has come to move from a simple measure of intelligence, which is an input into what is the output and the actual work getting done.

So if you go to the next slide, and here are some examples. These are some of our incredible customers. We talked about some of these at earnings as well that are really doing a lot of work at scale. And you can see the variety of different use cases, and that's really what jumps out on this slide. We have customers like Adiba recently went recently went public in Latin America. They are using this agent externally facing their customers. So every time a customer comes back to ask about loan status to understand what their next steps are, they are directly interacting with this agent. A great customer like Bouygues in Europe, they have their agent that they call Iris, which is helping their employees. And it's helping their employees with fairly complex tasks across all of the things that their employees need to do to really drive that internal productivity.

ADP is a great customer. They're actually using an agent internal to their company that's helping them with HR workflows. So this isn't even in just sales and marketing and so on. This is actually expanding what they think agent force can be used for. And then, of course, General Motors is using task-based agentic automation. So this is -- I have very specific tasks that I need to go accomplish. These tasks are in the flow of work. They are where my employees are working in Salesforce and Slack and that automation is driving a lot of productivity. So that's really been encouraging because we see customers that are experimenting with a variety of use cases, pure employee productivity. Employee assistance with more complex agents. And then, of course, really the important use cases, which is we now feel confident enough in this agentic technology that we're going to have our customers interact with this agent. So that's been really, really encouraging to see and a lot more to come with all of these customers that are really starting to add more use cases.

Let's go to the next slide. But this is really the bottom line here. There has been a tremendous amount of energy around building. We can wipe code, we can accelerate the deployment of software, and we are significant users on MK's team and across all of our engineering teams, where we believe that this technology is accelerating our ability to build, and that is remarkable. However, there isn't an enterprise in the world that wants to vibe operate. The build is the first part of this journey, and we have really worked over the last couple of decades with our customers to help them run their business. Now to run your business, after you build, you need to understand how do you want to test the capability? Is it working? How do you evaluate it? How do you observe it? Is it driving your KPIs? Is it driving your outcomes? How do we continuously optimize.

And that is where the fact that we are so deeply embedded with our customers, the fact that their most valuable work, which is how they interact with their own customers, happens on Salesforce really gives us a deep understanding of how we take the best of this intelligence technology turn it into remarkable experiences but then importantly, help businesses operate and manage that capability. But I'm going to stop there.

Let's go to the next slide because rather than just talk theory, we actually want to just take a few minutes and just show you how the product works end-to-end. And for that, we're going to bring in the incredible game Sumner to walk us through a quick demo of what this experience actually looks like.

Yes. Thank you so much, Madhav. So what are we looking at here? What we're looking at is the type of agent that we are helping our customers create, which is essentially an agent that represents the brand. But as Madhav and MK just talked about, for it to do that reliably, it's got to be grounded in those 4 systems: engagement, agency work and context.

And let's just start with context. So if I just give this agent and instruction, I need to reschedule my flight. We know -- we know that to do this job reliably to answer that question, the agent has got to be grounded in that enterprise context that might have just -- or that MK talked about. -- got to know who the customer is. It's got to know what their flight was. It has to know what an appropriate replacement flight might be. But customers also want to take these agents a step further. We want the agents to take action on the brand's behalf. And that means you need to give the agent some level of agency to respond flexibly across a whole spectrum of requests that the agent might get while, while always adhering to your business rules.

Now if we're going to transform all those customer experiences with agents, we need these agents to engage across all the different channels where customers are, which is going to include mobile but extends all the way out to voice and your 800 number with those CCaaS systems that MK talked about earlier. And if the agent needs to escalate to a human it means the agents have to work where your employees work, which means supporting seamless handoffs between the agent to employees inside the work systems where they are using to work and collaborate. And as MK and Madhav have just talked about, we are the only agent platform that brings together these 4 systems. And let's take a little bit of a deeper dive to explore exactly how that happens.

So this is agent force builder. This is where our customers define their agents and agents are defined with topics. You can think of these as essentially the jobs the agent is allowed to do. And behind each of these topics is essentially a little subagent that is comprised of both instructions and actions. And if we were to go into instructions, like these are the guardrails that you create that guide the agent's behavior. And because we've introduced this new scripting language, agent script, we are able to blend this kind of like deterministic logic, your business rules with natural language kind of instructions. And that is what gives agents for us this kind of the agency to adapt while always kind of adhering to your business rules.

Now there's also these agents are comprised of actions. And you can kind of think of these as the tools that we've equipped agent force with to actually do all of this work. And what would that work be? Well, it can be things like retrieving data from sales force or outside sales force with Data Cloud it can also be executing your business workflows. It could also be even using those MCP tools from kind of the open ecosystem that we participate -- and -- let's pause here for a second.

Yes, sure. This is really important. -- what Gabe is showing you is how the agent gets built. And when you think about how the agent gets built, he said some really, really critical things, and these are kind of the core and most important innovations that we brought in. Number one, tying in that context directly so that the agent is leveraging all of that enterprise data that is connected into Salesforce -- you don't have to build extra data connections. You don't have to move data around, it is seamlessly integrated into that data. So that was 1 point that he made, that is really, really critical. The second thing that's really important is One of our biggest learnings in the Agentic enterprise has been this need for determines to control.

These aren't just agents that are answering simple questions. These are agents that are executing on work -- and so how do you make sure you are tying that deterministic ability into the agent build is really, really critical. But really importantly, those business workflows sit in sales force today. And MK brought this up before when he called it the system of work. tying it back into the work and the process that is happening is what allows customers to not have to recreate process in order to roll out these agents. And that's a really important way in which these agentic deployments can go a lot faster and a lot easier. Go ahead, Dave.

Yes. Absolutely correct. And then as we move forward, we've talked about all the different engagement channels. So this would be where you extend agent force to all those channels where your employees and customers are -- and then if we go down to here to the very bottom, and I'm sorry, Zoom is in my way here. But you have data, which allows it to be grounded in that unstructured data like those knowledge articles. But honestly, the way to kind of like see all of this come together, I find it just like go test the agent and see how agent force actually goes and does a job. So this is the simulator inside of agent force builder that we can use to kind of see how the agents work or how agent force works. And I'm just going to ask you to find a flight from Seattle to -- and so like what is happening right now is agent force is kind of using that agency that we granted it to flexibly understand the intent to make a plan to ground itself and all that right enterprise context, to execute the actions and adherence with our business rules until finally, it surfaces the right answer.

And not just like surface is the right answer, but explains the reasoning that it used to produce that answer. And we've given our customers the tools to really dig deep into all of this and just really look at all the individual details that were used to create this reasoning. And Matt have talked a little bit about the Vive coding experience like we're trying to bring that vibe coding experience into the enterprise. So if you notice problems with any of this execution, you can just ask agent force to fix it. And instead of like it generating a bunch of ad hot coke that you have to then maintain yourself it's generating kind of metadata that sits on top of an enterprise-grade platform. And that's how we get -- help our customers get their agents ready for deployment.

But of course, 1 test, 1 test, never enough for these nondeterministic solutions, which is why we also have testing center, which uses AI to generate hundreds, if not thousands, of AI-generated test scenarios so that we can just test a whole spectrum of things that we different ways that customers might ask the agent to do different things to make sure that the agent is performing as you expect, across all of those different simulations.

And then long after deployment, we're giving our customers the tools to understand how their agents are doing against the backdrop of all their business KPIs. So they understand the value that agents are bringing to their business. And we're also not only helping them understand how agents are doing but also what the agents are doing. So you can drill down into this visibility across different topics and even highlight things that the agent could be doing better. And zoom all the way down into individual interactions to really see how an agent is doing an individual job, look at everything that's being done to do that job, interrogate it, troubleshoot it and that becomes that kind of flywheel that just makes the agent better and better and better. So this is how we're bringing together those 4 systems at MK and Madhav have just talked about, to convert that raw intelligence of these frontier models in the trusted enterprise work. I'll give it back to you.

Thank you so much, Gabe. Really appreciate it. So let's go back to the slides because we want to show you a little bit of how we think about the stock. But we know this question is going to come up. So we thought we would just address this head on. You've probably seen here in the last couple of weeks, a lot of announcements from the Frontier model companies about their enterprise agentic stack. So let me start with saying this -- these are companies that we deeply, deeply partner with, both OpenAI, anthoopic, the other model companies, the hyperscalers we are very close partners in really building this technology and bringing it to customers. And secondly, these companies are also customers of ours. And so we also work really, really closely together to make sure that they are being successful as they're building these remarkable companies with this remarkable technology that is genuinely changing the world and changing the enterprise.

But there's some important takeaways here when you think about what the frontier companies are saying about the Enterprise business. So if you go to the next slide, we kind of broke this down a little bit to map it to how we think about our stock. So let's just start with Frontier. We are in deep agreement with OpenAI that context really matters. As Gabe showed you, the workflows really matter, where your employees are working and how they are working is really, really critical. You need a system of agents across all of these important services in order to go deliver this capability out to the enterprise. And so that is really good validation of the things that we have said for a couple of years. The bottom line being the model layer alone, which, by the way, isn't really represented anywhere on the stack. But the model layer alone is insufficient to make sure that, that intelligence is being turned into work.

And in fact, we also were encouraged to see that OpenAI is partnering with many of the big system integrators that we work very closely with as well. Accenture, Deloitte and McKinsey and others because that implementation is really critical. Turning this into operation is really critical. And so this is a deep and important validation of our understanding of how these things actually get turned into real work. And then Anthropic, of course, has also been talking about their enterprise strategy. They had an event earlier this week where they talked about their strategy. And you kind of see how these experiences that Gabe talked about, the employee experience that we think of in Slack. These prompt and automation workflows that we've now been doing for a couple of years with our customers. And then, of course, these agents that are going to be building truly autonomous capabilities are really, really critical.

Now it's interesting in 1 of the main demonstrations that they showed, the experience began in Slack a group of people were talking about how do they improve the decision that they needed to make. But the immediate next step was someone needed to leave Slack and move to a different UX in order to go execute a task then they had to take that task, bring it back to slack in order for the decision to get made. Now we don't believe that's the right experience for users. We think all of those things have to happen in 1 place. And of course, we're deeply partnering with Anthropic to make sure that customers do not have to leave their flow of work in order to bring all of that intelligence and that capability. And so a deep validation of the things that I think we've been saying for a while as we have built this comprehensive stack that MK talked to you about before.

So let's go to the next slide. This is now a view of our system of agency. We touched on each of these things. So I'm not going to really get into repeat the detail that we just talked about but a lot of deep innovation at every layer. And this innovation is not limited to agent force. Gabe showed you the operating layer today, where we optimize, we analyze what that layer is built with Tableau. When we think about the orchestration layer and a genic system where agents are talking to each other, we are very closely tied with our MuleSoft technology to extend that across the enterprise. Of course, at the context layer, we're making sure that we're tying in with Data Cloud, with Informatica for all of the reasons that MK said to really surface up all of those capabilities.

And when you think about the experience layer, this is the work with our applications teams to really make sure this intelligence is surface for employees. It's working with Slack -- so you're in the system of engagement. It's working with all our channels like voice and chat and WhatsApp to make sure these agents are surfaced in those channels. And so it's a really critical strategy for us to bring these unified capabilities to our customers. But really importantly, we are unified but not locked in. We know we live in a heterogeneous environment that customers in the enterprise will want to connect a lot of technologies at every single layer. And so the open side of this equation really, really matters. -- openness at the data layer, the ability to orchestrate across all of these systems, the ability to share telemetry and data so that customers can do the analysis that they need and then the ability to really connect across all the interfaces.

It could be Microsoft, it could be Apple. It could be whatever interface a customer really wants to use and make sure that our agents are able to surface up in those interfaces. And so that's really the strategy and what we've done.

If you go to the next slide. But really importantly, strategy and a set of slides and a set of demos and blog posts are really not the business that we are in. The business that we are in is to be really, really deep in the trenches with our customers, really making sure this technology is making them successful. And it's been a real privilege to work with some of the biggest companies in the world. As I said, across industries and across use cases, so we can really, really understand how this technology can create value in a number of different scenarios. I won't drain the slide, I'm happy to talk about some customer examples and Q&A. But each of these customers has helped us drive a critical innovation in the product. Working with Williams-Sonoma really helped us understand how do we tie that context layer together to create an incredibly rich experience. And if you haven't played with it, you should go to Williams-Sonoma's website.

This is an agent that's helping you not just discover Williams Sonoma's products but really create experiences in your life -- and it starts from that in order to go in and then make product recommendations and actually think about what products customers want and then customer service, we're tying all that together requires a tremendous amount of context. -- deco is an incredible customer of ours. In fact, they just yesterday launched a brand-new voice experience for their candidates. And Adecco uses us to do what is their most important business process, which is qualifying candidates in order to match them to jobs. And that process is a perfect example of why LLM and determinism have to come together. You want to use LMs to create this rich experience with the candidates. It's flexible. It can ask them questions. It's empathetic to where these humans are.

But a qualification process has 30 steps. You want to make sure every single step is followed. If you just handed that off to an LM, it is not going to execute consistently and accurately across all of those things. Equinox. Equinox really helped push the boundary on how do you create rich experiences with this technology. This isn't just a bot that you put on a website. You want to have rich information. You want to have rich content. You want to have interactability, -- you want to have flexibility in how the agent actually plays out. And so it's really been incredible to partner with these customers as they're pushing the boundaries of how this agentic technology is going to be used. So what I want to do next is hand it back to MK. He's going to give us a little bit of view of where is this technology going? What does the future really look like.

Thanks, Madhav. I think what you saw in even gave stem was a hint of where agents are going to be called in other agents, the super agent, as we call it, right, because we want every customer of ours wants a single brand agent that coordinates work across everything else because when you go to sales for toccom, you're not going there intent of just asking a service question. You might want to go to sales. You might want to go to marketing and so on. The Williams-Sonoma is a good example, where you may asking about the Susha agent about some recipes and then want to go and purchasing things.

And so super agent becomes an important thing. We believe 2026 is the year that every company and the brand will choose a super agent and be ready for it. And so on the consumer side, with agent force. We have the super agents that can go talking to other agents or let other agents call into us next slide. But even more interesting on the employee side is where we believe Slack is going to play a huge role in the system of engagement and super agents for employees next slide. And that comes with Slack port. If you have not tried Slack pot, you must try today. And Slack part is a perfect example of how the context that's in Slack, where all our work gets done uses the power then of our AI tools to be able to go bring that right thing at your fingertips. And it's able to go orchestrate not just across all your data in your enterprise, but across all your agents as well to get your task done.

And as you can see here, we've already seen huge success with Slack part. In fact, we heard from many, many customers, where if the Slack bot was turned off, they literally said we can't work anymore. So it's become such an important ingredient just a few months since it's been released. So that is how we believe both at the consumer side with our agent for super regions, on the employee side, with our Slack pot and Slack super agents, we're going to really bring the power of agents talking to agents to your fingertips.

I think that's the end, correct? Yes. So with that, thank you all, and we're ready for your questions.

Awesome. Thank you so much, Mava and may -- we are going to jump into Q&A now. As a reminder, please do submit your questions via the Q&A feature in the Zoom channel. To start here, we have a question that we've been getting pretty regularly from investors this week. People are really excited to see the agent force momentum, the $800 million ARR, the strong growth -- but people really want to understand what the long-term ARR ceiling or long-term growth rate assumptions are when we think about our path to our fiscal year '30 revenue target. So maybe I could start and then pass it over to Madhav. I think first, just what we're really excited about with that $63 billion. We have incorporated Informatica, of course, but it also takes into account the net new AOV performance we've had over the last few quarters.

And when we gave you the update at Investor Day on how we see the slope of the curve into the back half of this coming fiscal year, that's what really gave us a lot of conviction is we're seeing this broader adoption motion that's agent force, but also let me go deeper on my core apps. Let me go deeper with my products with Salesforce and really driving a broader set of adoption than just agent force over here and the rest of the business over here. So maybe Madhav can help bring that to life in the conversation here.

Yes, I think it's important for us for everyone to get an understanding of how we go to market and what the monetization strategy looks like. So when you think about agent force, you can think of Three key ways in which we bring this capability to market. Number one, as Val mentioned, -- we sell products that create premium experiences for employees. So this is a license business. This is an upsell uplift business. And we have products that are add-ons to our cloud. So we call them agent force for sales first for service. We have all of these products for the industries as well.

And then we've got the most premium agent force 1 edition, and those are 50% to 70% uplift on a per seat basis. And these products are really ensuring that in employee scenarios were driving that productivity. We're driving the agency that customers really have for all of those kind of employee use cases. So that's a really significant part of the business. Half of the ARR really comes from that license uplift business. And we're continuing to see expansion and growth, a remarkable trajectory. We just launched that product in the middle of last year and remarkable momentum there. That's 1 type.

The second type that's really critical is the consumption business. And so what Gabe showed you is an example of an external-facing agent that is doing a lot of complex tasks. In many cases, those tasks cut across marketing and commerce and service and these are agents that are truly autonomous creating new types of experiences -- and so we sell that as a consumption business. And that business also has grown really signify a significant ARR on that business. And that gives customers the ability to really build these flexible multiuse case agents. There's also a lot of value. You imagine in an agent that is now acting as the front door, as MK said, as we build towards these super agents future. That is a remarkably valuable experience from a customer perspective and something that we expect we will also be able to generate a lot of value from.

So that's the second model. And then the third model for some of our customers that really go end-to-end with us is this new agent force enterprise-level agreement. And those agreements are really looking holistically across a customer. They're thinking about the licenses and the seats. They're thinking about what are the consumption agentic use cases. how is this customer going to use data cloud? How do we integrate across their enterprise with MuleSoft? How do we bring the power of our analytics with Tableau. And so a comprehensive really at the transformation level and that we introduced not that long ago, and we have a lot of customers and great momentum on that front as well. So that's really how you should think about the 3 monetization models. And as Val said, expect uplift in all of those things. So today, we report agent force is kind of a sum of those things, and we will continue to do that.

But we expect agent force to really penetrate and uplift all of those businesses. And so far, we're really seeing a lot of expansion in each of those buying models.

So the next question here is 1 that I think kind of ties very closely to this question. And when we think about the longer term, obviously, we had a record quarter with RPO, $72.4 billion in Q4 of FY '26. But how do we think about the trade-off, as you mentioned, between seat licenses, a generic enterprise license agreements and the flexible consumption credits, especially in the context of potentially reducing seats, right? I think everyone saw some of the news that came out yesterday. So how do you think about that? How do you think about the growth in agentic work units with that as a backdrop.

Yes. And maybe, Val, you could start with some of what we shared at Investor Day on how we think about the expansion on a per customer basis because I think that will be...

Yes. I think just to remind everyone, when we think about the overall wallet share expansion opportunity that we have with our customer base. If we are able to address the agenetic enterprise opportunity with these customers -- it's not just an incremental add-on type agreement, right? When we're going live with products like agent force Data 360, we're not only getting this motion of customers more willing to go deeper on their current applications whether it's in Service Cloud, they want to add on field service because they want to plug in to tie in the agentic experience to be able to plug in across that use case or they're willing to go from just a Sales Cloud service cloud experience to add on Tableau Slack because now they have confidence in the ability for these agent capabilities to lift all of those products and the underlying context to get a lot of value from all these different touch points, that for us, when we've seen customers who have gone live early, we've actually seen a significant uplift that goes beyond 20%, 30% growth.

it goes 2 to 3 to 4x of an overall spend expansion. So when we're trying to address this opportunity, we're really trying to address 3 things. First, of course, we want consumption. We want to ensure that we get high-value consumption. Agentic work units is a really good measure of that, and Madhav, you can touch on that. The second is we want to have a lot of value in the seats that they have today, we still see seats expanding right, across sales service slack, there's still growth that we're seeing today. Longer term, that might change. But I think a motion that's been really exciting for us is these bundled SKUs, agent force on edition, the more premium seats where they're actually increasing their ARPU and to translate that to customer terms, they're getting more value out of that existing seat and are willing to pay more for that seat base.

And then the third piece is really around that data in context, right? We just brought Informatica into the fold. It's been a great first quarter for us with that asset. But now with Informatica, MuleSoft, Data 360, Tableau, all these assets together really give us a broad scope to be able to address the context, data needs that our customers have. And that gives us a lot of confidence in that 3 to 4 kind of expansion opportunity that we shared at.

So let's build on what Val just said. I mean, 7 of our top 10 deals saw this kind of motion. This isn't the same as I have 1 more app I'm going to add, and that's going to give me 10%, 20% uplift. This is now -- I'm going to reimagine what my enterprise experience is going to be. And so that is a 2x and 3x and so on. And so when we really think about that, the right question that we've been really thinking about and that we talked about a little bit at earnings as well as every 1 of our customers is going to be on this journey of becoming an agentic enterprise. The really key question for us is -- how do we make sure that sales force is clearly and obviously the partner for our customers as they think about completely changing their customer experience.

Now we've had very encouraging growth on that front. We started with 3,000 agent force customers are now up to 23,000 agent force customers. And so the rate at which we are penetrating our customer base is really significant. We've added a lot of new customers along the way as well. And so that penetration of, let's go help our customers transform into these agetic enterprises is really the key -- that's on the employee side, that's on the data side, and that's on these very significant orchestrated super agents as well and those types of use cases that we're driving. To measure the work of those agents is really where we think about a tic work units, and MK, maybe this is something that you could help talk about a little bit as well. We really want to move from just measuring pure input consumption like tokens into output. So MK would love your thoughts on the Agentic work units and how you think about that for our customers.

Yes. Sounds good. First, let me add 1 more thing to what you guys said, and it kind of drives into the agent work unit. If you take that sales engagement STR agent, what it's able to do today is really go bring in more customers that we would probably never have even looked at before, leads and opportunities. Like, for example, even within Salesforce, like almost 90% of the folks who come to our website and others is too small for anyone to actually go have a meaningful conversation with them. Now with our sales agent it actually starts engaging with them, knows what they're doing and then it brings them up either to schedule a meeting with the salesperson or to actually close the deal.

Now that is an example where it's actually going to cost more seats to -- like more humans to be used to kind of create more sales, grow the top of the top line. Now coming back, 1 of the challenges we saw was just looking at a token usage, that doesn't give you the full picture because that's just -- okay, we are going have $1 billion, somebody else who's going to 1 billion and so on. With this new agent work unit, what we're able to say is it's not just about the tokens. It's also about the work that is happening within that business. So in the case of sales, it would include the workflow that's needed to go call and create the lead as an example. In the case of service, it's the work done to actually go understand that users intent and then go close the case or like create incidents and so on and so forth.

So each 1 of those, the agent work unit will capture that math of what is the actual work done in that system of context or in the system of work so that we can give a more comprehensive thing of how AI is actually helping your enterprise. And this is really important because we believe the Agentic business needs a canonical metric where we are showing that valuable work is getting done. When we measure -- as that is not internal use of agentic work units. That's not trial use of agent work units. That's not even the use of Agentic work units when customers are testing, which is super valuable, by the way.

But we want to hold ourselves -- and this industry is a standard of is real work happening in production. And I think having a canonical metric that can measure that is really, really important for us to understand how we're creating value with our customers.

To Madhav's point, we will welcome the rest of the industry to join us in this effort so that we can actually have some common metric across the industry to represent how work is actually getting down. Awesome. Our next question, I'm going to combine 2 questions into one. But Matt VanVliet from Cantor Fitzgerald is asking about super agents. Are they going to have different monetization elements to encourage uptake -- and then I'm also going to pull in a question that's tied to super agents and multi-agent orchestration. Specifically, if you're bringing in a third-party agent, how are you thinking about the data oncology? Do you have a layer that would help you understand and map the data across different systems. So maybe that second part can go to MK and the first part can go to Madhav.

Yes, absolutely. I mentioned the different monetization models that we had. I think another really important point here is, we have really learned over the last year just as we've innovated on the product, and you saw some of the incredible capabilities that we've built already and some of the things that are coming. We've also really innovated on the go-to-market and the pricing motion. And I think where we are is making sure that customers have flexibility and making sure that we're meeting customers where they are, where they are in the journey. If what they want is a model where they are still thinking about productivity in their employee use cases, great, let's make sure that we have offerings, and we have licenses that they can buy that they can leverage all this capability.

If they want to move to these more complex agents that they're building, including super agents in the future, let's move them to a more consumption model so they can really understand the real specific work that, that agent is accomplishing, and the monetization model is tied to that. that same argument is going to apply in the case of super agents. When you think about super agents, there are going to be actions that are executed across these agents, either within agent force or into external systems. We will absolutely think about how we monetize those actions as we do today. They're also going to be pulling in things at the data layer. And that data layer will all be monetized with the way we think about our credits and our data layer monetization. It's very likely in those super agent systems. They are going to be tying across the enterprise, so they have governance so they have observability.

So they have control, which means our MuleSoft capabilities will also be involved. And you've probably noticed over time, we're really moving towards a model where all of our consumptive products are on our single Flex credit system. -- it's fungible. It's movable across all these capabilities, and we make it as easy as possible customers to say, "I need the agent capability. I need the data capability, I need the analytics capability, I need the fabric and the governance across my enterprise. Can get all that with 1 mechanism at which I want to buy. And that's really what the Super agents are going to represent. They don't represent just agent force. They really represent that full unified stack that MK talked about to give customers the ability to take advantage of it. MK, do you want to talk about the data side?

I think you've sort of raised it very, very -- what are the things that I think you saw in 1 of the earlier mother slide is, for us, extensibility in working with your enterprise is a very, very critical part at every level of our stack. -- from the model layer to the data layer to the agency layer, work later and so on. And we are extending that same thing to multi agents as well. And the question specifically were all context. And this we all know, right, even humans, when we get transferred from 1 operator to the other, you got to go repeat all the context back again to saying what my problem is. And so we want to avoid that. And to that extent, the Data 360 layer that is creating the context with our agent force has open APIs through rest APIs, MCP, JDBC, et cetera, that all the other agents can also leverage. So when there is an agent to agent handout, there is no loss in context or translation. So that's one.

Second, to Madhav's point earlier, as these agents are learning, if you're using our agent Fabry, all the logs across those agents are also going to come back into data 360 and surface through our agent for studio. So that means you can actually understand how the lineage is working, how these agents are calling and actually start optimizing as well. And that helps into that circular loop that we can actually do to go optimize your agent in enterprise. So the short answer is -- our data layer can help you go across these agents and to also grab all the logs. Our mill soft layer can help you govern and monitor these agents and our agent for studio layer can actually help you go optimize them through our analytics.

Awesome. The next 1 here comes from an investor who is wondering about the maximum margin impact agent force can have on gross margins. Let me start and then Madhav can jump in on some of the things we're doing to optimize First, we, of course, have a product portfolio that's pretty broad and diverse. And as we launch new products, we always are looking to long term optimize what the gross margin structure looks like. Our expectations that we've been clear with investors about is we expect to maintain our gross margin structure -- we have some things working through this year as we invest in hyper force.

We invest more in third-party that longer term, we actually expect some efficiency on the gross margin side. But importantly, when we think about the construct from monetization through to optimization, the monetization side captures more than just sort of pass-through costs for LOM. As you've seen today, there's so much more in that overall agentic enterprise architecture that needs to be right that needs to be working in order for these to scale, to be reliable and to be really successful for our customers, and that includes much more than just kind of a pass-through cost. So I'd say when companies are out there saying, "Oh, we're worried about LLM pressure and that impact -- there's a lot more that we're doing than just sort of a pass-through.

The second side of how we're thinking about optimizing is we can view the kind of margin by customer view of when early adopters launch that scales and ramps through time, how we adopt things like hybrid reasoning, determinism. The testing center that you saw us show in demo, there are a lot of ways that we can optimize fine-tune. And then, of course, importantly, we're able to leverage a lot of different models in that architecture to be able to use the right model for the right task to be able to leverage some of that efficiency. So maybe you can touch on some of that.

Yes, absolutely. Look, efficiency at the infrastructure layer is something that we do every single day. And that applies to compute. It applies to storage. It certainly applies to the use of tokens in the model here. This is the newest kind of infrastructure and the newest kind of swappable infrastructure, especially as we have model choice with customers that we will continue to leverage how we are efficient at that infrastructure layer. But there's a really important point here that I think ties back to the Agentic work units. Now what the Agentic work units allow us to do now is they allow us to compare the work being done with the infrastructure supply. In this case, the inference capability and the intelligence capability measured by tokens that are going into those work units. So over time, we can understand which kinds of work are leveraging how many tokens over time. There are probably some kinds of work, whereas we build richer and more complex experiences the amount of tokens go up for a little while, and then we plateau as we start to think about it.

There's other kinds of work, and we talked about this earlier, as reasoning becomes more deterministic. As we're not relying on LLM for complex task execution, the number of times we have to use an LLM in that reasoning will drop. So we now have the ability to save for those kinds of work units are we driving efficiency from a system design perspective, from an agent construction perspective. And this really allows us to kind of dial in the amount of infrastructure costs we are spending for the work that's delivered. Now this is not different from what we used to do with regular compute technology and regular storage technology, but now we're going to be able to do the same thing with this new model technology.

We also fully expect just has happened on the infrastructure layer in the model layer as well, there's going to be continued improvements, efficiency, lowering of cost in these models as they continue to get more commoditized. We're already seeing some of that, and we expect that trend to continue in the future as well.

Great. Our next question is about MCP. And now that MCP allows external agents to interface directly with enterprise data how do you prevent other companies, foundational model companies from eventually bypassing agent force entirely and utilizing their own agent orchestration capabilities as those are getting better and are maturing, how do you prevent that from happening?

That I think even before agents were in place, we were an open company. We shared all our data. And yet people are still coming to us for doing all of the data processing and for all their work needs. And same thing here. We still had all our APIs open. Anybody could have built an agent outside us. And we told a lot of customers did try it 2, 3 years ago when LLM came out. They said, "Oh, all I need is just an LLM and I just give all the APIs and things will just work. And as we sort of -- and Gabe showed the demo and others and be showcased it, what we have is really an understanding of the business over the last 20, 30 years. What our customers have done is really build those business workflows, business data context and metadata and all of those.

So to really get your business successful, it's not just that data context or just raw data. It's really everything that goes on top of it, including your system of work, your agency all of the hybrid reasoning, everything that we talked about. And the context that gets print, it's not just raw data, it's really the context that you need to go build as well. So that's kind of why we are very, very confident that people need that stack that we talked about to get real business success. And we touched on this when we showed a little bit of what the model companies have talked about earlier as well. There is no question the context layer is incredibly critical. There is no question that the business process and the workflow layer is incredibly critical. There is no question that the interface where a customer engages with the company, where employees work is really critical.

And these experiences are not just unlocked by connecting up a bunch of MCPs together. It sounds easy in theory, but the experience really matters. The efficiency matters, the accuracy matters, the latency matters. These are implementation decisions that are really, really important that can we kind of talked about in a theoretical way of well, you can hook up any 2 things together and get them to work. But that's not actually how CIOs and companies implement things and how efficient and how well these systems work really does matter. By the way, our partners at the model companies really agree with us on this point. And so the question that you should be asking yourself is, are customers going to recreate all that from scratch. An entirely new stock to maintain an entirely new stock to observe. And entirely new track that, yes, you vibe-coded, but now you have to vibeoperate over the next several years. Are you going to recreate where your employees are working when they are actually getting incredibly productive work done today on surfaces like Slack?

Are you going to recreate every single business process that you have spent years and years really honing in sales and commerce and marketing and service. And that is where we believe the real work gets done. Capabilities like MCP are going to be incredibly impactful we're going to be tying those to agents outside of sale force, agents outside of sales force are going to be tying into us using all of that. And those are important building blocks, but a building block is not an architecture, and it's not an implementation, and that's really what we're focused on.

Great. Our next question is on Tableau. And specifically, is there any competitive threats or challenges with LMs and agentic analytics that you're seeing today. Obviously, Tableau had a weaker performance in Q4. So what is happening there, if that's not the case.

MK, do you want to start? Yes, I can start there. I think 1 of the big things, capital as well with , I think it's centrally different. The agent analytics is where sort of analytics itself is going. And you want to get the answers right this cannot be a allocated answer. Like if I -- if Mark wants to say, "Hey, what's going to be my quarter next year? And what's your thing? It can't just say it could be 80%, it would be 50%. It could be 30%, right?

You need precise answers. And that's really what Tableau always has strived for. making your data available to the -- to all of us that is guaranteed. Now 1 of the key things that we are working on very closely is to make sure those agent analytics can get to the right answers. So that starts with making sure you get the right what we call a semantic data model, right? And out of the box, we now ship for all the customer domains and also making sure that the conversion into Sequel and the semantic models is correct. And that is kind of -- we had a bunch of acquisitions we did as well to make that better. And this is what we believe is the future of analytics.

Like how do we make analytics really give you in a conversation of pattern and emitted in your line of work. And in fact, some of the demos that you might have seen already where we now have Tableau through Agent 4, stable through Slack part, all of those experiences we are trying to bring in Tableau relevant in your line of work. And all the applications that we now shipped, like marketing invent everything, you saw the agent force analytics and so on is also now all built on Tableau. So Tableau is much more deeply integrated into our stack. So we have expanded the TAM for Tableau into all of our existing sales force stack as well. Plus we are making sure Tableau will be the premier solution that you use when we have this agent analytics taking over. Madhav, do you want to add anything.

Yes. I think -- no, I think you answered the Tableau question, but I think this is kind of the broader point we made earlier, which is when you think about agent for us, it's not just the agent force part of the technology. It's the impact and the uplift that it has on every part of the portfolio. We're making our apps better with these agentic capabilities. As customers use the platform, they now will leverage Tableau to do the analytics that MK said. They're going to be leveraging data cloud and Informatica to really harden that context layer. They're going to be using MuleSoft to connect across. So we really think about the agent force momentum, you should really think of it in terms of all of these pieces coming together to create these experiences, leverage many, many parts of our stock to create that overall experience, and I completely agree with my the utility of a tool like Tableau in a world where the optimization and the management of agents is going to be a critical part of how every business works incredibly, incredibly valuable capability in that world.

Great. We're going to take our last question here, which is on data cloud or data 360. Clearly, Data Cloud is growing really well. It appears to be a prerequisite for preventing AI illucidations and agent force deployments so our customers who adopt both Data 360 and agent force together, showing materially better retention and expansion rates than those who are using agent force alone.

Yes. I'm happy to start and talk at MK. We see a huge overlap in the customers that are using data cloud to connect across their systems and the customers that are using agent for us. Data Cloud is also a key part of the agent force architecture. We use Data Cloud to make sure that we get all the analytics. We have Gabe showed you a slide that showed as you're testing the agent, every single moment that the agent is making a decision, executing something we call that a session trace. All of that session trace really sits in data cloud so that we can leverage the power of all of these analytics in this data.

So the 2 products are very closely tied together. And then, of course, customers also use data cloud to extend across the enterprise, bring in all of this context. So a huge overlap in that customer base -- and I do think that the products really are complementary and drive each other's momentum, and we expect that to continue. MK, anything you want to add on data cloud?

Yes. See, 1 of the things that we've also seen, in fact, even recently with a very big customer, is that as we lay the foundations of this, we can easily upsell so many different technologies because all our platform works together. And so that means somebody who is using agent force and Data Cloud, we can now upsell our Tableau stack on to them. If they're using service, now marketing works better because the same data and the magenta experience now can work with our marketing deeply. And so this thing costs us to be able to go upsell and cross-sell all our technologies together because foundationally, we have architected our stack so that the data and the agent stack underlies all our application experiences and all our systems of engagement.

So that is a huge boost to us. So it's not just about customers in retaining and growing our customers with data cloud and agent force, it's really growing and upselling all of these other clouds as well.

Awesome. Well, thank you all for joining. Thank you, Madhav, MK, Gabe for hosting today. We look forward to seeing you on the road over the next few weeks. And we have a bunch of questions here that we'll get back to you on, but we really appreciate the time. Have a good rest of your weekend.

Good afternoon, everyone. My name is Leila, and I will be your conference operator today. At this time, I would like to welcome you to the Salesforce Fourth Quarter and Full Year Fiscal 2026 Conference Call. This conference is being recorded. [Operator Instructions].

At this time, I would like to turn the call over to Mike Spencer, Executive Vice President of Finance and Investor Relations. Sir, you may begin.

Good afternoon, and thanks for joining us today on our fiscal 2026 Fourth Quarter Results Conference Call. We are trying out a new format today, and as such, have shortened our prepared remarks to ensure we have time for your questions. Our press release, SEC filings and a replay of today's call can be found on our website.

Joining me on the call today are Marc Benioff, Chairman CEO; and Rob Washington, Chief Operating and Finance Officer. We also have Miguel Milano, President and Chief Revenue Officer; and Patrick Stokes, President and Chief Marketing Officer, joining us for the Q&A portion of the call. Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties and assumptions, which could change. Should any of these risks materialize or should our assumptions prove to be incorrect, -- actual company results or outcomes could differ materially from these forward-looking statements.

A description of these risks, uncertainties and assumptions and other factors that could affect our financial results or outcomes is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q and other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements. As a reminder, our commentary today will include non-GAAP measures Reconciliations between our GAAP and non-GAAP results and guidance can be found in our earnings materials and our press release.

And with that, let me hand the call to Marc.

All right. Thanks so much, Mike. We're so thrilled to be here with everybody. And I'll tell you what we're here in this beautiful San Francisco on the 60th floor of Salesforce Tower, and it is recorded day 70 degrees the AI capital of the world, and we're coming here to you live. Really excited about everything that's going on. So let's start with the highlights from one of the absolute best years in our history and one of the best performances in software ever and guiding one of the best performances in software ever, we have delivered phenomenal performance across revenue, across margin expansion, across cash flow and CRPO and RPO. I mean the numbers are really incredible.

For the full year, we delivered $41.5 billion in revenue up 10% year-over-year and 9% constant currency. We had $11.2 billion in revenue for the fourth quarter, up 12% year-over-year, 10% in constant currency rose to $35.1 billion, up 16% year-over-year and 13% in constant currency, and we passed an incredible milestone with $72 billion in total RPO, which is up 14% year-over-year. Now that is a $72 billion in total RPO, up 14% year-over-year in case you missed that point. I did read a tweet that RPO does not matter. But evidently, we have it if it doesn't matter. So total RPO, $72 billion.

Last year, we laid out a path towards double-digit revenue growth by the second half of fiscal year '27 and we're hitting our marks. And based on our strong Q4 performance and the fast start with Informatica, we're updating our fiscal year 30 revenue target to $63 billion. Now that means we're only spending 2 years of the 40s, kind of hard to believe. I have never seen performance like this. But this obviously is not a rational market. We all know this. So we're using our remarkable cash flows to take advantage. This is not our first SaaS paclypse, we have been through many SaaS paclypses.

I remember the horrible SaaS pockets of 2020 when not only the software industry was doing, but we were all dying. But we made it through that. And now everyone is back, doing great -- so we're so grateful to make it through that, and we're going to make it through this at as well. And it's just a great marketing opportunity and a great buying opportunity, and that's why we are doing this incredible repurchase authorization to $50 billion. In fiscal year '26, we returned more than $14 billion or 99% of our free cash flow to shareholders. Thank you, Robin, for that.

And today, we're increasing our share repurchase authorization to $50 billion because -- these are some low prices. So Rob will share more about that in a moment. The biggest brands in the world are choosing Salesforce to lead their genetic transformation companies like Amazon Ford, AT&T Modern Pfizer so many, and these are big deals in Q4 wins over $1 million were up 26% year-over-year. That's just so we know, in Q4 wins over $1 million were up 26% year-over-year. Congratulations Miguel. Wins over $10 million were up 33% year-over-year. For example, the U.S. Army run by Army Secretary, Dan Driscol do an amazing job, has awarded us a 10-year indefinite delivery, indefinite quantity contract with a ceiling of $5.6 billion. Thank you, Dan.

This level of financial performance is a clear signal, a clear signal that companies across every industry and region are investing in Salesforce to become Agentic enterprises, just like we've been talking about now for 2 years, at Dreamforce that the Agentic enterprise is a real idea, and we're going to talk about agent force, and I think it just became an $800 million business. We're going to talk about that.

You've heard me talk about it at Dreamforce and on these calls, our vision of humans and agents working together for years, companies bought apps. We all use apps. I've got apps right here on my phone. I've got apps on my computer. But now I'm using apps and agents. I use them at home, I use them in my company. We can be talking about that. That is a reality. We have 83,000 employees here at Salesforce humans. And we have lots of agents running around as well. Miguel qualified 50,000 leads this week with agents. So we have apps and agents. We have humans and agents working together. We've been talking about that at Dreamforce as well. And this is just an incredible opportunity for Salesforce.

Our market is bigger than ever because not only selling apps, we're selling apps and agents. So bringing humans, agents, apps and data together not just to make people better at their jobs, but to redefine how work gets done. This is just an incredible exciting moment in software. So we're seeing incredible demand for agent force. In its first 15 months, we closed 29,000 deals, up 50% quarter-over-quarter. Customers in production have increased as well, nearly 50% in Q4. It can do more -- have more power, more capability than ever. If you haven't seen the new agent force, you haven't seen agent force, the level of determinism, the voice capabilities, agent for studio, agent force builder.

We are spending a huge amount of time on agent force. I just saw the new agent force demos from our team, it was incredible. We even have agent force running in Slack. We have agent force builder running in Slack. We have amazing things happening and our aid-inforce and data 360ARR, including Informatica, now exceeds 2.9 in billion. I heard ARR doesn't matter anymore. But in case it does, we have $2.9 billion, up 200% year-over-year, more than 75% of our top 100 wins in Q4 included both agent force and Data 360. In a bit, we're going to hear from 3 amazing customers, Wyndham, 1 of my very favorite customers in the world, the world's largest hotel chain, SharkNinja, I just got one of their great new products, I'm sure you know about they've got the best slashing machine. But 1 of the most innovative consumer product companies in the world and SaaStr, an incredible community of B2B software founders, executives, investors and I think you all know that I love Jason, but I've never been more excited about our business here at Salesforce.

No one else is delivering this level of capability at this scale to this many customers. And we are taking the power of the agentic enterprise of these apps and sales force, and we're giving them the security, reliability, availability, scalability that you need to make them successful in business like ours, but in all businesses, in small and medium businesses and general sized businesses and very large enterprises in the government and in ISVs as well.

So this is a category that just did not really exist a year ago. I would just say that look at IT service management. We just launched Salesforce IT service in October, Salesforce ITSM, and in just a few months, Miguel has won over 180 customers, amazing Miguel. But I especially love 5 customers who get to leave the purgatory of ServiceNow like Sunrun Cornerstone, Coolisys and there's others too that we're not allowed to mention, but I might mention them any way. Who are leaving in ServiceNow now for the new Salesforce IT service product, which is about apps and agents, helping you manage all your ITSM. But don't just think it's just that. We built an amazing new life sciences product this year. Agentforce for life sciences and since we launched so many of the global pharma companies, and I've met with so many of the CEOs myself, they're leaving Veeva, the purgatory of a including AstraZeneca, Novartis, Takeda and of course, Albert at Pfizer, they're all saying that they are going to Salesforce Life Sciences, which is a product that has apps and agents. And this is amazing.

They are the most regulated businesses in the world. and they're choosing Salesforce. And over the years, I've met with untold numbers of customers, call it thousands, call it more than that. They used to tell me maybe, okay, I want to roll my own AI. I'm going to build my own model, I've been to build my own agent. I said, "Tell me about that, let me know how that goes, show me exactly what you're doing. Or you can just turn it on in the Salesforce product you already have. You have Sales Cloud, turn on the agents. You have Service Cloud, turn on the agents, our marketing cloud, turn on the agent. You have Slack, turn on Slack bot and that idea that every app now has the capability to have agents.

So customers tell me that they want to basically kind of get to that next level. And the way to do that is by including this context, the ability for the AI, the data to know you. No better example of that than Slack bot immediately as you turn it on you're a Slack customer, it looks at all your slack. It looks at your DMs, it looks through Salesforce. It looks through Google. It looks even that Microsoft teams as hard as that is for some agents to go and do, but we've told them how to do it.

And then it says, I understand your business, and I can give you help, advice, support. And in fact, a recent survey of 100 CIOs found that the number of companies planning to use a platform like this -- this idea of apps and agents has now doubled just in the last 18 months because of this, they realize this is more than just turning on mac bot on your Mac mini okay, which, by the way, I have a MAC and a setup is great open claw. I love it. But for companies who want to have the reliability, availability, security, okay, the sharing models.

The key parts of that to really make sure that the business is safe and secure while you're running all these skilled agents. Well, let's just know that -- that is what Salesforce is doing. And that's why Salesforce has become one of these incredible companies because our platform provides these amazing 4 layers that you see right here. that everyone needs to convert raw intelligence into real work, everything they need to become in a genetic enterprise. Just look at this. Look at what we felt, look at what we have built, and thank you to our team, they have done a phenomenal job. Srini can't be here because he's in India. He was at the India AI Summit this week, he could not make it back here in time.

Look at what our engineering team has built, and thank you to them. Look at where it starts. First of all, yes, we can use all those large language models. We love them all. We love all of our children equally and down below here, whether it's anthropic or open AI or Mistral or Lama all of them, and there's more coming. They're amazing. World models are coming. They're amazing. They're all down below here, and we're using them. And then, of course, we bring them into Data 360, and that lets you harmonize your data, integrate your data and federate that means connect into other data sources throughout your company and grab it. Other data repositories, you might be using Snowflake or data bricks you might be using big query or anything, even IBM mainframes and you can bring it into Data 360, you activate your data and then it comes up into your apps.

So if you're using the service app, and you want to have an experience like help that salesforce.com for your company. Now the service app has that Agentic capability, the data is coming up -- and it comes up to the next level to agent force and you can build your agents, train your agents, put the guardrails in your agents, give them voice. They can talk now, they're talking.

And then all of a sudden, you can even manage and orchestrate and collaborate from Slack. So this is our architecture. And all of this is unified, integrated and that idea that we can deliver this unified platform to our customers to help them deliver humans and agents working together. So you can see right here, agent force has the tooling to build to manage to orchestrate the agents to make them talk to give them determinism, to give them the capabilities if they want. And then we have the engagement layer to deliver agentic enterprises, where work happens in Slack across our apps. If you haven't seen Slackbot.

I talked to a lot of customers. So I kind of see Slack but -- why are easy? I have the free edition? I'm like, maybe you should pay us and get the enterprise edition because, boom, that's when all the Slack bot turns on and you can go through your whole company, run your company. I had one of our customers over last night Neil Bushry at Workday. I'm like, have you seen Slack bot and he only like, "No, I have not seen yet. I'm like, you're the biggest latest merely have a like I to sit there and say, look at this, and I'm like said Slack but, I'm having drinks with a meal and I just am trying to like -- given the demo of Slack bot, what should I say to him? What is the strategy between Salesforce and Workday and then boom. It just went through the whole thing, showed him every deal.

He couldn't believe everything that was happening between these our 2 companies, he had to get updated because he's the new CEO of Workday. And it was amazing. That was my real experience. Together, all of this is the complete operating system for the Agentic enterprise. Yes, I'm using it myself. And we're using it, we're customer's hero. And that's crucial because look, we already know now, our customers aren't going to deploy just 1 agent. There's going to be many agents, many capabilities. the ability to automate many different types of work, and they're going to deploy hundreds or thousands. Many are going to be from us.

Others could be from other amazing companies like one that just mentioned Workday I love them. But these agents can't work in isolation. -- like it, each one of them needs to okay. So that home is Salesforce. And they are calling us through the MCP server or maybe even just through one of our core platforms, and the more agents that our company deploys us or anyone else, the more essential our platform becomes. This is my personal testimonial.

I'm giving you my personal testimonial how I run Salesforce. You can come here, I will show you how I run a business with apps and agents together. And it's why nearly 90% of Forbes top 50 AI companies. Forbes top 50 AI companies use Salesforce and Slack. And if there is a SaaS polyps, I think it might be eaten by the SaaS watch because there are a lot of companies using a lot of SaaS because SaaS just got a lot better with agents as a service. Now I won't tell you exactly tell you what that says. But let's just say they're SaaS and there's also agents as a service. Now I want to tell you how we're measuring the value our platform delivers to customers. Today, we are 1 of the largest consumers of tokens in the world to date, now over 19 trillion tokens. So we continue to show you that because -- we want you to see that we're actually doing what we say.

I know that there's been some enterprise software companies who say they're doing agents or they're doing AI, but then they're not showing up in the token rankings from the language model companies. So we're here is $19 trillion, okay, but we really want to take this to another level. And another level is a token on its own doesn't know your customers, your pipeline, your org chart, but Salesforce does. And the value isn't in the token. The value is in what our platform does with it. They work -- that's why today, we're introducing an additional metric. The Agenticwork unit created by our very own Patrick Stokes sitting here at the table. -- the AWU not to be confused with our customer, AWS. And AWU represents one unit of AI work, a genetic work unit. We're rolling this out to see how you like it actually here in earnings. It's a record updated workflow triggered, decision made. MCP called.

And to date, AI agents on the Salesforce platform delivered 2.4 billion agenetic work units. That is where AI isn't just thinking or calling things, it's getting work done, work got transactions, and in Q4 alone, we delivered about $771 million of them, we're still trying to exactly figure out exactly what these numbers mean for us. But what it means for me, is that we are doing what we say that is we are explaining that humans and agents are working together.

We are showing you a business running them. We are showing them how we are making our business better. Our service is so much better this year because we're using our new Service Cloud with our omnichannel supervisor deployed with agent force. Our sales, Miguel just hit record sales numbers, you can see them. We've never sold or had so much ACV in our history in the fourth quarter because not only does he have 15,000 account executives. But he has all these agents who are out there doing this amazing work. So that is so exciting. This is raw intelligence converted into the real work. It's driving efficiency and growth.

Okay. Now let me tell you about one of the biggest drivers of these work units, Slack bot. A lot of you use Slack, I use Slack every day. It's the employee, ultimate employee agent. And many of you know that ex the social media platform hosts about 500 million messages a day, right? Elen must do an amazing job on x, incredible what he has done. But did you know that Slack Host about 1 billion messages a day.

So while X amazing X, I use it myself. I just tweeted something 500 million messages a day. Well, Slack is hosting 1 billion messages a day. And remember, every one of them is about getting work done. That's why we bought it. Remember, Slack's ticker symbol was work. Slack bot can access all of those messages as well as your files, your calendar, your sales force, your Google, your Microsoft teams you're this year that Slack bot goes around, pulls it all together, -- and then it knows your business. So then it's able to orchestrate with other agents. It has an incredible partner marketplace, really the #1 AI ecosystem in the world and has more than 350 AI apps and agents already. There is no other AI ecosystem like it.

One of those partners is the ingrate [indiscernible], we love anthropic. We love Dario, Daniella. I tweeted about what they did yesterday, incredible demo. Just yesterday, Dario demonstrated how he is doing something amazing with Salesforce in the enterprise. Every single one of their demos, whether it was for HR, engineering investment banking, started at ending in Slack, pretty awesome. And so -- it's about agents and apps, humans agents. It's all working together. You can see it in his demos. You can see it in our demos.

By the way, anthropic runs its whole global operation on Salesforce and Slack I think actually every AI company does. Yes, I think they do. So maybe you saw they're hiring a Salesforce admin, Dario. Let us know if you need new names. But I think it's just a point we're making that sales force is doing great with these AI companies. We're so thrilled of our relationship with Dario and I think we just put another $100 million into the new round.

We're up about $330 million in topic invested is almost about 1% of enthropic. And believe me, I wish we had invested a lot more, John. I don't know why we didn't do more. Okay. With that, it's time we're going to hear from some of our most inspiring customers becoming Agentic enterprises. We have the great Mark. Mark, I see you. Mark is there from SharkNinja. Mark Hey, Mark, congratulations to you and your team, what a quarter? Mark, I'm so thrilled to talk to you, and I love all your products, and thank you for the Christmas presents. I have them, and I'm using them.

Appreciate it. I'm really happy that so much of our holiday selling season was really driven by the launch of Salesforce that, as you know, happened at the end of September and Would love to talk to you about it.

Well, Mark, you know that we've been working together now, just BMU as well as with our whole sales team to make we can automate all of SharkNinja. We want to automate your sales, service, marketing or commerce. Everything you're doing, I'm so excited about your future. We have our best team working with you. Give us your view of what's happened and the value we've been able to deliver, what's your biggest surprise? What in the slushy machine, what came out?

Look, Marc, I mean, we launched 25 products a year, and we're really innovating at speed. And we need customer service solutions that move just as fast I mean most companies treat service as a cost center. For us, Marc, it's really about lifetime value of the consumer. I mean we view service as a growth engine for the business. And it's not just about servicing problems, it's about building lifetime value.

We set up with you and your team, a guided shopping agent in 8 weeks right before the holiday season. I was nervous about it as I went to my team and I said, we're putting this in place in October. There's generally kind of a cutoff in our business where after October 1, you don't really do anything. And we launched this in 8 weeks, and it brought tremendous value to the consumer. I mean, it helped them with researching and buying and troubleshooting really all in one seamless conversation. So it was a great success for us this holiday season.

Well, Mark, I think that working with you has been extremely interesting because you're very much a B2C company. And there are so many exciting things that you're doing. When you look at what Salesforce has done and deployed, especially in regards to AI and agents and apps, where has it really impacted you the most?

Well, look, let me start with this stat for you. I mean, just since we launched Salesforce in Q4, I mean, agents have participated in 0.25 million consumer engagements during that period of time. So just in a really, really short period of time, 0.25 million engagements.

We put so many products out into the market and sometimes that many products creates complexity for the consumer. And so whether they're calling about a service issue or a troubleshooting issue or where is my order issue, it's allowed our customer service agents to focus on really the really challenging issues, and it's freed up an enormous amount of time for them -- it's a win for the consumer because the consumer is getting their questions answered quickly, they're not waiting. And it's a win for us because it's driving down cost. And it's, in the end, just having a better service experience.

Well, Mark, I just want to thank you so much. We're so grateful to you as a customer of Salesforce. It has been an absolute pleasure getting to know you, working with you -- and I think that we have such a great future together and thank you for the Christmas presents. I'm using them. I made some amazing Mango survey actually this week and it was awesome.

Sounds great. Thanks, Marc.

Bye, Mark. Great to see you. Well, I've been so thrilled to work with Mark, but I have to also introduce you to another really good friend of mine, Jeff at Wyndham and you probably heard from Jeff this week, he had a phenomenal quarter, doing great the #1 hotel in the world, Jeff, we are so thrilled. Jeff, congratulations on everything that's going on with Wyndham, we're thrilled. Give us your vision of what's going on in the world and with Wyndham and we'd love to hear how you're using Salesforce as well.

When we have -- Mark -- I mean, when you think about just how far we've come in the last year, today, we have over 5,000 deployments of agent force across our over 8,300 hotels. It is a huge, huge part of our Agentic platform, and we are really just getting started. We're starting to roll out to Canada and internationally. But with sales force tools like MuleSoft and Data 360, we have built a single source of truth, unified all of our guests reservation information and data, all of their loyalty information and all of their CRM data so that all of our agents now are operating with the same trusted and real-time guests and hotel information, which they weren't before.

We're calling it Wyndham Guest 360. It is a key enabler for our agent foundry. And it is delighting in better guest experiences, improving those experiences and building on increased loyalty engagement. But most importantly, Mark, you've talked a lot about about labor, which is a genetic, -- it is taking millions of dollars of labor costs from our small business owners in the front office out of their operation and it is driving millions of dollars of increased revenue for these franchisees.

Well, I just have to say I just have to say this 1 thing, which is I have been hugely surprised at how fast you have gone Jeff. We work with all the major hotel companies and I love them all, and I stay in them all. They're fantastic. I'm actually going to stay to Wyndham Hotel tonight. I'm flying East. But I have to ask you this question, Jeff, because I don't understand how are you going so fast? What are you doing? Is this because you're leading from the top? I mean, you seem to like -- I just talked from Mark at SharpNinja, he really is owning this -- why are you guys going so fast? Why are you doing so well? I mean it's just you're loading out these apps and agents that nor team is crushing it. What is going on?

We're in the hospitality business, and we always say it's all about humans, yes. But it is humans as you've always said, with agents who are driving that customer success together. Think about our customers. Before our integration with you all, our agents had to spend time gathering basic guest information on who Marc Benioff was before he checked in tonight.

And that was not easily at their fingertips or even worse, asking Marc for his information that we should have had -- and our agents now have encyclopedic knowledge. Think about it of all of your guests history, all of your booking behavior, all of your loyalty status because we tied it all together, giving us an ability to answer any question imaginable that any guests like you might have before you check in tonight before you stay.

In moments, not minutes, and we're booking you into your preferred room based on our knowledge, our guest, sales force knowledge of your past day history. We are successfully working now. I hope to upsell you a suite upgrade if we haven't already an early check-in Sounds like you're getting in at a late checkout tomorrow if you'd like one. I don't know if you're bringing -- if you have pets, but if you were, those agents would be selling you a pet or an F&B...

They're going to jump in.

But look, this is all being done autonomously, which small business owners and operators would not have had time to do before. we have been working so hard. It is generating so much money. We're seeing faster average speeds of answer. 0 hold times. I've heard you talk a lot about why no customer should wait. And that's why we're doing it. we're receiving and we're moving more importantly, millions and millions of dollars, as I said, in the front office, but we're generating millions of dollars of increased ancillary revenues to these small business owners. It's not costing anything.

And we're also seeing, which is really, really important, a 200 basis point increase in direct bookings. -- from AI voice agents and AI voice agent conversion versus having to get those bookings through expensive third-party online travel agencies. That is increasing guest satisfaction. Our guest satisfaction scores are up 400 basis points, they've never been higher. And this customer experience that we've created is more efficient. Again, humans with agents driving customer success, we're agent first, and we're very proud of it.

Well, I just want to thank you so much, Jeff, thank you, and thanks to your team because I'll tell you, it takes a great leader like you, but it also takes a great team and you've got both, and you've made something really incredible happened, a great job and congratulations.

We're proud to be with you. Our Chief Commercial Officer, who was on stage with you at Dreamforce. -- strict will be back this year.

So I hope you come to Dreamforce this year. Bye. Jeff. All right. Well, I want to now introduce you to an incredible person who I've known for 20 years, and it's very inspiring entrepreneurs, really become a huge influencer in the world is getting his hands story to the great company called SaaStr building agents, learning how they work, deploying them, really being on the bleeding edge, the cutting edge of this technology, and thanks for being here, Jason. I'm so thrilled to have you.

Super exciting. Yes. Congrats on the quarter, by the way.

Jason, I just want to ask you one question. What is it that's making this happen? What is inspiring you to kind of transform yourself and transform SaaStr to this incredible opportunity?

Well, look, maybe 2 things. If you're -- we're builders. We've been -- I mean, you were -- I think you were like on Radio Shack computers or something back in the day, right? We've been building since here rolling game we're building at our heart, right? And this is the most exciting time to build ever, ever for us as executives, entrepreneurs honestly, if you're not excited to be building an agentic you should quit, you should go off and go to pasture, do your next thing.

So we backed into agents because I got tired after our own big event of rebuilding the team and we went all in and we said, I want to try to rebuild the whole team with agents about almost 10 months ago, agent force was a key part of that. And we wanted to push it early. Can you really do all of this -- all these go-to-market motions with agents and the numbers are pretty good.

Well, you've been a pioneer. You -- it's a funny thing because in our own independent world, here we are, we're out here building agent force, Slack bot, you know that. We also acquired Momentum and we acquired qualified and so forth. We're so excited about these companies. And then all of a sudden, Well, you kind of were building our vision of the future, totally independently -- and so we felt very validated in a way. It was kind of crazy. But then we looked at you and said, "Wow, this is a true visionary, and you really have always had a lot of clarity, not just in SaaS, before that, you know that.

And now here you are as agents as a Service as well. You have your vision there now as well. So I guess once a visionary, always a visionary, -- but give us your vision then. Where are we going? Because you've heard about the SaaS pokalypse. And you know that this isn't our first SaaS pokalypse. We've had a few of them. But now where are we going over the next couple of years?

Well, I think -- and I think this is good for Salesforce, but I think we're underestimating how powerful these agents are. I think Look, for most people, AI is confusing, the media is confusing, what the hell is going on. Let me simplify this. I was just looking at our numbers on agent force this morning. So far, and again, we're a small organization. We went from humans to 2.5 and 20 agents, okay? That's a lot of change. But an Agentforce alone, as a tiny organization, we closed $2.7 million. That's not the the army contract you got, but that's a lot for us, 2.7% with an agent, and we have 3.5 million more in the pipeline. Those are agents and it works. And so that is exciting. -- that is exciting that these agents can go out and sell for you. And the first thing I did is...

Just kind of crazy and amazing is it's crazy.

It just wasn't -- not only was this not really possible a year ago -- and this is this -- a year -- the problem -- all of us, we were using chatGPT in the early days. It was all hallucinations. It was hard to believe this stuff would work even 18 months ago, wasn't it? It was hard to believe, but everything got okay last summer, and then at the end of the year, it got great. And there's reasons that Salesforce has got great, but to be nerdy, even a anthropic, your customer, when they rolled out these 4 do models, up to 4, 5 for B2B stuff like we do, it wasn't a little bit better.

It was like jaw-droppingly better. The hallucinations will be worse than a human mixes and the productivity side. So it's just -- we've never seen these gains and the idea that now our sales force instance can run autonomously versus doing manual data entry. I mean, this was always a dream.

I want to tell everyone exactly why I wanted you here because number 1 is, yes, we love -- by the way, market churning was awesome, right? And then we had Jeff at Wyndham. And these are very big companies, like good sized companies and not the biggest companies in the world, but incredible companies. But -- you're a small company. in some ways, a selepreneur, right? You're an entrepreneur or -- and I think that it is going to go across the whole market that is small businesses are benefiting, medium, we call small business 0 to 200 employees. Maybe that's where you are.

Then we have 200200 to 2,000 medium, and we have the 2,000 to 5,000 in general business. Then we have the 5,000 monsters then we have the government. We have software companies. Every segment is impacted by this. Don't you think every company is impacted.

I think everyone was going to look at their business and say, what can I fully automate with an agent. Everyone is -- you're going to unlatch a ton of creativity, right? The key thing that I've learned for folks is just start with 1 use case. For us, it was what you -- the idea you came up with like last summer, reactivate the leads the sales team never talked to. That was our first use case. Find something or with Wyndham.

A huge thing, right? Because like believe there's $20 million, $30 million. We don't even know, maybe 100 million people we didn't call back in the last 26 years. But Miguel called back 50,000 people with agents last week that we would not have gotten to. Even though he's got all these reps, he still doesn't have the ability to call everybody back. It's amazing.

We did 3,000 with agent force. And for 1 -- I was just looking at a couple of examples. We closed a $250,000 customer this week. But the first 1 with agent force was Freshworks. You know Freshworks. They do support and a bunch of other stuff. -- but they've changed. Gaurish isn't the CEO anymore. The marketing teams turned over. We don't know anybody. The agent found the right person and close the deal. That's sort of magical. That wouldn't have really been possible without agents they are.p

It's just like -- that's exciting.

Exciting. And the fact that every company can start with something here, they can reactivate something or even with Wyndham responding after hours. And actually, my old Head of Customer Success is now Head of SMB at PayPal, they use agent force. And he just told me -- texted me this morning or this morning, they have a broken merchant flow where folks would sign up to use PayPal and then they would abandon it like an abandoned cart. They put agent force on it and the conversion rates are much higher, but they couldn't get any people to do this, right? So all of us have some process that to do.

It's so exciting because you have humans and agents working together. You're working with your agents. It's the apps of the agents working together. But it's kind of fun because I think that for the last 26 years, you and I, we've been in this kind of SaaS industry, and it's all been all about apps. And that's now -- and the apps haven't gone away, but as PayPal is still using those apps, they -- by the way, PaycapPalis a huge customer in sales, B2B and also service call center contact center. But now just as you articulated so beautifully, more productivity, more capability, the ability -- the lost card idea. That's what we're finding this ability.

So now we're selling not just in the SaaS apps world, we're also selling agents -- and yes, these 2 are going to be 2 markets and who knows, maybe one will be bigger than the other. Maybe they'll both be the same size. We don't exactly know. I mean we just -- we just gave guidance that we're going to do $46.2 billion this year on revenue. So I can't tell you when the -- an agent force is like about an $800 million business now. So I can't tell you exactly when Agentforce will be a $46 billion or $30 billion. But it has the potential to go just like -- but plan

Help me that's 46 3, help me, you guys.

46x3 is 120 plus 18.

I think agent force -- and I'm not being infectious. I think it will be $1 million at the table because I think the value is about 3x the software -- this is why I think the SaaS clips or SaaS watch lips or whatever, I think there's some truth to this because agents are changing the world. And if you're not -- if you don't have agent force, if you're one of the leaders and you don't -- and you're not there, I think it's fair to be concerned, right? But the value -- I wrote this post about how much more valuable salesforce is as with our agents. It's not a little more value. It is like 10xx more valuable.

I don't know you are using Salesforce really 6 months ago.p

Not really. We -- our team had shrunk -- and the value is the data for some reps ever. never fire, they left. -- they -- the last.

Yes, now you have like a team of agents and humans and your company is bigger and more successful than ever. we're using sales force going to be amazing this year, right?

okay? Or even -- and actually, what's interesting is not only are these agents using more sales or, I just figured this out today. the most dated part of our software stack is a company called Marketo. You'll remember from the old days for marketing automation Back in the day, very innovative, right? Jo dropped in the day. We're sort of a prisoner. We're stuck on it. These agents.

I got some things to show you there.

Yes. But the agents, our sales force agents have taken all of that data and put into Salesforce. So now Salesforce is accumulating all the value from all these other stores and becoming the -- so that's why whatever the math is. I'm going to bet on the 150. I'm not going to -- it might take 8 years, but I think it's -- I think the Agentic side is worth 3 to 4x the software side.

Really appreciate you joining the earnings call. Great. Thanks, everybody. All right. There we go. We just have 3 great customers. We gave some numbers. And now I'm turning it over to you, Rob and take it over.

Thanks, Marc. What an amazing trilogy of 3 great questions. Absolutely. On a great year. We're going to turn to the numbers and tell everybody about it. So good afternoon. We closed an exceptionally strong fiscal year. We have rebuilt our platform to convert the raw intelligence of LLMs into real work that drives revenue, as we just heard about, reduces costs and scales reliably without limits. This is powering the transition to the genic enterprise for our customers and ourselves.

So to share a few data points, as expected, as Marc said, we had a great quarter. a great year. We finished the fiscal year '26 with second half net new AOV growth ahead of second half AOV growth. Agent force and Data 360 ARR inclusive of Informatica Cloud ARR reached $2.9 billion. That's up over 200% year-over-year. This includes Informatica Cloud ARR of $1.1 billion an agent force ARR of approximately $800 million, which is up 169% year-over-year. New bookings for agent force 1 edition and agent force for apps or as we call it our most premium SKUs nearly tripled quarter-over-quarter.

Our consumption flywheel is spinning faster than ever. In the quarter, more than 60% of agent force and Data 360 bookings came from existing customers expanding their commitments.

Looking at our largest deals, -- every single 1 of our top 10 wins included agent force, data, sales, service, platform and analytics. Our newest addition to our portfolio Informatica, landed in 6 of those top 10 wins, proving it is a critical component of us building the data foundation for the Agentic enterprise. So let's dive a bit further into these incredible results. Subscription and support revenue grew slightly above 10% year-over-year in nominal and constant currency.

Total revenue was $41.5 billion, up 10% year-over-year in nominal and 9% in constant currency, driven by agent force, Data 360, Slack, Agentforce sales and service performance. Informatica's Q4 results also outperformed our expectations. This strong performance was partially offset by continued weakness in marketing, in commerce, weaker-than-expected Tableau performance and the on-prem revenue timing in Tableau and MuleSoft we shared last quarter.

Q4 revenue attrition ended the year at approximately 8%, in line with recent trends. Our current remaining performance obligation, or CRPO, ended Q4 at $35.1 billion, which was up approximately 16% year-over-year in nominal and 13% in constant currency, driven by strong net new AOV, especially in agent force, Data 360, Slack and sales. This does include a 4-point contribution from Informatica. Our top priority remains accelerating growth.

Based on our FY '26 net new AOV performance, we are more confident in our path to reaccelerate organic revenue in second half FY '27. And as outlined at Investor Day. Given our strong net new AOV performance and the incorporation of Informatica, we are updating our FY '30 framework as follows: We are now targeting FY '30 revenue of $63 billion, which represents an 11% CAGR from FY '26 to FY '30.

We remain on track to roll a 50 by FY '30, and we are pleased that with our continued focus on operational excellence, we delivered 60 basis points of expansion in FY '26. As we think about FY '27 and fueling our framework, we are making targeted investments, including advancing our Hyperforce third-party infrastructure for trust and security, ramping our AE capacity and scaling FTEs to drive adoption.

These investments are partially funded by efficiency we've unlocked becoming the lean agentic enterprise. As our own customer 0. Before we turn to guidance, a quick update on capital allocation. I'm proud to say that we have achieved all elements of our Investor Day commitments including capital allocation.

Also, our Board has approved a 5.8% increase in our quarterly dividend to $0.44 per share. Additionally, and as you've heard, given the current stock price dislocation, the most prudent investment we can make is in Salesforce. We are updating our share repurchase authorization to $50 billion.

So let's talk about FY '27. We are initiating fiscal year '27 revenue guidance of $45.8 billion to $46.2 billion. growth of approximately 10% to 11% in nominal and constant currency. We expect subscription and support growth guidance of slightly under 12% year-over-year or approximately 11% year-over-year in constant currency. This is fueled by continued momentum in agent force and Data 360, and partially offset by weakness in marketing, commerce and Tableau.

Our non-GAAP operating margin guidance is 34.3%, an expansion of 20 basis points. As I mentioned, this is the year where we are making further investments to fuel long-term growth and ensure customer success with Agentforce. We expect GAAP operating margin of 20.9%, an expansion of 80 basis points.

Turning to Q1 guidance. We expect revenue of $11.03 billion to $11.08 billion, growth of approximately 12% to 13% in nominal and 10% to 11% in constant currency. CRPO growth for Q1 is expected to be approximately 14% year-over-year in nominal and approximately 13% year-over-year in constant currency.

Clearly, we are executing against our FY '30 framework, accelerating growth and investing with discipline, including investing in Salesforce via share repurchases.

Before we wrap up to better reflect our Agentic enterprise strategy, we are reevaluating our revenue by cloud disclosures in FY '27. So stay tuned for an update on this disclosure prior to our Q1 earnings release. Finally, a big thank you to all of our employees for their dedication and hard work delivering a very successful FY '26 and onward to an incredible FY '27.

Mike, I'll turn it over to you.

Thanks, Robin. And with that, we're Leila,we're going to go to the first question, please.

[Operator Instructions] And your first question will come from Keith Weiss with Morgan Stanley.

Excellent. Congratulations on a a really nice end to FY '26. -- particularly when it comes to the Agentforce numbers, the agent force members are definitely eye-popping getting to a big scale and still growing at really, really high rates. But on the other side of that, CRPO perhaps was a little bit disappointing.

On an organic basis, you grew that at 9%, just in line with your guidance. And typically, we expect a little bit of a bet, 100, 150 basis points of a beat. And I think that's soaking some concerns with investors can Salesforce do both? Can we grow a big agent for his business and sustain the growth and momentum in the broader sales force portfolio when we bring along the entirety of the business. So can you talk to that aspect, can agent force Catalan as the broader sales force product portfolio? Can it bring along everything? And what gives you confidence in that acceleration in the back half of the year?

All right. Well, I think that, that is absolutely a great question. And I think the reason why it's such a great question is because Salesforce is, just as you said, it's a comprehensive business. We're closing new business, new ideas. We have building new technology, and we also carry with us that we are a subscription business. So we're carrying with us our legacy as well, and we're renewing and moving that legacy business forward. That's also one of the exciting parts of Salesforce because that also gives us the predictability to understand what's going to happen in the future fiscal years.

So yes, we are innovating. We're creating the future. We're adding to the future. We're also renewing our customers. And I have to tell you, we're just very proud actually of the numbers. I mean this fiscal year is far better than I expected at the beginning of the year than the fourth quarter, actually, even in the third and fourth quarter, Miguel's numbers were far exceeded my expectations. And, to your point, agent force also and also Data 360 are exceeding our expectations. And yes, could we sell more? Could we renew more? Can we do more? Can we do this? Can we do all these various things we absolutely can, but we are very grateful for what we've been able to achieve so far. Robin, do you want to add to that?

Yes. I agree with that. I think we're monetizing AI keep through many different fashions. We've got multiple ways to monetize. We're seeing great growth, as I mentioned, in our premium SKUs. We're seeing acceleration. I think just listening to the 3 customer interviews talks about the great value that they're getting from core -- it's also important to point out, we didn't talk about it a lot, but our seats, we're still seeing them grow year-on-year and quarter-on-quarter.

So what we see is now with agent force with the system that you laid out, the system with the agency, et cetera. we're just seeing incremental value to our software. And some of it's going to be consumption-based, but we're going to have a hybrid model. Seats will continue to be a key component of our growth going forward. And what we hope to see is just what you heard from the 3 customers today, incremental value coming as the result of our Agentic technology and capabilities.

Your next question will come from Brent Thill with Jefferies.

Marc, the $50 billion buyback, I guess many are asking given the falloff in big multiples, why not lean a little harder in acquiring technology in M&A versus buying the stock back?

Well, I really appreciate that. I think, Brent, the way to look at this is, I'll just tell you how I look at it, which is that there's many uses of cash. Number 1 is dividend. We just increased the dividend by 5%. That's one use of cash, very important. And then we're also looking at buyback, traditional buybacks, okay? And so we're doing that. We've done that very aggressively over the last few years, as you know. And acquisitions, we will continue to do acquisitions, but using our new formula that we put into place, and we've done now quite a few acquisitions using that new formula and it's been great. I wish I had used it actually through the entire history of Salesforce, I think we have a much better understanding of how to do acquisitions that are accretive to the business, but not dilutive to investors.

And then debt, so I think there is a role here that we're just very underleveraged on our balance sheet. And I think, look, you're a great banker. You've been a great banker for decades now. I think if you look at our balance sheet, now we're going to do more than $16 billion in cash flow this year we're not using debt effectively. And I think at these prices in the market, the ability actually to kind of come to terms that we had some acquisitions in the past like Slack and Tableau that diluted our investors, I think, now is the opportunity to take some of that stock back out of the market. And these are great prices. I'm sure you would agree with that.

And we want to use our capital correctly. And I think that is a great way to do that. And I think our stock is a great price, and I want Robin to buy as much of it as he possibly can.

And I'd maybe add to that, Brent, doesn't preclude us from doing all the things you mentioned to grow, as Mark just said, with our free cash flow with our cash balance with our access to market were going to do, we brought 10 companies, and we also returned over 99% of our free cash flow to our shareholders, be your buybacks and dividends. So as we think about optimizing our balance sheet to Marc's point, we're positioning ourselves to grow organically and inorganically and also return value to our shareholders.

I think that when you look at such a huge cash flow number, although we just finished a $15 billion a year coming into it, what will we be probably at least a $16.5 billion cash flow year, then we should be really just thinking about how do we use cash correctly. What is the right way to use cash. And yes, I think that there are many ways to use cash. But focusing on those 4 things, the dividend the buyback, the acquisition and debt, all 4 critical. And if you have other ideas or you have other thoughts, we're very open. I'd love to have the conversation, of course.

Our next question will come from Kirk Materne with Evercore.

Marc, you alluded to it in your comments, the presentation actually by Anthropic, I thought was an interesting example of sort of a better together strategy with you and one of the model partners. But there is continued concern that those providers might become more competitive with you over time. I was wondering if you could just give us an idea of how you see the lines of demarcation in terms of partnering as well as potentially competing down the line, where do you think you guys have a right to win, where they might have a right to win. I think just a little bit more color on that would be helpful in terms of people's view of where we might be going in terms of the partnerships with those companies.

Well, no, I'd be delighted to do that, and maybe we can even put up our slide again of our kind of stack diagram because it makes it really clear what our vision of the world is, which is at one very critical part of this these new models whether it's open AI, whether it's in anthoropic, whether it's Gemini, whether it's LAMA, whether it's you pick the Deep Seek, Mistral, there's so many -- you can go off as well to look at that there's thousands of them.

We make some of them ourselves. These models are new parts of our infrastructure that we really did not have in place a few years ago. We had some of our own models. You remember when we did Einstein, and I would talk about on the earnings call that I was using Einstein to understand what was happening in my business, that was all based on Salesforce models. That we had. So we've always had models at the bottom of our infrastructure, but now we really are able to kind of say, look at this, we've done 19 trillion tokens without these models. So these models here, that's who we have today. They will change over time. They're a critical part of our infrastructure.

I think the strategic question that you're asking is this, not only does it look like that in the slide that we just saw. But -- could those models themselves become platforms. So could open AI then also be a platform could entropic platform, can Gemini be a platform can deep seek be a platform can Mistral be a platform, can Lama be its own platform. So that in the way that we have Windows and Mac, or HTML or different things as platforms where applications all of a sudden appear will all of a sudden an application come in within one of those platforms and then use some of those services.

Absolutely. Those could be new platforms, there will also be other new platforms. I have a platform right here as well. iOS. There are many platforms. And our job as a software company is to help our customers to create success and to take that and help them connect with their customers in a whole new way. So we'll deliver our products, our capabilities, our value proposition with our customer relationships, of course, we have over 150,000, I think, customers on our core, 1 million on Slack.

We have 15,000 sales reps who are out there their job is to work with customers to help architect their future success with these ideas. And our primary vision though, today, because this in the current reality -- this is about humans and agents working together. And these customers, like you saw today with Wyndham, with SharkNinja, even SaaStr, even Salesforce. Our job is to take what's available today and make it successful.

And that isn't where those platforms are today, as you know. And in your business, you have -- you work for an amazing company. Keith works or an amazing company. And these large banks where we are providing a lot of automation for the sales professionals, the service professionals. There is a lot to do to not only automate those call centers, those contact centers, the sales forces, the employees with Slack, but then to also then unleash the agents in a way that is compliant, that is secure, that is available, that is scalable, that is reliable, that is able to operate in hand in hand. So if you go to help.salesforce.com today, and you want to get help from Salesforce, you know that you're going to be able to automatically connect to our contact center as well.

That's incredible. We couldn't do that just a couple of years ago. as you know. So that's the current way we're deploying. Well there could there be other ways that we deploy. It's definitely possible the future could have many different forms, but we can see right now what we're going to sell this year to our customers. We have a lot to sell and a lot to do.

Your next question will come from Gabriela Borges with Goldman Sachs.

I wanted to ask the team about the $2.4 billion disclosure on AWUs. Tell us a little bit about how you translate the tokens and the Agenticwork units to monetization? I know you've been working on ALA -- how do you think about the evolution of the time and the pricing model, Jason, from Sater was just talking about the agent valley of the stack being created a 4x more than software value at the stacks. So tell us a little bit more about how the ELAs are going and Robin for you specifically, how does it impact gross margin?

I think Patrick should really lead this AWU discussion because it's kind of his brain child and he was very unhappy that I keep bringing out this token number because I'm very impressed. We have 19 trillion tokens, but because I think that really shows that we're really using these products to deploy these agents.

Well, I mean everybody can now know agent force is hugely successful. And all the new capabilities of agent force, the determinism, the voice, the programmability, agent for studio and Fort Builder and now Slack bot as well. But I think that then there's another level of this idea of agentic work units. So why don't you tell us what your vision?

Yes, sure. So as we started looking at how our customers were using agent force, and we started looking at how we're consuming tokens from the model providers, right? All those models that sit at the bottom of our layer from open AI and from anthropic, -- what they're doing is they're providing intelligence into our system, and we're able to measure that intelligence through the lens of a token, and that's how most of these model companies are charging. It's the amount of tokens that your platform, in our case, is consuming.

But when we started looking at that across our customers, we can start to see, okay, our top 10 customers are consuming this many tokens. We know how many tokens sales force is consuming internally. But it begs the question, well, is it -- are they doing anything? Are they working? Are they providing any value? Or is it just input and output of intelligence, right? So you can ask it a question, it can write you a poem, but that's not really all that valuable in the enterprise world, what's valuable is creating a document for you or updating a record or helping us right here at this table, we all use Slack bot to prepare our notes here, our customer stories, we're all preparing that with Slack bottom. So what we did is we said, what if we could count those individual work units.

And then what if we could look at those work units relative to the tokens, and we said, "Oh, there's a relationship between the 2. We can start to see a ratio of tokens being consumed and work coming out. And that ratio starts to become really interesting because now we can look at our customers and say, "Hey, customer A, you have a really nice ratio. You're getting a lot of work done on the platform for the amount of tokens that you're consuming hey, Mr. Customer B, your relationship is actually not so good. You're consuming a ton of tokens and not getting a lot of work done. What can we do to help you? So -- it becomes a really kind of interesting way.

The tokens are kind of a leading indicator, but the work unit we think is a much more valuable indicator in terms of where the value is actually coming from for our customers and for our own transformation into an agentic enterprise. But maybe on the monetization, I can talk to you.

Yes, I mean this is something that we continue to look, I think you were asking specifically Gabriela about what does it do to gross margins. And as we think about margins in the short run, we think we're pretty neutral. Patrick talked about this differentiation between tokens and AWU, while tokens, those prices, we're working with our various partners, those are going to start to go down over time and commoditize, but also importantly, when you think about our products, engineering and product is working on ways to continue to fine-tune our products with things like agent force scripts, which is going to make it easier for us to produce the work, but reduce the overall costs. So those are things. And then again, we're optimizing. We're using customer 0. Marc talks about the fact that we're allocating resources. We're also looking at other things to overall continue to drive our efficiency down.

So short term, we don't see gross margins getting worse. fairly neutral, long time. We're doing everything in conjunction with our FY '27 framework and our overall operating margin improvement to continue to get efficiencies in gross margin and operating margin.

Miguel, do you want to take on the question about AWUs and kind of what we're seeing in the market and how customers are consuming this technology.

Yes. I've been working very hard for the last quarter to have this minute because I really want to tell you the story. -- was stellar. You heard the numbers at the time. We made a very clear commitment, Robin and I in partnership at the Investor Day, we shared 3 key messages to you all. Number 1 is we were seeing the very likely possibility of revenue reacceleration in 12 to 18 months. That was 4 months ago.

Today, we are saying that the revenue reacceleration, organic revenue acceleration of subscription and support is going to happen in H2 and we are very -- we are committed to that, and we are certain now because we've seen the net AUV growth outpacing the AUV growth in H2 last year.

We're sitting now in Q1. We're looking at Q1 and Q2 and I can tell you with absolute confidence that the AUV growth is going to significantly outpace the AUV growth. So now 4 quarters of will be pulling up the AUV growth is going to finally translate in H2 into a revenue reacceleration. That was number one.

Number 2 was the fiscal year 30 a long-term durable growth plan. we are recommitted to that to the point that we've increased the target from 60% to 63%. If you do the math, it's not all because Informatica, it's because we are more and more certain that we are going to hit the numbers.

And then the third thing, which is substantially important, and it goes to the monetization. And to the ILA question is we have found the formula to monetize AI. There are 3 ways Three ways, distinct ways, and the main ones that we are using to monetize AI.

Number one is our large installed base of 100 millions of seats, we are upgrading to our premium SKUs that contain already embedded AI and unlimited access to Agentic for employee use cases. Number one.

We've seen, as Robin referred to earlier, that SKU business has triple agent force, first edition and agent force store sales and service has tripled quarter-on-quarter. Last quarter, it doubled. So it's pretty monster -- the second way to monetize this is very peculiar because now our apps are agent force cells, agent for service, all of them are agentic.

So now the ROI that companies generate by implementing our apps has increased. So now we have access to new seats that before companies couldn't afford to roll out sales force or any of our apps. And the third way is for customer facing agent use cases, agents, we sell thrill the credits, flex credits. And companies, if you look at the bookings of agent force in Q4, 50% were credits, flex credits, fuel and 50% were higher SKUs.

If you look at the top 12 deals, which, by the way, record Robin and Marc, we've never done more than 10 deals above $10 million in the quarter. This was our best Q4 ever our best quarter ever. We did 12 deals, about $10 million. One of them about 50%, 3 of them are about 20%. When we look at those, and if you look at the 3 ways to monetize, 6 out of the top 10 deals basically were upgrades of the existing SKUs. Seven out of the top 10 deals, we added 6 and 5 of the top 10 deals included credits for agentic use cases, customer-facing use cases.

Three of them included everything. But the beautiful thing is in every study that we heard today that was very incredible these 3 customer stories. I have a bunch of stories that I wanted to tell you, but we're running out of time here. In every one of these stories, we are monetizing AI through these 3 different angles. And we are seeing it in the bookings. We are seeing it in the pipeline. I'm very confident about Q1. I mean, something happened in Q4 that was muster. I mean, Marc said a target to me and to my team, I need to see bookings starting with a number, and we deliver above the number that was incredible. I'm looking at the pipeline, double-digit growth in pipeline. I'm looking at my capacity. -- we've hired over time.

We started last year 12 months ago with 0% growth in ramped AEs. These areas that are ready to sell. It takes our as a year or so to sell to be prepared. We are starting this fiscal year with 15% to 17% more growth in ramped as -- that's Dynamite. We have double-digit growth in pipeline. I'm very confident about the net EUV growth significantly outpacing AUV growth. And ILS have been a big part of this. This is the #1 product that we sell now. We sold 120-plus ILS in Q4. I thought we're going to do between 50 and 100, we did 120. In the top 10 deals, we sold 8 ELAs in the top 10 deals. These are customers that are going all in and commit and commit long term to our -- to the future and there are outsized deals.

Your last question will come from Raimo Lenschow with Barclays.

I'll get a quick one. if your cross-sell or the token upsell is working so well, you said 60% of the bookings came from that one. it's kind of almost getting the message out to more customers quicker. You now have 29,000 customers. How do you think about that evolution from kind of getting new customers and getting these guys up and productive this year? How do you think about the the role there and what are the roadblocks?

Yes, Raimo. Good to see you again. Listen, we did 29,000 agent force transactions. We have approximately 22,000, 23,000 customers. But you said it very well. our role, the role of my team, the role of my executive, the role of all the -- as is to be in front of customers to explain these stories and the value that we can drive. I mean today, yesterday or today, I don't know when, there was a wall in Australia, we had 12,000 Yes. today, right? 12,000 customers.

It's actually tomorrow, but it's today.

It's Australian. I don't know, whatever 12,000 customers showed up -- it's happened. It's already happened, by the way, and I think we just need to -- the key message that we are conveying to our customers is we are, SaaS is more important than ever. In the world all this is -- I mean, we are so happy that this row intelligence exist, but to convert row intelligence into reliable, accurate scalable enterprise work, you need a solar infrastructure like the 1 that Marc described with our 4 layers system of context, the system of work, this is our big differentiator.

Nobody has 40% market share in sales and service. I'm sorry. In the customer domain, we are the systems of work. We have the system of agency, very sophisticated. Some companies are building it, whatever, but we have the best because we are proven in 4,000 production customers, 23,000 total customers. Nobody has that at the scale and the complexity because our agents are connected to the data connected able to trigger actions and then we have the system engagement, which is Slack.

I mean the demo of this entropic is incredible. It started in Slack. Then what did they do? They took it out to another UI, which is awful, by the way. But it's -- I mean, it wasn't really as nice as lag, but they did all the work, incredible work. Again, we are so lucky that this company exists. And then they copy paste it. they did that, right? They copy paste it and they put it back on Slack. Okay. Today, you can do that with Slack boat. You don't have to get out and in, and we have a great partnership with Anthroopic. But anyway, Raimo, we are very excited.

Patrick, I think you should come in here and talk about this.

Yes. I mean everybody right now, everybody through the past few years has been so enamored with the model, of course, it's this brand new thing, this intelligence layer that we never had but also the data. But what's really happening around us is the apps are changing. -- the UI is changing, as Miguel is alluding to. And that's really what we're seeing because these old apps of these point-and-click buttons, those were designed for human beings to interact with. But what happens when you have human beings and agents in the same place. right?

Suddenly, a lot of those interactions, those UI paradigms kind of get thrown away. You don't need all of this complex UI anymore. And that's what makes Slacks powerful, and I think that's what Anthropic knows. I think that's what we saw in their demos yesterday. -- right? You kind of like process the work. But ultimately, it's coming -- that work is getting done because some person or some agent is asking for it, and then you need to give it back to that person or that agent. And where do you do that? You do that in Slack. And that's what makes Slack bot so unbelievably powerful is you never have to leave.

And of course, it's powered by Claude. We love our partners of entropic but it knows all of the context of your business, not just the context of your systems of records as we think about it, but all of the conversations happening inside of Slack and has access to all of that and the knowledge that it gains from that truly unmatched. It might be our most important piece of data that we have.

And so when you put all that together into this brand-new user interface, that's really where we see this big transformation in SaaS happening. It's that the apps are going to -- they're going to change, and they're going to just turn into this environment where humans and agents are really working together.

And I think to add to that, if you think about customer success, right, we're really doubling down, as we said, on FTEs. And I think they're the folks that are on the ground with our selling teams, our solution selling teams to ultimately make this vision a reality. And I think that's the key component to converting it from ALS to ultimately consuming. That's what we want to continue to see happening as that consumption will continuing to fly.

Well, great. And we want to thank everyone for joining us today and look forward to seeing you soon.

Bye, everybody. Thanks so much.

Good afternoon, everyone. Welcome to the 2026 JPMorgan Healthcare Conference. As a reminder, following the presentation, there will be time for Q&A. Please make sure to wait for the microphone to come to you before asking your question. We're thrilled to have with us today Mark Sullivan, President of Salesforce. I'll hand it over to you to get your presentation started.

Thank you. Thanks, everybody, for being here. It's such a thrill to be at this conference again this year. It's also great to see the room sort of double in size for who's attending and what's going on at Salesforce. I was fascinated to check into my hotel. It has a very Dreamforce vibe in San Francisco this week. This conference just continues to get bigger and bigger and bigger, and it's been wonderful meeting with all of you this week, and we're only on day 2. So pace yourselves, 3 more days to go.

I'm excited to talk to you today about all the things that we're doing in health and life sciences at Salesforce. And it's been an extraordinary journey for the last couple of years, but in particular, even the last 12 months since I stood here in front of you last year. Last year, we were talking about agents and the impact of agents in technology in this industry. I think this year, we're talking about becoming true Agentic enterprises and taking advantage of that technology in ways that, frankly, we couldn't have even dreamed up last year or the year before.

And so we've made a lot of investments. We've made some huge commitments in this industry, and I'm going to walk you through that today and then give you an opportunity to ask some questions to understand where we are and what we're doing, but we're very proud of what we've done over the last year, we've been busy beasts, and I think you'll see that. Some forward-looking statements. I'll let you read this backwards before we get started. I may make some comments about our performance and our financials and our products and the future of those products. But obviously, those aren't commitments. So keep that in mind as we kind of move forward.

My name is Mark Sullivan. I work for the Mark with a C, I'm known as Mark with the K at Salesforce. There's a couple of Marks in Salesforce, but I'm responsible for our regulated industries, which is health and life sciences, along with financial services, which is a meaningful part of our company. And as we've gotten deeper and deeper into industries, which I'll talk about that briefly here today, the importance of industry depth and commitment into the industries that we serve, the 2 biggest industries that we serve are health, life sciences and financial services, so HLS and financial services. So this is important to us and the investments.

I'm going to start with a big thank you, which we always do. Thank you if you're a Salesforce customer. We serve so many in this industry. Thank you for being here today. Thank you to all the trailblazers and agent blazers and the people in our support community at Salesforce, which is vast. We've come really far over the last 26 years. And you'll feel like I'm reintroducing you to Salesforce today. You may have some perceptions of what Salesforce is. Everybody has grown up understanding we're #1 in CRM and all those good things, and that's great, and we still are. But we're really transforming as a company, and we're getting deeper and more focused into the industries that we serve. And at the top of that list is life sciences. So you'll hear about that today.

We do talk about doing well and doing good. We've guided for FY '30 up to $60 billion, and that's obviously impressive. The growth of that means a lot to us, and we wouldn't get there without our customers and our network and our partners and all the people that support us and all the companies that support us -- it's been an incredible journey. Our FY '26 guidance at $41.5 billion is also something we're very, very proud of. This company continues to grow at a very aggressive pace. It's just very different how we're growing today, what we're selling and how we're serving our customers.

And while that's great, the financial numbers are always important, and there's something we always want to put an emphasis on, I think we're even more proud of some of the awards we get about innovation, about philanthropy, about being an ethical company. It matters to us. And we started 26 years ago trying to bring easy technology to the enterprise in a trusted way. And that sounded like a crazy thing to do. Let's bring your customer data into the cloud. That sounded a little drunk and disorderly 26 years ago. Now it's all there, right? And it's actually more safe than it's ever been.

And as we get deeper into the industries that we're serving and as we enter into this agentic revolution, that safety and that trust is maybe more important than it's ever been. So we take that pretty seriously. And when we try to walk into your organizations and talk about the implications on AI and how you're going to use that, we want to do that in a way that's trusted, safe, auditable and the like so that you can get the most value from it in a way that you feel comfortable with at the end of the day.

Our industry-specific innovation is our DNA. We've -- we started the company 26 years ago, but for the last 20 years, we've really dove head first into industries. And it's shaped who we are as a company. It shapes who we hire. We now hire people that have lifelong legacies in the industries that we serve. That's different from generic technology wizards. We've always been able to hire those people, and that's great. But it's critical for us and maybe more critical now than ever before as we look at what happens in an agentic world to commit to these industries, to get deep into these industries, to understand the workflow of these industries and the criticality of that so that we can reshape it for this new AI revolution.

And so we're very committed. We have 13 industry clouds, but that's not really the story. It's really about transforming the industries that we serve and being committed and deploying our capital into specific industries for the impact that we would like to have. But -- we couldn't be more all in. I've grown up in industry, not as a pure technician, and that's allowed me to understand the language of the industries that we serve and to create value in the manner with which you would like to see it, not just a better technology solution.

If you look at what we're doing in health care and life sciences specifically, we are all in. Our boats have been burned. We couldn't be more excited about what's happening. This is very substantial for us. This is a $4.7 billion ARR business at Salesforce, which we think is simply extraordinary, and it continues to outgrow our industry businesses outgrow the rest of Salesforce. and we'll continue to do so in my opinion. And as we get into this Agentic revolution, you'll see that growth, I believe, accelerating into the industries that we serve.

And so we're very blessed to be working with 6 of the top 10 pharmaceutical companies in this space, which we think is very important. We also believe that the top 10 themselves is sort of a disproportionate amount of the industry, as you all probably know. So it's very important to win the top of that stack and to shape our future and our road map for all of our products working with those companies intimately to make sure we understand where they're going.

We're not interested necessarily in competing with other apps like what app does a competitor have and what app do we have? We would like to transform this industry. We think technology is in a place right now where this is revolutionary. And I use that word very intentionally so. It will change how we all work in a very meaningful way. The analogy I've used repeatedly is if you showed up at work tomorrow and you didn't know how to use a laptop and you had no idea how to use a cell phone, you'd be pretty compromised. I don't think you'd do so well, right? If you show up at work pretty soon and you don't understand how to harness AI in a safe way, it's going to be as if you showed up without your cell phone. You better know what you're doing and you better know how to do it in a really safe way, and we couldn't be more committed to that transformational moment in this industry because we think it's purposeful. We think it's impactful to the industry. And we think it's just a monumental opportunity unlike any other opportunity that we, frankly, have ever seen.

So we expect to continue to grow. We expect to be shaped by these top customers, and we expect to continue to win. I know it's a competitive thing, and you hear about our competition all the time. We're not focused on that really. We're focused on what we can do within the industry and how we can transform this industry. If you look at where we are, we've been very focused on commercial and the growth that we've had in life sciences, but we really want to emphasize the entirety of the supply chain. We want to understand how drugs are found, how they're manufactured, how they're distributed. We want to make sure that every aspect of this is changed. We think we can go faster. We think we can be more efficient. We can get higher levels of adoption. We can get through trials more successfully. We can serve members and customers more effectively. There's so much that can be done that frankly could not have been done in prior eras where we didn't have this opportunity to use agentic AI.

So understanding how to harness this and do that in a safe way on a trusted, integrated, fully integrated platform means everything to us. We're going to increment along this. We don't have every single piece of this done, but we're going to be shaped by the top customers in this industry so that we do this in a way that's very compelling and we get through all aspects of this entire supply chain to have a massive impact that we think will translate into not only a benefit for the companies, but a societal benefit. It's very purposeful for us and purposeful for our employees and purposeful for everyone that works at Salesforce because we think there's an incredible opportunity to change health care, period, not just have better tech. but to change health care. And we think that's an incredible responsibility and opportunity.

If you look at where we are, there's new ways of working, reducing admin time, unifying teams, simplifying experiences, accelerating your account-based orchestration and market impact. We're just seeing everything be changed. Everything is changing. And so it's up to us and the imagination that we deploy to figure out how we want to do this, right? There's -- the technology is something always that we've gone to. You log on to your app, figure out what's deterministic in that app. Now there's nondeterministic reasonable agents that can reason and take action for you. We think that has to reset how you think about this industry. We think that has to reset how you think about technology. And bluntly, in this industry, you might not be the best technicians in the world. There's a lot of chemists, there's a lot of doctors. You're in the business of saving lives, which is critical. We want you to focus on that. We want to make sure that we're thoughtful about how you handle the technology and how you handle this unique once-in-a-lifetime innovation wave that you have to take advantage of or you're going to fall behind.

We promised we sort of delivered. There's a lot of things I talked to you about last year that were hopes and dreams about what we're going to develop and how we're going to develop them and the capabilities that we're going to bring to bear within this industry. There is a list. I know there's a lot of words on this page, but these things are all GA today. Our product catalog, our data integration, medical, search, admin, developer, all these things are available from Salesforce out of the box using our deeply integrated platform and the agentic capabilities that we bring to bear. So this slide gets thicker and bigger, and there's a lot behind all of this, but this is all already right now. And our customers are using this right now. And of course, transitioning from something to something new might be perceived as difficult or more expensive. We disagree. We haven't had any customers leave us. They're all coming in, and we think these projects are going very, very well, and they're shaping us as a company and shaping how we execute in the marketplace. So there's a lot here and there's simply more coming.

How does this work? Why choose Salesforce when there's other alternatives? And you'll see a slide later, but I want you to think of a couple of layers in a deeply unified platform that are very important to us. Number one is the data layer. You have to be thoughtful about how you manage your data and making sure that you have the right data available to fuel those agents in the marketplace. So we bring to you Informatica, we bring our Data 360, we bring MuleSoft. All of that helps you optimize your data layer. On top of that, you have our application layer that's been available for 26 years. In there, you have a lot of the workflow and deterministic code that's leverageable to fuel your agentic future. And what you find in a nondeterministic world is anyone can build an agent on top of a data store, but there needs to be some rules. Just an agent on top of a data store is probably as good as the most irresponsible intern. You might have some challenges with their accuracy, how they make decisions, what they do, how they learn, building an agent in a trusted, deeply unified platform like this can avoid that and put you in a much better situation.

On top of that, you, of course, have an agentic layer at Salesforce, where you can build agents, you can design them, you can test them, you can work with them. You can also build hero agents that orchestrate other agents, whether they're Salesforce agents or not. These, in essence, are your digital employees. You need to know what they're doing, how they're doing it and orchestrate even agents that come from other brands. We will all live in a multi-branded agent economy, and we need to understand how to orchestrate that for safety and trust to make sure we have highly accurate, dependable outcomes from those agents. They should be your best employee, not your most irresponsible intern.

And then lastly, on top of that, we have an experience layer. We'll show up where you work. Even if that's in ChatGPT, whether that's in mobile, wherever you are, whatever application you're working in, your agent will be there. Your agent will be guiding you to make better decisions and we'll take actions rather than just generate outcomes for you. So we think this platform is very important. We're not suggesting it's the only platform. You've got to do everything agentic on Salesforce. I don't think that's a practical answer, but we do think it can be the center of your agentic future and it can orchestrate everything you do from an Agentic perspective. So we think that's very important. And people are choosing us for that, not because we have every feature that a competitor might have, but because we have those features and we're taking you to an agentic future. That's the difference. And understanding that this is a moment in time that is revolutionary from an agentic perspective. If you don't think that way and you just want to place an application with an application, Salesforce probably isn't for you. That's not what we're looking to do. We'd like to transform the industry using the technologies that are available, and that's what we've been doing since we started the company for 26 years.

If you look at it, it's not easy, but it's essential. Sometimes you might say that's a harder choice. maybe it was a harder choice when we all went online with our stores and maybe it was a harder choice when Amazon stopped selling only books, those are harder choices. I see it as that choice. I see it as that moment, like you've got to decide, do you want to take advantage of this new technology or not? There's been a lot of investment in AI that hasn't been fruitful that has been experimental, but I see that shifting and people understanding how to harness this now knows what it is. When we sat here a year ago, I'm not sure everybody understood this very well. Just the basic computer science of it, didn't understand it very well. There's been a lot of money spent. There's been a lot of experimentation. We've seen the good, the bad and the ugly associated with that, and we think we have an answer that's very compelling, safe and trusted to drive some meaningful change in this industry.

If you look at this, we have some customers that are showing up and doing this with us and helping us design -- so Fresenius and reimagining their health care experiences, how do reps show up to health care providers, changing how they show up, what they can do, how they can sell, how they can engage, how they can serve. Imagine showing up and having an agent army with you. They can keep you deeply informed about your customer and their needs and helping execute against what you're hearing. So we're designing that with them. We're very proud of it. They've got 4 disparate business units that we're going to bring together. They'll all operate on one platform now. So that takes a lot of confusion out of their business, makes it very clean and clear on how they operate and lets them show up very differently for their customers. And so we're really excited about that.

Look at AstraZeneca. They're using us too, to transform their whole customer engagement on a global basis. They're pretty big. They have a lot of impact in this industry. And so leveraging them on how they drive service, how they transform that customer engagement is everything to us. These customers are design partners for us. They're shaping our future. You could say this is custom. We're doing it all custom for them. That's absolute nonsense. We're doing this on our platform with all the out-of-the-box agents that I showed you, and we're building more agents for them with them to change the topography of this entire ecosystem. So we're very excited about that.

And lastly, CVS Health, massive opportunity on how they serve their customers. All that they've done with Aetna and all their growth and their commitment into this industry is fantastic. It's one of our largest customers now at Salesforce and taking them into the future on how they change, how they serve their customers, what they do and manage some disconnected systems in a way that is very compelling. So this is just some examples. There are many more.

If you look at this, our ambitions, again, are not just deal by deal. It's really to win on a much grander scale. We think that this industry needs it. There are labor shortages in this industry. There's brittle technology in this industry. It is time to kind of clean out the garage and fix the technology structure of this industry bluntly. It needs it more than ever. And we think this is a solution to some of those meaningful problems that this industry has faced for years that you couldn't overcome or couldn't find the capital to invest in. And so this creates that moment in time. Is that easier than just staying on the application that you have? Probably not. But do you want to differentiate? Do you want to lead from the front? Do you want to transform the industry, then that's who we want to work with, right? If you're just looking for a different application, there's probably somebody across the hall that can help you. That's not what we're trying to do, and we don't think about it that way.

Lastly, and I talked about this a little bit, sort of a top-down on the model that I talked about earlier, but we really do think data matters at the top, just a unified AI-ready data foundation. That sounds so easy. We all know it's not. Everybody has different data architecture investments that they've made historically. You all have different gravitational data stores, leveraging that data is regulated and you have to manage that in a compliant way. We understand that. We have an incredible zero copy ecosystem where we can tap into most of your data architecture. If you spent a lot of money on data architecture and you're trying to get value from that and unlock the value, we think we can help you do that in a way that we've never been able to do in the past. And so those investments should be leverageable and helpful for you, not something that you're depreciating or they're impacting your bottom line in a negative way. So we think we're in a great position to help you.

The unified application layer, we still think we are #1 in CRM. -- period and not because we say so, because it's straight up true. And we think the applications that we have are continuing to be leverageable. -- a lot of languages SaaS dead and the Agentic world is going to take over. There's still a lot to be said for the deterministic code, the workflow, what sits in those applications that has been built for 26 years and how that data can fuel your Agentic future. We think that's important. We think that's meaningful. We think that creates greater accuracy, greater outcomes for the agents that you're using.

And the unified experience layer, whether it's marketing or service or sales, whatever you're trying to do, understanding how to engage and where to engage with your customers, whether it's on a laptop, whether it's on a mobile device, whether it's on a computer, whether it's face-to-face, be in a better place. And so we just think that there are a few companies that can connect all of this in a cohesive, trusted way. We think we have a unique advantage in that regard. There are lots of companies that can build agents if you give them a data store and something to build an agent on, not in a way that's auditable, trustworthy, compliant, understands the regulatory environment and creates outcomes that are measurable and manageable for your industry. So we think that's unique, and we think that's very compelling, and that's why we're investing a lot of our capital in this.

We have over 200 plus, this grows every single day, agents and actions within each industry. And so as we work with our customers and develop agents, there's use case by use case where people are discovering new ways to deploy agents and leverage them within their businesses. What we've learned is there's a journey to that -- there's a sequence to that. There are some use cases that have higher value because they might be easier with a higher ROI immediately. There's other use cases that might be more complicated with the data architecture that you're leveraging might take longer. Maybe they have a big impact, but they might be more complicated. So understanding the sequence of those use cases and starting out of the box, if you start with -- we have use cases, we have agents that do that and you're not starting from scratch and you're working with us as a partner with tested compelling agents that have been leveraged by others, you're kind of starting on second base to a certain degree in our opinion. So that increases your speed to value and puts you in a much, much better situation. So it leverages your data investments. It leverages your SaaS investments, and it puts you in an accelerated path to value that we think is critically important because we are in a hurry in this industry.

As I mentioned before, too, there's what we refer to sometimes as hero agents. agents that might be focused on post clinical or regulatory or medical affairs or in the commercial space, they can do a lot of things, whether it's contract development, marketing campaigns and the like. These hero agents have to orchestrate the Agentic workforce. They have to understand how to interact with other agents, whether it's MCP or AA, whatever the technology is, we have that capability, and we can leverage that so that we make sure that we orchestrate your entire Agentic ecosystem and the Agentic architecture that you're working with. As agents continue to be constructed and deployed and used in this industry, you'll have more and more and more, you'll have many brands. You better understand how to register them, orchestrate them, manage them, understand the work that they're doing, the jobs to be done, understand how they're interacting with your human capital workforce so that it's safe, so it's protected. You don't want the most irresponsible intern running up and down your hallways, unregistered, making decisions and taking actions. You'd like to have that under control. You'd like to know where the prompt came from. You'd like to know what the outcome was, who generated the prompt, what was meaningful about that. And you probably would like to show that to your regulatory oversight or to any compliance policy that you have. We put you in a position where you can do that. We think these hero agents are very important because as the agent sprawl continues, you're going to have to orchestrate your agent army, if you will, for the betterment of your organizations.

So we talk about that. We call that agent fabric. It's part of what we do in that data layer that I discussed. And so that will show you how -- where are your agents today? What are they working on? What are the jobs to be done? How are they executing? How are they interacting with your human workforce as well. So you should be able to see that. You should be able to report on that. You should know what everyone is doing at any moment in time, make sure that they're all compliant. And if they have issues with following policy or any compliance issues, it could come back to you. Let's redirect that back to humans. So there's humans in the loop in everything that we do. We're not trying to replace every member of the workforce here. We're trying to make everybody monumentally better. We're trying to free up your time to focus on strategic issues that matter, which, by the way, is what you guys are good at, saving lives, developing solutions to help people. That's what we want to put you in a position to do, not managing your technology platform, right? We'd like to do that for you so you can focus on the things that you do best.

So we've done a few things from an acquisitive standpoint where we've bought some companies, and it's sometimes you wonder what the heck are they buying and why are they buying that? And how does it fit in? And it's not as clear. We're not doing this just to create new revenue sources for us by brand. But as you think about our Agentic future, there's things that we've acquired that I'm sure many of you have already read about that I've listed on this page, and they're very important to us because it helps us orchestrate your Agentic ecosystem and make sure that you can do what you need to do.

So if you look at Informatica, just an incredible company that we recently acquired, the MDM capabilities, understanding where the data is, the privacy and quality of that. It's not yesterday's Informatica. We all know that as an ETL organization. There's so much more they do for us that's helpful to understand where your data is. Look at Doti, what information exists, your search capabilities. So think about searching through your agents, understanding structured and unstructured data, finding that to be leverageable to arm your agents to be able to make better actions and decisions. Look at Spindle and A Primor, am I making the right decisions? Are we scenario modeling these agents? Do we test them? We give them case studies to work on just like you might a new employee? How do we model this through, so you're confident that you're getting what you need at the level of accuracy that you need it. Then you look at Regrello, how do we manage workflow generation and process automation. If I think about that entire supply chain in life sciences, Ragrela can look across all of that and say, look, what are the workflows, what are the issues? Where can we take advantage of opportunities. So this all fits together from our perspective, you see it one at a time reported in the news. But for us, these are the building blocks to our deeply unified platform that help you make better decisions as you work with your agentic architecture. So we think that's super critical.

Lastly, and I mentioned this, it's not just about the technology and the brands that we're working with. It's really about elevating all of you. What do you want to do? Do you want to manage your tech platform all day? Or do you want to help people, right? Do you want to help people get better? Do you want to focus on the strategic issues within this industry? We think we can provide you with a dozen professional chiefs of staff, if you will, to make your life a lot easier, to make you execute a lot better using our agentic architecture in a trusted and impactful way. This is your new cell phone. Like I said before, you're going to need it. you need to understand it. You need to be moving towards an agentic future. Your company needs to be an agentic enterprise. If not, it's going to be comparable to when company is on the Internet and you're not. It's that serious in our opinion. It's that impactful to some of the tech cycles that we've seen before. So we think this means everything if you have a plan, great. If you want to do that in a trusted way, we think we're in a great position to help you.

I mentioned also that just the industry sort of needs it. Look at this and just look at the structural barriers to agility within the industry. These are the things that kind of hold you guys back in my opinion, just your budget, your team structures, the skill shortages. There's a lot of chemists and doctors in this industry that don't know much about technology. That's problematic. There's a lack of tech strategy. Projects remain in pilot, they get stuck. There's a lot of starts and stops in this industry that are inefficient and slow you down. We've got to be better than that. We would like to show up as your partner and be vastly better than that. We try to solve these specific problems so that you can react, whether it's tariffs or other macro issues, regulatory changes, whatever you need to address, acquisitions, new trials, you've got to go faster. We all need to go faster and you have an opportunity to do that to get through some of these land mines and address your challenges around competition, margin pressure, all the revenue threats that we're all facing. This is a challenging industry. It's very competitive. It's going to get more competitive because those that understand how to leverage this technology will take advantage of it.

So there's more coming. You'll see more from us and more announcements. You'll see regulated content management coming quickly as we get into H2 of next year, and there's a lot of things. We've got quite a road map on what we're developing and how we're developing it for the industry. It's a long list. We will continue on that journey. That will never stop. for 26 years, all the products that we've offered had a constant refresh road map. We've done 3 releases a year for everything we brought to the market. This will be similar, if not faster, because of the commitments that we've made to the industry. And we're working with our customers. I mentioned 6 of the top 10 that are shaping the value that they believe that they should be driving in this industry. So that's influencing us every day on what we do and how we do it. And you'll see more around those commitments as we grow our investment in health care and life sciences, not just in commercial, but across the entirety of that value chain. So we're working through it. We need your input, your company's input. We need your guidance as to what matters and what doesn't. This is a highly prioritized approach. It can't be done all at once, but it can be done, and we want to go faster, and we are going faster.

So we're -- you can read the slide, we're radically simplifying treatment, accelerating clinical innovation and orchestrating healthier experiences, one unified Agentic platform. That's what's different. This isn't just another app alternative for you. This is an Agentic platform that comes with all the capabilities of an application as well that will transform your company, and we believe transform the industry. So we're very excited about that. We're going to see around the corner. It's great being here at JPMorgan Chase. There's more coming. I'll be in Davos. I don't know why they do this every year. We're going to put on boots and go sit in a snowbank, talk to each other. Someday, we'll do that in the Caribbean. But we'll be in Davos next week. You'll see Scope in Orlando in February, HIS in Vegas in March and then Becker in Chicago and many more. You'll see our world tours and other things. We will continue to drop our innovation and alert you to that. So pay attention. hop on the website, take a look at what's happening, look at what's happening in these events. We'll have lots of announcements as we go through all of these. You'll hear a lot more from us to understand where we're going. My goal is for all of you to understand where we're going. and how fast we're moving and to leverage your input to help us go faster to have a bigger impact. But we're really excited. Thank you all sincerely for being here. I'll open it up for questions. I've got a couple of colleagues, Kirst and Joe, that are happy to come up. These 2 rock stars sort of run our life sciences practice at Salesforce, so we can answer any detailed questions that you might have. But thank you all for your time. It's nice to see this room kind of packed. Last year, I think we had half the room, and I don't think it was full, but nice to see everybody here. So any questions, I'll open it up.

Thank you, Mark. And as a reminder, please wait for the microphone to come to you. Just raise your hand if you'd like to ask a question.

That's incredible. We have a question over here.