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📘 Marktkapitalisierung
📈 Was ist das?
Die Marktkapitalisierung zeigt, wie viel ein Unternehmen laut Börse aktuell wert ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft Unternehmen in Größenklassen (Large, Mid, Small Cap) einzuordnen und gibt Hinweise auf Marktmacht und Stabilität.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Große Unternehmen gelten als stabiler, zahlen oft Dividenden, wachsen aber langsamer.
- Kleine Firmen können stärker wachsen, sind aber schwankungsanfälliger.
- Die Marktkapitalisierung ist ein guter Indikator für Unternehmensgröße, aber kein Maß für Unter- oder Überbewertung.
📘 Enterprise Value (Unternehmenswert)
📈 Was ist das?
Der Enterprise Value (EV) zeigt, was ein Unternehmen tatsächlich kostet, wenn man es komplett übernehmen würde – inklusive Schulden und abzüglich Cash.
🧮 Wie wird es berechnet?
(= Marktkapitalisierung + Nettoverschuldung)
🏛️ Wofür ist es wichtig?
Der EV ist eine realistischere Bewertungsbasis als die Marktkapitalisierung, da er die Kapitalstruktur berücksichtigt. Er ist Grundlage für Kennzahlen wie EV/FCF oder EV/Sales.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Der Enterprise Value zeigt, was ein Unternehmen tatsächlich wert ist – unabhängig davon, wie es finanziert ist.
- Er ist besonders wichtig für professionelle Investoren, da er eine objektivere Grundlage für Bewertungsvergleiche bietet als die Marktkapitalisierung allein.
- Ein Unternehmen mit hoher Verschuldung erscheint im EV teurer, eines mit viel Cash günstiger – auch wenn sie an der Börse gleich viel wert sind.
📘 Nettoverschuldung
📈 Was ist das?
Die Nettoverschuldung zeigt, wie viele Schulden nach Abzug des verfügbaren Cashs tatsächlich verbleiben.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie zeigt, wie stark ein Unternehmen von Fremdkapital abhängig ist – und wie gut es in der Lage ist, seine Schulden kurzfristig zu bedienen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine niedrige oder negative Nettoverschuldung bedeutet hohe finanzielle Stabilität.
- Unternehmen mit viel Cash und geringer Verschuldung sind besser gerüstet für Krisen.
- Eine hohe Nettoverschuldung erhöht das Risiko – besonders bei steigenden Zinsen oder konjunkturellen Schwächen.
📘 Cash
📈 Was ist das?
Der Cashbestand zeigt, wie viele liquide Mittel einem Unternehmen sofort zur Verfügung stehen.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Er gibt Auskunft über die finanzielle Flexibilität: Ein hoher Cashbestand ermöglicht Investitionen, Rückkäufe oder Krisenresistenz.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Cashbestand zeigt finanzielle Stärke und Handlungsspielraum.
- Cash kann für Investitionen, Schuldentilgung oder Aktienrückkäufe genutzt werden.
- Allerdings: Zu viel ungenutztes Kapital kann auch auf mangelnde Investitionsideen hinweisen.
📘 Anzahl ausstehender Aktien
📈 Was ist das?
Die Anzahl ausstehender Aktien gibt an, wie viele Aktien eines Unternehmens aktuell im Umlauf sind und von Investoren gehalten werden.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie ist die Grundlage für viele Kennzahlen wie Gewinn je Aktie (EPS), Marktkapitalisierung oder KGV.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Je weniger Aktien im Umlauf sind, desto höher fällt z. B. der Gewinn je Aktie aus – wichtig für Bewertung und Dividendenrendite.
- Aktienrückkäufe verringern die Anzahl ausstehender Aktien – und steigern den Wert je Aktie.
- Kapitalerhöhungen haben den gegenteiligen Effekt: mehr Aktien → Verwässerung der bestehenden Anteile.
📘 Kurs-Gewinn-Verhältnis (KGV)
📈 Was ist das?
Das KGV zeigt, wie oft der Gewinn pro Aktie im aktuellen Aktienkurs enthalten ist – also wie „teuer“ eine Aktie im Verhältnis zum Gewinn ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KGV gehört zu den bekanntesten Bewertungskennzahlen. Es hilft Anlegern einzuschätzen, ob eine Aktie im Vergleich zu ihrem Gewinn eher günstig oder teuer erscheint.
🧮 Berechnung
📊 KGV (TTM) = bezogen auf den Gewinn der letzten 12 Monate (Trailing Twelve Months):🎯 Was bedeutet das für Anleger?
- Ein niedriges KGV kann auf eine günstige Bewertung hindeuten – oder auf Probleme im Geschäftsmodell.
- Ein hohes KGV kann Wachstumserwartungen widerspiegeln – oder eine überbewertete Aktie.
📘 Kurs-Umsatz-Verhältnis (KUV)
📈 Was ist das?
Das KUV zeigt, wie viel Anleger für 1 € Umsatz eines Unternehmens zahlen – unabhängig vom Gewinn.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KUV ist besonders bei wachstumsstarken oder noch nicht profitablen Unternehmen hilfreich. Es zeigt, wie hoch der Umsatz an der Börse bewertet wird.
🧮 Berechnung
Marktkapitalisierung = 1,26 Mrd. $ | Umsatz (TTM) = 2,45 Mrd. $
Marktkapitalisierung = 1,26 Mrd. $ | Umsatz erwartet = 2,53 Mrd. $
🎯 Was bedeutet das für Anleger?
- Ein niedriges KUV kann auf Unterbewertung hindeuten – oder auf schwache Margen.
- Ein hohes KUV kann hohe Erwartungen widerspiegeln – oder übermäßigen Optimismus.
- Besonders sinnvoll bei Wachstumsunternehmen, bei denen der Gewinn oder Free Cashflow (noch) keine Aussagekraft hat.
📘 Unternehmenswert zu Umsatz (EV/Sales)
📈 Was ist das?
EV/Sales zeigt, wie viel Anleger für 1 € Umsatz eines Unternehmens zahlen, wenn man auch Schulden und Cash berücksichtigt – es ist eine kapitalstrukturbereinigte Version des KUV.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Diese Kennzahl eignet sich besonders für den Vergleich von Unternehmen mit unterschiedlicher Verschuldung – sie zeigt, wie teuer ein Unternehmen tatsächlich im Verhältnis zum Umsatz ist.
🧮 Berechnung
Enterprise Value = 1,51 Mrd. $ | Umsatz (TTM) = 2,45 Mrd. $
Enterprise Value = 1,51 Mrd. $ | Umsatz erwartet = 2,53 Mrd. $
🎯 Was bedeutet das für Anleger?
- EV/Sales ist neutral gegenüber der Kapitalstruktur und eignet sich gut für Unternehmensvergleiche.
- Ein niedriges Verhältnis kann auf eine günstig bewertete Aktie hindeuten – ein hohes Verhältnis auf hohe Erwartungen oder Überbewertung.
- Besonders nützlich bei wachstumsstarken, noch nicht profitablen Firmen.
📘 Unternehmenswert zu Free Cashflow (EV/FCF)
📈 Was ist das?
EV/FCF zeigt, wie viele Jahre es dauern würde, bis ein Unternehmen seinen Unternehmenswert durch freien Cashflow „zurückverdient”.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Diese Kennzahl hilft, Unternehmen auf Basis ihrer tatsächlichen Cash-Erträge zu bewerten – unabhängig von Bilanzierungsregeln oder buchhalterischem Gewinn.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriges EV/FCF deutet auf eine günstige Bewertung bei starker Cashgenerierung hin.
- Ein hohes EV/FCF kann entweder auf Optimismus oder auf temporär schwachen Cashflow hindeuten.
- Besonders hilfreich bei reifen, profitablen Unternehmen mit stabilen Cashflows.
📘 Kurs-Buchwert-Verhältnis (KBV)
📈 Was ist das?
Das KBV zeigt, wie hoch der Marktwert eines Unternehmens im Verhältnis zu seinem bilanziellen Eigenkapital ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Das KBV ist besonders bei Substanzwerten (z. B. Banken, Industrie) relevant. Es hilft Anlegern zu erkennen, ob ein Unternehmen unter oder über seinem buchhalterischen Vermögen bewertet ist.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein KBV unter 1 kann auf Unterbewertung oder schwache Rentabilität hindeuten.
- Ein KBV über 1 zeigt, dass der Markt dem Unternehmen Mehrwert über den Buchwert hinaus zuschreibt (z. B. Marken, Patente, Wachstum).
- Das KBV eignet sich besonders gut für Unternehmen mit stabilen, materiellen Vermögenswerten.
📘 Eigenkapitalquote
📈 Was ist das?
Die Eigenkapitalquote zeigt, wie hoch der Anteil des Eigenkapitals an der Bilanzsumme eines Unternehmens ist – also wie stark es sich aus eigenen Mitteln finanziert.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Eine hohe Eigenkapitalquote steht für finanzielle Stabilität, Krisenfestigkeit und gute Bonität. Sie ist besonders relevant bei der Beurteilung der Verschuldung.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Eigenkapitalquote signalisiert finanzielle Stabilität – besonders in Krisenzeiten.
- Ein niedriger Wert kann auf ein höheres Risiko oder eine aggressive Verschuldung hinweisen.
- Wichtig: Die Eigenkapitalquote sollte immer gemeinsam mit der Eigenkapitalrendite betrachtet werden. Nur so lässt sich beurteilen, ob ein Unternehmen nicht nur solide, sondern auch effizient wirtschaftet.
📘 Eigenkapitalrendite (ROE)
📈 Was ist das?
Die Eigenkapitalrendite zeigt, wie effizient ein Unternehmen mit dem Kapital seiner Aktionäre arbeitet – also wie viel Gewinn es pro Euro Eigenkapital erwirtschaftet.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Eigenkapitalrendite ist eine zentrale Rentabilitätskennzahl. Sie hilft Anlegern zu erkennen, ob das Unternehmen eine attraktive Verzinsung auf das eingesetzte Eigenkapital erwirtschaftet.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Eigenkapitalrendite spricht für ein starkes, effizientes Geschäftsmodell.
- Besonders interessant ist sie bei kapitalintensiven Firmen oder solchen mit hoher Eigenkapitalquote.
- Wichtig: Ein sehr hoher ROE kann auch auf hohe Schulden hinweisen – daher sollte sie immer im Kontext mit der Eigenkapitalquote betrachtet werden.
📘 Return on Capital Employed (ROCE)
📈 Was ist das?
ROCE misst die Gesamtrentabilität eines Unternehmens – also wie effizient es das eingesetzte Kapital (Eigen- und Fremdkapital) zur Gewinnerzielung nutzt.
🧮 Wie wird es berechnet?
Das eingesetzte Kapital ist das gesamte betriebsnotwendige Kapital, unabhängig von der Finanzierungsquelle.
🏛️ Wofür ist es wichtig?
ROCE eignet sich besonders gut für den Vergleich unterschiedlich finanzierter Unternehmen. Es zeigt, wie effektiv ein Unternehmen Kapital investiert – unabhängig von der Kapitalstruktur.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher ROCE zeigt, dass ein Unternehmen sein Kapital effizient einsetzt – unabhängig davon, ob es durch Eigen- oder Fremdkapital finanziert ist.
- Je höher der ROCE im Vergleich zu ähnlichen Unternehmen, desto mehr Wert schafft das Unternehmen mit seinem investierten Kapital.
- Besonders wichtig ist der ROCE bei Firmen mit hohen Investitionen – z. B. in Industrie, Energie oder Infrastruktur.
📘 Return on Invested Capital (ROIC)
📈 Was ist das?
ROIC zeigt, wie effizient ein Unternehmen das Kapital investiert, das langfristig im operativen Geschäft gebunden ist – unabhängig davon, ob es aus Eigen- oder Fremdkapital stammt.
🧮 Wie wird es berechnet?
- NOPAT = „Net Operating Profit After Taxes“
- Investiertes Kapital = operatives Vermögen abzüglich nicht-verzinster Schulden
🏛️ Wofür ist es wichtig?
ROIC ist eine der präzisesten Kennzahlen zur Bewertung der Kapitalrendite – besonders im Vergleich zur Eigenkapitalrendite, weil es Verzerrungen durch Schulden vermeidet. Er zeigt, ob ein Unternehmen Mehrwert für alle Kapitalgeber schafft.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher ROIC zeigt, wie gut ein Unternehmen mit dem tatsächlich investierten (betriebsnotwendigen) Kapital wirtschaftet.
- Im Unterschied zu ROCE wird nur Kapital betrachtet, das wirklich zur Finanzierung operativer Aktivitäten dient – und verzinst werden muss.
- Besonders hilfreich, um die Kapitalrendite von Unternehmen mit viel „überschüssigem“ Kapital oder zinsfreien Verbindlichkeiten realistisch zu vergleichen.
📘 Verschuldungsgrad (Leverage Ratio)
📈 Was ist das?
Der Verschuldungsgrad zeigt, wie stark ein Unternehmen durch verzinsliche Schulden (z. B. Kredite und Anleihen) im Verhältnis zum Eigenkapital finanziert ist.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Kennzahl hilft, das finanzielle Risiko und die Abhängigkeit von Fremdkapital zu beurteilen. Ein hoher Verschuldungsgrad kann die Eigenkapitalrendite steigern – birgt aber auch erhöhte Risiken bei Zinsanstiegen oder Liquiditätsengpässen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Verschuldungsgrad steht für finanzielle Stabilität und Unabhängigkeit.
- Ein hoher Wert kann auf erhöhte Risiken hinweisen – insbesondere bei schwankenden Zinsen oder konjunkturellen Schwächen.
- Wichtig: Immer im Kontext zur Branche und Kapitalintensität bewerten.
📘 Umsatz
📈 Was ist das?
Der Umsatz zeigt, wie viel ein Unternehmen insgesamt mit seinen Produkten und Dienstleistungen verdient – also den Bruttoerlös vor Abzug von Kosten.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der Umsatz ist eine der zentralen Kennzahlen zur Einschätzung der Unternehmensgröße, Marktstellung und Wachstumskraft.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein wachsender Umsatz zeigt eine steigende Nachfrage und kann ein guter Frühindikator für Gewinnsteigerungen sein.
- Vergleiche von aktuellem und erwartetem Umsatz geben Hinweise auf das Marktumfeld und Analystenerwartungen.
- Wichtig: Starker Umsatz allein genügt nicht – auch Margen und Profitabilität zählen.
📘 EBITDA
📈 Was ist das?
EBITDA steht für „Earnings Before Interest, Taxes, Depreciation and Amortization“ – also Gewinn vor Zinsen, Steuern und Abschreibungen. Es zeigt das operative Ergebnis eines Unternehmens, bereinigt um bilanztechnische und finanzierungsbedingte Effekte.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
EBITDA ist eine verbreitete Kennzahl zur Beurteilung der operativen Leistungsfähigkeit – insbesondere bei kapitalintensiven Unternehmen oder im internationalen Vergleich.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hohes oder wachsendes EBITDA spricht für starke operative Erträge – unabhängig von Bilanzierung oder Steuerlast.
- EBITDA ist besonders nützlich, um Unternehmen branchenübergreifend zu vergleichen.
- Wichtig: EBITDA ist keine offizielle Gewinnkennzahl – Abschreibungen und Finanzierungskosten werden ausgeklammert.
📘 EBIT
📈 Was ist das?
EBIT steht für „Earnings Before Interest and Taxes“ – also Gewinn vor Zinsen und Steuern. Es zeigt das operative Ergebnis eines Unternehmens nach Abschreibungen, aber vor Finanzierungs- und Steueraufwand.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
EBIT ist eine zentrale Kennzahl zur Beurteilung der Profitabilität aus dem Kerngeschäft – unabhängig von Kapitalstruktur oder Steuersystem.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hohes EBIT deutet auf ein profitables Kerngeschäft hin – vor Zinslasten oder steuerlichen Effekten.
- Es erlaubt objektivere Vergleiche zwischen Unternehmen mit unterschiedlicher Finanzierung.
- Im Vergleich mit EBITDA zeigt EBIT bereits den Einfluss von Abschreibungen auf das operative Ergebnis.
📘 Nettogewinn
📈 Was ist das?
Der Nettogewinn ist der verbleibende Jahresüberschuss (oder -fehlbetrag) eines Unternehmens – nach Abzug aller Kosten, Steuern, Zinsen und Abschreibungen
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der Nettogewinn ist die zentrale Erfolgskennzahl – er zeigt, wie profitabel ein Unternehmen nach allen Kosten tatsächlich arbeitet.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein steigender Nettogewinn zeigt, dass das Unternehmen effizient wirtschaftet – trotz aller Kosten.
- Die Entwicklung des Gewinns beeinflusst z. B. direkt das KGV und weitere Kennzahlen.
- Im Zeitverlauf lässt sich ablesen, wie stabil und profitabel ein Geschäftsmodell wirklich ist.
📘 Free Cashflow (FCF)
📈 Was ist das?
Der Free Cashflow gibt Aufschluss über die echte finanzielle Stärke eines Unternehmens – unabhängig von Bilanzierungsregeln. Er zeigt, wie viel Spielraum für Dividenden, Aktienrückkäufe oder Schuldenabbau besteht.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
FCF reflects a company’s real financial strength – regardless of accounting profits. It shows how much flexibility a company has for dividends, share buybacks, or debt reduction.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Free Cashflow bedeutet, dass ein Unternehmen echte Finanzkraft besitzt – unabhängig vom bilanzierten Gewinn.
- Er ist oft die solideste Grundlage für nachhaltige Dividenden und Aktienrückkäufe.
- Sinkender FCF kann ein Warnsignal sein – auch wenn der Gewinn stabil aussieht.
📘 Umsatzwachstum
📈 Was ist das?
Das Umsatzwachstum zeigt, wie stark sich die Erlöse eines Unternehmens im Vergleich zum Vorjahr verändert haben – tatsächlich (TTM) und auf Prognosebasis (erwartet).
🧮 Wie wird es berechnet?
Erwartet = (Umsatz erwartet ÷ Umsatz Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Ein wachsender Umsatz ist ein zentrales Signal für steigende Nachfrage, Geschäftsausweitung und Marktanteilsgewinne – besonders bei Wachstumsunternehmen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Wachstum ist der Motor langfristiger Wertsteigerung – besonders bei Technologie- und Wachstumsaktien.
- Wichtig ist nicht nur das aktuelle Wachstum, sondern auch dessen Nachhaltigkeit.
- Prognosen zeigen, ob Analysten weiteres Potenzial erwarten – oder eine Verlangsamung.
📘 EBITDA-Wachstum
📈 Was ist das?
Das EBITDA-Wachstum zeigt, wie stark das operative Ergebnis eines Unternehmens vor Zinsen, Steuern und Abschreibungen im Vergleich zum Vorjahr gestiegen oder gesunken ist.
🧮 Wie wird es berechnet?
Erwartet = (erwartetes EBITDA ÷ EBITDA Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Ein steigendes EBITDA ist ein Zeichen für verbesserte operative Ertragskraft – unabhängig von Finanzierungsstruktur oder Abschreibungen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Starkes EBITDA-Wachstum signalisiert operative Effizienz und Skalierung – besonders relevant in Wachstumsphasen.
- EBITDA-Wachstum ist ein Frühindikator für Margen- und Gewinnentwicklung – sollte aber stets im Zusammenhang mit Umsatz und EBIT betrachtet werden.
📘 EBIT Wachstum
📈 Was ist das?
Das EBIT-Wachstum zeigt, wie stark das operative Ergebnis eines Unternehmens (nach Abschreibungen, aber vor Zinsen und Steuern) im Vergleich zum Vorjahr gewachsen ist.
🧮 Wie wird es berechnet?
Erwartet = (erwartetes EBIT ÷ EBIT Vorjahr − 1) × 100
Erwartetes Wachstum basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Das EBIT-Wachstum ist ein direkter Indikator für die wirtschaftliche Entwicklung des operativen Geschäfts – unter Berücksichtigung der Kapitalintensität (Abschreibungen).
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Steigendes EBIT signalisiert wachsende operative Rentabilität – auch unter Berücksichtigung von Abschreibungen.
- Das EBIT-Wachstum ist ein wichtiges Maß zur Beurteilung von Geschäftsmodellen mit hohen Investitionskosten.
- Im Zusammenspiel mit Umsatz- und EBITDA-Wachstum ergibt sich ein umfassendes Bild zur operativen Entwicklung.
📘 Nettogewinn-Wachstum
📈 Was ist das?
Das Nettogewinn-Wachstum zeigt, wie stark der Jahresüberschuss eines Unternehmens gegenüber dem Vorjahr gestiegen oder gesunken ist – sowohl tatsächlich (TTM) als auch auf Basis von Prognosen (erwartet).
🧮 Wie wird es berechnet?
Erwartet = (erwarteter Nettogewinn ÷ Nettogewinn Vorjahr − 1) × 100
Der erwartete Wert basiert auf Analystenschätzungen für das laufende Geschäftsjahr.
🏛️ Wofür ist es wichtig?
Der Gewinn ist die entscheidende Ergebnisgröße für ein Unternehmen. Ein wachsender Nettogewinn deutet auf steigende Effizienz, stabile Kostenkontrolle und nachhaltige Ertragskraft hin.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Wachsender Nettogewinn stärkt die Bewertung, Dividendenfähigkeit und Kursfantasie.
- Stagnierender oder rückläufiger Gewinn trotz Umsatzwachstum kann auf Margendruck hinweisen.
📘 Free Cashflow-Wachstum
📈 Was ist das?
Das Free-Cashflow-Wachstum zeigt, wie sich der freie Mittelzufluss eines Unternehmens im Vergleich zum Vorjahr verändert hat – also der Betrag, der nach allen operativen Ausgaben und Investitionen übrig bleibt.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Free Cashflow ist der echte, verfügbare Geldzufluss. Wachstum in diesem Bereich ist ein Zeichen für finanzielle Stärke und steigende Flexibilität bei Dividenden, Rückkäufen oder Investitionen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Sinkender Free Cashflow kann auf steigende Investitionen, höhere Kosten oder stagnierende operative Erträge hindeuten.
- Besonders bei Dividendenwerten ist das FCF-Wachstum wichtig – denn Dividenden werden letztlich aus dem verfügbaren Cash gezahlt.
- Ein negativer Trend sollte genauer analysiert werden – er ist nicht zwangsläufig schlecht, aber potenziell ein Warnsignal.
📘 Bruttomarge
📈 Was ist das?
Die Bruttomarge zeigt, wie viel vom Umsatz nach Abzug der direkten Herstellungskosten (Material, Produktion) als Bruttogewinn übrig bleibt – also der „Rohgewinn“ eines Unternehmens.
🧮 Wie wird es berechnet?
Auch: Bruttomarge = Bruttogewinn ÷ Umsatz × 100
🏛️ Wofür ist es wichtig?
Die Bruttomarge gibt Aufschluss über die Profitabilität eines Produkts oder Geschäftsmodells vor Fixkosten, Steuern und Zinsen. Sie zeigt, wie effizient ein Unternehmen produzieren oder einkaufen kann.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Bruttomarge deutet auf starke Preissetzungsmacht und effiziente Herstellung hin.
- Sinkende Bruttomargen können auf Kostensteigerungen oder Preisdruck hindeuten.
- Besonders im Vergleich zu Wettbewerbern liefert die Bruttomarge wertvolle Einblicke in die Geschäftsqualität.
📘 EBITDA-Marge
📈 Was ist das?
Die EBITDA-Marge zeigt, wie viel vom Umsatz als operativer Gewinn vor Zinsen, Steuern und Abschreibungen (EBITDA) übrig bleibt. Sie misst die operative Effizienz – ohne Verzerrungen durch Finanzierung oder Buchwerte.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die EBITDA-Marge hilft zu verstehen, wie viel operativer Gewinn ein Unternehmen aus jedem Euro Umsatz erzielt – unabhängig von Kapitalstruktur oder steuerlichem Umfeld.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe EBITDA-Marge zeigt starke operative Ertragskraft – unabhängig von Bilanzierungseffekten.
- Die Marge ermöglicht gute Vergleiche zwischen Unternehmen und Branchen.
- Ein stabiler oder wachsender Wert kann auf effiziente Kostenkontrolle und Skalierbarkeit hindeuten.
📘 EBIT-Marge
📈 Was ist das?
Die EBIT-Marge zeigt, wie viel Prozent des Umsatzes als operativer Gewinn nach Abschreibungen, aber vor Zinsen und Steuern übrig bleiben.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die EBIT-Marge misst die operative Ertragskraft eines Unternehmens unter Berücksichtigung der Kapitalintensität (z. B. Maschinen, Anlagen). Sie eignet sich gut zum Vergleich von Geschäftsmodellen mit unterschiedlich hohen Abschreibungen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe EBIT-Marge zeigt, dass ein Unternehmen auch nach Abschreibungen effizient arbeitet.
- Sie ist besonders relevant in kapitalintensiven Branchen.
- Langfristig stabile oder steigende Margen sind ein Zeichen wirtschaftlicher Stärke und Preissetzungsmacht.
📘 Nettomarge
📈 Was ist das?
Die Nettomarge zeigt, wie viel vom Umsatz am Ende als „Reingewinn“ übrig bleibt – also nach Abzug aller Kosten, Zinsen, Steuern und Abschreibungen.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Die Nettomarge gibt an, wie effizient ein Unternehmen über alle Stufen hinweg wirtschaftet. Sie zeigt, wie viel Gewinn tatsächlich je Euro Umsatz übrig bleibt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Nettomarge zeigt, dass ein Unternehmen nicht nur operativ stark ist, sondern auch seine Finanzierung und Steuerbelastung im Griff hat.
- Vergleiche mit Wettbewerbern geben Einblicke in die wirtschaftliche Qualität.
- Sinkende Nettomargen trotz Umsatzwachstum können ein Warnsignal sein – etwa für steigende Kosten oder sinkende Effizienz.
📘 Free Cashflow Marge
📈 Was ist das?
Die Free-Cashflow-Marge zeigt, wie viel vom Umsatz nach Abzug aller operativen Ausgaben und Investitionen tatsächlich als freier Mittelzufluss übrig bleibt.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Diese Marge misst die echte Liquidität, die ein Unternehmen erwirtschaftet – unabhängig von Bilanzierungsregeln oder Abschreibungen. Sie ist besonders relevant für Dividenden, Rückkäufe und Investitionen.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Eine hohe Free-Cashflow-Marge zeigt, dass ein Unternehmen nachhaltig liquide Mittel erwirtschaftet.
- Sie ist ein starkes Signal für finanzielle Stabilität und Ausschüttungspotenzial.
- Wichtig ist der langfristige Trend – sinkende Werte können auf steigende Investitionen oder rückläufige operative Effizienz hindeuten.
📘 Ergebnis je Aktie (EPS)
📈 Was ist das?
Das Ergebnis je Aktie (EPS) zeigt, wie viel Gewinn auf eine einzelne Aktie entfällt – und ist eine der wichtigsten Kennzahlen zur Bewertung von Unternehmen.
🧮 Wie wird es berechnet?
Die verwässerte Aktienanzahl berücksichtigt auch potenzielle neue Aktien, etwa durch Optionen, Wandelanleihen oder andere Umtauschrechte.
🏛️ Wofür ist es wichtig?
EPS bildet die Basis für viele Bewertungskennzahlen wie KGV, PEG oder Payout Ratio. Es macht den Gewinn für Aktionäre vergleichbar – unabhängig von der Unternehmensgröße.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- EPS hilft, die Profitabilität pro Aktie zu erfassen – und ist besonders wichtig im Zeitvergleich oder im Vergleich mit Analystenschätzungen.
- Steigendes EPS kann ein Zeichen für stabiles Wachstum oder Aktienrückkäufe sein.
- Wichtig: Verwende verwässertes EPS für realistische Bewertungen – besonders bei stark aktienbasierten Vergütungssystemen.
📘 Free Cashflow je Aktie (FCF je Aktie)
📈 Was ist das?
Der Free Cashflow je Aktie zeigt, wie viel freier Mittelzufluss einem Unternehmen pro Aktie zur Verfügung steht – nach Investitionen, aber vor Dividenden oder Schuldentilgung.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Der FCF je Aktie zeigt, wie viel liquide Mittel pro Aktie tatsächlich im Unternehmen verbleiben – wichtig für Dividenden, Aktienrückkäufe oder Schuldentilgung. Im Gegensatz zum Gewinn ist er schwerer manipulierbar und daher besonders aussagekräftig.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Free Cashflow je Aktie ist ein Zeichen für hohe finanzielle Flexibilität.
- Er zeigt, wie viel Kapital ein Unternehmen effektiv einsetzen oder ausschütten kann.
- Besonders relevant für dividendenstarke Unternehmen oder solche mit starker Kapitalrendite.
📘 Short Interest
📈 Was ist das?
Short Interest zeigt, wie viele Aktien eines Unternehmens aktuell leerverkauft wurden – also von Investoren geliehen und verkauft, in der Erwartung fallender Kurse.
🧮 Wie wird es berechnet?
Der Wert zeigt den Anteil der Aktien, der aktuell auf fallende Kurse spekuliert wird.
🏛️ Wofür ist es wichtig?
Short Interest dient als Stimmungsindikator: Ein hoher Wert deutet auf Skepsis oder negative Erwartungen gegenüber dem Unternehmen hin – kann aber auch zu einem „Short Squeeze“ führen, wenn der Kurs plötzlich steigt.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein niedriger Short Interest deutet auf Vertrauen in das Unternehmen hin.
- Ein hoher Wert kann ein Warnsignal sein – oder eine Chance, wenn sich die Stimmung dreht.
- Besonders spannend in volatilen Märkten oder vor wichtigen Quartalszahlen.
📘 Employees
📈 Was ist das?
Die Mitarbeiteranzahl zeigt, wie viele Personen ein Unternehmen weltweit beschäftigt – ein Indikator für Größe, Struktur und Geschäftsmodell.
🧮 Wie wird es berechnet?
🏛️ Wofür ist es wichtig?
Sie hilft bei der Einschätzung von Skaleneffekten, Effizienz und Personalkosten. Zusammen mit Umsatz und Gewinn lassen sich Kennzahlen wie Produktivität je Mitarbeiter ableiten.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Viele Mitarbeiter bedeuten große operative Komplexität – aber auch hohes Umsatzpotenzial.
- Produktivität je Mitarbeiter ist ein wichtiger Indikator für Effizienz.
- Besonders spannend bei stark wachsenden Tech- oder Industrieunternehmen.
📘 Umsatz je Mitarbeiter
📈 Was ist das?
Der Umsatz je Mitarbeiter zeigt, wie viel Erlös ein Unternehmen durchschnittlich pro Beschäftigtem erwirtschaftet – eine Kennzahl für Effizienz und Produktivität.
🧮 Wie wird es berechnet?
Die Mitarbeiterzahl stammt in der Regel aus dem letzten verfügbaren Jahresbericht.
🏛️ Wofür ist es wichtig?
Diese Kennzahl hilft, Geschäftsmodelle zu vergleichen – insbesondere zwischen arbeitsintensiven und technologiegetriebenen Unternehmen. Ein hoher Wert deutet auf Automatisierung, Effizienz oder hohen Wertschöpfungsanteil hin.
🧮 Berechnung
🎯 Was bedeutet das für Anleger?
- Ein hoher Umsatz je Mitarbeiter spricht für ein skalierbares und margenstarkes Geschäftsmodell.
- Ein niedriger Wert kann auf arbeitsintensive Prozesse oder geringere Wertschöpfung hinweisen.
- Besonders hilfreich beim Vergleich von Tech- vs. Industrieunternehmen.
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Globant SA — Q1 2026 Earnings Call
1. Management Discussion
Good afternoon, and welcome to Globant's First Quarter 2026 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions] Please note, this event is being recorded and streamed live on YouTube.
By now, you should have received a copy of the earnings release. If you have not, a copy is available on our website, investors.globant.com. We will begin with remarks by our Chief Executive Officer, Martin Migoya; our Chief Technology Officer, Diego Tartara; and our Chief Financial Officer, Juan Urthiague, followed by a Q&A, where they will be joined by our Chief Revenue Officer, Fernando Matzkin.
Before we begin, I would like to remind you that some of the comments on our call today may be deemed forward-looking statements. This includes our business and financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Please note that we follow IFRS accounting rules in our financial statements. During our call today, we will report non-IFRS or adjusted measures, which is how we track performance internally and the easiest way to compare Globant to our peers in the industry. You will find a reconciliation of IFRS and non-IFRS measures at the end of the press release we published on our Investor Relations website announcing this quarter's results.
I will now turn the call over to Martin Migoya.
Good afternoon, everyone, and thank you for joining us. We are standing at the beginning of the most important transition the technology services industry has lived through. This nearly $2 trillion industry is being rewired in front of us and the signals coming from the AI ecosystem and from the largest software companies are all pointing in the same direction. The influx of capital, the need for the right talent and the need to deploy cost-effective AI solutions quickly has never been greater. We have been providing AI solutions to some of the world's most important companies for more than a decade.
Globant was built for this moment. For 23 years, we have been building deep engineering capabilities and a profound understanding of our clients' businesses across more than 1,200 customers. We have built a strong AI-native services practice on top of that foundation. Enterprises do not need just models. They need AI-native services delivered by AI agents, supervised by humans driving their agentic transformation. That is exactly what Globant has been executing since 2025, and it is exactly what the market is now validating. This is our moment, and we are entering it from a position of strength.
As I meet with our customers around the world, their need to deploy AI solutions that add value and transform their business has never been greater and strengthens my conviction in our innovative business model. This is further supported by the convergence of the most influential voices in technology. Sequoia Capital through Julian Bek is calling services the new software, noting that for every $1 spent on software, roughly $6 are spent on services, and that AI lets enterprises buy outcomes instead of tools with autopilots replacing copilots and meaningfully different unit economics.
Satya Nadella is calling 2026 the year agentic systems start to reshape how enterprises consume software with the boundary between software and services gradually narrowing. And capital is following the thesis. This Monday, OpenAI launched a $4 billion deployment company, and 1 week earlier, Anthropic launched a $1.5 billion Enterprise AI venture with a different group of PE firms. The 2 most valuable AI companies in the world are putting capital behind delivery, not just behind models. We are proud to be an OpenAI partner since 2025, and every dollar of capital flowing into this layer expands the market for the model we have already built.
Q1 2026 revenue came in at $607.1 million, above the high end of our guidance. We are reaffirming the midpoint of our full year revenue outlook while raising the lower end of the range, narrowing our guidance with greater confidence in our trajectory. Importantly, Q2 guidance returns to sequential growth with the upper end of our guided range translating into year-over-year growth. Q1 appears to mark the trough of this cycle, and we see Q2 as a meaningful step toward a healthier trajectory. Free cash flow was strong and operating margin held within our guided range.
Our pipeline remains healthy and continues to build with strategic AI-native opportunities we expect to convert through the rest of 2026. On capital allocation, our original share repurchase program announced last September was completed during Q2, and our Board has now authorized a new share repurchase program of up to $125 million over the following 6 quarters, representing close to 7.5% of today's market cap and close to 15% of market cap in aggregate between the 2 plans. The program will be executed at management's discretion, balanced against our investment priorities, including the continued build-out of our AI Pods business.
We are committed to returning capital to shareholders because we believe Globant is undervalued relative to the trajectory we see in our pipeline and in AI Pods. A year ago, we announced the shift toward AI-native technology services on top of 2 decades of engineering and industry expertise. Our core business remains the foundation of the company, and the AI-native layer is its natural evolution. Our AI studios are progressing nicely, layering on nonlinear revenue, incorporating talent, sophisticating our offering and getting closer to what our customers need.
For each industry we serve, we are getting deeper. Our global delivery capabilities are helping our clients run the AI transformation they need with greater leverage, better unit economics and a more strategic seat at the table. Critical differentiators of our enterprise solutions are model independence and token sovereignty. Our clients are never locked to a single AI provider. Our platform routes intelligently across more than 140 models, giving enterprises the freedom to adopt the best available technology as the landscape evolves. And every token consumed stays within the enterprise's own governance. Their data does not train third-party models. Their institutional knowledge remains entirely their own. This is particularly beneficial for many of our innovative clients concerned with their intellectual property in highly competitive environments.
Our answer to the agentic transformation is the combination of 2 things: our AI Pods and our forward-deployed engineers. The AI Pods are AI-native service units, each specialized by task and by industry that deliver outcomes instead of effort. The forward-deployed engineers are the human layer that lands inside our customers, embeds AI Pods into their reality and drives the agentic transformation from the inside.
The annual recurring revenue of our AI Pods has reached $32.8 million as of March, with strong growth versus Q4. AI Pods is a young, fast compounding practice in our portfolio, and the percentage growth rates we are seeing at this stage reflect early base dynamics that will naturally moderate as scale builds. We have already incorporated the AI Pods business model in 40% of our top 20 revenue-generating accounts, up from 30% from last quarter. The AI Pods pipeline stands at $352 million, including a clear path to coverage in 70% of our top 20 clients.
Gross margins on this model continue to run materially above our blended company gross margin. As AI Pods grow as a share of our revenue mix, their structurally higher margin can begin to contribute to our blended margin profile over time. AI Pods and AI-native services are an important evolution of how we deliver value and a meaningful growth lever going forward. Within our digital studios, data and AI, which includes core AI deployments such as NLP, analytics, facial recognition, machine learning and data science is now our second largest studio by revenue right after engineering. Both studios are growing markedly above the company average, with data and AI growing north of 25% year-over-year and engineering in the mid-single digits.
This growth mix reflects the priorities shaping enterprise technology investment today. AI is present in 100% of our pipeline. Every project, without exception, incorporates it either as a core element or as a satellite component. Within that, 26% of opportunities are AI core, a figure that rises to 32% when looking only at deals originated in 2026, reflecting the accelerating shift in how clients are coming to us. We are particularly proud of the evolution of our revenue per Globant.
As of Q1 2026, we are run-rating a level north of $90,000, representing 8% year-over-year growth. This has been supported by the steady expansion of our AI Pods business and the AI tooling we have embedded into our delivery. This is the structural signature of a company moving up the value chain. What we are seeing in the market reinforces every part of this picture. Our big deals with large customers continue to gain momentum and AI transformation programs are now the predominant pattern across our pipeline.
Three large pools of demand are converging on AI-native delivery, technical debt and core modernization estimated at $1.5 trillion to $2 trillion across the world's 2,000 largest public companies; interface and experience debt across customer-facing surfaces; and agentic process transformation, the redesign of business processes and operating models around agents. Globant is positioned across all 3. We are winning the modernization pool as an AI-native partner as the IGT relationship with Apollo demonstrates and private equity is becoming a structural channel for us. The largest prize, however, is agentic process transformation.
AI is now adopted across the vast majority of our projects, and the real gains come not from layering AI on top of unchanged processes, but from reengineering the business around agents and rewiring the organizational chart itself. Across our studios, our 100 squared accounts continue to gain traction and maintain momentum. Our top 50 clients grew over 5% year-over-year in Q1 with our top 10 and our 2 to 5 cohort growing at similar rates, all meaningfully above the company average. AI Pods are now showing up in concrete ways across every studio.
A quick tour. In financial services, our work with Banco Galicia is scaling. They have validated the productivity, speed and quality of our AI Pods, and we are now successfully deploying an operating model to manage the high use case backlog. We are now focused on implementing a new AI Pod dedicated to the definition and construction of data products with an initial use case targeting the reduction of the customer contact rate. We are also applying AI Pods in our work with a leading student loan company in the U.S. to modernize its loan management systems at scale and speed.
In health care, Life Sciences and Private Equity Studio, we are migrating 5 clients to the AI Pods model. At EmployBridge, the first pilot was executed in Q1, and we expect the remaining scope to convert during Q2 into a fully AI Pod engagement. Johnson & Johnson continues to be the largest account in this studio with continued growth. In media, entertainment, sports and hospitality, our 15-year relationship with the Walt Disney Company continues to expand dialogue with several discussions for AI Pods. We are keen to grow with the company by delivering an interconnected experience anchored by Disney+ and across all core businesses.
The LA Clippers, one of our most visible partnerships through our work on the Intuit Dome, is transitioning their full operation to AI Pods. Our partnership with FIFA is now in its fifth year. Diego Tartara will share how we are progressing our support across FIFA's business digital initiatives. At the same time, we have expanded our role as their technology partner for the 2026 and 2027 World Cups, enhancing their digital platforms, delivering a new fan engagement mobile application and bringing our AI-native capabilities to one of the world's most watched sporting events.
The Mexican Football Federation has chosen sports and performance to build the most advanced football intelligence ecosystem, including new Physical AI applications to further improve sports performance. The agentic solution implemented in LaLiga exemplifies the characteristics of a modern sports organization and will serve as a lighthouse for the industry. We now work with all of the big 3 cruise lines and look forward to growing our work in this space based on our expertise in customer experience.
In gaming, we continue to develop our AI project with Riot. Since booking the largest deal in this sector with them last year, we are now integrating our AI Pods model into quality assurance. In retail, we introduced AI Pods into our dialogue with one of the largest retailers in the United States, with whom we have worked for 4 years. The retailer was previously considering a global compatibility center, but exposure to AI Pods shifted the conversation toward an agentic-first solution by unlocking more value and efficiency to build a new mobile app and loyalty program.
In the technology space, we are happy to announce that we are strengthening our strategic partnership and 360-degree relationship with Google, where we are projecting strong growth into new areas. In the energy space, we continue our 3-year relationship with the U.S. Green Building Council, migrating our work on their primary certification, LEED version 5 to AI Pods. Although the change has been recent, we have already seen significant improvements in process efficiency, and we look forward to seeing this growth in the future.
The aviation space has been going through some turbulence by volatility following the sudden rise in fuel prices. This has further reinforced the efficiency gains delivered through our AI Pods model. Two of our largest airline clients will be transitioning from a traditional delivery model to AI Pods as part of a multiyear commercial and digital transformation. This shift will allow them to increase throughput, reduce cycle times and operate with a more flexible cost structure, helping offset fuel-driven pressure while continuing to modernize core systems, improve direct channels and enable more dynamic retailing capabilities.
In our new markets region, although our clients face many challenges due to the currently volatile situation in the Middle East, Globant continues steadfast in being a strong and stable partner, focusing on long-term growth. Our partnership with Qiddiya City has centered on major projects, including Six Flags Qiddiya City and Aquarabia, the largest water park in the Middle East, with Globant building the end-to-end digital backbone for the guest journey. We are also partnering with Saudi Arabia's local organizing committee to reinvent the football experience centered on the fan ID ecosystem, focusing on a unified AI-powered platform connecting identity, venue access, safety and fan engagement at scale.
The Enterprise AI Studio anchors the platform layer that powers AI Pods with multi-cloud integration across Azure, AWS, Oracle and Google Cloud. Our partnerships with the major hyperscalers, AWS, Google, Microsoft and Oracle Cloud Infrastructure all expanded this quarter, and we were named Google Cloud Country Partner of the Year in Argentina for the fourth time. With AWS, this quarter, we surpassed the original KPIs from our strategic cooperation agreement signed last September, aimed at several ambitious indicators, including annual recurring revenue and new solution development. We also continued to deepen our relationship with NVIDIA, which is central to how we deliver AI-native services at the compute and infrastructure layer. Together, these alliances make Globant the AI-native orchestration partner that connects model providers, hyperscalers and the enterprise.
And finally, our AI-powered network, which elevates advertising, marketing strategy and media. GUT kicked off the year with incredible momentum, adding 18 new client logos and delivering groundbreaking work, a surreal celebrity-driven music video, which became a full-blown cultural event for Cheetos, the Stella Artois FIFA World Cup 2026 campaign featuring David Beckham in the U.S., a special project for Bancolombia and Pura Magia, a new campaign in partnership with Disney, which reimagines the meaning of transformation at Walt Disney World. Q1 2026 delivered above the high end of our revenue guidance, advanced AI Pods into a clearly strategic position in our portfolio, and gave us additional evidence that the macro shift toward AI-native services is being underwritten by the most credible investors in the technology space.
In summary, we are reaffirming the midpoint of our full year revenue outlook, which implies quarter-over-quarter improvement throughout the rest of the year and also a strong focus on capital allocation and returns and accelerating the highest-margin product in our portfolio. We are confident in 2026. I want to thank our clients for their trust, our partners for their collaboration and our Globers around the world for the work they do every day.
With that, I will hand it over to Diego, our CTO, who will walk you through the technology and delivery layer. Thank you.
Hello. Globant is no longer preparing for the AI era. We are operating within it. We are systematically reinventing our delivery model so that every solution we deliver is secure, scalable and AI-native from day 1. This is what's driving the $352 million pipeline in AI Pods and the technology layer underneath is what makes this work, and that is where I want to focus today. We have evolved our signature delivery framework built on hundreds of autonomous units to embed AI into every dimension of execution. The 3 pillars of our delivery model have been overhauled to meet this moment.
Our Globers are not just using AI. They are augmenting their technical domains to become multidisciplinary orchestrators. We are also expanding to new roles such as our forward-deployed engineering team. We have redefined project management with AI-powered observability and agentic workflows that drive measurable efficiency gains. AI readiness and accountability are now mandatory across all offerings, evolving our agile DNA into a truly AI-native model. We are also building what we call our agentic economy, an inner source ecosystem of more than 20 validated cross-industry agentic solutions that we package as deployable assets directly into AI Pods engagements, whether it is an IT root cause analysis tool for airlines or a supply chain agent for oil and gas. These assets are now being replicated across media, pharma and tech in weeks rather than months.
We put special focus on the major demand pools that Martin mentioned, AI delivery, modernization and technical debt. Our forward-deployed engineers are prototyping these solutions in 14 to 21 days. This is the practical mechanism that lets Globant participate in what Sequoia and others have called the services as the new software era. We are building compounding IP that generates recurring value and positions us as a long-term strategic partner. AI Pods are how that IP gets monetized. As we approach the 2026 World Cup, our work with FIFA is accelerating. AI agent networks with human supervision will power key FIFA platforms, enabling more consistent fan engagement across competitions, smarter activation of partnerships and faster deployment of new digital experiences.
In Latin American football, Deportivo Toluca, the current Liga MX's champion has launched a new engagement platform developed by Globant and our sports products division, Sportian. The platform offers supporters live in-match services, ticketing, e-commerce, statistics and exclusive content, helping the club personalize the fan experience. In consumer goods, we are working with Grupo Mariposa, one of the region's leading CPG companies to transform their marketing model around the consumer. The initiative integrates data, AI, martech and agile methodologies to enable smarter, faster, more precise decisions.
Marketing evolves into a continuously learning system in which creativity and technology adapt together to consumer behavior. Globant is supporting CMPC, a global leader in sustainable pulp and paper to deploy an AI-powered solution that enhances supply chain traceability and compliance, end-to-end visibility, regulatory adherence and a clear sustainability narrative. Our ecosystem continued to deepen in Q1. We announced a strategic partnership with Adyen for next-generation merchant payment experiences. We obtained the GenAI competency from AWS and achieved expert status for SAP Business Data Cloud specialization.
Our collaboration with Adobe expanded as we became the first customer experience orchestration partner in Lat Am. Our partnership with Autodesk now includes integration with Tandem digital twin technology, unlocking new efficiencies in design and operations. Combined with the partnership recognitions Martin shared earlier, this reinforces our position as the AI-native delivery layer. In Q1, we published 2 new reports through our research arm, one guiding financial institutions on adopting real-time AI-driven operations, and another helping airlines transition to modern retail models. Both are available at reports.globant.com.
Our role in this market is straightforward. We turn AI from a tool into a delivery model, and we package the IP we generate into assets that our clients can deploy. The technology layer behind AI Pods is now compounding, and that is what gives us conviction in the trajectory Martin described today.
With that in mind, I will now turn it over to Juan. Thank you very much.
Hello, and good afternoon, everyone. I am pleased to discuss our results for the first quarter of 2026. We have begun the year with a focus on stability and execution. We are operating in a discerning client environment, and we are seeing buyers concentrating on high-impact agentic AI projects and digital transformation, which is exactly where we are positioned. We are executing on the financial front, protecting the bottom line, improving working capital, increasing CapEx efficiency and repurchasing our shares.
In the first quarter, our revenue stood at $607.1 million, representing a 0.7% decrease on a reported basis, coming in above the high end of our guidance and reflecting a 400 basis point improvement in year-over-year trajectory compared to last quarter. Q1 revenues included 200 basis points of FX tailwind. The improvement is most visible in our top accounts. Our top 50 clients grew 5.2% year-over-year. Our top 10 grew 4% and our 2 to 5 cohort grew 8.2%, all materially above the company average. Many of our top 20 clients returned to positive year-over-year growth this quarter. This is aligned with our 100 Squared strategy.
Our revenue per employee also increased again this quarter, driven by our pivot into platform and AI-led delivery, which allows us to maintain our revenues with a slightly lower headcount. Our adjusted gross profit margin for the quarter was 37%. Gross margins continue to be impacted by the relative strength of Lat Am currencies, primarily the Mexican peso, the Colombian peso and the Brazilian real compared to the prior year, alongside statutory cost increases in our delivery centers. Over time, as AI Pods grow as a share of our revenue mix, their structurally higher margin profile can begin to contribute to our blended company margins. This is the longer-term margin opportunity we are building toward.
Our adjusted operating margin came in at 14.1% for the quarter, with SG&A at 18.5% of revenues. The effective tax rate for the quarter stood at 23.5% within our guided range. Our adjusted net income for the quarter was $65.2 million, representing an adjusted net income margin of 10.7%. Q1 adjusted diluted EPS came in at $1.50, above the midpoint of our guidance. This number absorbed meaningful FX headwinds, primarily from the Mexican peso, the Colombian peso and the Brazilian real. On an FX-neutral basis, adjusted EPS would have been higher. The underlying operating performance was consistent with our internal plan. Our balance sheet remains strong, ending the quarter with $200.5 million in cash and short-term investments or $161.2 million in net debt.
During the first quarter, we invested $50 million to repurchase shares as per the plan announced in October 2025. Our original share repurchase program was completed during Q2. In Q1 2026, we generated $36.1 million of free cash flow, achieving a free cash flow to adjusted net income ratio exceeding 55% compared to negative $5.7 million of free cash flow in Q1 2025. This is the first time Globant has generated free cash flow in the first quarter since 2019. We expect to continue generating strong organic free cash flow for the full year 2026. We will continue to allocate capital with discipline across 2 priorities: returning capital to shareholders through the newly authorized repurchase program and investing in high-return growth initiatives, principally the continued build-out of our AI Pods business.
Now let me move to our outlook for Q2 and for the remainder of the year. For the second quarter of 2026, based on current visibility, we expect revenue to be between $610 million and $616 million. The Q2 year-over-year guidance implies at the midpoint, a positive FX tailwind of 100 basis points. We expect a non-IFRS adjusted operating margin between 14% and 15% and the IFRS effective income tax rate is expected to be in the 22% to 24% range. Non-IFRS adjusted diluted EPS is expected to be between $1.45 and $1.55 per share, assuming an average of 43.6 million diluted shares outstanding during the second quarter. With respect to the full year, at the midpoint, we are maintaining our 2026 revenue guidance unchanged. We expect revenues in the range of $2.462 billion to $2.508 billion, implying 0.3% to 2.2% year-over-year growth, with approximately 100 basis points of FX tailwind. Both Q2 and subsequent quarters imply sequential growth and a healthy exit rate more aligned with industry growth averages.
In terms of profitability, we continue to expect our adjusted operating margin for the full year to be between 14% and 15%. Our margins continue to be pressured by the strength of Lat Am currencies relative to the dollar. The IFRS effective income tax rate is expected to be in the 21% to 23% range. For the full year, we are also reiterating an adjusted diluted EPS range of $6.10 to $6.50, assuming an average of 44.1 million diluted shares outstanding for the full year.
To conclude, Q1 was a quarter of steady execution. We are seeing improvements across our top clients. We are executing on the things that we can control, and our balance sheet remains a source of strength. Our focus on embedding AI into the core of our value proposition is clearly resonating with our most strategic partners. Thank you for your continued support.
[Operator Instructions] So with that in mind, we will take the first question from the line of Bryan Bergin from TD Cowen.
2. Question Answer
Maybe my first one, just as it relates to demand conversion, can you just talk about what you've been seeing in the broader conversation? So it's good to hear the traction on the AI Pods. But when you just think about the broader conversation, have you seen anything shifting in more recent weeks, April and May? How is that compared to the first quarter as it relates to pipeline conversion?
Yes. The pipeline remains -- sorry. The pipeline remains in a very healthy state. Conversion is quite good. We're seeing large deals that we have been closing during last year and also closing during this first quarter that will gain traction moving forward. So it's configuring like a space in which we'll have like several big deals starting to yield some results moving forward, and we are very happy for that.
Of course, there are some concerns around what's happening in the Middle East. However, we see the business healthy there. We have some concerns around airlines and the amount of the price of the fuel that is kind of changing the landscape for some trips. But in general, we see a quite positive environment in terms of bookings, long-term deals, which are extremely important that are coming back and gaining traction.
And one remarkable thing that I would like to mention is that the growth on the main accounts is way above what we are seeing in the full company, right? So this is kind of the result of the focus we are having on the 100 square accounts and the focus that we are getting on those large customers that are needing more than ever. When we talk about AI Pods, we're talking about a way to deliver the traditional services. We're not talking about a specific offer, but we're talking about the broader conversation, too, and a new way of delivering that broader conversation in a way which is AI-native. So I cannot split the conversation from the AI Pods from the broader conversation. But yes, I can say that in general terms, conversations are going in the right direction.
Okay. Okay. That's clear. And then maybe on the margin, Juan, can you quantify just how much FX pressure there is within the gross margin in the first quarter and in your outlook for this year? And in gross margin assumption for the year, are you including any tailwind from these -- from the AI Pods structures?
Sure. So in the first quarter, compared to the last quarter, we see about 1 percentage point of FX headwind coming from mainly Colombia, Brazil, a little bit in Mexico. In terms of -- for the rest of the year, so far, the assumption is the same. I mean we cannot predict what's going to happen in terms of FX, but we will definitely work to be as efficient as possible to increase utilization levels as different ways to offset part of that. And we do have very little positive impact being assumed toward the last part of the year.
As you know, last quarter, we mentioned a run rate -- an expected run rate of $60 million to $100 million of AI Pods, and that's going to be towards the end of the year. So even though it's growing very fast, it is still a small part of our business. But what is more interesting is that this continues to scale the way it is scaling? It's a good place to be looking into the future, right? Because this model is proving to be with better margins overall relative to the rest of our business or to the rest of the delivery models.
The next question comes from the line of Maggie Nolan from William Blair.
Maybe to follow up on what Bryan was just talking about. The AI Pod margin is obviously quite strong. Do you expect that to be sustainable into the future? Or what are your expectations for competitive pricing pressure there?
Yes. I mean as always -- I mean there is competition. But at the same time, we see that as we scale projects with AI Pods, we improve significantly our agents. We improve how we use the different models and the tokens. And also they get more efficient because the agents that we build, as they learn, as they evolve in the project, they get more efficient as well. So I think that, that's going to take us or that's going to help us offset whatever pressure might come from other places. So the expectation for us is that the AI Pods delivery model will overall deliver higher margins than the other more traditional...
We are in the trend of growing revenue per head for many, many years already, right? So this is constantly reflecting the way we understand how to scale our business, always looking for margin or looking for new practices and innovation, and customers are reacting quite well to that as the numbers demonstrate.
Martin, maybe to build on that revenue per head comment, I would imagine that the forward-deployed engineers are contributing to that growth as well. And maybe you could just comment on how those capabilities differ from your historical workforce and what additional changes do you need to make to the workforce to continue to capture market share?
Yes. I will answer the first part. The second one will be on Diego. The forward-deployed engineers is something that we have been doing for many, many years. We didn't call it that way. But our engineers working at our customers' premises and understanding the processes and trying to propose like new ways of doing things. And now they became like agents of transformation, but instead of using just one platform, they can use pretty much any platform. And so they are being very welcome within our customers. And this is something we have been doing forever.
And now I think the next generation of understanding or knowledge has to do with changing full processes. I mean processes that before were impossible to change. Now it's possible to automate or at least thinking in a totally different manner. And that kind of mindset is the mindset that we are embedding and putting into our teams in front of our customers or forward-deployed engineers in front of our customers. I don't know, Diego, if you want to complete.
No, I think Martin captured pretty well the whole idea. So Maggie, just to give you an idea and similarity, this is the actual version of what an enterprise architect used to be. The thing is they're called deploy because now there's a platform involved that you need to deploy and then implement. And implementation is exactly what Martin said, which is having knowledge on how to map the company's data structure, architecture, different components, connect that and build and create the platform for building the solutions on top of that. So it's that typically accounts for the top-notch engineers, the most senior-tier engineers. And like you said, they tend to contribute to that revenue per head uplift.
Next up is Tien-Tsin Huang from JPMorgan.
Martin, I like your comments on the -- in the prepared remarks about the rewiring of the industry and things like that. So I'm just curious, just to focus on that with these LLMs investing in services, how do you see the competitive landscape changing? I know we've seen this a little bit before in software and enterprise software. Do you see it differently here? It is a validation of services, of course, but not sure exactly what their long-term intent without domain knowledge can be like what Globant has. So how do you see the competitive dynamics evolving here?
That's a great question, Tien-Tsin. Great to see you back. So first, I believe that the massive change that is happening and the things that must be done moving forward are so large, but so large that there's no way that all those things can be captured by just 1 or 2 companies, which, by the way, wouldn't be independent. So I think the value of being an independent company, the value of being able to create and facilitate -- can you hear me?
Yes.
Okay. Sorry -- so the value of creating and saving the tokens that the customers are producing, the value of advising your customer and reengineering the processes without any bias and being able to use the best possible technology is still there. So I know -- I would like to say that I've been in this business for many, many years, and we have seen many times in which companies are moving back to services from product to services.
And I believe this is a huge stamp of approval that we have been talking about that for the last 2 years. I mean the big prize is deployed. It's not just the model. And we are playing the game of deploying it. And our relationships with our customers and trust and confidence and level of innovation is absolutely there. So I see this as a very exciting news. So I don't know, Diego, if you want to...
I want to make a little comment. We are actually in conversations with our partners. The same companies that are putting together their services are in conversations with that. And this is actually the model that the industry has been having for 20 years. It's what Amazon does, it's what Google does. They all have services capabilities, Microsoft as well. And that's the excuse to capture business and route it to the partner network. So a ton of the work that we do for AWS, as an example, comes from AWS themselves. So this is actually a very -- and that's why their team is actually so small in scale. So the idea is the major lift of this type of work should be done through their partner networks, but they need to be able to capture. If they don't provide services, they are not a go-to person for capturing that.
That's a full demonstration of what we do, 100%.
Yes. No, I'm glad you guys answered it that way. It feels like a validation, and I think the market, hopefully, will appreciate that. Maybe just my quick follow-up, just to ask a model question for you, Juan. Just thinking about -- I think you talked about it earlier, Bryan's question, but just thinking about Q1 being the trough, 2Q seeing a little bit of sequential growth. Should we continue to assume it builds from there based on the backlog of work and what you expect in terms of closed sales? I mean should we walk into faster accelerating growth and then we exit the fourth quarter a little bit faster, assuming there are no other surprises from the macro?
Yes, definitely. When we look at the fourth quarter last year, we did -- we closed at minus 4.7%. We look at this quarter, it was minus 0.7%. The next quarter -- and between Q1 and Q4, there was some sequential decrease. Now when we look at Q1 to Q2, we're going to see that there is sequential growth. We might also -- depending on where we land within the range, there's a chance that we end up with some year-over-year growth. And when we look at the second part of the year, the combination of more working days that are still relevant, plus what Martin explained at the very beginning, some large contracts that have already been signed, they will start to generate incremental revenues.
I think that's what should help us to have sequential growth both in Q3 and then in Q4 and probably end the year in a much better way when we look at the year-over-year growth. And then on top of that, we will see, hopefully, the acceleration of our AI Pods that should be very -- I mean should be -- it is important because it's going to start helping us not just on the growth, but also on the margin going forward.
The next question comes from the line of Bryan Keane from Citi.
Can you just talk a little bit about those larger clients? Your top clients are growing faster with you guys. Maybe is that just a sales focus and a little bit about maybe what those clients are doing in particular that could be the start of something bigger as we go forward this year and into next?
Yes. Thank you, Bryan. I'll take that one. So we are seeing some very strong growth on our top 10 clients, around 4% and quarter-over-quarter. And that is a result of the 100 square strategy where we've been investing so much focus and effort. When you take a look every sample that you take from our top 20 clients, you'll see that the growth is really much higher than the rest of the lineup of clients.
And the kind of work that we are doing largely focuses on AI-infused projects. We are advancing conversations around migrating existing operations or starting new development with AI Pods in the vast majority on our top customers. So a lot of focus on using AI to gain efficiency to develop faster, better to get to market in better shape to deliver more features and to test these products with consumers in real-life production in shorter iterations.
One very good example of that is Disney, where we're also seeing some very nice recovery this year compared to 2025. And where the focus of the new CEO, Josh D'Amaro, is really interconnecting the Disney guests, the Disney customer experience using Disney+ at the center. And by having Josh coming from parks and experiences, he knows very well our work with Disney for so many years, and we are very well positioned to capitalize on his strategy moving forward. And at the same time, obviously, we are also having with both Disney parks and Disney media, a ton of conversations around migrating their operation to AI Pods as well.
I want to add something to that because I think it's important. You talked about large customers. And with every single large customer, operational efficiencies and getting the most out of money is still the conversation. It's there. And those large accounts, those top accounts, typically, they either belong to a heavily regulated market like airlines, banks. They have very high standards of security. And when you see that, we have deployed AI Pods on 40% of the top 10, correct me. 40% and more are on the way, which pretty much not only validates AI Pods, the concept with top clients, but also speak, most of those companies are pretty advanced when it comes to AI. It's not like they haven't tested, they haven't done it. And still, they found a lot of value there. So I just wanted to add that because I think it connects with what they needed and what Fernando mentioned before.
No, that's really helpful. And then just a quick follow-up. Middle East exposure in general, how much do you guys have? And what's the outlook for Middle East kind of going forward? Will it -- I mean have you built in some cushion for potential disruption there?
Yes, I'll take that one. So when we look at new markets, that accounts for about 6% of revenues. Middle East is about 2/3 of that. In the numbers that we provided, the midpoint basically is assuming that things will continue more or less the way they are. We are seeing deals getting closed. We are seeing some deals actually starting, hopefully very, very soon.
The strong pipeline as well.
The pipeline is very solid. So the way we build the guidance for the year, basically the lower end would imply a significant deterioration of that business. That's the main assumption on the low end is a deterioration from today that so far, we are not seeing it in our numbers.
The next question comes from the line of Arvind Ramnani from Truist Securities.
Good set of results. I wanted to follow up on the question Tien-Tsin asked earlier. Certainly kind of validation sort of these Anthropic and OpenAI making these investments, it validates the services model in terms of like last-mile delivery. I think that's quite clear. Do you all kind of view them as a little bit of competition because they're going to be out there grabbing some resources, competing with your clients? And how do you view the competitive environment? And just on that as well, if you can also comment on sort of the relationship you have with Palantir.
Arvind, thanks for your question. This is an extremely large market. I mean as I was saying before, every day, there's a new company that is trying to compete there, and these guys has very good distribution. But they have some, I would say, some things that are structural. For example, any of those 2 companies that are being formed right now cannot offer like model independence or cannot offer now like the way of -- I would provide you with a piece of advice, which is absolutely the best for you, right? And that's something that is difficult to cope with. But of course, we see them as a competitor. We see them as also a partner because we do things and they will do things through us.
We have built in these years, in these 23 years, exactly what they want to build right now. This is a massive support to our long-term business. And the other thing is this is not a business in which one winner takes all. There are other business in which one winner takes all. In this business, there's a -- it is a business in which the relationships with the customers count the whole relation -- corporate relationships and MSAs you have and people that knows people and things like that counts a lot. And I would say that this is a scenario in which we have a lot of assets and a lot of things that we developed with the years to cope with that.
So again, this is a massive market. I said $2 trillion, only for technology. If you expand that into BPO, into core process, all the processes that you have outside there, it is much larger than that. So I don't know. This is something that is too large. The change is that much. We are innovating. We are bringing the latest way of thinking to our customers. The customers are loving it. I feel extremely confident. I feel extremely confident that for us, it's only a great signal of what we're building, as I said on my opening remarks.
Yes. Yes. Martin, I would agree with that sort of my own research also suggests that enterprises are looking for multi-model approaches because if you just kind of go with a single model, whether it's Anthropic or OpenAI model, you kind of are locked into that model, right? But -- and then you're kind of stuck with their pricing and kind of development. But if you have this multimodel orchestration layer on top, then you can -- and not just these 2, right, you can even use some Chinese models. So what are you saying makes a ton of sense.
Not only that, Arvind, but also hybrid models where you...
You can switch.
You can actually use your own locally run chip models for simple things. So yes, that is totally correct.
Right, right. And if I can just also maybe reask the question on Palantir, right? Because, I mean are you all seeing Palantir on certain deals? Do you look at them as a partner? Or do you compete with them? Kind of what's your approach on Palantir?
No. We see them as a partner. I mean we like them. They're a great company. They -- I think that in certain places, in certain specific situations, we cooperate. So again, we are a company that needs to solve the problems of our customers in the best possible way. And that commitment that we have and that we will continue having is independent on any of the products that we use in the back.
And sometimes we have things that can do a good portion of what our customers need, we use them. Some other times, we need to go with a partner and we go with a partner. But what is not compromised in any of our decisions is that what we are proposing to the customer is the best for them. So I see Palantir as a company that we can cooperate, that we can expand our relationship, and we respect them a lot. They have a great product. And we believe that in certain places, we will cooperate with them.
Perfect. And then just kind of a quick follow-up, right? I mean certainly, a good set of results. When I think of like guidance, which is reaffirmed -- was that reaffirm mostly because you're being a little bit conservative? Like why not raise guidance in line with the beat and the momentum and all of that?
Arvind, there is -- as you know, we have part of our business in the Middle East. The situation there, as you know, changes all the time. And we need -- we wanted to be in a safe place and not take unnecessary risk at this point in time. There is nothing to gain from taking too much risk on the guidance.
The next question comes from the line of James Friedman from Susquehanna.
I'll just ask Slide 2 upfront. So Martin, I'd be interested in your perspective about Globant GUT. It seems like it's kind of like the higher end of strategy consulting. And I'm wondering how you can use Globant GUT to generate incremental revenue downstream. And then, Juan, if I could just ask, last year, macro was under pressure in Lat Am. If you could just give us the macro for -- the quick notes on macro, macro for dummies in Latin America, that would be great.
I would take the first. I will ask Diego to complement. But GUT for us is a very good way of entering customers, marketing and technology and to the AI gets connected deeper every day. And the kind of caliber of ideas that these guys are having is really impressive. When I see the reviews that we do every month with the teams, and I see when the guys from GUT come, it's very rewarding to see the caliber of campaigns, the caliber of ideas, the caliber of customers that they are getting. And this is for us, like a door open for then come with all the rest of innovations we have on the technology side and keep on selling. I see this as a magnificent vehicle to expand that relationship that every day, marketing, technology, operations will be more integrated into the same thing. And we can, as a company, tackle those 3 things with our offering.
When we look at Latin America, we are seeing a more stable scenario. Argentina is the country that is driving most of the growth in the region right now, followed by Brazil. But in general, I think it's a more stable scenario relative to other years.
The next question comes from the line of Guggenheim from Jonathan Lee.
I appreciate the commentary earlier about the positive bookings environment. Is there any way to quantify what bookings were in the quarter, how that momentum may have trended from January through March and what you saw in April into May?
In the second quarter, no?
No. I mean -- so basically, when you look at the first quarter and April and the couple of weeks from May, situation is similar. We are not seeing big changes there. Overall, we had a very strong Q4. As you remember, it was a record quarter. That is helping us a little bit on what happened in Q1, where we were able to exceed a little bit our initial guidance. And it's also helping us to reaffirm the full year. The level of bookings that we've seen in Q1 and in whatever has passed of Q2 is also allowing us to maintain the guidance even in the situation that we know that the new market region is under a little bit of stress. But so far, no big changes, and that's enough for the guidance that we have today.
Got it. Appreciate that color. And what in your customer conversations gives you confidence around that back half ramp, particularly around sequential growth in the fourth quarter? And how much go-get is potentially needed there?
So I mean, as we were discussing before, part of the -- or the second part of the year has 2 main components. One, which is a higher number of days in the second half of the year. And the second one is there is basically 4 large customers with whom we have already signed contracts and those contracts should be able to help us because they are scaling as we speak, right? One of them is a professional services company that has been one of the drivers of the lack of growth in that sector that is coming back. There is a big tech company that we recently became a preferred vendor that's going to help us also on the second part of the year. So -- and then we have already spoken about a gaming company in the last quarter and a PE-backed company as well. So those 4 contracts that are scaling as we speak, combined with the account days of the second half are the drivers of the second half of the year.
The next question comes from the line of Sean Kennedy from Mizuho.
Congrats on resilient results, really great to see. So I was wondering if you could discuss a bit more about the early customer feedback from AI Pods. And specifically, what are they saying are the greatest benefits from the program? And if there are specific industries that are seeing more traction than others currently?
So like I mentioned -- sorry, like I mentioned before, one of the good things is that the data comes from our top accounts, which are the main drivers of the growth of AI Pods. So 2 different things. The first one is the benefits of the models, both in terms of efficiency but also in terms of the quality of the outcome. So we've not just proven that we can produce faster, but actually that the quality and the full product and release is top notch, right, according to the standards.
So feedback has been very positive. In fact, a lot of the growth, we typically -- the way we do AI Pods is we have an experimentation phase -- we have -- and then we have a scaling phase. And so typically, you don't scale if you haven't passed a testing, right, a POC, only one part operating under this model and then they do the switch. So it is important to understand that when we are reporting revenue, it's actually -- it has been tested. A couple of things that I think are super important and make a big difference.
First of all, the process is baked into the tool. And this is actually great. This is the first time we can do that. Before that, the process was actually a manual, if you wish, and you train people to follow that process. Now it's being baked into the tool. So it's a lot more resilient to people and it holds your knowledge. The second one, token consumption. This is something that we haven't mentioned, but it's extremely -- it's becoming extremely important. A lot of the companies that have implemented tools such as cloud code, Copilot, et cetera, they're working with them, and they're not getting the most out of that.
But on the other hand, they have increasing spend on the token consumptions that start to be actually part of their P&L, an important part of the P&L. And part of that consumption comes from misuse of the tool. which means incorrect prompting and data preparation, incorrect description of the process you must follow, quality gates, et cetera, et cetera. So a task well executed typically takes 1/3, 1/4 or even less tokens than the same task with reprompting corrections, et cetera, et cetera. So that's another interesting and important data point because you can actually see the tool in action and you pay for what it actually produces output.
So feedback so far has been great on every single implementation. The efficiencies have been shown, and that's why it is a keeper. We have had not a single client actually going back from AI Pods, which I think it's a solid statement of the benefits it has.
Yes. And also 2 more things. The fact that you can have like an enterprise-ready process baked in into that thing. I mean there are plenty of people now by coding solutions inside corporations. But then they're local in their machines, they're not scalable, not secure, not ready for the enterprise. And with our AI Pods, we're being able to grab those things and those ideas and take it to the next level in terms of enterprise readiness. So that's extremely important. How the process is documented all along the way, and we have an enterprise-ready kind of solution, right?
And then the rest of the things is just benefits, right? You consume less tokens, you have a corporate process inside there. You can repeat the process and improve the process every time with your customer, you can customize the process with the data of your customer. So it's much better than the traditional services. This is what Diego was describing, is a real AI-native service as opposed to the traditional service. And this kind of scale on supervision is more similar to an assembly line rather than just a massive matrix of projects that you need to fulfill. So the current business is not going anywhere. And as you see and demonstrated, it will keep on being and keep on existing.
But this AI Pods is on a different level of execution, totally AI-native, totally AI-driven plus human supervision and it's being charged per consumption. You don't need to interview people. You don't need to do anything. You just submerge it there and everything gets executed with enterprise class and human supervision to ensure that you are doing the right thing.
So it's really a different value proposition, and our customers are really welcome it because it's a totally different way of being transparent to, right? A full transparency in each asset that we create, each artifact gets connected to a number of tokens, get connected to a number of consumption that you have there. So it's really paying by the output rather than paying hours. So it's really a new model.
The next question comes from the line of Gustavo Farias from UBS.
My question is on capital allocation. So buybacks, of course, suggest the confidence that you have in the stock. But on the other hand, it could limit potentially strategic M&A. So if you could please share how do you see the need for M&A in the short to medium term to remain competitive?
We are always looking for things and for opportunities. That won't go away. And the other thing on the buyback, right, was -- it's at management's disposal. And as we see an opportunity to buy the company that we know that is Globant, and that we trust, and we think it's undervalued. So -- but if we find a better opportunity or better use to invest, of course, on our AI Pods or a company that we like and we want to acquire, so on and so forth. I mean we are not limited in doing so. So a constant assessment on which are the priorities for our capital is being carried out, but we want to be extremely disciplined in how we increase our return on equity or return on invested capital moving forward. I don't know, Juan, if you want to.
No, definitely. We have the firepower to do M&A in case we want. But of course, I mean there is one stock that today is trading at a very low multiple, and it's a company that we know very, very well, and that's our company. So between that and buying something else, sometimes it really needs to be very, very strategic. It really has to meet a very clear need for us at this point to go and do that because at the current valuation, there is a mismatch between Globant and some companies in private sector.
Very clear, guys. If I may follow up. I think last quarter, you guys seemed a little bit conservative on tackling fixed price contracts, mainly on margin concerns. And we see fixed price as a percentage of revenues roughly stable versus last quarter. What's your current view on that?
Yes. The market today pushes for fixed price. It's something that is a reality across the industry. Interestingly, now we have tools that allow us to deliver in a more efficient way. So we can use our AI Pods to deliver on many of those contracts. So we are more confident on the fixed price than what maybe we would have been a year ago or 2 years ago. So it's something that we need to look at because the market is pushing for fixed price. And the tools that we have today in front of us allow us to do better than -- or to do well in fixed price contracts as well.
The last question that we have time for today, unfortunately, comes from the line of Surinder Thind from Jefferies.
I guess, Martin, you've been very clear about the ambitions for the AI Pods model. Is 2026 effectively the year that you're gathering, I guess, data points to kind of really push forward with the strategy at this point? How do we think about where the longer-term ambition is? How much of your revenue can you get there? And then what is the current friction in terms of why clients aren't adopting it faster given all of the data points that Diego kind of highlighted?
I didn't get the last part of your question, Surinder.
The last part is just that Diego highlighted a lot of really positive data points about the AI Pods model. And so how do we think about that in terms of why clients wouldn't be adopting it faster? Is there a natural balance within your business ultimately in the long run between the AI Pods model, maybe fixed price contracts? Or how do you think about where all this is heading and where you would like it to ideally be?
Sure. AI Pods is kind of a way of delivering, which is absolutely different from before. And it's an AI-native service in which we deliver in a totally different manner from before. Now our forward-deployed engineers are there just trying to do the agentic transformation, the AI agentic transformation of our customers, helping them with processes with reinventing and rethinking marketing processes, human resource processes, account receivables, account payables, finance processes.
So there's a constant connection between how you create a future project with our deployed engineers and how ambitious is that project and how you deliver that. Both things must be extremely innovative. And this is what we're bringing to the market. First, the idea, how to make an agentic transformation of your business. And then when that is ready, we don't deliver in the traditional manner, but we deliver with AI-native services.
So long term, my ambition is that although our current business as we deliver today will keep on existing because many of our customers is the preferred way of engagement, this new way will start to slowly, number one, gaining market share, right, from other competitors; and number two, transforming the way we deliver our current services for our customers. So the ambitions are large. I prefer to refrain from giving you any number, but I have in mind like as a way of transforming our current business into something totally different.
And this gives you a place to think about many other things, like how to create those tokens that we will use in the AI models, how to distribute them, how to route them, how to -- I mean it's a pretty different game when you start thinking about charging per output or per consumption in the case of software development life cycle. But then when you are talking about an AI-powered operations, you may charge per streaming monitoring hour or ticket sold.
I mean there are hundreds of different delivery units that we may use on our AI Pods that our customers will be extremely tangible and not in the same way it used to be. So this technology is giving us an opportunity to change the whole business, and this is the aspiration we have. Now how fast we can do it will depend on our customers on how good our AI Pods work, so on and so forth, that is what Diego was describing. I don't know, Juan or...
Listen, we are seeing like many, many very interesting conversations progressing with all of our top customers, right, most of our top customers. And our top customers are really marquee customers, and they are leaders in the space and where they are. And without exception, they are either in the piloting phase or scaling phase and those who are about to start are assessing the technology. But the interest we are seeing in the top customers is very strong. There's no structural friction with the clients whatsoever in the model. I think it's just a matter of our clients understanding the technology and progressing the processes and so on and so forth.
That's helpful. And then just as a quick follow-up on the commentary about the forward-deployed engineer. How much of that based on your earlier comments, is what I would call just a rebranding of the way that work used to be done in certain instances? Or how much of that is potentially structurally different that you guys might have to do, meaning does a forward-deployed engineer have to be on-site to a larger extent? Does it change some of the economics? How does that impact you guys given that you guys have optimized for mostly delivery offshore?
I think it's actually -- it's an interesting question. So I'll tackle that in 2 different stages. First, the formation. I mean, what does it mean and what's the delta between a very good engineer and a forward-deployed engineer. First of all, is the platform and knowledge of the platform. Any forward-deployed engineer deploys a platform and has to have profound knowledge of that platform. The second one has to do with the work that most of enterprise architects used to do, and that's the keeper, which is understanding the architecture components, data, security, et cetera, of the target client and what's the best integration strategy.
The third one is a little bit of building on top of that with regards to building the solution. So that's the enablement of the forward-deployed engineer, then it comes to solutioning. And the deployment is actually functional to that solution. So it's also important that, that person understand the problem is trying to address. So there's a conversion and reskilling that while conserving a lot of the learnings of that type of engineer, you need to build something on top of that. So we needed a retraining of most of our top engineers to make them forward-deployed engineers.
And do they have to do more work on-site or -- because on-site are very different than offshore.
Yes, second part of the question. Yes, we can actually execute a lot, typically what's called the discovery. It's a lot better when it happens on-site because a lot of the things have to do with interviewing people that are related not only with the platforms, but also with the areas and the processes you need to convert. So typically, if you do it on-site, it's a lot better, still can be done offshore, and we have done it.
So with that in mind, that's the last question we have time for, unfortunately. I will now turn it back to Martin Migoya for some closing remarks. Martin, please go ahead.
Thank you, Arturo, and thank you, everyone, for being here today and for your continuous support. Thank you so much. See you in the next quarter.
Thank you.
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Globant SA — Q1 2026 Earnings Call
Globant SA — Q1 2026 Earnings Call
Globant übertraf Q1‑Guidance, bestätigt Jahres‑Mittelwert, setzt auf AI‑Pods als margenträchtigen Wachstumstreiber bei gleichzeitigen FX‑ und geopolitischen Risiken.
📊 Quartal auf einen Blick
- Umsatz: $607,1 Mio. (Q1 2026) – über dem oberen Ende der Guidance; -0,7% YoY berichtigt
- Bruttomarge: Adjusted 37%; belastet durch starke Lokalwährungen in LatAm (Mexiko, Kolumbien, Brasilien)
- Operativmarge: Adjusted 14,1%
- Ergebnis: Adjusted Net Income $65,2 Mio. (10,7% Marge); Adjusted Diluted EPS $1,50
- Cash & FCF: Cash $200,5 Mio.; Free Cash Flow $36,1 Mio.; Net Debt $161,2 Mio.
🎯 Was das Management sagt
- AI‑Pods: Kernstrategie: spezialisierte, AI‑native Service‑Units mit erneutem Fokus auf Outcome‑ statt Stunden‑Verrechnung; ARR AI‑Pods $32,8 Mio. (starkes QoQ‑Wachstum)
- Liefermodell: Kombination aus AI‑Pods und Forward‑Deployed Engineers zur Prozess‑Reengineering und schnellen Produktivsetzung
- Unabhängigkeit: Modell‑Unabhängigkeit und Token‑Souveränität als Differenzierer; enge Hyperscaler‑Partnerschaften und OpenAI‑Kooperation
🔭 Ausblick & Guidance
- Q2‑Guidance: Umsatz $610–616 Mio.; Adjusted Operativmarge 14–15%; Adjusted EPS $1,45–1,55; Q2 soll wieder sequenzielles Wachstum zeigen
- Jahresprognose: Umsatz $2,462–2,508 Mrd. (≈0,3–2,2% YoY); Operativmarge 14–15%; Adjusted EPS $6,10–6,50; Midpoint bestätigt, untere Grenze angehoben und Bandbreite verengt
- Risiken: FX‑Effekte (LatAm‑Währungen) und geopolitische Unsicherheit im Nahen Osten; Management nennt Q1 als zyklischen Tiefpunkt
❓ Fragen der Analysten
- Pipeline & Conversion: Nachfrage bleibt „gesund“, Conversion gut; größere abgeschlossene Deals sollen ab H2 stärker wirken; keine detaillierten Booking‑Zahlen genannt
- AI‑Pods Rentabilität: Management sieht strukturell höhere Margen und Nachhaltigkeit durch effizientere Agenten‑Nutzung; Wettbewerb wird als Partner/Erweiterung des Marktes betrachtet
- Risiken & Kapitalallokation: Middle‑East‑Exposure ~2/3 von „New Markets“ (~6% Umsatz insgesamt) bleibt Unsicherheitsfaktor; Buyback ($125M neues Programm) wird gegen M&A‑Opportunitäten abgewogen
⚡ Bottom Line
- Implikation: Solides Q1‑Beat, bestätigte Jahresprognose und aktiver Buyback signalisieren Management‑Vertrauen; AI‑Pods bieten Aussicht auf wachstumsnahe, margenstarke Umstellung, während FX und regionale Risiken die kurzfristige Performance begrenzen.
Globant SA — Q4 2025 Earnings Call
1. Management Discussion
Good afternoon, and welcome to Globant's Fourth Quarter 2025 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions]. Please note, this event is being recorded and streamed live on YouTube.
By now, you should have received a copy of the earnings release. If you have not, a copy is available on our website, investors.globant.com. We will begin with remarks by our Chief Executive Officer, Martin Migoya, our Chief Technology Officer, Diego Tartara; and our Chief Financial Officer, 6 Juan Urthiague, followed by a Q&A where they will be joined by our Chief Revenue Officer, Fernando Maskin. Before we begin, I would like to remind you that some of the comments on our call today may be deemed forward-looking statements. This includes our business and financial outlook and the answers to some of your questions.
Such statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Please note that we follow IFRS accounting rules in our financial statements. During our call today, we will report non-IFRS or adjusted measures, which is how we track performance internally and the easiest way to compare Globant to our peers in the industry.
You will find a reconciliation of IFRS and non-IFRS measures at the end of the press release we published on our Investor Relations website announcing this quarter's results.
I will now turn the call over to Martin Migoya.
Hello, everyone, and welcome back. Globant has spent 20 years helping the world's leading companies build and transform their technology, developing deep engineering capability, real industry expertise, and long-term client partnerships along the way. That is and will always be our foundation. Over the past year, we have been adding a new layer on top of it. And what I want to share today is how that layer is already changing our trajectory. .
Enterprises are moving from AI experimentation to AI execution. After a period of significant investment with limited returns, our clients are now deciding with greater clarity. They understand AI's potential and they are seeking partners who can deliver real outcomes, not just pilots, but production-grade solutions built with knowledge of their industry, their systems and their business logic. That is exactly what we built with our AI pods, running on top of our industry specialized AI studios, and that is why we believe Globant is the AI native technology solutions company.
The partner enterprises are choosing to close the gap between AI investment and AI impact. We launched our AI pods 9 months ago, and it is already proving real success with our customers. In 2025, we achieved both our highest revenue and strongest free cash flow generation ever while simultaneously restructuring our delivery organization and transforming our delivery model.
In Q4, we produced the highest quarterly bookings of the year, up 32.4% year-over-year. Our pipeline remains robust at $3.4 billion. I want to use this call to walk you through our results, our strategy and the specific metrics that demonstrate why we are convinced about the path ahead. The IT professional services industry faces a structural shift. Technology capital is flowing overwhelmingly toward AI infrastructure, with Gartner projecting IT services to grow just 4.4% in 2026, less than half the rate of overall IT spending. However, the big 4 hyperscalers are approaching $700 billion in combined 2026 CapEx, nearly triple the level of just 2 years ago.
The scale of that investment is extraordinary, but it also created a massive implementation gap. In 2025, MIT Research showed that most enterprise AI pilots did not deliver measurable P&L impact yet and a significant number of companies paused or restructured their AI initiatives during last year. Meanwhile, technical debt across the Forbes Global 2000 stands at $1.5 trillion to $2 trillion according to HFS Research, and Forrester reports U.S. customer experience quality at an all-time low after 4 consecutive years of decline.
What this tells us is not that AI is failing, it is that the industry is entering its execution phase. After an 18-month cycle of experimentation, enterprises now understand what AI can do for their business and are actively seeking the capability to implement it at scale. This shift from exploration to execution is currently driving our record bookings.
We are living through a generational transition. Think about what happened when AWS launched. It did not just offer cheaper servers, it gave birth to an entirely new industry. Cloud-native companies, modern SaaS, the entire start-up ecosystem over the last 15 years, none of that existed before AWS made elastic accessible infrastructure possible. That is the moment we are at now in technology services.
AI-native delivery, intelligent agents supervised by domain experts, operating on a token subscription model is not a better way to do what we already do. It is the foundation of an industry that does not yet fully exist. Globant has been the first to define what AI native technology services look like and 2026 is the year the market begins to validate that bet.
Our core business, deep software engineering, digital transformation and domain expertise built over 2 decades is not going anywhere. Enterprises will continue to need that capability for many years to come and we will continue to grow it. What we are doing now is adding a new and powerful layer on top of that foundation, an AI-native offering that scales with the AI opportunity itself.
For years, a company's digital products were it's moat, building differentiated software required hundreds of top engineers and hundreds of millions of dollars. AI has made it faster and more accessible to build. And that is actually a demand accelerant for the entire industry. When every company can build software more efficiently, differentiation no longer comes from whether you can build. It comes from how much you build, how fast you iterate and how continuously you evolve.
We are entering an era of dramatically more software creation and dramatically faster competitive cycles. Our deep engineering expertise and 2 decades of domain knowledge now supercharged by AI position us perfectly to meet that demand. Against that backdrop, we see 4 clear and growing avenues of demand.
First, agentic workflow orchestration. Enterprises need autonomous AI agents coordinated across complex systems, not point solutions but end-to-end workflows that actually move business processes forward.
Second, core modernization at AI speed. The Global 2000 carries $1.5 trillion to $2 trillion in accumulated technical debt, a massive anchor on innovation. AI native delivery allows us to attack this backlog at a pace previously thought impossible, enabling the enterprise agility our clients need to compete and win.
Third, custom software reclaiming ground from SaaS. For years, SaaS was the default answer for enterprise software needs. AI-native delivery is now expanding the range of what enterprises can build economically, making highly personalized software viable for use cases that were previously only practical with off-the-shelf platforms. This is not about replacing SaaS, it is about enterprises having more options, more control over their data, their workflows and their competitive differentiation. SaaS and custom software are increasingly complementary, and we are uniquely positioned to deliver both.
Fourth, AI governance and corporate sovereignty. As enterprises deploy agents from multiple vendors across departments, data scatters and controller roads, they need a trusted orchestration partner to govern it all and keep every interaction under their control. Our partnerships with NVIDIA, OpenAI, AWS, Salesforce, SAP, Oracle, Microsoft, Google, Adobe and others are central to this strategy. We are the AI-native orchestration layer that makes it work for our clients.
Our AI pods are AI-powered service units specialized by task and industry. AI Pods software creates and evolves technology. AI agent workflows supervised by Globant experts produce working software artifacts on a token subscription model. AI Pods ops automates business processes in production with institutional knowledge compounding with every token consumed. The customer owns everything, no seats, only usage.
Unlike traditional models, our AI pods operate on a subscription-based capacity model. Clients subscribe to a dedicated tier of orchestrated output with a defined token consumption cap. The delivery engine powering both is Globant Enterprise AI, our proprietary platform with 4 interconnected hubs, the enterprise hub connecting securely to all corporate systems. The AI hub routing intelligently across 140-plus LLMs while preserving full data sovereignty, the agent hub where we build and publish industry-specific agents encoding 20 years of domain expertise and the AI pods hub where clients subscribe and scale.
What I want to be explicit about is that this platform did not appear overnight. We have been investing in Globant Enterprise AI for years, building real product, real orchestration infrastructure, real security and compliance architecture. That investment is embedded in our operating expenses and reflected in our current EBIT margin. In other words, the margin profile you see today already carries the cost of building a proprietary AI platform.
12 months ago, AI pod's revenue was 0. In 2025, we have reached an exit rate ARR of $20.6 million, with gross margins between 45% and 60% compared to our blended gross margin of 38%. This is not an experiment. This is a business. For 2026, we are targeting between $60 million and $100 million in AI Pods exit rate ARR. On top of that, we expect that margin profile to improve further as the subscription model scales and the cost per token continues to decline.
This represents a fundamental shift in our structural profitability DNA. As AI Pods scale as a share of revenue, they are expected to expand our overall margin profile. Our AI Pods pipeline reached $283 million in Q4, up 34% over Q3 and now represents 8% of the total pipeline versus just 3% in Q2. Over 60 AI pods operate across clients globally with 24 new subscription offerings closed last quarter alone.
Several of our top 10 clients have completed rigorous security and procurement approvals and are actively running AI pods on the platform today. The pipeline is converting, the revenue is flowing, and we are just getting started. Based on the record bookings we are reporting today, the accelerating AI pod's adoption across our client base and the improving pipeline conversion trends, we have a clear line of sight to returning to positive year-over-year organic revenue growth by mid-2026. This is not a hope. It is supported by the bookings we have already signed and the pipeline that is converting.
Our 100 squared accounts drove 73% of total bookings this quarter, a clear reflection of the market shift toward high-value long-term transformations. Underlying these record bookings is our reorganization around AI studios by industry. The record bookings we are reporting today are a direct reflection of that organizational transformation we did last year. Several of our top clients have already moved past the pilot phase and are scaling AI pods across their entire operations.
Let me share a few examples. We are working with Employee Bridge and Apollo-backed portfolio company, driving AI-led transformation through our AI Pods subscription model. After a successful pilot phase, Employee Bridge decided for AI pods as their core operating layer, accelerating delivery and driving rapid adoption across the business. We are also working with Banco Galicia, one of Latin America's most prominent banks.
After the pilot phase with our AI pods, they performed an assessment to gauge the efficiency of the model among other vendors and similar teams. Our AI pods ranked first in nearly every criterion, leading the institution to move to the decision to move to a scaled phase. With YPF, Argentina's century old state oil company. With our human-supervised AI agents, we created a resource orchestration platform to help YPF better coordinate their complex supply chain reaching over 5,000 providers.
Our solution has already helped them reduce the requirement to contract process cycle by 30% to 40% as well as boost the productivity of their supply buyers by up to 50%. Through the use of AI on Globant's orchestrated platform, we are helping them with inventory optimization, enabling YPF's managers to obtain the best possible products for the task at hand before ordering new inventory.
We have a long-standing relationship with FIFA, helping them enrich their fan engagement channels in the digital age. Through the deployment of AI pods, we were able to move beyond traditional consulting services and achieve a major financial milestone for the organization, reducing costs by 20% without compromising the velocity or quality of our engineering output.
Our initiative with La Liga demonstrates how AI pods rapidly transform an entire ecosystem. In just 3 months, we moved from concept to execution, deploying AI agents across critical functions like budget preparation, contract analysis and audience data. The result is a massive leap in institutional productivity.
By moving from traditional services to AI native solutions, we are enabling La Liga to shift new functionality at a speed previously deemed impossible. We also applied our AI pods model to our long-standing partnership with Santander to power their new digital payment platform Santander Pay. By deploying a specialized product definition AI agent within the pod, we cut the projected time for the apps product definition in half.
This AI native approach drove a 50% increase in the client team's overall productivity. In summary, it clearly demonstrated how we can accelerate the software development life cycle for one of the world's leading financial institutions. The professional services industry is being restructured right now. The companies that own the orchestration, the domain expertise and the talent to supervise AI at scale will define what comes next.
We will be relentless in delivering value for our clients, our partners and our shareholders. We will be disciplined in how we invest. And we are determined to build what we believe is the defining AI native technology services company of the next decade. Globant has spent 20 years building the foundation for this moment. We have the platform. We have the people. We have the offering. And with that, I'll hand it over to Diego Tartara, our CTO. Thank you very much.
Thank you, Martin. Hello, everyone. It's great to be here. Following Martin's perspective for the industry, we keep on firmly executing on our own reinvention and those of our clients, listening to customers, helping them understand their gaps and curating tailored solutions that create real business value. This goes beyond cost savings and efficiencies and into strategic areas such as increasing market share or improving customer satisfaction.
To do this, Globant has overhauled our delivery model to ensure that the quality of our delivery is both technology focused and client-centric. The teams that previously executed under the delivery and operational areas have now been brought under the technology umbrella. This way, our teams operate without siloed priorities and have more cohesion between offering solution quality and delivering results on time.
The result has been tech-powered solutions for our clients that have a stronger operational backing. I'd like to share a few examples with you. We are working with a leading bank in North America that is launching a strategic enterprise-level modernization of its credit and debit card platform, moving from Gen 2 to Gen 3 accounts on AWS.
Globant has been selected as the strategic partner to lead this migration, delivering a next-generation cloud blueprint that elevates performance, accelerates delivery and positions this line of business for continuous innovation at scale. This project showcases our strength in helping financial institutions that are already in the cloud and at the forefront of innovation to continue pioneering the industry. We have also been working with Trafilea, a global e-commerce group that builds and scales direct-to-consumer brands needed to rapidly migrate new client stores to their Trafilea platform.
We built an AI-powered solution that automates the entire process, resulting in a 40x faster migration. This not only saved Trafilea significant time and resources, but also enabled faster onboarding of new customers. In the pharmaceutical industry, we are working with PharmaMar, world leader in the discovery, development and commercialization of marine-derived anticancer drugs to accelerate oncology research with AI.
Through Globant Enterprise AI, together, we created a multi-agent AI system that delivers more than 90% accuracy in complex data retrieval and reduces time to insights up to 15 fold, helping scientists select high-potential drug candidates for clinical development in a fraction of the time previously required. This intelligence system integrates information from internal databases, scientific publications and regulators such as the FDA and EMA, allowing PharmaMar's teams to identify promising treatment combinations and make more informed, faster decisions.
We also partnered with tourist to develop the foundations of the world's first universal agentic protocol for tourism. AWS, Salesforce, Amadeus, Red Sea Global and Riad Air, among others, are also part of the initiative. We presented it at Davos in Switzerland to over 30 global CEOs and it is gaining strong traction as the standard for how AI delivers seamless, personalized traveler experiences at scale.
GUT had a landmark 2025. The agency closed the year with breakthrough campaigns for some of the world's most high-profile brands, including a fully integrated 360-degree campaign renaissance of snacking that took over the Las Vegas Sphere and launched Chitos and Doritos simply naked product line. GUT is a genuine competitive differentiator, and its creative momentum continues to grow.
Strengthening our partnerships with leading AI model developers, enterprise platforms and hyperscalers remains a key priority. Globant continues to present its strategic partnership with OpenAI to top clients in its key markets. Weeks ago, we hosted their first multi-industry event in Spain to discuss opportunities with over 60 current and potential clients in that region. In December, AWS granted us competency certifications in both financial services and media and entertainment, further solidifying the autonomy and quality of solutions of our AI studios.
We also received the SAP Excellence Award 2025 for delivery quality in Latin America, thereby becoming the most certified SAP partner in the region. Our Salesforce ecosystem capabilities also expanded significantly, reaching expert level implementation distinctions across MuleSoft Anypoint, Data Cloud and Agent Force, along with top-tier partnership status across multiple Salesforce clouds.
Our teams will take the stage at the NVIDIA GTC in March to share how La Liga is transforming its business through the most ambitious AI program in global sport using Agentic AI to build connected intelligence across operations, competition management, content, marketing, sporting performance, broadcast and fan engagement. In such a disruptive year, we considered it especially important to share our perspective with the global business community.
In Q4, we published industry reports on retail, games and our annual tech trends outlook. You can download all of them at reports.globant.com. While AI continues to dominate many conversations, the real differentiator in 2026 will be execution. Companies that want to remain relevant must accelerate their transformation journeys. Over the past year, we've evolved globin to be the partner of choice for organizations ready to act and set the pace for the next decade. Thank you very much.
Hello, and good afternoon, everyone. I am pleased to discuss our fourth quarter results. We are encouraged by the stabilization of our top line performance and a shift toward more optimistic client sentiment, which represents a meaningful improvement over the conversations we were having 9 months ago.
We closed the year with a solid quarter in terms of operational discipline with revenues, operating margin and free cash flow metrics above our initial estimates. In the fourth quarter, our revenue stood at $612.5 million, coming in above our guidance of $605 million. This represents a 4.7% year-over-year decline, including a positive FX tailwind of 180 basis points.
Now let's turn to profitability. Our adjusted gross profit margin for the quarter was 37.6%. Gross margins were slightly impacted by the USD weakness relative to LatAm currencies and, to a lesser extent, by statutory cost increases in two of our main delivery centers, Colombia and India. However, our adjusted operating margin remained at 15.5% for the quarter, flat sequentially.
We successfully optimized our delivery pyramid and tightly managed our SG&A, allowing us to protect the bottom line while we work on accelerating our growth. The effective tax rate for the quarter stood at 23.5%, and our adjusted net income for the quarter was $68.9 million, representing an adjusted net income margin of 11.3%. Adjusted diluted EPS was $1.54, consistent with our profitability targets.
I am particularly proud of our cash generation mechanics this quarter. During the fourth quarter, we generated $152.8 million of free cash flow, marking the highest quarterly figure in our company's history and achieving a free cash flow to adjusted net income ratio of 221.6% for the fourth quarter or 355.3% on an IFRS basis.
On a full year basis, free cash flow reached a record $211.7 million, translating to 76.6% of adjusted net income and 203.6% on an IFRS basis. During the fourth quarter, we invested $50 million to repurchase shares as per the plan announced in October 2025. We plan to continue executing on the share repurchase program. A significant improvement in our days sales outstanding, combined with working capital and CapEx efficiencies, helped drive an improvement in our liquidity.
We ended the year with $250.3 million in cash and short-term investments, an increase of nearly $83.3 million sequentially. With a modest total net debt position of $116.4 million, our balance sheet remains strong, providing us with the flexibility to continue our disciplined capital allocation strategy, including our share repurchase program.
Now let's move to our outlook. Let's start with our 2026 full year guidance. Based on current market conditions, we are providing a revenue range of $2.460 billion to $2.510 billion, implying 0.2% to 2.2% year-over-year revenue growth with approximately 100 basis points of FX tailwind. We have set the lower end of our range as a prudent baseline. The upper end reflects the conversion trends we are already seeing in our pipeline and the accelerating adoption of AI pods across our client base.
In terms of profitability, we are expecting an adjusted operating margin to be between 14% and 15%. This range includes the impacts of USD weakness and statutory cost increases in Colombia and India. We view the lower end as a stress test scenario as it assumes a further appreciation of local currencies beyond today's spot rates.
The upper end contemplates a more positive currency environment and the benefits of our ongoing efforts in SG&A dilution and increased utilization. We continue to prioritize our operational discipline to offset these headwinds and drive toward the higher end of our margin target. The 2026 IFRS effective income tax rate is expected to be in the 21% to 23% range.
Finally, we are guiding an adjusted diluted EPS of $6.10 to $6.50, assuming an average of 44.2 million diluted shares. The lower end incorporates the conservative margin assumptions I mentioned earlier, specifically the potential for continued USD weakness. At the same time, the upper end reflects the operating leverage we expect as we scale. For Q1 2026, we expect revenues in the range of $598 million to $604 million. This is an improvement relative to prior years, where the Q1 decline was more significant.
The Q1 year-over-year guidance implies at the midpoint a 300 basis points improvement relative to the Q4 year-over-year performance. For Q1, we expect our adjusted operating margins to be between 14% and 15%. Gross margins will be slightly impacted by the weakness of the USD plus certain statutory cost increases in Colombia and India, as mentioned before.
The IFRS effective income tax rate is expected to be in the 22% to 24% range. And adjusted diluted EPS for the first quarter is expected to be between $1.44 to $1.54, assuming an average of 43.7 million diluted shares.
To conclude, 2025 was a year of consolidation and evolution. We have diversified our revenue streams shifted our go-to-market, streamlined our operations and strengthened our financial foundation. We entered 2026 with a healthy pipeline, a more efficient delivery model, which embeds AI in all our projects and the financial strength to capture the opportunities ahead. Thank you for your continued support.
[Operator Instructions] So with that in mind, we'll take the first question from the line of Bryan Bergin from TD Cowen.
2. Question Answer
So two questions. I'll ask them upfront here. First, just a growth clarification for the year on the upper end. I think you mentioned it assumes a solid pod demand trend that you've been seeing in 4Q. But does it also require some level of macro or broader demand improvement versus it being like the same macro backdrop?
And then my second question is on the pipeline on your GenAI solutions, when we think about the clients that are utilizing these pods, is it pieces of work, broader engagements. Can you kind of just talk about where it's being used specifically as well as then the net impact from like a transition from old to new, if you can kind of get us there.
Thank you. So as for the first part of the question, the upper end of the guidance assumes that we will continue to perform very well with our AI pods, plus some improvement in the overall market. The midpoint is a most likely scenario as usual, where we see basically more or less more of the same. I mean no big changes in the macro, no changes, no big changes on the business overall. And that's how we built the guidance for the year in terms of revenues. As for the second part, I will let Martin.
Yes. What we are seeing in our 7 out of our 10 top customers, we're seeing that people are loving it. And when I say loving it is that people are really looking to change the model from ours or other types of engagement into these kind of output model in which, of course, we charge the tokens but always there's a business result attached to those things.
So what is happening is that sometimes we're transitioning that work from our kind of engagement to this new kind of engagement. In some of our customers, there are some small pilots that are starting to happen. In some others, we're going now from pilots into scale without any kind of ask in the middle because the results are really amazing, as I laid out on the examples I provided.
So that is kind of changing the whole dynamic around the future of the company, right? Now we are able to not just scale our teams with new people, but now we can also be connected to everything that is happening on the AI space in a direct way. There's a new market that we are creating, which is called the AI-native technology services companies. And those AI-native technology services companies must find a way to deliver their services, having agents that repeat certain processes that ensure that what is produced is enterprise class with the right security, with the right kind of characteristics for what they need to be produced. And then humans supervising those assets that are being created.
And that transition has been -- 12 months ago, indeed, 9 months ago, this product didn't exist. And now we are in a situation that we have in 2025, more than $20 million in ARR and now we are scaling big customers, like the one I mentioned, like FIFA, like Santander, like La Liga, like Employer Bridge and many others.
So I feel that change is very healthy. It positions us in a different place. And of course, everything is mounted on top of what we already have, more than 800 relationships with top-notch corporations, 28,000 people that are ready to supervise all kind of products that we can produce those patients the right technology platform to be able to deliver those services and a commercial model, which is absolutely different from anything that we have seen before. And the best thing is not just a prediction, but also a real business. So we're extremely happy with that. I don't know if that answers your question.
Well, I guess it partly did. The aspect I'm trying to get at is, you mentioned, certainly, the gross margin is very high relative to what your historical is, right, in these pod structures. But I'm trying to think about the revenue transition. So if you start from scratch great and engagement, but if you start on a client that had an existing engagement, what is that revenue? Like you're getting more productive? Is there a netting impact there?
I'm absolutely happy with exchange in the revenue. I mean we are kind of getting the teams that we had in that customer and transforming that into AI Pods with a very different revenue proposition and a different revenue value proposition. So it's a transition that is happening slowly, but it's happening. And sometimes, there are new customers. Sometimes there are customers that are working with us on a fixed price that we are delivering now in this new way. So that transition is starting to happen, and we expect that transition to gain momentum as the year progresses.
Certain customers, Bryan, what you're going to get is that this additional productivity that we have can translate into helping them to reduce all the technical debt that you typically find in organizations. In other cases, it may be in a specific project that you are able to maybe to price in a way that is more cost efficient.
So there's going to be a lot of cases, right? But the common factor here is that a lot of the technical debt that many of our customers have now we can be more productive and we can offer them to do basically part of that additional work with our airports as well.
Thank you, Bryan. The next question comes from the line of Maggie Nolan from William Blair.
I'm hoping that you could comment on your expectations for Latin America in 2026, just particularly given some of the recent uncertainty that's resurfaced related to tariffs?
Sure. So Latin America, as you remember, at the beginning of '25, we faced some issues and the region for a few quarters was showing negative growth. But then towards the second half of the year, we started to recover, and we actually ended up in a very healthy manner, being Latin America, the fastest region for the quarter. They are different, as you pointed out, there are different situations in different countries, Argentina and Chile which are two of our main operations are doing very well.
Brazil, it's okay. We are basically performing in line with our expectations. And now, of course, we need to see what's going to happen in Mexico is a little bit of an unknown at this point. But the main countries are performing well. I think that the recovery that we achieved in the second part of the year when we look at which are the customers driving that, most of them are in Argentina. So we don't see -- we are not -- we don't see any headwind coming from Latin America.
Okay. Great. And then you sounded pretty optimistic about converting the pipeline as well, but I also caught in the prepared remarks that maybe you're expecting clients to look for larger scale or longer duration projects, which I would imagine would kind of change the pace of pipeline conversion and will change the ramp-up of revenue over time. So can you help us understand how that's reflected in the guidance and maybe if it's different from historic? .
Yes, Maggie. So what we are seeing is shorter sales cycles in smaller deals and the bigger deals, still lagging just a little bit behind the slower than we would like to in terms of closing and ramping up. But leveraging the amazing quarter we had in -- the amazing quarter, we had Q4 and also Q3, we're expecting to start ramping up onboarding and converting to revenue very quickly in Q2 and in H2 even.
So it's true that the clients are cautious are taking time to make a decision when it comes to very large investments. But the robustness of the pipeline is still there. The quality of the deals is very solid. The 100 square are performing very, very well, where the vast majority of the bookings are coming from, as Martin said, 73% in Q4. So I'm pretty confident that this combination will allow us to move forward in a very confident way.
Thank you, Maggie. The next question comes from the line of Puneet Jain from JPMorgan.
So with all the news flow over the last 1 or 2 months around evolution of Agentic AI. What does that mean for IT services spend? Like Martin, you mentioned that it's time for some of those AI investments to move into execution. Are you seeing like increased urgency among your clients to embrace Agentic AI given like all the news flow over the last 1 or 2 months?
Yes. In the last few months, what we have seen is that companies are moving into action in that space. The avenues are, how can I accelerate my [indiscernible]. How can I replace some not very deep Software-as-a-Service solutions. How can I automate my processes using AI. How can I replace workflows of Agentic AI processes that I had before, of course, they must be supervised by humans.
And I believe those 3 avenues and the fourth avenue is that how can I improve my customer experience that research really bumpy when I read it about the idea of consumer happiness, yes, consumer happiness about how interfaces and experiences are evolving is falling in the last 4 years in a row. So there's a big technical debt of $1.5 trillion to $2 trillion, but also there's a big consumer experience that.
So another avenue of demand is saying, okay, how can I update all these interfaces to the next generation of interfaces. So all these avenues are creating like a lot of demand for AI, I believe that the way to deliver those next-generation services, those AI native services must be absolutely different from what we did in the past. And imagine that we have each of these AI Pods, Puneet, unit are like a recipe or like a set of instructions like a process that we have been refining for years and years.
It has different steps to create enterprise-ready, security-ready types of solutions and what we are producing using those tools is really much more scalable than before and really much faster than before. So customers are seeing that now. If you just throw AI tools to people, you don't get those results. And that's why it's so important to stress the point that this new industry is the way to create the savings that you are expecting or if you don't want savings, is the way to create the productivity that you're expecting from these AI teams.
So that's why I believe that the AI Pods are really catching up. It's a pretty simple way of understanding how to make those savings real as opposed to just keep on throwing licenses of AI tools to people to use them. I'm not really sure that they will use them in the correct way. And again, it's much more different to orchestrate and to supervise a set of agents producing software and that's real productivity and just throwing AI tools to people. It's an order of magnitude of difference between the two things. And this is exactly what we are doing in our AI pots. So yes, I'm seeing momentum, and that will keep on growing. That will keep on growing.
Okay. And then all the spending on AI, whether it's for core modernization, consumer experience, AI Pods. Do you think like it will represent like incremental spending on IT services? Or will this those budgets will stem from cutting elsewhere other parts of discretionary spend?
No. Look, I mean I think humanity will create 100x more software than before. And that is only expansionary for us. So I don't see that this will -- well, now we are happy with this small increment on the productivity and the small increment on the functionality of our product. You hear and you listen companies delivering much faster functionality than before live. I read many examples during the last few weeks.
So I believe that this is something that we will only keep on growing and the more you can do, the more you consume, and that's a historical trend, right, in every single -- so if we can produce more software faster, we will use more software and we will expect more functionality and we will expect more customers to be happy. So it's not a trend.
I mean, sometimes what I see analysts and when I see reports, I'm going to read to report, I see that there's a kind of a limited amount of scope, and what I'm trying to -- the message I'm trying to convey to you is that there's no limit amount -- there's no limited amount of scope. Just the technical depth is another industry of our size, just the technical depth, right? If you add on top of that, the consumer experience debt, all the new -- there's no way that it will be the same amount of software as before. It will be 100x more software. So that will be translated into better solutions with more platforms, with more AI Pods, with a stronger pipeline. Well, all these things are building up.
In my speech, what I said is 4 years, we have received -- sorry, for almost 2 or 3 years now, the vast maturity of the investments has gone into AI infrastructure that don't necessary translate into demand on the professional service space. Before that same investment, were going into better cloud that was yielding better software as a service, more implementation services, but that cycle now needs to come back. And that's why I made the point on the technical depth, on this consumer experience that because at some point, those things needs to catch up. Otherwise, the Consumer Experience Index will keep on going down for years and years and years, and doesn't make any sense.
In the moment, we can have the better and the best experience for our customers, we're having a decline in customer satisfaction for interactions with companies. How can we explain that? So one way or another, companies has been distracted investing in AI, throwing AI to people now is the time to make it -- to get it serious.
Thank you, Puneet. The next question comes from the line of Bryan Keane from Citi.
I guess just thinking high level, Globant has always been a double-digit grower, organic grower and this year was kind of a transition year, grew 2% for the year and obviously down 5% for the fourth quarter. What can you point to like specifically happened this year that might not be recurring in years to come? Was it just certain client consolidation? Was it any AI pricing pressure that was priced into the model? Like what exactly is the difference that happened this year that necessarily won't recur as we go forward?
You mean this year 2025, right? .
Yes, 2025 versus, yes, going forward.
Yes. I think 2025 was a year of uncertainty in general. Companies retracted budgets in many cases. I think it was a year in which macro uncertainties were extremely hard to overcome for many of our customers, and we suffer that. I think that right now, the situation is a little bit more clean in that aspect. So that increased my expectations of having a more normal year. That kind of compounding downwards on the revenue last year, we bottom on that revenue, and we expect to come back to growth in -- by the year-over-year by the half of this year.
So the exit rate will come back to a pretty decent level of growth as we approach the end of this year. So what you see on the year-over-year is kind of, okay, it was a year of reaccommodation, restructuring, customer uncertainty so on and so forth. The whole industry growing slower, which is kind of killer. And now we are catching up and we are starting to grow again and towards the end of the year, the exit rate will be much healthier than what you are seeing now. A note on the year-over-year that you are seeing, this already represents something that is stationary, right, that has to do with the moment of the year. And it represents a huge improvement from what we did last year at the same time. I know if you now this one or Juan may...
As Martin is referring to, the first quarter compared to the first quarter of last year. So the beginning of this year is definitely better than the prior year, but the cadence of the quarter last year is somehow impacting the growth rates for 2026. When you look at 2026 exit rates, they are more like mid-single digit. And if we keep on compounding, that should put us in a better place for '27.
Now of course, there has been an industry situation. I mean if you look at the vast majority of the players, they are all between 3%, 4%, 5%. So there has been less growth in the sector after massive investments in COVID times and around that time. There is a little bit of giving -- going past that period of massive investments, but the needs are there. The pipeline shows that customers have been accumulating debt technical debt, and that needs to start converting at some point. Of course, [indiscernible] macro, a solid U.S. economy should help eventually.
I think that we are coming out of 2 years of a lot of uncertainty globally and that has not helped. But all in all, in summary, I think that the fourth quarter shows a bottom in terms of year-over-year numbers. Q1 already shows a better performance relative to Q4, and the expectation is for that to continue throughout the year.
Yes. My quick follow-up one is what do we -- how do we model out head count growth and revenue per head for this year? And does that model change at all as we get more embraced with more of the AI Pods?
Definitely, yes. We are seeing that we can do slightly higher numbers. We can continue to grow our revenue per share with the same or even less head count. The AI bot model by definition requires less people. It's the AI Pods, which are agent supervised by some few people. So there less need for talent. So I think that not just for loan, but in general, the sector will start to change a little bit that trajectory of head count and revenue that we have seen in the past 20 years. definitely, the more we are able to penetrate our customers with AI Pods. The more the mix of airports relative to the rest of the business increases, that should be a positive for revenue per head and also for margins. .
Thank you, Bryan. The next question comes from the line of Arvin Ramani from Trust Securities.
It appears that there is an issue on the line of Arvind. So we'll jump to the next question. The next question comes from the line of Jim Schneider from Goldman Sachs.
I was wondering if you could maybe address -- on the AI Pods business, the path to get to the upper end of the range on the $100 million in a run rate ARR in that business. What is required for you to get there? Do you -- how many more bookings do you need to put in, how much is supported by your existing pipeline of AI Pods business? And I guess maybe you just kind of talk about the broad outlook on your confidence of kind of getting to the high end of that range.
Great question. Thank you, Jim. The higher part of that range could be achieved with not many big customers moving into that model. But let's see. That's why we are always being cautious here. We are extremely excited about the progress of that. Now we are seeing engagements of $20 million, $18 million, $15 million being transitioned into this kind of engagement, which is extremely encouraging for us.
So we expect to achieve those numbers. But I don't want to be -- I mean, it's the first time we are guiding them. I don't expect to guide those numbers every quarter either, but I'm trying to be moderate here. So -- but I'm quite optimistic about the possibilities of reaching to that top line -- top guidance that we did at the end of 2026.
If I can add to Martin. The behavior of the pipeline when it comes to AI pods is very encouraging. We've seen a positive trend and a very accelerated growth. So -- and on top of that, the openness of our top customers to start piloting, right, and to start scaling up when you review the list of clients are starting to ramp up in this new technology, it's really encouraging. So we are very confident and we trust that we are going to be very close to the range that we guided in terms of AI Pods.
That's helpful color. And then maybe you talk a little bit about the profile of the gross margins for your overall business as we head through the year Juan, I know you mentioned some issues relative to FX and regional costs that were sort of providing some pressure in Q4. Should we expect that we're sort of at a trough on gross margins and we can see acceleration throughout the year? Or how should we think about how that shapes up?
Thank you, Jim. So I mean, yes, we have been impacted by the U.S. dollar weakness. If you look at Colombian peso, Mexican peso, Chilean peso, Brazilian real, most of the currencies where we operate in Latin America have had significant appreciations throughout 2025 and that is what impacted the first -- sorry, the last quarter of last year and what is also impacting the beginning of this year.
I think that the dollar is getting to a point where it's on an average, it's kind of on a very low place relative to historical terms. So there has to be a little bit coming from there. But also more importantly, I think that we need to keep on focusing on not just looking at what's happening with the currencies, but moving the business towards AI Pods because that's where productivity increases that where margins become higher and the more we operate on those models, the more efficient, we can run them.
So I think that pricing will be okay. I mean it's not going to be a massive growth this year in terms of pricing for the general business. But definitely, there is an opportunity to increase our share of AI Pods and hence maintain or improve our gross margins as we scale that business.
Thank you, Jim. The next question comes from the line of Jonathan Lee from Guggenheim.
I wanted to ask, what in your customer conversations in January and February gives you confidence around the conversion time lines that are contemplated in your outlook? Particularly given some of the client caution you've called out and some of the conversion challenges you may have seen historically? .
So we are seeing clients more open to resuming big deal conversations. And in the past, we are seeing also some of the volatility and the uncertainty lowering their levels in their conversations. And also another interesting fact to consider Jonathan, is that when we architected the numbers for 2026, we were able to bake in some very relevant deals that we closed in Q3 and Q4, right? And some other deals that we are working on that hopefully will close before the end of Q1.
So some of that volatility going away and some of the clients being more open and those deals that we closed, and we are in the process of onboarding and ramping up, give us the confidence that the trajectory will be different.
Great. That's encouraging to hear. And just as a follow-up, can you help decompose what you're expecting across your verticals over the course of the year? And are there any that you expect to decelerate versus accelerate relative to what you've seen?
When we look at our different industries for this year, for last year, financial services had a good year, growing approximately 13%. We have seen consumer retail and manufacturing performing very, very well. We continue to expect to see that behavior in that particular industry. So far, we have not seen the recovery of professional services, which has been kind of one of the drags in 2025. .
Technology will come back. We are starting to see some big deals shaping up with our tech customers, which was another sector that was not doing as we wanted last year. But definitely, when we look at the Q4 and some of the expectations going forward, that's going to be fine. And finally, health care, health care and gaming, right? Those are the two that are big deals that have already been signed that are in the process of ramping up and that are part of the explanation of the sequential growth that we should see for the rest of the year. So that's, in general, I try to go to all the industries as we report them. So hopefully, that helps.
Thank you very much. The next question comes from the line of Sean Kennedy from Mizuho.
Congrats on the bookings growth and momentum in the business. Great to see. So I was wondering about AI pods and the conversations with your customers. Are you seeing their procurement teams becoming more comfortable with the AI Pods business model versus legacy?
That's a great question, Sean, thank you. This is [indiscernible] of the most challenging things. However, as the thing gains -- as the idea gains momentum in the industry on the analyst side, on you guys, the procurement teams are getting more relaxed. And also, I believe that the fact that we are talking something that is extremely solid and it's, I would say, an order of magnitude more transparent than the traditional model, procurement love it.
So whenever you can tie any asset that is being produced to the amount of tokens and understand that, that correlation is what you're paying is much better than saying we consume this amount of hours to do whatever. So I think the AI Pods offering is extremely solid. Of course, a long road on convincing more people about this. The more you help us, the more we can do it. So we appreciate any kind of explanation on your reports.
And analysts from Forrester, from IDC, from McKinsey, from Bain, they're already explaining this way of working. And 70% of the people, as I read in a report the other day, 70% of the people that are buying technology are expecting a change in the way the engagements happen. And the answer to that change is either a monthly subscription, an amount of tokens or some kind of combination there, but it must be on that cycle. So procurement teams are responding quite well to that.
Having said that, of course, it's always complicated, but it's not impossible. And the business is pushing very hard for that.
And there's also when we started this, we tied the AA parts with the capacity that it was equivalent to Timoftamount of people, right? And procurement is used to that ensure -- and we become much more mature nowadays. And we are actually talking in correlating the consumption and the subscription with outcome to a certain provide full transparency as well. So there's also -- we've been getting a lot more mature in describing and showcasing how an AI bot performed and data has also relaxed a lot of the procurement teams. .
Got it. And then as my follow-up. I think you stated at the high end of the guide embeds that the current conversion levels that you're seeing are consistent. So I was just wondering how it's been trending over the last few months.
For AI Pods or in general?
Excuse me.
You're talking about AI Pods or in general?
No, no, just in general, in total. .
Look, they are -- I mean, we build the guidance a couple of weeks ago. And so far, the conversion rates that we are seeing some of the big deals that we closed last year that are ramping up. They make us comfortable to be at the midpoint of what we guided. The pipeline that we have plus the expectation of some improvement throughout the year somehow can take us to the upper end. But definitely, with the current level of -- or the current conversion rates, plus we have already done during Q4 and the beginning of this year, that will take us -- should take us to the midpoint of our guidance. But again, that doesn't -- the midpoint doesn't include any material improvement or material change on the overall environment. .
Thank you, Sean. The next question comes from the line of Arvin Ramani from Trust Securities.
Good set of results. I'll set of questions on AI. So I'll kind of hop on to the trend. I mean, AI Pods generated about, I think you said $21 million in ARR this quarter, very impressive given it's still early. But still, it's less than like 1% of your overall revenue is still pretty small. But when you look at this model, it's basically designed to do more work with tokens and less with humans. And as this AI Pods scale, how do you prevent them from cannibalizing your core seed-based revenue?
And then secondly, what is the internal modeling saying about the revenue crossover point when you're doing -- you're generating more from like token-based revenue versus head count based revenue?
I'm not in a position to prevent cannibalization. So I want that transformation to happen. And that puts us in the right side. And that means that as AI grows, we will keep on growing. And the way we are delivering our services with these AI Pods is by far very scalable. It kind of the style years and years of experience and the configuration [indiscernible] we are using for each of those AI Pods and how the agents must run the process is really very, very impressive to see how those small recipes to achieve the assets that our customers have are really changing the way we are using AI and the current models that we have, because we are baking into those configuration files, all the experience that we have in the company.
So this is the north for us on how to deliver technology and solutions moving forward. And of course, there will be customers that are comfortable with the hours and our current business we have with them and so on and so forth. And I'm extremely happy to keep on doing that. But we are extremely encouraging our customers to move to this new model because we believe on the benefits for transparency, for productivity, for the long-term relationship we have with them.
And not necessary AI Pods are cheaper, they are more productive. So we see a transition year in which we were going to be transitioning from one kind of business to the other type of business. So it will be like a rational migration rather than anything else. So I don't know if that answered your question.
For the second part, as we migrate the business to AI Pods and AI Pods start to gain share, hopefully, by the end of the year with the current forecast that we have in our internal projections, the numbers that Martin mentioned in terms of ARR for the end of the year. So definitely, we went from 0 to $20 million run rate in just 2 quarters. The model has been under a lot of evolution, a lot of testing with customers, a lot of internal work on making sure that it is -- it creates a differentiation for [indiscernible] that makes us stronger relative to other players or other models that may be out there.
And now it is starting to accelerate. As we discussed before, when we look at which are the customers that are now getting on board, which is the size of some of the deals. Now it's not just the -- let's try with a small thing here, but some customers are actually talking about $10 million, $15 million, $20 million being migrated to the new model. So I think that we are starting to get that acceleration after a couple of quarters of understanding the customer and getting feedback.
We just launched this in Q3 last year. So it's only a few quarters that [indiscernible] around. It's already creating interesting revenues, creating a lot of momentum with customers. I would say that by the end of the year, will be more relevant relative to overall pie. But definitely, it will be next year when the curves start to get closer.
Yes. And also for your models and for everything that you are covering us, I think that we must acknowledge here that the industry is shifting and that this new industry of our AI native services is going to be, in essence, different from what it used to be. And AI native services is leveraged on, of course, on knowledge, but also on repeatable processes and things that we have never had before. So in the same way, Amazon created the cloud computing industry when they launched Amazon Web Services. Of course, at our scale, I don't want to be comparing with Amazon, but our scale, we are kind of executing this vision of AI native technology solutions. .
And the way to model that and the way to do that is absolutely different from what it used to be. That's why I started talking about ARR because it's kind of a recurring revenue that is not coupled to the amount of people. Right now, we are using people to supervise what the agents are producing. Every kind of asset has a certain amount of time for those things to be supervised, so we can calculate how much people we need for that. But what we believe is that the revenue has nothing to do with the amount of people that we are putting there.
The revenue has to do with the amount of assets that we are creating and how enterprise-ready those assets are, right? You can use [ Code X ] but you won't get all the discipline and the rigorous approach that enterprise software needs. So what we are creating here our process is to create assets that are enterprise-ready, security-ready that they have the scalability and the repeatability and maintainability that you need to have moving forward.
So it's really a different way of understanding the industry itself. There's a $2 trillion industry that must change to a new model, and this is the very beginning of that.
Yes. That's inedible helpful. Just a quick follow-up here, you're going to -- just a quick follow-up. In terms of like the token side, the tokens cost your particular amount of money and then you're charging your customers. What are the margins you're making there higher or lower than the company?
As we reported, margins are between 45% to 60% depending on the AI Pods. And depending on the customer and depending on the things that we need to create. We expect that margin as we progress with time to increase as we get more efficient with technology and we get more efficient, supervising and the technology for supervision gets improved, too. So this is the kind of model we have in mind.
As we are able to supervise more assets with the same amount of people with less people or with better technology, we will need less supervision and we want to increase our margins. And that's a virtuous cycle that happens here. But not just that, every single conversation and every single token is being installed on our enterprise AI platform. And those tokens can be used to improve the processes and to retain corporate
Sovereignty of the processes of the company. So this is kind of an explosion of productivity and -- and it will reshape the whole industry and not just for software development, it will happen also for process operation.
Today, we have AI Pods called AI bot software, and we have another AI Pods operations. And also both of operations they get that kind of doing things for operating certain processes of companies, and we charge it also per consumption. So it's a radically different way of understanding how professional services and how services will be rendered moving forward. There's a lot of value to add for companies like Globant, and there's a lot of change of mindset that is needed to understand this new industry. I could be talking forever about these.
Thank you very much, Arvind. Unfortunately, that's all the time we have for our question-and-answer session for today. So with that, I will now ask Martin to provide some closing remarks. Martin, the line is open.
Thank you so much, Arturo, and thank you, every one of you, for your support, for your help and for being here today. Bye-bye. See you next quarter. Thank you.
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Globant SA — Q4 2025 Earnings Call
Globant SA — Q4 2025 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $612,5 Mio. (Q4), über Guidance $605M, -4,7% YoY.
- Bookings & Pipeline: Q4‑Bookings +32,4% YoY; Gesamtpipeline $3,4 Mrd.; AI‑Pods‑Pipeline $283M (8% des Gesamt‑Pipeline).
- Margen: Adjusted Gross Margin 37,6%; Adjusted Operating Margin 15,5%.
- Ergebnis: Adjusted Net Income $68,9 Mio.; Adj diluted EPS $1,54.
- Cash & FCF: Q4 FCF $152,8 Mio. (Rekord); FY FCF $211,7 Mio.; Cash $250,3 Mio.; Aktientranch‑Rückkäufe $50M in Q4.
🎯 Was das Management sagt
- AI‑Pods & ARR (Annual Recurring Revenue): AI‑Pods als token‑basierte Subscription; Exit‑rate ARR Ende 2025 $20,6M; Ziel für 2026: $60–100M Exit‑ARR; Pod‑Bruttomargen 45–60% vs. Blended 38%.
- Plattform & Organisation: Globant Enterprise AI (4 Hubs) plus Reorganisation in industrie‑spezifische AI‑Studios; Delivery unter CTO zur besseren Abstimmung von Technik und Auslieferung.
- GTM & Kundenfokus: Konzentration auf Kern‑Accounts (≈Top‑100); 73% der Q4‑Bookings stammen aus diesem Kundenkreis; enge Partnerschaften mit Hyperscalern und Modell‑Anbietern.
🔭 Ausblick & Guidance
- Jahres‑Guidance 2026: Umsatz $2,460–2,510 Mrd. (0,2–2,2% YoY), Adjusted Operating Margin 14–15%, Adj diluted EPS $6,10–6,50; IFRS Steuerquote 21–23%.
- Q1 2026: Umsatz $598–604 Mio.; Adj Op Margin 14–15%; EPS $1,44–1,54.
- Risiken & Treiber: Währungsstärke lokaler Währungen (USD‑Schwäche) und gesetzliche Kostensteigerungen in Kolumbien/Indien drücken Margen; obere Range hängt von Pipeline‑Conversion und AI‑Pod‑Adoption ab.
❓ Fragen der Analysten
- Pipeline‑Conversion: Kernfrage, ob obere Guidance ein besseres Makroumfeld voraussetzt; Management: Midpoint benötigt kein Material‑Makro‑Improvement, Top‑End setzt stärkere Pod‑Konversion voraus.
- Geschäftsmodell‑Übergang: Diskussion zu Kannibalisierung vs. Migration: Management erwartet bewusste Migration zu token‑basierten Pods mit höherer Produktivität und besserer Revenue‑per‑Head‑Dynamik.
- Margen & FX‑Druck: Analysten wollten wissen, ob Q4 ein Margentief war; Management: kurzfristig FX und lokale Kosten belastend, langfristig sollen AI‑Pods strukturell Margen heben.
⚡ Bottom Line
- Fazit: Globant wandelt sich zu einem AI‑native, abonnementorientierten Anbieter: starke FCF‑Generierung und Buybacks stützen Aktionäre kurzfristig; mittelfristig bieten AI‑Pods Potenzial für höhere Margen und wiederkehrendes Wachstum. Hauptrisiken: Währungsbewegungen und Tempo der Pipeline‑Conversion.
Globant SA — Q3 2025 Earnings Call
1. Management Discussion
Good afternoon, and welcome to Globant's Third Quarter 2025 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions] Please note this event is being recorded and streamed live on YouTube. By now, you should have received a copy of the earnings release. If you have not, a copy is available on our website, investors.globant.com.
We will begin with remarks by our Chief Executive Officer, Martin Migoya; our Chief Financial Officer, Juan Urthiague; and our Chief Technology Officer, Diego Tartara. This will be followed by a Q&A section. Before we begin, I would like to remind you that some of the comments on our call today may be deemed forward-looking statements.
This includes our business and financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC. Please note that we follow IFRS accounting rules in our financial statements.
During our call today, we will report non-IFRS or adjusted measures, which is how we track performance internally and the easiest way to compare Globant to our peers in the industry. You will find a reconciliation of IFRS and non-IFRS measures at the end of the press release we published on our Investor Relations website announcing this quarter's results. I will now turn the call over to Martin Migoya.
Hello, everyone, and welcome back as Globant presents its earnings for Q3 2025. We appreciate your continued interest as we navigate the ever-evolving technology landscape. Our commitment to innovation and reinvention remains at the core of who we are. The speed of change is only accelerating. This quarter, we are excited to share how we are not only adapting to market trends, but also proactively shaping the future of our industry.
Our focus on sustainable growth and delivering exceptional value continues to drive our efforts as we look ahead. Our business fundamentals remain strong, and we continue to perform by putting innovation first. Our AI Studios bring together our talent to provide a new kind of AI-based solutions specific for each industry. They transform how consumers interact with brands and how our clients run their businesses. Our AI bots are our next-generation offering designed to deliver agentic AI-based services that scale faster, operate more transparently and focus on measurable outcomes.
They combine the speed and autonomy of AI with the creativity and oversight of our experts enabling customers to access continuous outcome-driven transformation at scale. All our agentic AI-based solutions from our industry-specific AI Studios to our AI Pods are orchestrated through Globant Enterprise AI, our central intelligence platform that acts as the golden path for enterprise-wide AI adoption and impact.
Delivered through a transparent consumption-based model, it transformed AI from isolated experiments into predictable, scalable and measurable source of enterprise value. Together, these elements form the backbone of Globant's growth to provide value for our customers and shareholder returns. During Q3, we generated $617.1 million in revenue, $2 million above our most recent guidance. We also launched a share buyback program, reflecting how bullish we are on our long-term prospects.
The pipeline has hit another all-time high currently at $3.7 billion, representing 30% year-over-year growth. It marks the solid demand we see for our services, and it grew this quarter despite very strong bookings. AI continues to emerge as the world's dominant technology with an expected market of $4.8 trillion by 2033. It will have made a 25x increase in 1 decade. Over the past few months, we have seen a healthy dose of realism in the AI space.
There has been a shift beyond hype towards tangible and effective adoption. We see a tremendous potential in AI transformation today. While Software-as-a-Service has played a crucial role in corporate technology by providing efficient and scalable solutions, our new AI Pod subscription model represents a significant evolution in how organizations can leverage technology. With our AI Pods, we empower leaders to develop tailored solutions that effectively address their unique and ever-changing needs.
Our AI Studios and Core studios are having these conversations with our clients to provide clarity in AI transformation, build versus buy and cost optimizations that are top of mind for corporate leaders today. Since doubling down on our 100-squared strategy this year, we have seen the execution being shown in bookings and revenue. Our top 5 clients grew sequentially by 2.1%, exceeding the company's average growth over this period.
The share of clients we have identified as 100-squared potential as part of our total bookings is currently 56.7%, up from 50% last year. Today, we have over 1,000 engagements related to Gen AI, Core AI or data currently running, representing 1/3 of our overall projects. We have over 900 projects related to AI readiness in our pipeline.
The new offering of AI Pods a departure from traditional consulting engagement models has nearly doubled in its share of our pipeline. This growth significantly outpaced the overall pipeline expansion. Clients access these solutions via the Globant Enterprise AI platform, which serves as a multipurpose Hub.
First, as an AI Hub connecting seamlessly with more than 140 LLMs, clients can interact with the LLMs that is best for their needs without being locked into a single provider. Second, it is a corporate Hub that connects with all major corporate information systems and data lakes like SAP, Salesforce, Databricks and many others. And third, an agent Hub that allow clients to create Agentic workflows to automate corporate processes.
Globant Enterprise AI can be acquired on a subscription basis. This shift to our subscription revenue model is not just a theoretical goal. It is actively underway in our most valuable client base. Within our top 20 customers, a group that collectively represents close to 40% of our total revenue, we're currently embedding our subscription model with 17 of them in meaningful ways. This is a huge milestone, specifically considering we officially launched this methodology in June of this year.
We're encouraged to see how our clients are incorporating this new model. For example, at YPF, the largest shale oil operator in the world outside the United States, we're moving into full execution with 46 agents to optimize sourcing, inventory, contract and supplier management, bringing clarity and efficiency to how the company interacts with its complex supply chain. As you know, Globant has a talent for applying AI to reinvent the human experience in entertainment, which is why we are particularly proud of our new engagement to bring Agentic process to La Liga, one of the world's top sports league.
Diego will expand on this later. A great example of our growing partnership is our work with Natura, the Brazilian multinational cosmetics company. This quarter, we announced that Globant will lead their S/4HANA migration, chosen for our ability to seamlessly integrate innovation and AI into SAP methodology, development and testing while enhancing traditional implementation efficiency. Together with SAP's Joule, our AI agents and platforms will accelerate delivery, reduce time to market and support the clean core strategy by anticipating deviations and suggesting real-time corrections.
Governed by our AI agents, this project brings a new vision from how technology can transform SAP implementations and drive business performance. This month, we also announced an important partnership with Riot Games. The company behind global esports phenomena, League of Legends and Valorant. Globant will support its advancement in artificial intelligence, new game development, esports experiences and software engineering capabilities.
Over the next several years, both companies will push the boundaries of technology to deliver richer, more personalized experiences for millions of players and fans globally. This partnership is one of the largest agreement in the history of our games business. We are proud to work with companies that continue to shape global esports culture and inspire millions of players. We're making decisions to unlock the full power in our core studios as well.
We recently announced that all of Globant's marketing and advertising efforts were consolidated under the GUT brand umbrella. Today, Globant and GUT bring a uniquely consistent and complete value proposition to the entire C-suite, empowering CTOs and CEOs to transform their business through technology while helping CMOs push creativity and marketing performance better than ever. Just as Amazon transformed the technology landscape by removing friction from how business access and scale computing infrastructure effectively, inventing the modern cloud industry, we aim to do the same for technology and professional services through our AI Pods and subscription model.
Traditional consulting engagements are filled with friction, lengthy planning cycles, detailed scope definition, change request and constant budget negotiations that slow down execution and dilute impact. Our AI Pods eliminate those barriers by combining Agentic AI with expert human oversight in a transparent token-based subscription model that focuses on outcomes rather than hours.
We defined supervised token capacity and continuous monitoring, execution becomes faster, auditable and adaptive, allowing our clients to focus on delivering value instead of managing project logistics. We are not just redefining consulting. We're leading a revolution in how business access technology and professional services. Thank you for joining us on this exciting journey.
Hello all. As we look at the third quarter, one thing has remained constant, the urgency for enterprises to deliver measurable results through AI. We have tirelessly enhanced our portfolio of services and products around that very premise to enable our clients to apply AI faster and effectively to unlock business value at scale. What we are doing with La Liga is a great example. The world's most successful football league is becoming the first global sports organization to adopt Agentic models to reinvent its business end-to-end from talent development, performance analysis, workflow automation to personalized content creation.
This quarter, we also expanded our footprint in immersive high-impact experiences. Through our strategic collaboration with Adobe and Red Sea Global, Saudi Arabia vertically integrated real estate developer, together, we're building a connected visitor experience platform from trip planning to arrival and stay. The platform unites content, data and AI agents to deliver personalized context-aware journeys at scale.
Globant Enterprise AI is at the core of our AI-centric solution and keeps delivering on our commitment to make it the best common gateway for clients to navigate the complex forest of AI. Less than a week after OpenAI launched the Agentic Commerce protocol in late September, we released a new version of Globant Enterprise AI, including ACP and enabling our clients to create AI agents capable of executing commercial transactions safely and intelligently.
Our partner ecosystem remains critical to scaling our AI vision. And as we see that our clients' biggest challenge is not the lack of technology, but the complexity of integrating it for real business outcomes or how to make their long-standing core systems agile intelligent and cloud native without disrupting the business. With Unity, the world's leading platform to create interactive experiences, we joined a service partner program combining Globant's global footprint with Unity's real-time 3D capabilities to power new immersive and interactive experiences in industries such as automotive, health care and manufacturing.
With AWS, we achieved the MSP partner program designation, recognizing our ability to deliver end-to-end cloud transformation and manage mission-critical operation at scale, a fundamental layer for AI adoption. While other provides basic cloud migration, Globant differentiates by focusing on cloud-native development and optimization. We leverage the full stack of AWS services from serverless computing to their Bedrock AI platform, to build resilient, scalable and cost-efficient solutions.
With Microsoft, we have been appointed as finalist of the 2025 Microsoft Media and Telco Partner of the Year Award. Globant was honored among more than 4,600 entries from more than 100 countries for demonstrating outstanding Microsoft cloud application services, devices and AI innovation during the past year. And by joining the IBM Quantum network, we are preparing our clients to embrace quantum computing and unlock the next computing paradigm, ensuring they remain ahead of the curve as the future of intelligent systems unfold.
GUT, now powered by Globant's global creative and marketing capabilities, keeps accelerating cross-selling and elevating leading brands, including AB InBev, P&G, Mercado Libre, [ Easting ], Kraft Heinz, Verizon and Havaianas. Also, Brazil's team created the first fully AI-generated campaign for Mercado Libre, Latin America's largest e-commerce platform in partnership with Samsung.
Additionally, the official Cannes Lions report was published, listing that as #9 global agency network at Cannes Lions 2025. Across sectors and geographies, our team continue to execute with passion and creativity. Our AI Pods are gaining traction. Our AI platform continues to improve and new industries are embracing our approach to reinvention. We believe the winners will be those who act decisively today, and we are positioning Globant to help them accelerate that journey as we continue shaping the future of enterprise transformation. Thank you very much.
Hello, and good afternoon, everyone. I am pleased to discuss our third quarter results. During this period, we increased our top line, expanded profitability and generated strong free cash flow, all while maintaining a prudent and healthy balance sheet. Our revenues reached $617.1 million, up 0.4% year-over-year and 0.5% sequentially, exceeding our previous guidance expectations. Excluding the positive impact of foreign currency, revenue was flat year-over-year. Turning to profitability. We closed Q3 with an adjusted gross profit margin of 38.1%, flat relative to our previous quarter despite significant FX headwinds coming from LatAm currencies.
Our adjusted operating margin reached 15.5%, an increase of 50 basis points sequentially. In addition, this quarter, we managed to dilute adjusted SG&A by 20 basis points sequentially. The effective tax rate for the quarter stood at 29.4%, increasing significantly due to the acceleration of the Argentine peso depreciation during the quarter, which resulted in higher taxes than anticipated. We were able to partially offset this impact with FX hedges. Despite the mentioned tax effect, we achieved an adjusted net income of $69.7 million with an 11.3% adjusted net profit margin, flat relative to our previous quarter.
Adjusted diluted EPS for the quarter was $1.53 based on 45.6 million average diluted shares in line with our guidance. Our balance sheet remains strong, ending this quarter with $167 million in cash and short-term investments or $205.3 million in net debt. We repaid $56.7 million of our debt during the quarter, reducing our total leverage. During the third quarter, we generated $67.5 million of free cash flow, achieving a free cash flow to adjusted net income ratio exceeding 96% -- this strong performance is consistent with our historical pattern, where free cash flow generation is much stronger in the second half of the year.
Lastly, as mentioned by Martin, authorized a $125 million share repurchase program, which reflects our belief in our long-term strategic position and our commitment to enhancing shareholder value. Now let's turn to our guidance. Demand trends across our client base have started to stabilize, though the macro environment remains fluid. For the fourth quarter of 2025, we expect revenue to be at least $605 million, reaffirming the implied guidance provided in our prior earnings call. This Q4 guidance implies a minus 5.8% year-over-year growth and includes a positive FX impact of 150 basis points.
We expect a non-IFRS adjusted operating margin to be at least 15% and the IFRS effective income tax rate is expected to be in the 22% to 24% range. Non-IFRS adjusted diluted EPS is expected to be at least $1.53 per share, assuming an average of 45.2 million diluted shares outstanding during the fourth quarter. For the full year 2025, we now expect revenue to be at least $2.04474 billion, representing 1.3% year-over-year growth.
This expected growth includes a positive FX impact of 30 basis points. We now expect our non-IFRS adjusted operating margin to be at least 15% and the IFRS effective income tax rate is expected to be in the 23% to 25% range. Our full year non-IFRS adjusted diluted EPS is expected to be at least $6.12 per share, assuming a full year average of 45.2 million diluted shares outstanding.
To conclude, while much of the uncertainty persists, we are confident in our market position and ability to adapt. Our DNA is built on constant reinvention and industry-leading growth. Based on our operational discipline, we will continue investing in our AI studios, our subscription model and top-notch talent to deliver differentiated value to our customers. Thank you for your continued support, and we look forward to sharing more updates on our growth and achievements in the coming months.
Thank you, Juan, and hi, everybody. [Operator Instructions] we take the first question today from the line of JPMorgan. Puneet.
2. Question Answer
So I wanted to ask about AI use cases. Like are you seeing clients looking for AI use cases in Globant GUT area like AI-powered form factors for customers to do retailing or banking through new form factors?
Thank you, Puneet, for the question. You said new what?
So the new platforms, like the new way like in which consumers can buy stuff or do banking, like -- which is powered by AI.
Yes. I think the whole consumer experience is being transformed, and there's a lot of active projects that are going into the direction of changing that interface from a navigational interface towards a transactional or, I would say, a conversational interface. And in that direction, we have been doing several projects on those areas in many different customers. But it's not just connected to financial services. I would say that this kind of conversational interface is being seen in many different areas and in many different type of industries. I would love Diego to take it over.
Sure. So Puneet, here's an overview of how -- what we are seeing and how it's working. Many large companies, especially the ones that are heavily regulated, what they're doing is they're building their platform for AI transformation and development. But while doing that, they're already doing AI projects.
You mentioned, as an example, financial services. Fraud detection is one of the examples. Hyper customization for client management is another one. With regards to operation -- internal operation, portfolio management is being also handled by Agentic systems these days. So that is how it looks now. Even the most regulated sectors are jumping into AI, doing AI projects. There's -- I have to say that more than half of our projects are heavily related to AI these days. AI, sorry.
No, that makes sense. The reason I ask, it seems like there's a lot of demand -- the underlying demand for AI, but that's not reflecting in overall results. So do you think the clients are at a point that all those AI use cases and AI projects that they are ready to move them into mainstream or into production so that can overcome the weak macro or other headwinds that you faced. Basically, can -- should we expect much better growth rates next year based on the pipeline, based on what your clients are saying compared to current trends?
Yes. I mentioned in my part of the speech, I was saying, Puneet, that the pipeline grew to something that was 30% higher than in the same period last year. And about 900 projects are currently being inside that pipeline that are based on this kind of AI transformation projects. So I see a clear evolution from the beginning of the year in which projects were more exploratory and now there are more kind of transformational efforts going across the different parts of the company.
And this is not just on what we were talking before, which is consumer interaction, but also on how to run processes. And specifically on that case, we announced a case with YPF, but also the one with Riot Games with the one with Natura, which AI kind of takes a central role. And I think that this is something that will keep on evolving as we move forward.
Also, our AI part offering is also gaining a lot of momentum. It's kind of the pipeline more than double from what we had on the last quarter, just in 2.5 months that we launched the initiative. Bookings are also high. The number of customers got increased substantially, too. So we are seeing that AI is taking like a central role.
Of course, the digital transformation projects, the enterprise projects, like SAP migrations, now all of them are including this kind of AI initiatives inside of them. So it's difficult to split them, but it's very clear that digital technology is making an impact. And again, it's not that it's easy to implement one of these things and make it productive and make it into production for large corporations.
We're talking about probabilistic systems that needs to be managed in a slightly different way from the traditional systems, and that will require a lot of our help to our customers moving forward. And I see pretty much all the industries now growing as opposed to the last few quarters. All of the industries are moving forward in terms of revenue.
So that is helping. And as you have seen on the news, we have announced many deals with many different big companies and large deals in many different sectors. So I hope that will propel the revenue for 2026, and we will see good growth next year.
The next question comes from the line of TD Cowen. Bryan.
I was hoping if you could just help us connect the strong pipeline commentary with the operational headcount dynamics just sequentially. I understand you were going through a transition here. But can you give us a sense of just early 2026 client budgeting conversations? I think just trying to determine when a growth trough may form for you? And just any early commentary you're willing to share here on next year's top line potential?
Yes. I would take the pipeline thing. The pipeline, as I said, is much higher. The conversion speed as opposed to what we see in the first half of the year has also increased in the last few months. So that makes us happy. And I would say that we see a clear evolution towards the end of the year with all the deals we have. In terms of the headcount, I would like to take it to Juan to answer it.
Look, in terms of headcount, as you know, last quarter, we announced a business optimization plan to align our company, our headcount to the needs of the business, given the changes that we put in place in terms of industry studios, in terms of the subscription model and also looking at the level of growth. You have to keep in mind that we started the year with expectations of much higher growth.
Now all that is aligned. We are seeing flattish type of numbers for fourth quarter. And when we look into 2026, and we look at how the new AI studios -- the new AI industry studios are tractioning combined with the traction on the pipeline and also on our top customers with related to the subscription model, I think that puts us in a much better place to start thinking about 2026. The conversations with customers are ongoing. Everybody is finalizing budgets. When we look at all our internal numbers, initial numbers, we are seeing more growth in '26 than what we have now for the rest of the year in '25.
So we are optimistic. I think that the situation is improving. You start to close deals like the one we recently announced with Riot Games or the one or some other things that are being worked right now where they are growth oriented. And for us, that's always great news, right? When we start to see all the deals we are doing with YPF or with Mercado Libre, a lot of those deals are growth oriented.
And when that happens, we tend to do better, we tend to gain market share, and that puts us in a much more optimistic position relative to '26 than what we were before. And as you can see, we guided -- I mean, after a difficult year in terms of guidance and everything, this quarter, we were able to maintain the implied fourth quarter. We were able to raise a little bit the full year number based on the $2 million that we exceeded the number in Q3. So in general, we think it's a much better quarter, and we are optimistic about '26.
Okay. That's helpful. And maybe just one on the margin front. So obviously, that's a bigger focus for you going forward. Talk about the early efforts around efficiencies and how you're feeling about those efforts?
Yes. So this quarter, we had a good quarter in terms of operating income. It increased about 50 basis points sequentially during Q3. Together with accelerating growth, we have mentioned over the last two, three calls, and we continue to mention that there is a much bigger focus also on maintaining or improving margins, also on our free cash generation. It's a moment that until the level of growth becomes much higher, we need to pay attention at the same time to all those variables together, right?
And that's what we are doing. We will be executing on that. When you look at, for example, the CapEx levels going forward, they are going to be a little bit more aligned to the current levels of growth. So we are paying attention not just to the revenue or to the top line, but also to the gross margin, and you can look at the numbers. There has been a lot of peers taking margin significantly down. We have been very cautious on not doing that. If you look at our margin, gross margin was stable, operating margin improved. And when you look at the fourth quarter, operating margin is again above 15%. So we are trying to balance all the different things that are happening at the same time.
The next question comes from the line of Citi. Bryan.
Just want to ask about the pricing environment in general. There's some concern just with Gen AI that there's pricing pressure through contracts and contract pricing as cost saves get passed on to clients. How do you guys think about the whole pricing environment through -- as Gen AI gets put into all these contracts? And what do you think about pricing as you head into next year?
Thank you, Bryan, for the question. We don't look at major pressure on the pricing environment. I believe that the deals that we are putting together has kind of a lot of value added, and that help us to position the pricing in the place we want. Indeed, the revenue per head is doing okay. So it's not changing or going down. So that's a good sign of us being able to maintain that pricing efficiently.
But the most important comment I would say is there's a very strong connection between what you offer and how much you can charge for that and which is the value that you're creating for your customer. And at Globant, we have always paid a lot of attention to that value creation and to that specialization. And now with our AI studios that are capable of delivering like a very substantial know-how for each of the industries in which we specialize plus our Core studios are bringing solutions that can go across pretty much all the industries and I think that value proposition is resonating quite well.
And if you add on top of that, we are accelerating the offering. And now we are discussing with 17 out of the 20 top customers, the next-generation model on how to engage with us, with our AI Pods and with the subscription model. And Enterprise AI, which is our platform, also is gaining a lot of traction as each time we sell an AI Pod, it has to do with our Enterprise AI platform. So I believe that this is being accepted and this is being like -- we are able to reflect that on the price that we put on proposals, hence, maintaining our margin and maintaining our revenue per head. I don't know, Juan or Diego, if you want to comment?
No, I think that you pretty much summarized it. If you think about the individuals, like on a profile basis and you tell me how does probably that price compare to what it used to be 4 years back, yes, there's pressure there. But the mindset today is about efficiency. The mindset is about business impact. And when you talk about that, and that's one of our main strategies with the AI studios. When you talk about that, conversation changed completely. So -- and that's why we've been able to maintain our revenue per head.
Got it. And then that's helpful. And then just, Juan, just thinking about the third quarter being roughly flat in revenue growth and then it drops to about 7% organic ex currency. Can you just help us to step down in revenue growth? What's causing that? And then I'm guessing this might be the trough in revenue growth in the fourth quarter? And then what does the first quarter look like sequentially?
On the -- talking about the fourth quarter, the main impact that we have over there are the furloughs in mostly in professional services. That's impacting pretty much -- that's explaining pretty much the decrease on a sequential basis. When we look at -- and I'll just give you some color on Q1. But when we look at the Q1 right now in all the numbers that we are seeing, -- we don't see any scenario similar to what we had in the last few years.
For example, 2025, Q1 was sequentially down 4.7%. We don't see anything similar to that at this point, anything at all. And that puts us in a much better place to get the year that gives us also some -- when we look at, okay, how the year is building up, how are the conversations with the customers, what each AI studio is bringing to the table, which are the -- we just signed a very large deal with a gaming company as we discussed. When we accumulate all that, the Q1 number is definitely a lot better than what we have seen in prior years, right? And I think that puts us in a much better place getting into 2026.
The next question comes from the line of William Blair. Maggie.
I wanted to put a finer point on the margin question, particularly as it relates to SG&A. Can you drive more SG&A dilution from here? And are you planning to? Or is this a reasonable level for SG&A to settle as a percentage of revenue?
We closed the quarter at 17.7%, almost 1 point below Q4 last year, for example. There is -- of course, there is always room to keep on diluting over time, but we also need to balance the growth that we expect to recover. We need to balance all the changes that we are making in terms of our offering, all the changes we are making about our business units with all the AI industry studios.
So there is more room. But I mean, as always, you need to keep looking at 10 to 20, even 30 basis points of dilution every year, not more than that. But definitely, as a business, this is a business that has the potential to run at about 15% SG&A over time, but it's something that you have to achieve as you scale, right? When you look at which are the companies that are running at those levels, those are the ones that are already at a very large scale. I think that 17.9%, 17.8.7%, it's a good number for the size that we have right now, given all the different things that we are doing these days, right? So I think that's how we see SG&A, Maggie.
That's helpful. And then it does sound like there's some momentum building across the business. I was wondering if you could comment on professional services, in particular, maybe if you back out the impact of the furloughs that you already commented on, do you feel like that vertical is showing signs of stabilizing?
Yes, definitely. I mean when you look at -- and I think when we are looking into Q1, for example, it's one area of recovery, right? I mean after the furloughs in Q4, we have started to see stabilization in one large customer that was impacting that group. Plus we are seeing growth in two or three others that will help us to offset what has happened to that customer that I mentioned before.
But even in that large customer, now it has stabilized in a new level. But we see opportunities to recover from this new level upwards. So we are -- I think on professional services, once we go through the furloughs, that's the bottom of that sector for us, and we should start to see better numbers going forward, starting in Q1.
The next question comes from the line of Goldman Sachs. Jim.
As Jim tries to get his line back, we will go on to the next participant. The next question comes from the line of Guggenheim, Jonathan.
Can you help unpack some of the vertical and geographic assumptions around that 4Q outlook and maybe the level of conservatism that you're assuming?
Yes. As mentioned, the one sector that will come down further down is professional services because of the furloughs that is going to be impacting that sector. And pretty much for almost all other sectors, we're going to see stable numbers. So I think that's something that, again, I think that after a few quarters of moving pieces, we are definitely seeing stabilization in the business with some green shoots that are putting us in a more positive way looking into '26.
Deals like some of the ones that we announced today have been on the cook for several months and you start to see them closing. Some of them and companies are again becoming more aggressive in terms of growth. And I think this is always a positive sign for Globant. Conversations are a much better place than where they were 6 months ago. So we are more confident about '26. And we think that, that's something that will be very positive for the business.
Yes. And also, I think it's quite clear how the difference in terms of conversion that we have seen in the -- at the very beginning of the year. I mean, at the very beginning of the year, everything kind of get frozen, right? And now the things start to move not at the speed we saw in 2021, but much faster than before.
And that is quite remarkable because -- and also the pipeline generation has been quite strong because we closed like large deals. And even closing those large deals, the pipeline grew a lot. So I think that dynamic is very different from what we have seen in the first half of the year. And that's the most remarkable part. That conversion coming back, our AI studios being able to articulate that value proposition much better. I think that evolution of Globant and that evolution of the market are two positive things to consider moving forward and into 2026.
Appreciate that color, guys. As you think about your confidence around 2026, what gives you incremental confidence that these client conversions or these pipeline conversion should continue into the middle of next year?
Well, we saw in the last few months, a lot of activity in the space. I would say, abnormal as opposed to 1 year ago or something like that. So I believe that this momentum will continue moving into Q4 and Q1 next year that would generate increasing opportunities and incremental opportunities. And as Juan said, we don't see something happening on the first quarter like happened in the first quarter of 2025. I mean first quarter of 2026 will be much more close to Q4 than it was before. So I think that, that's a positive sign of what we are seeing and how the momentum is coming.
Jonathan, I think that what we are seeing is mostly shared by the industry today. So I think that everybody has been more positive about the market, the overall market condition about 2026. So I think that we are -- after a few quarters of -- or a few quarters or even a few years, if you look at some of our peers of a very negative sentiment in terms of the market, in terms of the opportunities, I think that everybody is becoming a little bit more constructive, and we are on that same boat.
Yes. And everybody is realizing that creating these projects takes a lot of energy and takes a lot of knowledge and takes really deep knowledge on how to navigate the AI landscape that is exponentially growing and exponentially becoming more complex. So I think that discussion is coming to an end and people are starting to realize that, yes, they want to adopt AI.
They need someone to help them adopt AI. Hundreds of new projects that didn't exist before now are happening and are possible to happen. And then the traditional projects need to keep on going now accelerating with the new AI technology.
So the opportunity keeps on building, keeps on being very large for the whole industry. And I'm more convinced than ever that once we pass this kind of difficult situation during the first half of the year, the opportunities moving forward will multiply and expand our opportunities for 2026.
The next question comes from the line of Itaú, Maria Clara.
I just wanted to explore more about how you can balance employees and growth ahead. So even the current headcount and utilization levels, do you believe that you need to hire new people to honor a potential acceleration of growth in 2026? Or maybe your employees are becoming more productive with AI, so you are fine with your current headcount?
Yes. Thank you, Maria Clara. So there's going to be a combination of slightly higher utilization and hires. We're not going to be able to get back to higher levels of growth without incrementing a little bit our headcount going forward. We have made all the equalization or the balancing of the level that we need right now. But as we get into next year and as we start to see those deals materializing utilization, there is still room to go up because even though we increased 50 basis points, we're still below our target of 80%.
So there is some room there. But also we see that headcount is still part of the equation. Of course, AI increases productivity for our developers, but you also will see headcount growing as we get higher levels of growth going forward.
The next question comes from the line of UBS, Leonardo.
First of all, congrats on the huge leverage reduction, 20% quarter-on-quarter. I've been particularly critique about cash generation now you've proved me wrong. So congrats on the figure. My question is about AI. I think you mentioned something about the embedded solution in 17 -- embedded AI Pods in 17 out of the top 20 clients, right? You said they are embedded in a meaningful way. I would like you to discuss that a little bit so we can try to assess how could that eventually become revenue?
Leandro, let me first clarify what I said. I said inside 17 of the top 20 accounts, we are discussing about that. Not in all of them, we included already the AI Pods, but in some of them, yes. But the important thing is that those discussions are progressing quite healthy. And I think the acceptation in general of the model around a consumption model instead of different kind of metrics, while you have like variable scope and you need to have a methodology that don't punish you and is more transparent than other methodologies that you have in the past is the concept that has been extremely well accepted by our customers.
So what we foresee is that many new deals will come and are coming with that offering inside the proposal by default. So what we are seeing is a natural growth of the pipeline of this. The conversion of that is quite healthy it's almost doubling the pipeline, doubling the conversion and the amount of customers is almost doubled from the 18 that we announced last quarter into what we have now. So I believe that those are the variables to have in mind. I don't know if you want any specific explanation on how we are implementing those things, but please expand your question, if you want.
Guess, I didn't learn since 2020. No, it's quite clear on that. I think just if you could talk a little bit -- maybe this is difficult to predict, but maybe a little bit ahead 3, 5 years, how much of revenue could come from subscription model and if AI Pods will be the single driver of outcome-based out of time and materials? Or are you thinking on something else?
No. Look, I mean, I don't have like a prediction to share with you about how much of the revenue that will be. Yes, what I can tell you is that the model is progressing much faster than any other thing that we have proposed to our customers in the past in terms of next-generation proposals. So that's a clear sign that it will take over, I think, by storm next year, but I cannot predict a specific number.
I know you want to include it in the model, but the thing is I don't have a number to provide to you at this moment. It's just 2.5 months. But the things are the signals that we're receiving from the customers are very, I would say, positive.
The next call -- next question comes from the line of Sean Kennedy from Mizuho.
So I was wondering if you could discuss what factors could raise conversion rates for the pipeline because as you noted, the growth there is robust. Is it just as simple as a better global economy? Or are there other factors like AI as in your customers are taking more time to think through their AI strategies before investing?
Yes. I think there are several factors that may help. Of course, as the global economy improves, it makes more sense for people to make more transformational projects. I know companies are -- I think that by the nature of understanding and going deeper into the benefits that any company can get from this new technology, I think companies are starting to understand that they need to move out from, I would say, trials into full programs.
And this always takes time. And in other massive technology shifts we have seen in the past, this took time. So we expect now to -- there will be needed some more time for the companies to agree that they need to go in the full transformation -- multiyear full transformation AI program for every single area. But the good news is that we are seeing that happening already, maybe not in 100% of the cases, but in many more cases than 6 months ago.
So that's a clear maturity of understanding how these projects must be developed that will help in the -- sorry, that will help on the conversion of these deals. And then if interest rates goes down, if the economy in the U.S., which is one of our main markets, has been quite stable if you take out the investments in AI. So I believe that this will come back to growth in some way as the whole economy improves, and that will help a lot, right?
But then on the internal side, on the Globant side, as we progress with our AI studios and as we progress with our offering, -- and as we progress with our value proposition of new ideas like the AI Pods and the enterprise AI and the subscription model, all those things will help customers say, okay, yes, let's do it. Enterprise AI is a perfect path for adoption of AI.
It will isolate you from any vendor dependence. You can connect with 140 LLMs on one side, on the other side with all the corporate information systems, then you can use those two things to create agents and to create workflow that automate processes, but also that transform how consumers interact with your brand. So as that value proposition gets stronger and deeper and goes deeper into our customers, I think conversion will accelerate, too. So there are multiple factors that are affecting in my perspective in the future. But I don't know, Juan or Diego.
No, I think just to add a little bit on top of what Martin said. I think there's something related to what you mentioned, Sean, that the market continues to be in a mood that is about efficiency and impact, right? And this is very important because what we see is, first of all, all the proposals that we send, they're being evaluated. And of course, they need to understand the impact that will have in the business.
And they're either a go or no. But I think with regards to the time it takes to evaluate proposals, close them up, which has certainly, there are larger period of times, lead times until closure. I think that it has a lot to do with the maturity, both of the market and the technology as well, evaluating a proposal, how to properly use new platforms, the proper models, the implementation, which is super complicated.
And you have three different offers that might be totally different and you're not even super mature with regards to that tends to take a lot more time. I think that will only improve in time. And hopefully, we will get back to the usual times of the industry.
Great. Good to hear. And then as a quick follow-up, I was wondering if you're seeing demand from helping companies, or companies prepare for AI in terms of data and cloud, like before the AI Pods implementation?
I think there was an interesting data point mentioned in the script. There is 900 projects or potential projects in the pipeline that are what we would call data readiness projects, which is either data, either generative AI, either AI Pods or a mix of the above.
So there is plenty of projects that are happening and plenty of projects that are in the pipeline that are AI related. We still see many companies that need to get prepared for making a better use of AI, right? And that's going to continue for a while. And you have some companies that are there, others that are getting there.
Sorry, but not all the projects are generative AI. I mean there's a lot of projects that is traditional AI, machine learning projects in which a massive amount of information is being involved and models are being trained or tuned or -- I mean, not all the projects are about conversational projects or interfaces.
There's a lot of AI projects that is the traditional AI projects, of course, get enhanced by the use of generative AI, but it's much more the traditional data gathering and then trying to train models based on that information to predict certain factors or certain things that you cannot do only by using a generic LLM, right?
So it gets accelerated by using LLMs, but it's traditional AI or fine-tuning or doing machine learning on specific industries, on specific sectors on specific areas of the company that are also fueling that pipeline and that amount of projects that Juan was mentioning.
Thank you for your question, Sean. Unfortunately, that's all the time we have for the Q&A section today. I will now...
Arturo, hold on a second. There was one that got missed on the line. I don't know if he's ready for the question. Jim?
Jim, are you there on the line? If not, we can move to one more question then. I'm sorry. Unfortunately, that's all the time that we have today. I don't see Jim there. But with that, we will conclude the call today. And I would like to turn over the line to Martin. Martin, please go ahead for some closing remarks.
Thank you very much, guys, for supporting us, for being here with us for another quarter of Globant and looking forward to see you on the next one.
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Globant SA — Q3 2025 Earnings Call
Globant SA — Q3 2025 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $617,1 Mio (+0,4% YoY; +0,5% q/q) — $2 Mio über Guidance.
- Adj. Betriebsmarge: 15,5% (+50 Basispunkte q/q).
- Adj. EPS: $1,53 (verwässert, durchschnittlich 45,6 Mio Aktien).
- Pipeline: $3,7 Mrd (+30% YoY), AI‑Projekte stark vertreten.
- Cash/Buyback: Free Cash Flow $67,5 Mio; $125 Mio Aktienrückkaufprogramm autorisiert.
🎯 Was das Management sagt
- AI‑Strategie: Fokus auf AI Studios, AI Pods und die Plattform Globant Enterprise AI; Ziel: von Projekten zu abonnement‑/verbrauchsbasierten Lösungen wechseln.
- Kunden & Partnerschaften: Große Deals/Referenzen (YPF, Riot Games, Natura, La Liga); Partnerschaften mit AWS (MSP), Unity, IBM Quantum und GUT‑Konsolidierung.
- Operative Disziplin: Headcount‑Anpassungen, Schuldenrückzahlung ($56,7 Mio) und Margenfokus bei gleichzeitigem Investment in AI‑Produkte.
🔭 Ausblick & Guidance
- Q4‑Leitplanken: Umsatz ≥ $605 Mio (impliziert −5,8% YoY); Non‑IFRS Betriebsmarge ≥15%; Non‑IFRS EPS ≥ $1,53; positive FX‑Einwirkung ~+150bp.
- FY2025: Umsatz ≥ $2,04474 Mrd (+1,3% YoY); Betriebsmarge ≥15%; Non‑IFRS EPS ≥ $6,12; IFRS Steuerquote 23–25% (Q4 22–24%).
- Risiken: FX‑Effekte (argentinische Peso‑Depreciation erhöhte Steueraufwand), Furloughs in Professional Services wirken dämpfend auf Q4; Konversion des AI‑Pipelines‑Risiko.
❓ Fragen der Analysten
- Pipeline → Umsatz: Analysten hinterfragten Konversionszeitpunkt; Management sieht stärkere Konversion gegen Ende Jahr/Anfang 2026, nennt aber keine kurzfristigen Garantien.
- Personal & Produktivität: Thema Hiring vs. höhere Auslastung — geplant: leichte Einstellungen plus Auslastungssteigerung (Ziel ~80% Utilization langfristig).
- Pricing & Margen: Nachfrage nach Preisdruck durch Gen‑AI; Management betont Wertangebot/Branchenspezialisierung, verweigerte aber konkrete Langfrist‑Anteilsschätzungen für Subscription‑Umsatz (keine %‑Prognose).
⚡ Bottom Line
- Kernaussage: Kurzfristig moderates Wachstum und konservative Q4‑Leitplanken; mittelfristig bietet die beschleunigte AI‑Pipeline und der Wandel zu AI‑Pods/Subscription substanzielle Upside‑Optionen. Wichtige Beobachtungspunkte: Konversion der Pipeline, FX‑Effekte und Wirkung der Q4‑Furloughs.
Globant SA — Q2 2025 Earnings Call
1. Management Discussion
Good afternoon, and welcome to Globant's Second Quarter 2025 Earnings Conference Call. I am Arturo Langa, Investor Relations Officer at Globant. [Operator Instructions] Please note, this event is being recorded and streamed live on YouTube. By now, you should have received a copy of the earnings release. If you have not, a copy is available on our website, investors.globant.com. We will begin with remarks by our Chief Executive Officer, Martin Migoya; our Chief Financial Officer, Juan Urthiague; and our Chief Technology Officer, Diego Tartara. This will be followed by a Q&A section.
Before we begin, I would like to remind you that some of the comments on our call today may be deemed forward-looking statements. This includes our business and financial outlook and the answers to some of your questions. Such statements are subject to the risks and uncertainties as described in the company's earnings release and other filings with the SEC.
Please note that we follow IFRS accounting rules in our financial statements. During our call today, we will report non-IFRS or adjusted measures, which is how we track performance internally and the easiest way to compare Globant to our peers in the industry. You will find a reconciliation of IFRS and non-IFRS measures at the end of the press release we published on our Investor Relations website announcing this quarter's results. I will now turn the call over to Martin Migoya.
Good afternoon, everyone, and thank you for joining us once again for Globant's quarterly earnings. It's always a pleasure to connect and share how we are continuing to evolve and improve. For us, innovation and reinvention are occasional events. They are part of our DNA. And right now, we're building on that tradition with a clear and steady focus on the future.
In the second quarter, we delivered revenue of $614.2 million, representing 4.5% year-over-year growth. Our pipeline is at all-time high, $3.7 billion, up 25% from last year. Although the macro environment has extended sales cycles, our teams are laser-focused on converting this pipeline into signed work in the coming quarters with large potential deals in health care, financial services, CPG and gaming, among others. These large engagements, many already in advanced stages, position us well for conversion in the coming months reinforcing our focus on high-value clients with strategic impact.
Internally, we are fine-tuning the organization to be not only more efficient and profitable, but also more nimble and better aligned with the needs of the next generation of business models. Our aim is to ensure Globant is structurally agile and positioned to compete and win in an evolving landscape while continuing to deliver strong results for our shareholders. Juan will walk you through the details shortly.
Globant's AI pods, which I introduced last quarter, are the virtual teams for the digital workforce. They are powered by Agentic AI and orchestrated by our experts. The way companies access our AI pods is unique in the industry through our monthly subscription model. It is a consumption-based outcome-aligned pricing that provides guaranteed time and cost savings shifting the value proposition to concrete results.
After just 1 quarter, we already have 18 clients who have chosen this new model, and our subscription model accounts for a significant portion of our recent pipeline growth. We look forward to expanding this in the future. The AI world is moving at incredible speed, and there are 2 major races going on. The first is over who builds the best foundational models or agents. And that race is OpenAI, Anthropic, Meta, xAI and other. Every week, new models, frameworks and tools emerge, but this is not our race.
The second is about who applies AI better, faster and with greater return on investment on specific business cases for every company in every industry. For companies, the expansion of all these new foundational models present an immense opportunity, but also a challenge of determining the right combination of models, tools and approaches for their specific needs while managing data privacy and compliance.
It is more like entering in a dense and constantly changing forest where familiar paths disappear and new ones open overnight. In that environment, you need not chest him up, but an experienced guy who knows how to adapt the route as the terrain shifts. At Globant, we take on that role, helping our clients find the safest and most effective path forward.
We remain 100% client-centric while leveraging our deep partnerships with all major AI leaders to ensure our clients get the best of each ecosystem. This means we can select or combine the most advanced models and capabilities available in the market, integrating them in ways that are tailored to each unique task and business context.
Globant Enterprise AI is the toolkit we bring into that complex forest. It is the golden path for our customers' generative AI adoption and impact. Offering seamless access to all major LLMs, it provides traceability, auditability and granular access and cost control. It includes a library of hundreds of industry-tailored plug-and-play business processes and a state-of-the-art retrieval augmented generation pipeline optimized for proprietary corporate data, delivering faster, more relevant and contextual precise insights.
Enterprise AI integrates with major enterprise platforms, manage AI-driven workflows across department, connects human teams with intelligent agents and is fully compatible with A2A protocols and MCP servers. The platform use a token-based execution model to align AI usage to measurable business value. We launched the 2.0 version of Globant Enterprise AI.
Diego will go into more detail on this shortly. When you combine that with the industry-specific expertise of our AI studios, you get a fully integrated engine for transformation across the entire AI value chain. We go beyond offering AI services. We architect and connect every layer of the AI stack, then deliver it as scalable subscription-first solution.
Our AI studios continue to drive deeper engagement with major global clients, unlocking cross-selling opportunities and deploying specialized talent from across our global network and restricted by regional boundaries. Part of growing is partnering with the best. A couple of weeks ago, we announced a multiyear collaboration with OpenAI as one of their few global services partners.
By combining their world-class models with our engineering capabilities, we're delivering secure, responsible and scalable AI adoption worldwide. We're already integrating GPT-5 across all layers of our enterprise AI platform and embedding it into our AI Pods processes. Along a similar line days ago, we took a big step forward by becoming one of the few global partners to sign a strategic collaboration agreement with Amazon Web Services.
Diego Tartara will expand on this later.
We have teamed up with LaLiga, Spain's premier football league on a multiyear transformation program through Sportian, our sport tech joint venture. This is not just a technology project. It is a game changer. By embedding our AI pods at the heart of their operations, we will unlock the full power of AI agents in sports to boost team performance, deepen fan engagement and drive operational excellence across the league.
It is a clear example of how global enterprise AI is helping world-class organizations to embrace AI at scale and win in the most complex high-profile arenas. We have strengthened our position in the robotics and AI ecosystem by investing in InOrbit, a leading robotics integration company. This expands our capabilities, enabling advanced orchestration of different fleets of robots and autonomous systems across industries.
It ensures we can integrate physical automation into enterprise workflows at scale, connecting AI agents not only to digital process, but also to real-world robotic operations. Today, our revenue mix is more diverse than ever. North America remains our largest market with 54.1% of our revenue. Latin America accounts for 19.7% and is showing strong recovery with new records in bookings. Europe represents 19.6% and is our fastest-growing region sequentially, up 8.1% with major wins in aviation and financial services.
New markets grew an impressive 84% year-over-year and is currently 6.6% of our total revenue. The Middle East leads this surge, driven by our work on several Giga-projects. Our 100 square program continues to gain momentum with our client base growing and diversifying. And Diego will share more on recent client wins and large-scale engagements that illustrate this strong momentum.
49 clients now generate more than $10 million in annual revenue, up from 39 a year ago. 339 clients generate over $1 million annually, up from 329 last year. Over the past 21 years, we have earned a unique position in our industry by fusing advanced technology, human creativity and a deep understanding of our clients' needs. In 2025, the complexity of the environment is matched only by the scale of the opportunity as AI redefines business models, value chains and competitive advantage.
Our mandate is to help clients navigate this change with precision and foresight, capturing value across every layer of the AI stack. With AI Pods, our subscription model, AI studios and the 100 square approach, we're delivering Globant as a full stack AI company, one that designs, builds and integrates technology platforms and industry-specific expertise into scalable solutions.
This integrated model ensures we remain not just relevant but indispensable as enterprise embrace the AI-powered future. We're as energized by the challenges ahead as we are by the opportunity. And with this team, I have no doubt we will capture them all. Thank you very much.
Hello, everyone. I'm happy to be back. I want to expand on the offering of Globant's Enterprise AI 2.0 version that now includes and Agent to Agent and the marketplace of Agent for its users, among other new features. It enables a full AI adoption addressing 3 core needs of our clients.
First, governance. Organizations need to be in control of their own AI journey with strong security, risk management, traceability and guardrails for both models and conversations. Globant Enterprise AI provides leaders with the control they need to map their exposure to both cost and risk.
Second, build capability. Companies need the tools to create and deploy solutions connected to the enterprise systems. Globant Enterprise AI platform is home to the lab for Agent creation, orchestration and ensuring interoperability. As of this quarter, the lab now supports the model context protocol and the agent-to-agent protocol. These enhancements allow seamless integration of agents and tools from across the AI ecosystem like Google Cloud, Azure AI Foundry and Amazon Bedrock.
And third, impact, the ability to explore, combine and share solutions and to operate them so they can generate measurable business outcomes. This is where AI moves from pilot to scale adoption, ensuring that investments translate into tangible value across the organization. In this layer, we have recently launched a specific module for our clients called the station. It offers a curated searchable library of in-house built AI agents tailored to diverse business and industry needs, streamlining discovery while removing friction.
With just a few clicks, users can now deploy agents via intuitive orchestration tools, speeding time to experimentation and value. Organizations using Globant Enterprise AI have reported an 80% reduction in legacy systems modernization times and a 50% increase in software development costs. Globant Enterprise AI also powers a lineup of hundreds of industry-specific agents along with 3 flagship agents tailored to each of our core studios.
Globant CODA is our Agentic suite for our digital studios, a key component of how we reimagine software development life cycles and how we deliver value. Navigate for our enterprise studio. It optimizes business operations and performance and FUSION from GUT Studio launched at Cannes Lions this year, it enhances full funnel marketing, communications and advertising. It streamlines processes from content creation to campaign optimization.
Now let's discuss our work with some fascinating clients as we partner with them on their reinvention journey. In gaming, we're working with one of the leaders in producing real-time 3D content to deliver interactive solutions to high-growth sectors, including digital twins, automotive, health care, life sciences and manufacturing. By employing our global delivery network, we will be helping this company to expand to new commercial markets, unlocking new business for them.
On the technology side, we will be integrating their products into enterprise technology stacks, supporting new go-to-market strategies and codeveloping tailored solutions. Our sustainable business studio is proud to be collaborating with the Worldwide Fund for Nature. Together, we are developing tools that link traceability with carbon footprint assessments. This initiative engaged multiple stakeholders, including national agribusiness entities, industry leaders and civil society, facilitating the transition towards more sustainable meet production practices.
The complexity and the time-sensitive nature of the challenges the WWF faced led them to unlist our low-code GeneXus platform. This collaborative effort will accelerate the adoption of sustainable practices, support regulatory compliance and empower producers globally. We're excited to announce a partnership with a world leader in premium spirits to develop a generative AI-powered commercial insights agent.
This innovative tool will provide our clients' employees with immediate access to critical data insights, streamlining decision-making in product development, marketing, sales and strategy. By automating data retrieval, we are helping them to reduce the time and cost of traditional business intelligent workflows, allowing the teams to focus on strategic initiatives. The agent will enhance efficiency through self-service decision support and tailored recommendations.
This initiative is just the beginning as the commercial insights agents will lay the groundwork for future applications in brand planning, commercial forecasting and innovation. We are redefining the potential of AI-powered enterprises and unlocking new growth opportunities.
Regarding our partnerships, days ago, we advanced our relationship with AWS by establishing a strategic collaboration agreement to accelerate AI adoption and enable Globant to provide clients in specific industries with enhanced support for cloud migration, generative AI adoption, industry-specific solutions while helping them to optimize their cloud usage and manage expenses efficiently.
We're collaborating with Salesforce to deploy Agentforce and Data Cloud across multiple industries, automating their teams and enhancing their ability to support their customers, tailor marketing journeys and better segment their clients. As Globant's creative industry pillar, GUT advanced on large-scale projects for top brands, including Progressive, Procter & Gamble, DoorDash and more as well as new projects for Havaianas, RIMOWA, among others. Thank you, everyone, for joining us again.
Hello, everyone. I will now review our Q2 2025 financial results before providing our outlook. Our performance this quarter is very aligned with our expectations back in May. Revenue for the second quarter came in at $614.2 million, representing 4.5% year-over-year growth or 1% in organic constant currency and 0.5% growth sequentially. Our non-IFRS adjusted operating margin was 15% for the quarter, holding steady despite some FX headwinds in LatAm currencies and demonstrating pricing and cost discipline in a tough market environment.
Non-IFRS adjusted diluted EPS for the quarter was $1.53 an increase from the $1.51 we reported in the second quarter of 2024. Turning to the balance sheet. Our cash and cash equivalents and short-term investments totaled $174.2 million. Net debt as of June 30 was $255 million. During this quarter, we increased our debt capacity to up to $1.1 billion. Free cash flow for the quarter was negative $2.9 million compared to negative $28 million from the same period last year.
As always, we expect to generate strong free cash flow during the second half of the year. This quarter, we executed a business optimization plan. As explained by Martin, during Q2, we launched a new go-to-market strategy centered around our AI industry studios and our 100 square accounts. The recently launched Globant subscription model based on AI and our proprietary Globant Enterprise AI platform is getting traction with our customers.
While we have delivered strong growth for many years, we have observed a more tempered demand environment over the last few quarters. The business optimization plan is part of our response to this organizational and demand changes and to best position ourselves for the next wave of growth. The primary goal of this plan is not only to protect our near-term profitability, but more importantly, to create the capacity to increase our investments in strategic growth areas for the rest of 2025 and beyond.
This plan ensures we have the right talent and resources to execute on our AI-centric strategy and capture future opportunities while managing our cost base on the current market. The main actions under this plan included a comprehensive review of our workforce to align skills and size with our strategic priorities, which resulted in a reduction of approximately 1,000 employees or 3% of our workforce during Q2, a consolidation of our global office footprint based on an analysis of our facilities and lease contracts and the strategic prioritization of our delivery centers to support future expansion.
In connection with these actions, we recorded a onetime charge of $47.6 million in the second quarter. This plan should generate $80 million in annualized savings. These savings will be critical in protecting our profitability in the short term despite FX headwinds in LatAm and will also be reinvested to fuel our growth engines, specifically our AI platform development and our people.
We are taking decisive action now to build a more resilient and agile organization, ready to lead when the market accelerates. Now let's talk about our business going forward. Based on current visibility for the third quarter of 2025, we expect revenue to be at least $615 million, which implies 0.1% year-over-year growth. This expected growth includes a positive FX impact of 50 basis points.
We expect a non-IFRS adjusted operating margin to be at least 15% and the IFRS effective income tax rate is expected to be in the 20% to 22% range. Non-IFRS adjusted diluted EPS is expected to be at least $1.53 per share, assuming an average of 45.6 million diluted shares outstanding during the third quarter. For the full year 2025, we now expect revenue to be at least $2.445 billion, representing 1.2% year-over-year growth.
This expected growth includes a positive FX impact of 25 basis points. For the full year, we now expect our non-IFRS adjusted operating margin to be at least 15% and the IFRS effective income tax rate is expected to be in the 20% to 22% range. Our full year non-IFRS adjusted diluted EPS is expected to be at least $6.12 per share, assuming 45.5 million diluted shares outstanding during 2025. Thank you for your continued support.
Thank you, Juan, and hi, everyone. So as we go through the Q&A section of this call, I will announce their name. [Operator Instructions] So with that in mind, thank you very much. And we'll take the first question from the line of Tien-Tsin Huang from JPMorgan.
2. Question Answer
I wanted to ask just on the AI-based delivery model. And I think you mentioned on the subscription side, you had 10 clients that chose that model. I think I heard that. Can you tell us a little bit more about that? What work is being done? And how would the work and maybe the contract terms compare to what you would normally see in a more traditional model? Maybe start with that, if that's okay.
Thank you so much for the question. It's -- actually it's 18 customers.
18, sorry.
18 paying customers. And yes, look, the pipeline grew incredibly fast in terms of opportunities. We also were able to generate those 18 paying customers under the subscription model, and that has been very well received by our customers. What we do is on the back of all these customers who were doing Agentic AI, generating the code, the development, the need -- the software that our customers need. And we are charging that with that subscription in which we are taking the risk on our side of supervising what the agents create.
So supervision -- we hope that, that supervision with time will go down. And now it's at levels in which we want to be sure that we get the same quality as the traditional model that we have. So we're extremely excited with what we are seeing with our customers and the type of contracts is sometimes like the large portion of the discussion with the procurement offices and so on and so forth because it's kind of a new place where they haven't -- they never heard about.
But I'm very happy with the results. I'm very happy with the pipeline, how well received was with our customers. Kind of they are used to -- or they understood the model of having a subscription and limits on tokens. So I don't know, Diego, maybe you can.
No, I think, Tien-Tsin, for the most part, -- the most mature aspect is actually how we deliver value, which is how do we build software and the approach that we took. I think it was the most difficult and risky because this is actually changing rethinking about the way of doing it. This is not infusing AI into an existing processes. We reshuffle the whole thing to make the most out of it.
And that's actually complex because you need to convince your client that has been working on a certain way for a long time. You need -- you even charge for this service in a different manner, but you bring and make reality what has been a promise, which is the positive impact of AI on an enterprise environment.
And like Martin said, reception was amazing. I thought getting traction out of this would have been a little bit more complicated, et cetera, but the market and then our clients understood this perfectly well. We received the right type of questions, which is amazing. So pipeline is growing healthy. And I'm actually convinced that this is a major change that will definitely propel the future of Globant.
And by the way, Tien-Tsin, the growth on the pipeline -- a good portion of the growth of the pipeline between last quarter and this quarter is because of this. So it's new conversations and now things are triggering out. So we're very happy.
Okay. I know it's a lot of -- and I respect you guys are pushing for this so hard so quickly. It's great. So just you mentioned the pipeline, and it sounds like there's a lot of AI content overall in the AI side -- on the overall pipeline. So are you assuming a lot of conversion of the pipeline in the outlook in the second half? What's changed there? And do you expect some of these deals to close, for example, in the second half? Or could they get pushed even further out given the newness and what's happening there?
We're seeing the conversion -- I mean, the macro still is pretty uncertain. So we decided to go on the conservative side. We're seeing conversion in August and conversion like doing very well and much better than expected. And so we're positive about that. But we want to remain very cautious around the idea of the second half of the year.
The next question comes from the line of Bryan Bergin from TD Cowen.
So I'll ask on the optimization. Maybe can you talk about how far through those initial changes you have progressed? We could see the 3% billable headcount reduction on a sequential basis. Should we expect any further activity kind of carry through into 3Q as well? Or is that now through the system?
So on the headcount side, you're going to see some additional reductions happening in Q3, which already happened by now. The costs have all been accounted for during the second quarter because the plan was all provided at that point in time. There is also additional effects that are going to happen throughout the rest of the year in terms of the office consolidation and the talent development consolidation that we are doing. But the vast majority of the plan has been already implemented, especially on the people side. Between what we did in Q2 plus some additional adjustments in Q3, that's already done.
Okay. Okay. And then my follow-up is on the creative performance. So can you give us a sense how GUT performed here, really the creative pillar relative to other studios. And I ask because there's incremental concerns on the street about these particular areas from Gen AI risks, right, and the ability for enterprises to do more themselves. So I'm curious if you're seeing any trends specifically around that creative area that would support or refute that perspective.
Yes. It's a quite small operation, though, but it has been growing nicely.
18%.
So we're very happy with that. And I would say that from the quality and the caliber of work that we do, it's not the work that would be affected faster by the AI. I think that for those that are doing like the outsourcing of generation of images and creation of specific campaigns for different channels, that impact could come faster. Our FUSION agent is targeting those kind of customers that want to automate that pipeline of creation of content.
So I'm very bullish about the idea of how our entering into that creative space will grow in the future. So what we are seeing is that between all the technology that is coming into the marketing space plus the amazing brand that we have with GUT in the space, we're creating like a very good momentum for the future. And we are -- I'd say we're fully aligned with all the efficiencies that can be made in that space. So I don't see that as a threat even more, I see it as an opportunity.
And also, Brian, when you look at how we create revenues in that, the vast majority comes from branding -- company branding, company positioning, it's very high level, very strategic positioning of companies. It's not that much at the kind of campaign or short-term campaign or advertising that you could assume that might get impacted. So we are not seeing impacts there. On the opposite, it's one of the fastest areas of growth at Globant.
The next question comes from the line of Maggie Nolan from William Blair.
I'm wondering if the enterprise AI platform is creating enhanced stickiness with your customers compared to maybe traditional more project-based engagements.
That's a great question, Maggie. Look, I think that there's -- the enterprise AI platform is like the golden path for generative AI adoption for our customers. It's an enterprise class kind of integration of all the very, very complex AI ecosystem that is there to make it tangible, to make the things work. So you don't just marry with one LLM provider, but you can choose which to use.
And then you can integrate all the workflows in your company and then you can connect with all the corporate information systems and then you can create your agents to generate those processes that companies need. So we are using enterprise AI for every single engagement on the AI pods side. We are using enterprise AI for many customers that are finding or trying to find a safe path to implement AI inside their corporations.
So it's becoming like a key component, as I mentioned on our last earnings call, it is a key component for the creation of the AI ecosystem inside corporations where you don't just need to access LLMs, but you need to administer permissions, you need to administer access, you need to control costs of the things that you do. There's a lot of things that happens on the inner work of an enterprise class implementation of AI that is bring to life or brought to life by enterprise AI.
So for me, it's extremely essential. It can be mounted on top of all the big hyperscalers platforms. It can use many of those services. So it is very well integrated into our solutions. And I think moving forward, it will be a key component of everything we do. So I don't know, Diego, if you want to.
No. Just to add to that, Maggie, I think Globant type of services and delivery quality have created a great stickiness with our client. And you can see that by the low churn and maturity, especially on the top accounts, which have more than 10 years with us right now. However, from a model perspective, in this specific case, you're actually -- the service as a software model where you actually build someone that's bespoke but based on a platform and you have the opportunity to operate that as well I think it's a great way of outsourcing functions as opposed to the traditional BPO.
So from the software delivery perspective, you leave something with your client, which is they have the opportunity to use GeneXus Enterprise AI to build their agents, et cetera. And we can help them build custom maintain and operate solutions for them. So from the pure model itself, I think the answer is clearly yes, it provides more stickiness.
That's really interesting and kind of exciting to hear for the business model. And then one other thing I wanted to ask about the script, it sounded like there were a couple of larger deals that were close to closing. Maybe comment on those and the growth trajectory you're expecting by geography, by vertical kind of revenue growth and how the pipeline is shaping up?
Okay. So Maggie, just a couple of deals that we are seeing now, a big deal on the financial services space, which is right in the final stages and also another big deal on the health care and life science space. Both of them in the U.S., which are pretty exciting to see how the market is recovering.
Also, we are seeing some deals on the enterprise side for CPG companies in Latin America. Also, Latin America is recovering as is explained on the numbers, too. So we're seeing like good signals across the board. And it looks like the U.S. is recovering, Latin America is recovery, which was the 2 big things that we had on our last earnings call. I don't know, Juan, if you want to.
Yes, definitely. When you look at LatAm, after going down for a number of quarters, this is the first quarter it's sequentially up. So I think that's good news. It shows like a stabilization, and we are seeing and we are making progress towards the end of the year -- for the rest of the year, in LatAm. In the case of the U.S., when we exclude some of the impact from professional services and some of the -- some small impact on technology, the rest looks okay. BFSI with a very strong performance. Travel and Hospitality, very strong performance.
So in general, yes, we are coming out of a number of quarters where the level of growth is lower. However, we start to see some positive numbers and some -- especially on the pipeline. When you look at the deals, it continues to expand. So in a way, we are just getting ready for that recovery whenever it comes.
The next question comes from the line of Jonathan Lee from Guggenheim.
Can you help unpack some of the assumptions around the revised growth outlook and maybe the level of conservatism you're assuming? And how should we think about any potential acceleration off of your implied 4Q exit rate, if any?
Yes, sure. So when you look at the guidance back in May and the new guidance, basically, there are a number of things that happened in the quarter. When we look at the second quarter, we were able to meet or slightly exceed actually the guidance that we provided. Looking into the full year number, I mean, as you remember, we had a significant reduction in the guidance for the year back in May.
Now you look at the EPS for the year, it is slightly up. There's a small tweak on the revenue line, mainly coming from one professional service customer and some small things that happened in technology. But overall, just a small tweak there. At the same time, when you look at Latin America, it's not coming down anymore. Sequentially, it was up this quarter. We are seeing kind of a stabilization and starting to build up based on the pipeline.
When we look at the end of the year, I think that when we look at the U.S. economy, at some point, things will start to get better. We're not seeing further deterioration, which is good news, but things will have to get better. Companies will need to invest in the near future. They cannot withhold investments forever. So that's something that's going to have to happen.
When you look at the size of the pipeline, the pipeline, it continues to build. When you look at all the changes that we did in our go-to-market with AI industry studios, the success that we are starting slowly but steadily showing progress on the subscription model. I think those are good -- all good things that are shaping up, and we expect that to start getting traction in the future.
So I think we are doing a lot of changes. We did a lot of changes on the structure. We did a lot of changes to have the right people with the right skills in front of customers, people with the right skills given the new technologies that are coming that resulted in a significant business optimization plan. So we are doing lots of things to make that progress that I think is going to happen in the near future. We are working.
And also as a general comment, I think that the amount of the opportunities are showing up on the pipeline. But I would say that as a general understanding of this -- of all the things that are happening is that the amount of new projects, as we have been saying for many, many quarters, the amount of new projects is incredible.
And the complexity in any corporate environment to implement any of these agents into production with the right railways for the LLMs, with the right access permission, with the complexity of connecting with production data, with the complexity of implementing that and then taking it to -- and spreading it out in a big organization, we are leaving it ourselves. We want to implement agents, it takes us a while to generate even using the most sophisticated tools, take us a while to make it happen in the whole organization because we need to connect to complex systems.
And that is creating like a massive set of opportunities that before didn't exist. This is on top of all the digital transformation work. This is on top of all the enterprise migration that is happening and will keep on happening. So I think the opportunity for us is massive and it's reflected on actual numbers. First conversion has been slower, but I believe that little by little, these corporations will come to us saying, listen, we need help to implement this.
Now we need -- we have seen the first cases. A year ago, I was saying well, this is like very small like small and proof of concepts that are happening. Now we're seeing customers saying, "no, I want like a full AI transformation program to change my processes" because I discovered that it's not that easy to make it happen, and we need help.
So that's creating like a massive opportunity for us. And I believe that's why I'm so bullish about the future of our company and all the moves in which, of course, new ways of delivering the same things are needed, and we are delivering that. So I'm extremely excited about what's coming.
On the heels of those opportunities, can you talk through some of the pricing discussions you're having, particularly around potential impact to pricing from your AI pod model as well as just given the rather competitive environment that you're seeing today?
Yes. Jonathan, listen, the pricing of our AI pods leads us to a much better margin than what we have on a traditional project. So I think that explains by itself. I don't know, Juan.
No, at the same time that it has better margins. It is cost effective for the customer as well. So it's a model that so far, the way we are selling it, the way we are contracting with customers is a win-win. So they are getting part of the productivity gains. We're getting part of the productivity gain. So it's working well. We need to make sure, as Martin said at the beginning, that we continue to deliver the same quality that we have always delivered to our customers.
So over time, as the coding gets better, the agents get better, we should even be able to hopefully improve a little bit those margins. But it's marginally positive and pricing, it gives customers some efficiencies straight away.
Next question comes from the line of Divya Goyal from Scotiabank.
We cannot hear you, Divya. We cannot hear you. It looks like you're on mute.
Let's go to the next question, and we'll come back to Divya, I'm sorry. The next question comes from the line of Sean Kennedy from Mizuho.
So I was wondering about the North American deceleration. Was that due to certain like planned projects ramping down and lower conversion in the last few quarters? And how has the North American pipeline conversion been trending since May?
Thank you, Sean, for the question. So North America was sequentially down 2%. It's very much focused on a customer in professional services and some small customers in technology. But when you look at the pipeline, when we look at some of the deals that we recently closed that Martin mentioned in health care, in BFSI, and we are optimistic.
I think that after several quarters of instability and changes and tariff discussions and macro and all that, things are not great, but at least they are more stable in a way. We are -- we look at the pipeline, the majority of the pipeline is getting built out of the U.S. And we believe that with the new go-to-market with AI studios, industry studios, we're going to be able to take advantage of that.
So we are positive on North America. Of course, Martin mentioned at the very beginning, deals take longer to close. That is something that was not common in the past. I mean, at least a few years ago. We are now living with that. But we start to see some big deals getting closed, which was difficult a couple of months and quarters ago. So bigger deals are starting to close again.
Got it. And then in Latin America, it was nice to see the sequential growth there. Could you kind of discuss in more detail about what you're seeing on like country-by-country basis?
So Argentina is probably the best performing country around this time in the region. We start to see recovery in Brazil, Peru and Mexico. And they are not all of them growing, but we are not seeing the deterioration that we saw, for example, in Brazil and Mexico earlier this year or late last year. So we see the stabilization there, some recovery in the case of Mexico and a very strong Argentina.
The next question comes from the line of Nate Svensson from Deutsche Bank.
I wanted to follow up on Jonathan's question on pricing. So nice to hear that the new subscription-based model is going to be accretive. But if we think about sort of revenue per head dynamics, excluding that, just 18 projects so far, a relatively small portion of the base. I think last quarter, revenue per head was up 2.8%. We have it a touch lower, maybe closer to 1% this quarter. So just wondering how you're thinking about pricing trends for the overall book of business for the remainder of the year, especially given all the dynamism and uncertainty in the macro.
Yes. So far, we have been able to either maintain or slightly grow our revenue per head, which I think given the market that we have seen in the last 2 to 3 years is quite remarkable. So we have been -- maybe at the expense of sometimes growth, we have been very consistent on trying to maintain our pricing, trying to maintain our margins, working hard to protect profitability and somehow the results have been showing that over the last 2 years.
Pricing, yes, it's not a very hot market. So pricing is a challenge and you have to negotiate. But we, as a company, we believe that we need to protect profitability. We need to have deals that are -- makes sense for the company, right? We don't want to -- we always try to protect margin for -- since we were public.
And our margins actually, if you look at gross margins, they've been between 38% and 41% for the last 15 -- 10, 12 years as a public company, right? So for us, we know it's easy to take prices down, but we work very hard to avoid those situations and the revenue per head shows that as well.
Yes, makes sense and it's good color. And I guess related to margins, I wanted to ask about utilization as well. I think last quarter on the call, you talked about improving utilization as a potential margin lever opportunity. So I think last quarter, utilization fell sequentially and year-over-year to, call it, 78%. Any update on what that was this quarter? And then in light of the business optimization, I guess my guess would be that utilization maybe gets a little better, but expectations for the rest of the year?
Yes. Utilization is up about 40 basis points this quarter, and we expect to take it even further up with all the business optimization plan that we did, part of that creates or improves our utilization rates as well. So we always talked about 80% to 81% as a target utilization number, and that's still valid, and we are working towards that. We also mentioned in the past that in a very hot market, it's always easier to drive utilization up. But I mean, we are making progress. And this quarter, we were able to increase that by about 40 basis points.
The next question comes from the line of Leonardo Olmos from UBS.
Can you talk a little bit about the potential or not concentration of consultancy firms or IT services among clients? I mean, are clients talking to newer firms? Or are they just concentrating the biggest one? Because I thought and please correct me if I'm wrong, that you may be not growing that much with clients with revenue around on top of $1 million. If that's the case, please correct me. But all in, I want to know how competition is and how prices are and if clients are concentrating with lower number of IT services companies?
Yes. We have been running a lot of these consolidation processes. And the good news is that we have been selected in all of them. And I think that -- or in pretty much all of them. So that's one thing. The second thing is we have more accounts yielding more than $1 million than a year ago. So that speaks by itself in the -- to your question. And the other thing is, yes, companies are looking for a differential offering. They are tired about the traditional big massive consulting firms that do not innovate or that they are not bringing anything new to the table.
And one of the reasons why we are being able to maintain our position and leadership is that we are offering something new. And we are telling to the market, listen, the model will change, and we are changing faster than that. So I'm extremely excited about that. And I think that the future will keep on showing that smaller companies like Globant, right, has a much higher impact on how corporations transform themselves to become the next versions of themselves. So I'm very bullish on that. But please, my teammates here.
No, no. I think like Martin said, vendor consolidation happens cyclically on a cycle. We've been through many of them, and most of our top clients have done that. And those were actually opportunities for us because we ended up -- in the vast majority, we ended up selected. I think that at this particular moment, what it's interesting is that procurement instead of coming up with consolidation, et cetera, because of a requirement of the business, on the contrary, opens up.
And what this means is it opens the possibility to bring boutique type of companies. Why is that? They're smaller, they react fast to changes in the technological landscape. So typically, when these major changes happen, you see the opposite. As opposed to consolidation, open it up and soften the vendor selection. What's good about this is that we've been running alongside those companies and we've been getting those type of opportunities.
In most of our clients, we're either leading AI or executing our client strategy. Many of our clients have either selected a Chief AI Officer or their Chief Data Officer has put together a strategy. And they said, "Globant, now I need your help to scale that -- this." So -- and I think that's the most important aspect that I would like to quote. It's not -- the other process has been running over and over for a long time. But when this happens, you set apart companies that innovate fast, that take bold decisions from the ones that take longer.
Yes. And also our focus on 100 square program, right? I mean we are paying a lot of attention to those accounts that can multiply for us that can -- that has the potential of having a larger need of making these massive transformations. And I think that, that approach is extremely important for our future, and we will keep on paying a lot of attention and our best people into those accounts.
Thank you very much, Leo. So that will be all for the Q&A section of today. Thank you all. And with that, I...
Can you all hear me? Thanks for bringing me back. I really appreciate it here. I just want a little bit more color. I know you provided a lot of information on the AI pods. But could you help us understand what's the scale and scope of some of the engagements you're seeing? And are you seeing some of these engagements expand into existing clients? Or are you also seeing some net new clients adopting and getting interested in this AI pods methodology or a solution offering that you have?
Divya, listen, the pipeline contains like a lot of new customers, and I would say more than half is current customers. The conversion itself has been on current customers and the new customers -- and some new customers, but I would say that the vast majority of what we closed today are current customers plus 2 or 3 new. So -- but it's very interesting to see the dynamics inside the pipeline because inside the pipeline, you have a lot of customers transforming deals and making deals they used to be like traditional deals, but now moving into this new subscription model.
And then we have a lot of new customers that we didn't have before. So we announced it. It was quite low profile. We just sent e-mails to some of our -- but I received, for example, an e-mail from a hyperscaler saying, "Hey, Martin, look, we understand this quite well. We like what you're doing, and we would love to know more about it," and that happens yesterday.
So what I'm saying is creating momentum, Bain Capital -- sorry, not Bain Capital, Bain Consulting put out a report to talk about the new model like it was a very interesting report talking about how this new model should be the next choice model. And we're very excited. But I don't know -- covered it all. Okay. So that's the answer, short answer. You have one more.
It's great. It's very exciting. I can tell you, as an outcomes-based pricing models pick up across the sector you're definitely leading the trend is what I would say. One more question that I wanted to understand, like I know some of your peers have been talking about helping global enterprises set up global capability centers or GCCs, is that something Globant has been participating in, helping the global enterprises grow their offshoring unit? And what is the role, if at all, that you play in there? That's all for me.
Yes. The answer is yes. We are participating in many of those deals. One of the deals that we're just about to close or is closed already is about taking over one of these centers. Our proposal as opposed to the traditional proposal is a proposal that includes our AI pods, and it's something that we're pretty proud because we won because of that.
And I think that is something that -- I mean, this new strategy, this new AI Pods model comes with 2 things. First, it makes savings tangible. And second, it provides a level of transparency of what we do that is unparalleled to any other model in the past. So we can give you a report of every single token that we used and how we use it and which is the artifacts that has been created using those tokens and how we supervise that and how we make sure that all those things make sense.
So in essence, I believe that it's a breakthrough on the offering is something that we're extremely excited. But yes, we are participating in all these deals. And hopefully, we will win them all.
Thank you Divya and I apologize for that. Thank you. So with that, we conclude the Q&A section for today. Thank you all. And now I will turn it over to Martin for some closing remarks. Please go ahead, Martin.
Thank you, Arturo, and thank you, everyone, for participating, for your continued support and looking forward to see you on our next earnings call. Chau, bye-bye.
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Globant SA — Q2 2025 Earnings Call
Globant SA — Q2 2025 Earnings Call
📊 Quartal auf einen Blick
- Umsatz: $614.2M (+4.5% YoY; organisch in konstanten Währungen +1.0%; +0.5% q/q)
- Pipeline: $3.7B (+25% YoY; All‑time high)
- Marge & EPS: Non‑IFRS Betriebsmarge 15%; adj. diluted EPS $1.53 (vs $1.51)
- Bilanz: Cash & Äq. $174.2M; Nettoverschuldung $255M; FCF -$2.9M
- Restrukturierung: Einmalaufwand $47.6M; ~1.000 Stellen (~3%); erwartete Einsparungen $80M p.a.
🎯 Was das Management sagt
- AI‑Pods: Subscription‑basiertes, outcome‑orientiertes Modell (Verbrauchs‑/Token‑Pricing); 18 zahlende Kunden nach einem Quartal; Pipelinewachstum stark davon getrieben.
- Enterprise AI 2.0: Plattform‑Updates (Agent‑to‑Agent, Marketplace, Retrieval‑Pipelines); Integration mehrerer LLMs und Audit/Governance‑Funktionen; GPT‑5‑Integration erwähnt.
- Strategie & Partnerschaften: Fokus auf hohe Kundenwerte (100‑square‑Accounts, AI‑Studios), strategische Partnerschaften mit OpenAI und AWS sowie Investition in Robotik (InOrbit) zur Verknüpfung digitaler und physischer Automatisierung.
🔭 Ausblick & Guidance
- Q3 2025: Umsatz mindestens $615M (~+0.1% YoY; beinhaltet +50bps FX), Non‑IFRS Marge ≥15%, adj. EPS ≥$1.53 (verw. Aktien ~45.6M).
- Gesamtjahr 2025: Umsatz mindestens $2.445B (+1.2% YoY; inkl. +25bps FX), Non‑IFRS Marge ≥15%, adj. EPS ≥$6.12; IFRS Steuerquote 20–22%.
❓ Fragen der Analysten
- Skalierung AI‑Pods: Analysten fragten nach Vertragsstruktur, Umfang und ob Wachstum aus Bestandskunden oder Neukunden kommt; Management: Mehrheit aus bestehenden Kunden, aber auch neue Interessenten.
- Konversion & Timing: Pipeline hoch, aber längere Verkaufszyklen; Management bleibt vorsichtig, erwartet Konversion in den kommenden Monaten, betont Unsicherheit durch Makro.
- Kosten & Auslastung: Bereinigungsplan größtenteils umgesetzt; weitere Reduktionen in Q3 möglich; Utilization +40bp in Q2, Ziel weiterhin ~80–81% und $80M jährliche Einsparungen zur Reinvestition.
⚡ Bottom Line
- Fazit: Solides Margenprofil bei moderatem Umsatzwachstum; kurzfristig belastet durch $47.6M Einmalaufwand, mittelfristig Upside durch AI‑Subscription‑Modell, große Pipeline und Partnerschaften; Hauptrisiko bleibt die Geschwindigkeit der Pipeline‑Konversion in einem zögerlichen Makroumfeld.
Finanzdaten von Globant SA
Umsatz
Der Umsatz stellt die Summe aller Einnahmen eines Unternehmens z. B. für dessen Produkte oder Dienstleistungen dar.
Umsatz (TTM) einfach erklärtDirekte Kosten
Direkte Kosten sind die Kosten, die direkt im Zusammenhang mit der Herstellung des Produkts oder der Dienstleistung entstehen.
Bruttoertrag
Der Bruttoertrag gibt an, wie viel vom Umsatz nach Abzug der direkten Herstellkosten im Unternehmen verbleibt. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von der Bruttomarge (engl. Gross Margin).
Brutto Marge einfach erklärtVertriebs- und Verwaltungskosten
Die Vertriebs- & Verwaltungskosten (engl. Selling, General & Administrative expenses, kurz SG&A) beinhalten alle Aufwände für Marketing und den Verkauf sowie die allgemeine Verwaltung des Unternehmens.
Forschungs- und Entwicklungskosten
Die Forschungs- und Entwicklungskosten (engl. research & development costs, kurz R&D) geben Auskunft darüber, wie viel das Unternehmen in die Forschung und die Entwicklung seiner Produkte investiert. Vor allem prozentual vom Umsatz und im Vergleich zu direkten Wettbewerbern sind die Kosten interessant.
EBITDA
Das EBITDA (Earnings Before Interest, Taxes, Depreciation and Amortization) ist der Gewinn des Unternehmens vor Zinsen, Steuern und Abschreibungen. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von der EBITDA-Marge.
Abschreibungen
Abschreibungen stellen Wertminderungen von Vermögensgegenständen des Unternehmens dar (z.B. durch Abnutzung von Maschinen).
EBIT (Operatives Ergebnis)
Das EBIT (engl. Earnings Before Interest and Taxes) ist der Gewinn des Unternehmens vor Zinsen und Steuern, das auch als operatives Ergebnis bezeichnet wird. Berechnet man den prozentualen Anteil vom Umsatz, spricht man von
der EBIT-Marge.
Nettogewinn
Der Nettogewinn stellt den Gewinn oder Verlust nach Abzug aller Kosten dar.
Nettogewinn einfach erklärtaktien.guide Premium
| Mär '26 |
+/-
%
|
||
| Umsatz | 2.451 2.451 |
0 %
0 %
100 %
|
|
| - Direkte Kosten | 1.595 1.595 |
1 %
1 %
65 %
|
|
| Bruttoertrag | 856 856 |
2 %
2 %
35 %
|
|
| - Vertriebs- und Verwaltungskosten | 496 496 |
4 %
4 %
20 %
|
|
| - Forschungs- und Entwicklungskosten | - - |
-
-
|
|
| EBITDA | 362 362 |
0 %
0 %
15 %
|
|
| - Abschreibungen | 110 110 |
9 %
9 %
5 %
|
|
| EBIT (Operatives Ergebnis) EBIT | 251 251 |
3 %
3 %
10 %
|
|
| Nettogewinn | 109 109 |
28 %
28 %
4 %
|
|
Angaben in Millionen USD.
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Firmenprofil
Globant SA agiert als ein digitales Unternehmen, das Dienstleistungen im Bereich der Informationstechnologie anbietet. Es bietet Anwendungsentwicklung und -wartung, Tests und Infrastrukturmanagement. Das Unternehmen wurde 2003 von Martín Migoya, Martín Gonzalo Umaran, Guibert Andrés Englebienne und Néstor Nocetti gegründet und hat seinen Hauptsitz in Luxemburg.
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| Hauptsitz | Luxemburg |
| CEO | Mr. Migoya |
| Mitarbeiter | 28.510 |
| Gegründet | 2003 |
| Webseite | www.globant.com |


