Snowflake's 2026 Q3 Earnings Call: Contradictions Emerge on AI Revenue, Guidance, and Customer Behavior

Date of Call: December 3, 2025

Financials Results

• Revenue: Product revenue $1.16B in Q3, up 29% YOY (Q4 product revenue guide $1.195B–$1.20B, ~27% YOY; FY '26 product revenue raised to ~$4.446B, ~28% YOY)
• Gross Margin: Non-GAAP product gross margin 75.9% in Q3
• Operating Margin: Non-GAAP operating margin 11% in Q3, expanded >450 bps YOY (Q4 guide 7%; FY '26 target 9%)

Guidance:

• Q4 product revenue expected $1.195B–$1.20B, ~27% YOY.
• Q4 non-GAAP operating margin expected 7%.
• FY '26 product revenue raised to approximately $4.446B, ~28% YOY.
• FY '26 reiterated targets: non-GAAP product gross margin 75%; non-GAAP operating margin 9%; non-GAAP adjusted free cash flow margin 25%.

Business Commentary:

• Product Revenue Growth and AI Impact:
• Snowflake reported product revenue of $1.16 billion for Q3, up 29% year-over-year.

• This growth was driven by strong performance in core business and expansion into data engineering and AI workloads, highlighted by achieving a $100 million AI revenue run rate a quarter earlier than anticipated.

  

• Customer Acquisition and Expansion:

• Snowflake added 615 new customers in Q3, setting a new record.

• The growth was driven by strong customer retention, with 28% of all use cases deployed during the quarter incorporating AI, indicating increased customer engagement with AI capabilities.

• Operational Efficiency and Financial Discipline:

• Snowflake's non-GAAP product gross margin was 75.9%, with a significant 450 basis point year-over-year expansion in non-GAAP operating margin.

• This efficiency was achieved through disciplined financial operations and strategic investments in sales and marketing.

• Strategic Partnerships and Market Expansion:

• Snowflake's strategic partnerships, such as with Google Cloud and SAP, are enhancing customer value and expanding market reach.
• These partnerships are driving more than 12,600 customers to adopt Snowflake's AI data cloud, accelerating innovation and customer engagement.

Sentiment Analysis:

Overall Tone: Positive

• Management described a "strong quarter," raised FY '26 product revenue guidance to ~$4.446B, highlighted $100M AI revenue ARR achieved early, and pointed to record new customers and expanding margins (non‑GAAP operating margin 11%), signaling confidence and momentum.

Q&A:

• Question from Sanjit Singh (Morgan Stanley): Why did Q3 beat vs. midpoint and how should we square that with a strong Q4 guide; can you color types of customers and use cases adopting Snowflake Intelligence and Cortex AI?
  Response: Q3 essentially played out as expected (29% growth); a hyperscaler outage reduced revenue ~$1–2M; the FY guide is the primary signal of fundamentals; Snowflake Intelligence is rapidly adopted across functions and industries because it unlocks enterprise data for business users.

• Question from S. Kirk Materne (Evercore ISI): With AI, are you landing new logos with more products initially or still landing small and expanding?
  Response: Snowflake Intelligence enables hyper-customized demos/POCs that help win new logos and broaden initial product adoption beyond the core warehouse, expanding surface area.

• Question from Brent Thill (Jefferies): When will AI-influenced bookings convert to go-lives and drive further consumption in back half '26?
  Response: Consumption trends are already driving the Q4 beat; we use ML-based forecasting, are prioritizing accelerating go-lives, and leverage AI to speed implementations.

• Question from Brent Thill (Jefferies): Is the $200M Anthropic commitment in backlog or how should we think about it?
  Response: The $200M is a buy-side commitment (we're buying from Anthropic), part of a commercial and go‑to‑market partnership rather than a simple backlog recognition.

• Question from Daniel Knauff (Deutsche Bank): How did migrations impact product revenue this quarter vs. last, and can you unpack Q4 operating margin guidance?
  Response: Migrations are early but accelerating (AI and acquisitions like Datometry help); large migrations are lumpy; Q4 guidance should not be over-interpreted versus the annual guide—the FY view is the more meaningful indicator.

• Question from Raimo Lenschow (Barclays): How will zero-copy data sharing impact adoption and monetization for Snowflake?
  Response: Zero-copy/bidirectional data sharing accelerates data collaboration, reinforces Snowflake as the single pane of glass, and is a win‑win that supports customer value and platform centrality.

• Question from Arti Vula (JPMorgan): Are customers tying Snowflake budgets to AI budgets and changing buying behavior (longer contracts, more products)?
  Response: Customers increasingly center AI on Snowflake when products deliver real value; enterprise‑grade AI tooling, data structuring, tuning and eval capabilities are driving broader, deeper adoption.

• Question from Matthew Martino (Goldman Sachs): What about the Snowflake platform allows customers to accelerate AI journeys and will the market consolidate on fewer platforms?
  Response: Snowflake's integrated data+AI stack (Intelligence, OpenFlow, Snowpark, Cortex suite) simplifies AI adoption and enables consolidation of more use cases onto the platform.

• Question from Aleksandr Zukin (Wolfe Research): How confident are you in expansion rates as go-lives occur and how should we think about timing of large-deal revenue?
  Response: Customers typically expand into slack capacity post-signing; the consumption model is risk‑free and drives expansion—product revenue and full‑year guidance better reflect trends because large deals are lumpy and timing varies.

• Question from Patrick Edwin Colville (Scotiabank): What exactly comprises the $100M AI ARR and what is the next milestone?
  Response: The $100M primarily comprises the Cortex suite (Cortex AI, AI SQL, Cortex Search, Cortex Analyst) plus Snowflake Intelligence; the next milestone is broader Snowflake Intelligence adoption and making all Snowflake data AI‑ready.

• Question from Brad Reback (Stifel): How do you balance investing to capture the opportunity with driving margin expansion?
  Response: The company will continue to invest (especially go‑to‑market and enablement) while driving operational efficiency and upskilling to expand margins—it's not an either/or.

• Question from Michael Cikos (Needham): Was Q3's upside driven by one‑time migrations and has the guidance philosophy changed on margins?
  Response: Q3 variability is normal in a consumption model; prior quarter included large migrations; guidance philosophy remains unchanged and relies on ML forecasting—refer to the full‑year guide for trends.

• Question from Matthew Hedberg (RBC): How quickly is the $100M AI ARR growing and thoughts on Crunchy Data/Postgres integration vs OLTP/OLAP balance?
  Response: AI ARR is growing rapidly though not being separately guided; Postgres (Crunchy Data) and Unistore will broaden transactional/OLTP capabilities within Snowflake and support agentic solution use cases.

• Question from Tyler Radke (Citi): How are the four 9‑figure deals structured/duration and any FY '27 headwinds/tailwinds to call out?
  Response: Four 9‑figure deals reflect strong customer commitment but bookings are forward‑looking and lumpy; near‑term outcomes depend on consumption patterns—FY‑27 visibility will depend on post‑holiday (Jan–Feb) consumption behavior.

Contradiction Point 1

AI Revenue and Growth

It involves the growth and significance of AI revenue, which is a crucial area of investment and strategic focus for Snowflake.

At what rate is AI revenue growing, and how are customers prioritizing OLTP vs. OLAP in Snowflake? - Matthew Hedberg(RBC)

2026Q3: AI revenue is growing quickly, driven by Snowflake Intelligence. Customers welcome Postgres support, enhancing OLTP capabilities within Snowflake. - Sridhar Ramaswamy(CEO)

Is the outperformance due to demand normalization or AI budget inclusion? - Aleksandr J. Zukin(Wolfe Research)

2026Q2: The core business remains strong, with net revenue retention at 125%. However, AI is increasingly recognized as valuable, with AI components driving additional budget allocation from large customers. This trend will continue to impact revenue. - Sridhar Ramaswamy(CEO)

Contradiction Point 2

Customer Behavior and Revenue Guidance

It reflects differing perspectives on customer behavior and its impact on revenue guidance, which is critical for investor expectations.

Why is the Q4 revenue growth guidance the strongest in years despite a 29% product revenue growth this quarter? Can you share details on the customer segments adopting AI products and the use cases enabled by Snowflake Intelligence? - Sanjit Singh(Morgan Stanley)

2026Q3: We delivered 29% year-over-year revenue growth, and the Q4 guidance reflects customer behavior heading into the next quarter. The annual guidance is the best signal for long-term business trends. - Brian Robins(CFO)

What drove the higher-than-expected consumption in Q2? - Brent John Thill(Jefferies)

2026Q2: The quarter saw significant contributions from large customer migrations and new workloads. Core analytics business growth was strong. Some contribution from Crunchy Postgres, but core business was the primary driver. - Michael P. Scarpelli(CFO)

Contradiction Point 3

AI Revenue Impact and Growth Rate

It involves differences in the reported impact and growth rate of AI revenue, which are critical for understanding the company's strategic focus and financial outlook.

Are customers linking Snowflake investments to AI budgets? How is this affecting purchasing behavior? - Arti Vula (JPMorgan)

2026Q3: AI revenue is growing quickly, driven by Snowflake Intelligence. - Sridhar Ramaswamy(CEO)

How do current macroeconomic conditions compare to the post-COVID downturn, and are there any impacts from current macro issues? - Karl Keirstead (UBS)

2026Q1: Cortex is not a material part of our financials in Q1. - Sridhar Ramaswamy(CEO)

Contradiction Point 4

Sales Compensation and Partnership Strategy

It pertains to the company's sales compensation strategy and its approach to partnerships, which are crucial for revenue growth and market expansion.

Are you expanding your product offerings to increase market reach through AI and Snowflake Intelligence? - S. Kirk Materne (Evercore ISI)

2026Q3: AI demos make the value of transitioning to Snowflake clearer by demonstrating use cases specific to each customer. AI significantly enhances the aperture for new customer acquisition. - Sridhar Ramaswamy(CEO)

How should we interpret new partnerships between data companies and enterprise software vendors like ServiceNow or Salesforce? What changes have been made to the sales compensation model? - Kirk Materne (Evercore ISI)

2025Q4: Partnerships are driven by data centralization. Snowflake plays a central role in data ecosystems. Our partnerships with ServiceNow and Salesforce facilitate bidirectional data movement, while maintaining customer data control. - Sridhar Ramaswamy(CEO)

Contradiction Point 5

Revenue Guidance and Consumption Patterns

It relates to the company's revenue guidance and consumption patterns, which are key indicators for performance and future growth.

When do you expect these go-lives to launch, and how will they impact the second half of 2026? - Brent Thill (Jefferies)

2026Q3: We expect Q4 revenue to be hefty due to strong consumption trends. - Sridhar Ramaswamy(CEO)

What differentiates Cortex Agents from other agent offerings? Can you discuss large customer trends and expansion rates? - Brad Zelnick (Deutsche Bank)

2025Q4: We expect Q4 revenue to be in the range of $1.135 billion to $1.145 billion, and our guidance for the full year fiscal 2023 is for revenue to be in the range of $4.46 billion to $4.48 billion. Product revenue growth for the full year is expected to be in the range of 53% to 54% year-over-year. - Mike Scarpelli(CFO)