Snowflake (SNOW) Q3 2026: AI Revenue Run Rate Hits $100M as 50% of Bookings Influenced by AI
Snowflake’s Q3 marked a pivotal AI inflection with $100 million in annualized AI revenue, one quarter ahead of target, and half of new bookings now directly influenced by AI use cases. Enterprise adoption of Snowflake Intelligence and Cortex AI is rapidly expanding, accelerating both data migrations and multi-product engagement. Raised full-year guidance and robust RPO growth signal durable momentum, while management balances aggressive investment with margin discipline amid a consumption-led model.
Summary
- AI Drives Customer Expansion: Snowflake Intelligence and Cortex AI adoption are accelerating new logo wins and deepening enterprise relationships.
- Consumption Model Validated: Record RPO, stable net retention, and multi-product engagement reinforce durable growth visibility.
- Margin Expansion Remains in Focus: Management balances rapid innovation with operational discipline, reiterating margin targets despite front-loaded investments.
Performance Analysis
Snowflake delivered a standout Q3 with product revenue up 29% year-over-year, driven by durable expansion in both core data workloads and AI-driven use cases. Remaining performance obligations (RPO), a forward indicator of contracted revenue, accelerated to 37% growth, reflecting strong multi-year commitments and a record four nine-figure deals in the quarter. Net revenue retention remained robust at 125%, highlighting the company’s ability to drive incremental value within its expanding customer base.
AI adoption is now a central growth engine: Over 7,300 accounts are using Snowflake’s AI capabilities weekly, and 28% of all new use cases deployed in Q3 incorporated AI. The company’s $100 million AI revenue run rate, reached a quarter ahead of plan, signals real-world usage and validates Snowflake’s positioning at the center of enterprise data and AI transformation. Margin performance was solid, with non-GAAP product gross margin at 75.9% and operating margin expanding more than 450 basis points to 11%, even as Snowflake front-loaded go-to-market hiring and R&D investment to capture the AI opportunity.
- RPO Acceleration: 37% RPO growth reflects strong multi-year demand and record large-deal signings, reinforcing forward visibility.
- AI Use Case Penetration: 50% of new bookings influenced by AI and 28% of new deployments incorporating AI signal deepening platform stickiness.
- Margin Expansion Amid Growth: Operating margin rose 450bps YoY, showing efficiency gains despite heavy investment in AI and sales capacity.
Snowflake’s consumption-based model, where customers pay based on actual usage, continues to drive both predictability and upside, with Q3 described as a “normalized” beat following lumpy migration-driven upside in Q2. Management’s guidance philosophy remains unchanged: focus on annual trends, not quarterly variability, and let consumption patterns drive the outlook.
Executive Commentary
"This momentum has enabled us to achieve a major milestone, $100 million in AI revenue run rate, achieved one quarter earlier than anticipated, thanks to our pace of innovation, cross-functional collaboration, and early adoption among many of our marquee customers."
Sridhar Ramaswamy, Chief Executive Officer
"We achieved strong booking results, signing four nine-figure deals. This represents a record number of large deals signed in a single quarter. Our ability to expand with existing customers and bring new ones onto the platform underscores the strength of our business model."
Brian Robbins, Chief Financial Officer
Strategic Positioning
1. AI-Centric Platform Expansion
Snowflake’s AI data cloud is rapidly becoming the cornerstone of enterprise AI strategy. The launch and rapid adoption of Snowflake Intelligence, an agentic AI solution, and Cortex AI, a suite of AI tools for verticals like financial services, are unlocking new use cases and driving both new logo wins and deeper expansion within existing accounts. The company’s AI capabilities are not only a pull for new customers but also a push for legacy data migrations, accelerating the shift from on-premise to cloud-native architectures.
2. Multi-Product Land-and-Expand Motion
Snowflake’s go-to-market motion is evolving from single-product landings to multi-product engagements at the outset. AI is now part of nearly every new customer pitch, with demos and proof-of-concepts tailored to showcase the art of the possible on customer-specific data. Products like OpenFlow, which streamline data ingestion from diverse sources, and Snowpark, the analytics engine, are broadening the platform’s surface area and making Snowflake integral across the full data lifecycle.
3. Ecosystem Partnerships and Data Collaboration
Strategic partnerships with hyperscalers, SaaS vendors, and AI model providers are deepening Snowflake’s ecosystem integration. Recent alliances with Google Cloud, SAP, Anthropic, and others are expanding model access, enabling zero-copy data sharing, and driving joint go-to-market motions. These moves are making Snowflake the “single pane of glass” for enterprise data and AI, simplifying collaboration across platforms and vendors.
4. Operational Discipline and Margin Focus
Despite aggressive investment in innovation and go-to-market, Snowflake maintains a disciplined approach to margin expansion. The company front-loaded sales and marketing hiring to seize the AI opportunity, but expects efficiency gains from workforce maturation and AI-driven productivity tools for internal teams. Management reiterates commitment to balancing growth with profitability, targeting 75% product gross margin and 9% operating margin for the year.
Key Considerations
Q3 marked a convergence of accelerating AI adoption, ecosystem expansion, and operational discipline, positioning Snowflake for sustained high growth and margin leverage. The company is now a critical enabler of enterprise AI strategies, with a platform that spans ingestion, analytics, governance, and agentic AI. Investors should weigh the following:
Key Considerations:
- AI Revenue Pull-Forward: $100 million AI run rate achieved a quarter early, signaling real enterprise usage and platform differentiation.
- Data Migrations Remain in Early Innings: Management estimates only 15–20% of legacy workloads have migrated, leaving a large TAM untapped.
- Multi-Year Bookings and RPO Strength: Four nine-figure deals and 37% RPO growth provide long-term revenue visibility and validate large enterprise adoption.
- Consumption Variability: Quarterly beats are less indicative in a consumption model; annual guidance and RPO are more reliable signals of underlying health.
- Margin Expansion vs. Growth Investment: Front-loaded hiring and R&D are being balanced with efficiency gains and margin discipline as the business scales.
Risks
Snowflake faces several material risks despite strong execution. The consumption model introduces inherent quarterly variability, making near-term forecasting challenging. Large migrations are lumpy and hard to predict, while competitive intensity in data cloud and AI platforms remains high. Macro uncertainty, cloud provider outages, and evolving customer requirements for data sovereignty and AI governance could also impact growth and margin trajectory. Management’s ability to maintain both innovation velocity and financial discipline will be tested as the AI adoption curve steepens.
Forward Outlook
For Q4, Snowflake guided to:
- Product revenue of $1.195 to $1.2 billion (27% YoY growth)
- Non-GAAP operating margin of 7%
For full-year FY26, management raised guidance:
- Product revenue of approximately $4.446 billion (28% YoY growth)
- Reiterated margin targets: 75% product gross margin, 9% operating margin, 25% adjusted free cash flow margin
Management highlighted several factors that inform the outlook:
- Consumption trends and AI-driven use case expansion are key inputs for forecasting
- Large deal signings and RPO strength provide confidence in durable growth
Takeaways
Snowflake’s Q3 results and guidance reflect a business at the center of enterprise AI transformation, with accelerating adoption, durable multi-year commitments, and balanced operational execution.
- AI Momentum Is Self-Reinforcing: Early AI revenue traction is already driving new bookings, legacy migrations, and cross-sell, positioning Snowflake as the backbone of enterprise data and AI strategy.
- Consumption Model Drives Predictability: RPO and multi-year bookings provide visibility, while quarterly revenue may remain volatile due to customer usage patterns and migration timing.
- Watch for Broader AI Penetration: Future growth will hinge on continued expansion of AI-powered use cases, deeper ecosystem integration, and Snowflake’s ability to accelerate migration from legacy data platforms.
Conclusion
Snowflake’s Q3 marked a decisive AI inflection point, with robust revenue growth, accelerating adoption, and durable multi-year commitments. The company’s strategic focus on AI, ecosystem partnerships, and operational discipline positions it for sustained high growth and expanding margins as enterprise data and AI needs continue to converge.
Industry Read-Through
Snowflake’s results underscore a broader enterprise pivot toward AI-native data platforms, with rapid adoption of agentic AI and multi-product suites now table stakes for industry leaders. The company’s success in pulling forward AI revenue and driving large-scale migrations signals that enterprises are consolidating spend around platforms that can deliver both analytics and AI outcomes. Competitors in cloud data, analytics, and AI infrastructure should expect intensified demand for integrated, enterprise-ready solutions, while legacy vendors risk further disintermediation as customers accelerate migration to cloud-native, AI-powered architectures.