In its fiscal Q2 2027 report, Snowflake showcased a strong $6 billion run rate with 37% year-over-year product revenue growth, driven in part by AI integrations. While gross margin guidance is lowered to accommodate rising AI-related costs, operating margins are improving due to controlled expenses.
- 37% year-over-year product revenue growth at $6 billion run rate
- AI products drive around half of recent growth acceleration
- Gross margin guided down slightly to cover AI costs despite higher operating margins
Market signal
Snowflake's fiscal Q2 2027 results reveal robust growth momentum at a $6 billion annualized product revenue run rate, with 37% year-over-year growth recorded. This marks consecutive quarters of accelerating performance, driven substantially by new AI-enabled functionalities such as the Cortex AI Gateway and coding agents adopted by around 60% of customers. This growth includes a recent acquisition's contribution, but organic demand remains strong.
The company's approach to billing AI consumption within existing consumption metrics, rather than isolating it as a separate billing line, highlights an integrated product strategy that blends AI-driven analytics with core platform usage seamlessly. The revenue acceleration is broad-based, sourced from large enterprise customers rather than niche AI labs, signaling strong enterprise adoption of cloud data platforms integrated with AI.
Operator impact
Snowflake’s gross margin has been guided down slightly—from 76.4% last year to around 74% forecast for fiscal 2027—primarily due to the increased share of fast-growing AI workloads, which incur higher costs for inference and cloud resources. Unlike some competitors, Snowflake absorbs these AI costs rather than passing them directly to customers, reflecting an operator decision to invest in AI capabilities at an internal margin expense.
Despite declining gross margin, Snowflake has managed to improve its non-GAAP operating margin year-over-year by over 400 basis points to 15.3%, with a full-year guidance increase to 14.5%. This improvement comes from disciplined expense management, including slowing headcount growth to offset rising cloud costs. This operational efficiency supports sustainable growth even as AI-related costs reshape margin dynamics.
What to watch next
Operators should monitor how Snowflake manages AI workload growth and related costs, especially as AI consumption expands further within the enterprise customer base. The balance between continuing strong revenue growth and gross margin pressure will be critical to sustaining operating margins. The company’s strategy to fold AI consumption into existing metering versus creating standalone AI offerings may influence competitive positioning and sales approaches in the tech-market.
Another key area is the evolution of remaining performance obligations (RPO), which showed a slowdown in growth rate to 30% year-over-year and a nominal decline in absolute dollars. Tracking RPO trends will help assess the durability of forward revenue visibility in the context of aggressive AI-driven product expansion. Watching Snowflake’s next-quarter guidance and adoption rates of AI functions will be vital for evaluating ongoing momentum.