Snowflake in the AI stack

The business and what the filings show

Snowflake runs a cloud data platform that companies use to store, combine and query their data, and increasingly to run AI models and agents on it. It charges mainly for consumption, the compute and storage customers use, rather than for seats. Over its latest four quarters it reported $5.4B of revenue, +32% on the year before, at a 67% gross margin and a −23% operating margin. Free cash flow was $1.2B, far above its operating result, largely because stock-based compensation is a large non-cash cost, and remaining performance obligations $9.0B.

Snowflake sits where the AI build-out meets enterprise data: models are only as useful as the data they can read, and much of large companies’ structured data sits in platforms like it. Its 10-K lists Snowflake Intelligence and Cortex Agents among the capabilities that became generally available in its fiscal 2026, letting business users build data agents without writing code. Consumption pricing means AI workloads show up in revenue as soon as customers run them, without waiting for a contract renewal.

The same pricing cuts both ways. Customers can optimize or move workloads quickly, and Snowflake competes with the clouds it runs on, which offer their own data and AI services. Its revenue growth against the layer, and its gross margin as AI workloads add compute cost, are the numbers that show whether AI is becoming a new source of consumption or a reason to use cheaper alternatives.

How AI shows up in the numbers

AI shows up at Snowflake as consumption: customers running models, agents and AI functions on data already in the platform. It pays the clouds for the compute underneath, so AI usage lifts revenue and cost of revenue together, and gross margin shows how much of that it keeps. Its earnings releases show how often it quantifies AI results.

For scale, Snowflake’s revenue over the latest four quarters equals 1% of the $566B the five largest buyers spent on capital projects over their latest four quarters. Their capex rose +81% on the year before, while Snowflake’s revenue grew +32%: slower than the spending, so it is capturing a smaller share of each new capex dollar, or more of its business sits outside the build-out.

How it talks about AI

In its latest earnings release, furnished to the SEC on September 2, 2026, Snowflake mentioned AI 9 times in 3,000 words of narrative text, about 3.0 mentions per 1,000 words. Of its 7 sentences about AI, 3 included a number: a revenue figure, a growth rate, a customer count or another measurable result. Across the 8 releases we read, back to November 20, 2024, AI mentions per 1,000 words went from 0.4 to 3.0.

Specific claims are easier to check against the numbers than general enthusiasm, which is why the share of AI sentences that carry a figure is worth watching alongside how often AI is mentioned. The sentences below are quoted from the release as published, after removing safe-harbor text and company boilerplate.

• “Snowflake delivered another strong quarter, with product revenue of $1.49 billion, up 37% year-over-year, as Snowflake continues to power the enterprise AI revolution," said Sridhar Ramaswamy, CEO of Snowflake.”
• “AI Momentum : CoCo surpassed 9,100 accounts 1 , adding more than 2,000 accounts in the quarter alone, while CoWork expanded to 5,800 accounts 1 .”
• “AI continues to compound our advantages, creating a flywheel effect across the business.”

Source: earnings release (Form 8-K, Exhibit 99.1), September 2, 2026.

The trend in the numbers

Since the start of 2023, Snowflake’s largest quarter by revenue was Q2 2026 at $1.5B, and its highest gross margin was 69% in Q3 2023. The latest quarter set the revenue record for the period.

Quarter by quarter, Snowflake’s revenue grew +29% in Q3 2025, +30% in Q4 2025, +33% in Q1 2026, +35% in Q2 2026 on the same quarter a year earlier. Growth has been accelerating.

Gross margin in the latest quarter was 67%, against 68% a year earlier, little changed. Operating margin moved from −30% to −17% over the same span. Over the latest four quarters it turned 23% of its revenue into operating cash flow and spent 1% of revenue on capital projects, against 2% a year earlier.

Where it sits in the stack

Snowflake sits in the software and applications layer of the AI stack. It sits at the top of the stack, where revenue from end customers has to come from; its own spending flows to AI clouds.

Among the 27 companies in this layer on our map, it ranks number 12 by revenue and number 5 of 27 by revenue growth. Its gross margin of 67% compares with 78% for the layer as a whole, so it keeps less of each dollar than the layer average. The full layer analysis is on the software page.

Latest four quarters for 10-Q filers; latest fiscal year for 20-F filers. Companies under $100 million of revenue are left out.

Against the 27 US-listed companies in its layer, Snowflake grew +32% over the latest year versus +19% for the layer combined, and converted 22% of revenue into free cash flow versus 33% for the layer. It is taking share of the layer’s revenue.

What has to go right, and what could go wrong

What has to go right. Enterprises have to run their AI on data where it already sits, making Snowflake a place AI workloads run rather than only a place data is stored, at margins that hold as the compute bill grows.

What could go wrong. If the clouds’ own data and AI services, or open table formats that let customers query data with any engine, pull AI workloads elsewhere, consumption growth could slow even as AI adoption rises.

These describe the conditions the business depends on, as the filings show them. They are not a view on the stock.

Through the lens of Investing in AI

Rob May’s book offers six mental models for telling AI moats from traps. The one most useful for Snowflake’s layer is “AI challenges traditional SaaS assumptions”: Per-seat pricing, zero marginal cost, smooth ARR curves, and automatic land-and-expand break down when software does work on your behalf. The mistake is not using SaaS instincts. It is using them automatically.

The question it asks of any company is: What work is this product actually doing, and how does pricing map to it? Applied to Snowflake, the filings on this page are the place to start: the margin trend shows whether it holds scarce value or passes it through, the customer and financing disclosures show who it depends on, and the commitments show what it has promised before the revenue arrives.

Customers and concentration

US companies must disclose any customer that accounts for 10% or more of revenue, and foreign filers usually describe their largest customers. Concentration matters because a company’s growth is only as durable as the handful of buyers behind it, and in the AI stack those buyers are often the same few companies.

• “Additionally, there were no customers that represented 10% or more of the Company’s revenue for each of the fiscal years ended January 31,” 10-K, March 20, 2026

Commitments and backlog

• Backlog. Snowflake reports $9.0B of remaining performance obligations, 1.7 times its revenue over the latest four quarters: contracted revenue not yet earned.
• Purchase commitments. $78M of unconditional purchase obligations as of July 31, 2026 (10-Q): what it has contracted to buy from its own suppliers.

What to watch

Snowflake’s next quarterly report will cover the quarter ending around October 30, 2026. Large companies must file a 10-Q within 40 days of a quarter’s end and a 10-K within 60 days of the fiscal year’s end, so the new figures should arrive by about December 29, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• Revenue growth against the layer: consumption pricing means AI usage would show here first.
• Gross margin, where the compute cost of AI workloads it buys from the clouds would appear.
• Remaining performance obligations, which show how much customers are committing ahead of use.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from Snowflake’s SEC filings, latest period ended July 31, 2026. Other companies: all company pages.