
While Snowflake posted a slew of impressive Q2 results, the one that best reveals the company’s enormous potential is that 25% of customer use-cases are now built around AI solutions.
“Our progress with AI has been remarkable,” Snowflake CEO Sridhar Ramaswamy said in teeing up some dazzling stats about AI deployments.
“Today, AI is a core reason why customers are choosing Snowflake, influencing nearly 50% of new logos won in Q2. And once they’re on our platform, AI becomes a cornerstone of their strategy, powering 25% of all deployed use cases with over 6,100 accounts using Snowflake’s AI every week,” Ramaswamy said, emphasizing the strategic role embedded AI is playing “across the data life cycle to accelerate analytics, transform workflow, and even power migrations.”
And Ramaswamy’s claim of “remarkable” progress with AI clearly manifested itself in the Q2 results for the period ended July 31, with product revenue up 32%. Contrast that to the previous quarter, in which product revenue grew 26%, and there’s no doubt that the combination of Snowflake’s core analytics business and its rapid rollout of AI solutions and technologies is generating powerful appeal among business customers.

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Here’s a quick overview of Snowflake’s Q2 results, and then I’ll offer some additional perspectives from Ramaswamy:
- product revenue of $1.09 billion, up 32%;
- RPO of $6.9 billion, up 33%;
- 751 Global 2000 customers now using Snowflake;
- 654 customers spending at least $1 million over the last 12 months; and
- a net-revenue retention rate of 125%.
Since becoming CEO about 18 months ago, Ramaswamy has rebranded Snowflake as “the AI data cloud” and has relentlessly emphasized the simple truth that a company cannot have a successful AI strategy unless it first has a successful data strategy. That position at the core of the AI Revolution has attracted enormous levels of competition, and Snowflake will have to continue to execute flawlessly as much-larger companies — SAP, Oracle, Microsoft, and others — along with high-flying companies of similar size such as Palantir and Databricks — look to grab share in that same “AI data cloud” space.
Ramaswamy boldly staked out Snowflake’s position in his closing line on the Q2 earnings call by saying, “In closing, Snowflake is at the center of today’s enterprise AI revolution, delivering tremendous value throughout the end-to-end data life cycle.”
Can it hold that center position? That remains to be seen–but here are some of the AI-centric approaches Ramaswamy is pursuing to ensure that Snowflake does just that.
1. Snowflake Intelligence: “We are continuing to advance our leadership in enterprise AI with Snowflake Intelligence, in public preview. This platform enables every user to talk to their enterprise data, turning structured and unstructured data into actionable insights through natural language. And it powers the creation of intelligent agents directly on enterprise data.”
2. OpenFlow connectivity: “We have extended our connectivity platform with Snowflake OpenFlow, making it easy to bring in structured, unstructured, batch, or streaming data.
Built on our acquisition of Datavolo, OpenFlow provides seamless access to all enterprise data and now supports data capture from Oracle through a strategic partnership. With customers already using OpenFlow to unlock new value from their data architecture, OpenFlow expands our reach into the $17 billion data integration market.”
3. Data Sharing: “We are continuing to strengthen our platform and help our customers do more with their data to deliver great business outcomes. As more companies face the challenge of data spread across different places, we’re helping them effectively share data and collaborate. As of this quarter, 40% of our customers are now data sharing on Snowflake, driving powerful network effects that strengthen our ecosystem and expand customer value.”
4. Cortex AI: Investment firm BlackRock “is leveraging Snowflake Cortex AI to help its team serve their clients more and at a much larger scale. Our technology allows them to pull together pieces of information they have on a client from their past portfolio, not from a recent call, and get instant insight. It’s like a superpower: it helps them understand exactly what each client needs so they can provide the best possible service.”
Final Thought
Revolutions are always messy — after all, that’s the whole point of turning things upside-down, isn’t it? Ramaswamy has done a great job in leading Snowflake to the heart of the AI Revolution, but the next 18 months will be even more challenging because the strategic high ground Snowflake has captured will be under constant attack from all of those competitors mentioned above.
That might not be great news for Snowflake, but it is surely excellent news for business leaders because, in the Cloud Wars, the biggest winners are always — always! — the customers.
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