Snowflake’s AI Drive Lifts Revenue Outlook as Q1 Highlights Turn Up the Volume on Growth

Lead: Snowflake (SNOW) sets the table for an AI-fueled quarter

Snowflake, the NYSE-listed AI Data Cloud company, reported its first-quarter numbers for fiscal 2027, ending April 30, 2026. The headline figures center on product revenue of $1.33 billion, up 34% year over year, with total revenue of $1.39 billion—up 33% year over year. Public filings show no EPS figure in the excerpt, so there isn’t an immediately visible earnings surprise or EPS consensus to compare against street estimates from this release alone. What is crystal clear is that Snowflake is leaning into AI-enabled growth, and management has nudged its revenue forecast higher for the year, signaling confidence in the AI-driven expansion story.

Key highlights that move the needle

• One-quarter product revenue of $1.33 billion, up 34% YoY; net revenue retention sits at 126%—a sign of expanding **customer value** and cross-sell momentum.
• Remaining performance obligations (RPO) of $9.21 billion, up 38% YoY, underscoring durable demand and a robust pipeline for future revenue.
• Customer base continues to scale: 779 customers with trailing 12-month product revenue >$1 million, up 29% YoY; 46 crossed the threshold in Q1 vs. 26 a year ago.
• Enterprise footprint expands to 813 Forbes Global 2000 customers, reinforcing Snowflake’s position among large, cash-generative buyers.

AI momentum and product velocity: Cortex Code, Snowflake Intelligence, and more

The company highlights traction across its AI stack: Cortex Code and Snowflake Intelligence are cited as catalysts for accelerating product revenue growth. Snowflake notes that more than 13,600 accounts are using Snowflake AI capabilities, and that AI innovations have contributed to the strongest sequential product revenue dollar growth in company history. The narrative also references that Cortex Code is in use across over 7,100 accounts, with tools like Snowflake Intelligence driving additional engagement. These lines of progress feed into the broader thesis of Snowflake as a data platform that is increasingly embedded in AI workflows rather than serving as a standalone data warehouse—an important distinction for investors focused on long-tail margin dynamics and platform leverage.

Partnerships, collaborations, and an acquisition tailwind

Strategic partnerships form a backbone of Snowflake’s go-to-market. The company expanded its collaboration with AWS through a new $6 billion multi-year agreement designed to accelerate enterprise AI adoption globally. It also deepened its partnership with OpenAI to deliver advanced AI capabilities through co-innovation and joint go-to-market efforts, and extended capabilities from its SAP partnership to general availability. In a separate strategic move, Snowflake signed a definitive agreement in May 2026 to acquire Natoma, an enterprise Model Context Protocol platform for AI agents, signaling a push to simplify securely connecting AI to everyday tools inside and beyond Snowflake. The Natoma deal hints at Snowflake’s intent to weave governance and context more tightly into AI-enabled workflows.

Outlook and the earnings narrative: what investors will watch

Management states that they are raising the full-year product revenue guidance, a sign that the AI-led growth engine remains intact and that the company expects continued momentum. The release, however, does not present EPS figures or a formal earnings-per-share outlook, which means the market will be watching how operating expense discipline and margins evolve as the AI product suite scales. In other words, there’s an implied EPS trajectory here, but the explicit numbers and the EPS consensus from analysts will come from subsequent quarterly updates and investor presentations. Expect the near-term focus to center on how durable the AI-driven upside is, whether gross margins expand with higher product velocity, and how much operating leverage Snowflake can squeeze from a broader AI-enabled customer base.

Implications for Snowflake and sector peers

Snowflake’s Q1 narrative reinforces a broader industry arc: data clouds increasingly embed AI capabilities, and enterprise customers are willing to scale. The combination of rising RPO and a growing base of >$1 million customers suggests durable uptime and expansion potential, even as headwinds like competition intensify in the data-analytics space. The AWS and SAP partnerships, coupled with a significant Natoma acquisition, hint at a strategy to anchor AI-enabled workflows within the ecosystem of large platform players, reducing friction for customers to adopt Snowflake as the central data and AI operating system. For peers—names who chase AI-enabled data platforms—the bar has shifted from “how fast can you grow revenue” to “how effectively can you monetize AI-enabled data assets while preserving margin.” Translation: the AI tailwind is real, but investors will demand evidence of sustainable profitability as net-dollar retention remains the clearest proxy for long-term pricing power and product-market fit.

Analyst take: a pragmatic reframe for the AI data cloud

What makes Snowflake’s update interesting is not just the absolute growth numbers, but the qualitative shift toward AI-native product velocity and greater enterprise scale. The 126% net revenue retention signals that Snowflake is not merely a data warehouse vendor but a platform that embeds AI features deeply into customers’ daily workflows. The Natoma acquisition could be a play to nudge agents’ tooling into Snowflake’s orbit, potentially improving user retention by lowering the friction to connect a customer’s tools with Snowflake’s data and AI capabilities. If the AI partnerships translate into multi-year ARR expansion and margin improvement, Snowflake’s stock could begin to price in a more durable earnings narrative—one where EPS materializes as a function of operating leverage rather than a primary driver of growth.