’s stock price succumbed to marketwide fear of AI software-as-a-service (SaaS) disruption, sending it to long-term lows. However reasonable the fears may be, the sell-off is overblown, since AI is software, and software companies like Snowflake lean hard into it. While it is possible for an AI modeler to disrupt Snowflake’s business, the more likely scenario, which is already happening, is that Snowflake embeds AI models into its business.
Not only is AI available as a tool throughout its stack, but Snowflake’s product is also critical to AI as it manages data in a unified, cross-cloud manner, enabling direct interface between enterprise data and leading AI models. The takeaway is that Snowflake is central to AI training, especially for inference, the next phase, and its stock price is setting up for a reversal and recovery.
As it stands, fiscal 2026 year-end highlights include a focus on agentic capabilities and automation. Market participants from NVIDIA’s CEO, Jensen Huang, to a host of analysts think fiscal year (FY2027) is the pivotal year, and Snowflake is making the moves to capitalize on it. Agentic capabilities center on Cortex AI and Snowflake Intelligence, enabling agents to interact with data, reason through tasks, and trigger outcomes.
Snowflake’s Q4 Results Signal Market Bottom
Snowflake had a solid Q4 FY2026, with revenue of $1.28 billion growing by nearly 30% year-over-year, outpacing MarketBeat’s consensus estimate by more than 230 basis points (bps). The strength was driven by product demand (up 30%), new clients, and penetration. New clients grew by 40% on a net basis, underpinned by a 27% increase in the largest. Net retention rate, a measure of revenue growth among existing clients, came in at a robust 125%, underpinning a 42% in remaining performance obligation (RPO). RPO, a measure of unrealized contract value, points to continued growth, as it is leading revenue and driven by dual tailwinds.
Margin news is also solid. The company experienced margin pressures, including increased sales, marketing, research, and development expenses, but far less than anticipated. The net result is that GAAP losses narrowed compared to the prior year, and adjusted profits outperformed estimates. The 32 cents of adjusted earnings came in a nickel above MarketBeat’s reported consensus, more than 1800 bps, and highlight the cautious tone of the guidance.
Management forecasts another solid year, but the 27% product growth they target is below the consensus estimate. The upshot is that analysts are panning the guide as cautious, citing upside potential and a clear pathway to 30% growth driven by AI.
The bad news is that more responses than not include a price target reduction, narrowing the range around the consensus estimate; the good news is that sentiment held steady at Moderate Buy, and the potential for outperformance provides a bullish catalyst later in the year. As it stands, more than 40 analysts cover this stock and show a moderately high conviction in the $252 consensus, a 50% upside from late February support levels.
Institutions Are Accumulating Snowflake Stock
The institutional data reveal that, as a group, institutions have been accumulating Snowflake stock for more than a year. Their activity aligns with the early 2025 price rally and ramped higher later in the year as price action retreated. Early 2026 activity reveals selling accelerating, but buyers are more than matching the pace, putting them on track for the third-most active quarter in years.
Early 2026 institutional activity aligns with a technical bottom. The price action retreated to long-term lows in early February, rebounded, retreated back to the lows, and has since rebounded again. The post-release activity suggests support remains strong, but headwinds to price action are present. The market was capped at the 150-day exponential moving average, which aligned with the recent highs, and may struggle to move above it. In this scenario, Snowflake’s stock will consolidate at or near current levels, and the risk of a deeper correction remains.
Snowflake’s 2026 catalysts include expanding product lines and capabilities, and strategic partnerships. Partnerships with OpenAI and Anthropic are working to integrate LLMs into the platform and boost enterprise adoption. Other catalysts include acquisitions and the expansion of business lines, such as the recent purchase of Observe. It improves the company’s observability functions, enabling better handling of telemetry and performance monitoring. Among the risks is the consumption-based pricing model. Companies might see Snowflake as a way to control spending and reduce its use.
