Snowflake's stock spiked as investors rushed to price in a future where data clouds power autonomous AI agents that can search, analyze and act across corporate systems. The surge, which lifted the ticker $SNOW as much as 49% in recent trading, was driven in part by media scrutiny of the company's work on an internal product called Cortex and by broader enthusiasm for generative AI applications that could boost demand for cloud data services.

But Snowflake cautioned that Cortex is not yet a finished product. "We have not rolled it out yet," Singh said. "We are testing it. If we see an error, we add more context into the semantic model. As we add more data, we will build more semantic models." Company executives and insiders interviewed by Forbes and other outlets emphasize that the system is still under development and is not expected to be available to customers until 2026.

The promise of AI agents is straightforward and alluring: software that can read a company's data, synthesize insights, generate reports, carry out transactions and orchestrate workflows across applications without continuous human direction. For Snowflake, which sells storage, query processing and data-sharing services, agent-style applications could translate into higher compute usage, more premium services and deeper customer lock-in. That potential helps explain why investors are willing to assign a rich premium to the stock on the prospect of future AI-enabled revenue.

Yet analysts and former product developers caution that moving from laboratory demos to reliable, enterprise-grade agents is hard. Technical obstacles include controlling so-called hallucinations—instances where models produce plausible but incorrect outputs—integrating agents safely with internal systems, and scaling semantic models to cover diverse enterprise datasets. There are also business-model questions about pricing, margins and whether customers will pay for integrated agent services or continue to prefer best-of-breed point solutions from cloud hyperscalers and SaaS incumbents.

Regulatory and ethical issues add a further layer of complexity. Agents that access sensitive customer data raise privacy and compliance concerns that could slow enterprise adoption, forcing Snowflake and peers to build extensive governance and auditing controls before broad deployment. Investors who bid up the stock are effectively betting that these technical and policy hurdles can be cleared and that Snowflake will capture a disproportionate share of the resulting revenue growth.

For now, the market reaction underscores a recurring pattern in technology investing: expectations about future capabilities can swing valuations sharply even when those capabilities remain experimental. What will matter over the next 18 to 24 months is whether Snowflake can move Cortex from internal trials to controlled customer pilots, demonstrate reliable accuracy and governance, and unveil a clear path to monetization. Until then, the stock's rally may reflect more about the fevered demand for AI narratives than the present-day fundamentals of the data cloud business.