Snowflake Inc (NYSE:SNOW) is set to report first-quarter fiscal 2027 results after the close on Wednesday, with Wedbush Securities saying the Street's $1.32 billion revenue estimate is too conservative as enterprises ramp up AI spending built on internal data infrastructure.
Wedbush analyst Dan Ives maintained an Outperform rating and $270 price target on the data cloud company, keeping it on the firm's AI 30 List ahead of results.
The brokerage said enterprises are still in the early stages of building out AI strategies, with growing demand for platforms that can govern and orchestrate the proprietary data feeding those systems. Ives argued that Snowflake's core data warehousing capabilities place it at the center of that buildout rather than on the periphery.
Snowflake carries a remaining performance obligation backlog of $9.77 billion, which Wedbush said reflects increasing enterprise reliance on the platform for both traditional data workloads and newer AI use cases. The company now counts more than 13,000 customers in its ecosystem, with roughly 5% spending $1 million or more annually and more than 50 customers spending in excess of $10 million.
Wedbush pushed back on what it described as a market misconception that has weighed on the stock, arguing that advances from frontier AI model providers such as Anthropic and OpenAI do not reduce the need for data platforms. The firm said enterprises still require security controls, data lineage, and governance frameworks before connecting AI models to production systems.
"The market is treating advances at Anthropic as if better models reduce the need for data platforms, when in reality, enterprises will significantly push more proprietary and sensitive data into AI workflows as models improve," Ives wrote, adding that this dynamic increases demand for governed and auditable data infrastructure.
The brokerage also noted that Snowflake's model-agnostic architecture, which allows customers to switch between Anthropic, OpenAI, and open-source models without rebuilding data pipelines, positions the company as a neutral layer between enterprise data and external AI systems.
Wedbush characterized Snowflake as a "second derivative" beneficiary of the AI buildout, forecasting that cloud migration by enterprises over the next 12 to 18 months will drive further growth across the software AI layer.