Snowflake and OpenAI make a $200 million bid to corner corporate data intelligence market
Snowflake made its fortune by acting as the ultimate data warehouse for companies. By pioneering the separation of cloud storage from computing power, it allowed organisations to dump vast lakes of corporate information—from customer logs to supply chain metrics—into the cloud, organising it into neat, queryable rows. It was a lucrative business model that culminated in the largest software IPO in history in 2020. Yet, in the age of generative artificial intelligence, being a passive reservoir is no longer enough. Data must not only sit; it must speak, reason, and act.
This imperative explains the logic behind the announcement on Monday (February 2, 2026) that Snowflake has entered a $200 million, multi-year partnership with OpenAI. The deal, which integrates OpenAI’s most advanced models directly into Snowflake’s data infrastructure, represents a significant tactical shift for both firms, signalling that the battle for enterprise AI has moved from the chatbox to the database.
To understand the stakes, one must look at Snowflake’s current predicament. The company faces fierce competition from Databricks, a rival that has historically been stronger in the complex data science required for AI, and the “hyperscalers”—Amazon, Microsoft, and Google—who own the underlying infrastructure. Snowflake’s nightmare is “data egress,” where customers extract their data from Snowflake’s storage to feed it into AI models hosted elsewhere.
Closer to data
By embedding OpenAI’s technology, including the touted GPT-5.2 model, directly into its “Cortex AI” layer, Snowflake is attempting to invert the business model of the industry. Instead of moving heavy data to the models, they are bringing the models to the heavy data.
For Snowflake, the implications are existential and financial. The company is effectively turning its platform into an operating system for the enterprise. By enabling “AI Agents”—software entities capable of performing multi-step tasks like analysing sales data and drafting emails—Snowflake hopes to increase the consumption of its “credits” (its unit of pricing).
If a CFO can query the database in plain English to forecast quarterly earnings, the compute-heavy inference runs on Snowflake’s metre. It transforms the company from a storage facility into an intelligence factory, justifying its premium valuation in a market that has grown skeptical of software-as-a-service growth rates.
A bypass to enterprise AI
For OpenAI, the calculus is equally strategic. While ChatGPT captured the consumer imagination, the long-term profitability of the San Francisco-based lab relies on deep integration into the corporate backend. Partnering with Snowflake offers a bypass around the formidable “cold start” problem of enterprise AI: the lack of accessible, structured data.
Snowflake’s 12,600 customers, including giants like Canva, already have their most pristine data governed within Snowflake’s walls. This deal hands OpenAI a direct line to the proprietary information of the Fortune 500 without the friction of complex integration, cementing its models as the default cognitive engine of the corporate world.

The benefits for enterprises are, at first glance, compelling. The primary allure is the reduction of “data gravity” friction. CIOs have long been wary of sending sensitive proprietary data via API to third-party model providers due to security and latency concerns. This partnership ostensibly solves that by keeping the data within Snowflake’s “governed” perimeter.
The promise of “Snowflake Intelligence”—an agentic layer that allows employees to converse with their organisation’s entire knowledge base—could theoretically democratise data analysis, removing the bottleneck of needing SQL-proficient data scientists to answer basic business questions. It offers a cleaner, more secure architecture for deploying AI than the patchwork of vendors most companies currently struggle with.
Beware of sticker shocks
However, corporate buyers should temper their enthusiasm with caution. The most immediate concern is the tightening of vendor lock-in. Snowflake has long been criticised for its high costs; adding compute-intensive AI agents to the bill could lead to sticker shock. By building agents that rely specifically on OpenAI’s proprietary architecture within Snowflake’s environment, companies may find it technically and contractually difficult to switch to open-source alternatives or rival models in the future.
Furthermore, there is the question of reliability. The announcement emphasises “governance” and “trust,” yet large language models are notoriously prone to hallucinations. deploying “AI agents” that can take action—not just retrieve information—adds a layer of operational risk. If a Snowflake-hosted agent misinterprets a schema and generates a flawed financial report, or triggers an erroneous supply order, the “tangible return on investment” promised by the press release could quickly turn into a liability.
This partnership represents a consolidation of the AI stack. Snowflake and OpenAI are betting that in the future, the distinction between the database that remembers and the AI that thinks will dissolve. For the enterprise, the convenience of this union is undeniable; the price of admission, however, will be total commitment to their combined ecosystem.
Published – February 02, 2026 07:31 pm IST

