At this week’s Snowflake Summit ’26, Snowflake announced that it will be what it calls an “intelligence system” for the enterprise. A solution where AI agents, governance, customer data and business operations work together without constantly moving data from one system to another.
For marketers, the conclusion was simple: bring AI to data, not data to AI.
AI gets closer to data
One of the biggest themes was Snowflake’s push toward agentic AI. The company rebranded several AI offerings and introduced CoWork and CoCo as building blocks for creating and deploying AI-driven workflows.
Snowflake also launched Cortex Sense, a contextual layer designed to help AI systems understand company-specific language, processes, and business rules. The idea is to give agents enough operational context to produce more reliable responses and fewer hallucinations.
For marketing teams, this could mean AI tools that can understand campaign structures, audience definitions, product catalogs, and internal performance metrics without constantly being hand-held.
Claude comes to Snowflake
Snowflake has also expanded its partnership with Anthropic, integrating Claude models directly into Snowflake. This means marketers can analyze customer data, generate content, explore trends, and run more complex analytics without exporting sensitive data to another platform.
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This is important as businesses become more cautious about where customer data goes. Snowflake builds on a broader trend in enterprise AI: keeping data governed and bringing models to it.
Breaking down data silos
The company has also taken several steps to reduce data silos. Cortex Agent Sharing allows organizations to securely share AI agents across Snowflake accounts. A brand, for example, could give an agency access to an AI-powered audience analytics agent without exposing the underlying customer data.
Snowflake has also expanded support for Apache Iceberg and open data architectures. For marketers, the practical benefit is clear. Customer data is in many places, and teams need ways to work from a single, governed source of truth without constantly copying data sets.
Governance becomes conversational
Governance has also benefited from a more conversational treatment. Horizon Catalog updates allow users to define access and privacy rules in plain English, which Snowflake then turns into enforceable policies for data, AI tools, and agents.
This could quickly become important. As AI moves into customer-facing workflows, governance is no longer a back-office concern. Marketing and data teams need ways to control access, protect privacy, and keep AI systems within approved policies without slowing everything down.
The takeaway for marketers
The biggest announcement wasn’t about a specific model, agent, or feature. This was Snowflake’s view on how enterprise AI should work.
Instead of sending customer data to separate AI platforms, Snowflake is betting that businesses will want AI, analytics, governance and activation to happen where the data already lives. For marketers, this could mean less time assembling tools and more time using AI throughout customer journeys with privacy, governance and data quality built in from the start.
