At this week’s Snowflake Summit ’26, Snowflake presented its proposal to become what it calls an “intelligence system” for the enterprise. An environment where AI agents, governance, customer data, and business operations all work together without constantly moving data from one system to another.
For marketers, the bottom line was simple: bring AI to data, not data to AI.
Artificial intelligence gets closer to data
One of the biggest themes was Snowflake’s push towards agent artificial intelligence. The company has rebranded several AI offerings and introduced CoWork and CoCo as building blocks for building and deploying AI-powered workflows.
Snowflake also launched Cortex Sense, a context layer designed to help AI systems understand company-specific language, processes and business rules. The idea is to provide agents with 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 constant monitoring.
Claude arrives at Snowflake
Snowflake has also expanded its partnership with Anthropic, bringing Claude models directly to Snowflake. This means marketers can analyze customer data, generate content, explore trends, and perform more complex analytics without exporting sensitive data to another platform.
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This is important as companies become more cautious about where customer data goes. Snowflake leans into a larger trend in enterprise AI: keeping data governed and fitting models.
Break down data silos
The company has also taken several measures to reduce data silos. Cortex Agent Sharing allows organizations to securely share AI agents across Snowflake accounts. A brand, for example, could provide an agency with access to an AI-powered audience insights agent without exposing underlying customer data.
Snowflake has also expanded support for Apache Iceberg and open data architectures. For marketers, the practical benefit is clear. Customer data resides in many places, and teams need ways to work from a single governed source of truth without endlessly copying data sets.
Governance becomes conversational
Governance has also received a more conversational treatment. Updates to Horizon Catalog allow users to define access and privacy rules in plain English, which Snowflake then transforms into enforceable policies across data, AI tools, and agents.
This could become important quickly. 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 rules without slowing everything down.
The takeaway for marketers
The biggest announcement wasn’t for a specific model, agent, or feature. It was Snowflake’s take on how enterprise AI should work.
Instead of sending customer data to separate AI platforms, Snowflake is betting that companies will want AI, analytics, governance and activation to happen where the data already resides. For marketers, this could mean less time piecing together tools and more time using AI across customer journeys with privacy, governance and data quality built in from the start.
