Snowflake’s new AI tools solve a key marketing challenge

At the Snowflake Summit ’26 this week, the company made a strong case for becoming what it calls a “System of Intelligence” for the enterprise. The vision is one where AI agents, governance, customer data, and business operations seamlessly coexist without the constant need to shuttle data between different systems.

For marketers, the core message was straightforward: Bring AI to the data, not the data to AI.

A major theme of the event was Snowflake’s push into agentic AI. The company rebranded several of its AI offerings and unveiled CoWork and CoCo as foundational tools for building and deploying AI-driven workflows.

Another key launch was Cortex Sense, a context layer designed to help AI systems grasp company-specific language, processes, and business rules. The goal is to equip AI agents with enough operational context to deliver more reliable answers and minimize hallucinations. For marketing teams, this could translate into AI tools that intuitively understand campaign structures, audience definitions, product catalogs, and internal performance metrics without requiring constant guidance.

Snowflake also deepened its partnership with Anthropic, integrating Claude models directly into its platform. This allows marketers to analyze customer data, generate content, explore trends, and run complex analyses without ever exporting sensitive information to another platform. This move is significant as companies become increasingly cautious about where customer data travels. Snowflake is betting on a broader enterprise trend: keep data governed and bring the models to it.

Efforts to dismantle data silos were also front and center. Cortex Agent Sharing enables organizations to securely share AI agents across different Snowflake accounts. A brand, for example, could grant an agency access to an AI-powered audience analysis agent without exposing the underlying raw customer data. Additionally, Snowflake expanded its support for Apache Iceberg and open data architectures. The practical benefit for marketers is clear: customer data resides in many places, and teams need a single, governed source of truth without endlessly duplicating datasets.

Governance itself got a more conversational upgrade. Updates to Horizon Catalog allow users to define access and privacy rules in plain English, which Snowflake then translates into enforceable policies across data, AI tools, and agents. This capability is becoming crucial as AI moves into customer-facing workflows. Governance is no longer just a back-office concern; marketing and data teams need ways to control access, protect privacy, and keep AI systems within approved boundaries without creating bottlenecks.

The most significant announcement, however, wasn’t a single model, agent, or feature. It was Snowflake’s overarching vision for how enterprise AI should function. Rather than funneling customer data into separate AI platforms, Snowflake is betting that companies will prefer to have AI, analytics, governance, and activation happen where the data already lives. For marketers, this means less time spent integrating disparate tools and more time leveraging AI across the entire customer journey, with privacy, governance, and data quality built in from the ground up.