The shift toward autonomous AI agents with the power to carry out critical business decisions is accelerating innovation, but it is also amplifying security risks across your data and AI estate. A recent Snowflake report reveals that 96% of businesses continue to struggle with critical hurdles, including data quality, skills gaps and legacy system integration.
To successfully move AI projects into production, securing data is nonnegotiable. It requires careful consideration of how AI agents interact with your data and measures to defend against malicious prompt injections. Security leaders must constantly ask: "Is our platform built to govern production-grade AI and can it defend our enterprise at the speed of AI?"
At Snowflake, we are committed to providing native, proactive, enterprise-grade security capabilities for all your data and AI workloads. Our approach is designed to provide security leaders and platform architects/administrators the confidence they need to deploy agentic applications at scale while maintaining data integrity and supporting regulatory compliance.
“As AI becomes increasingly embedded across the marketing industry, having the right security foundations in place is critical to our business scaling innovation responsibly. Snowflake’s new AI security capabilities have the potential to provide greater visibility and control over how AI systems access and interact with personally identifiable data, helping us scale AI adoption responsibly while maintaining the trust our clients expect.”Ankur JainChief Cloud and Data Modernization Officer, AcxiomLast week, we announced the intent to acquire Natoma to bring governed model context protocol (MCP) access to the enterprise. At Summit 2026, we’re announcing many enhancements to our security portfolio that focus on three core areas, all of which are vital to AI success and business growth:
