Welcome to the second part of our two-part special on Gartner’s “4 Ways Generative AI Will Impact CISOs and Their Teams” report! If you’ve missed the first part on model composition, you can read it here. Today, we will explore why security specialism matters in an AI security tool, particularly where AI quality is concerned.

Snyk’s goal has always been to empower developers to build fast but safely. This is why we created the developer security category and why we were amongst the first advocates of “shifting left.” Now, AI has changed the equation. According to Gartner, over 80% of enterprises will have used generative AI APIs or models, or deployed their own AI model, by 2026.

Over the years, application vulnerability management has been vital to DevSecOps — which emphasizes shared security responsibility across teams. However, as development practices have evolved, security teams must learn how to adapt and meet developers within their existing workflows. For example, containerization, infrastructure as code (IaC) AI coding assistants, and increased reliance on third-party code are all commonplace in the typical development lifecycle.

We are thrilled to announce the new Snyk Analytics for Snowflake, allowing Snyk customers to seamlessly access and analyze Snyk’s data from their Snowflake account.