AI coding assistants are fundamentally changing how software gets built.

Developers can now generate applications, dependencies, infrastructure definitions, and deployment configurations faster than ever before. But while development velocity has accelerated dramatically, governance models still rely on manual reviews, disconnected tooling, and trust assumptions that no longer scale.

The result: organizations are deploying more software than ever — with less visibility into what’s actually moving through their delivery pipelines.

In this session, we’ll explore how AI-generated code is reshaping software supply chain risk, why traditional security approaches are struggling to keep pace, and what modern artifact governance should look like in high-velocity engineering environments. We’ll also share how organizations are approaching secure software delivery with integrated CI/CD, artifact governance, dependency protection, and policy-driven deployment controls.

Key Takeaways:

• Why AI-generated dependencies are creating new trust challenges
• The growing importance of artifact provenance and traceability
• How governance is shifting from static approvals to continuous verification
• Why software delivery pipelines are becoming critical security boundaries
• What platform and security teams must rethink as AI adoption scales