AI is transforming the software development lifecycle, moving beyond code generation toward autonomous agents that can test, deploy, and manage software changes. But as development accelerates, are enterprise databases prepared to keep pace?

As AI agents increasingly initiate database changes, organizations need to automatically capture what changed, who or what initiated it, whether it complied with policy, and what happened afterward. Looking ahead to 2027, probabilistic AI systems will require deterministic controls to ensure database changes are authorized, validated, and auditable, without slowing down software delivery.

Join Liquibase to learn:

• How AI agents are changing database operations

• Why deterministic governance and auditability are essential

• How to identify risky changes before deployment

• What controls to prioritize for the AI SDLC 

Key Takeaways:

1.  AI agents are changing your database, and you should govern them like any other contributor.

2. Probabilistic AI needs deterministic guardrails and a complete audit trail.

3. Catch risky changes before they deploy, without slowing delivery.