Enterprises write the rulebook for AI-generated code
Provenance tracking, review gates, and dependency policies are turning AI coding assistance from a developer perk into governed infrastructure.
Anne Nygård via UnsplashAI coding assistants arrived in enterprises through developer enthusiasm and settled in ahead of policy. The policy is now catching up. Engineering organizations are formalizing rules for machine-generated code: what must be tracked, what must be reviewed differently, and what may not be generated at all.
Provenance is the anchor requirement. Compliance teams want to know which code a model wrote, which model wrote it, and what the model was shown, both for license exposure and for the audits that regulated industries already face. Tooling vendors have responded with attribution tracking that engineering leaders describe as necessary and nobody describes as finished.
The practical effect on productivity has been smaller than skeptics predicted. Teams report that governance slowed adoption for a quarter and then became routine, the same arc that source control and code review followed in earlier decades. The tools stayed; the anarchy did not.