From Prototype to Production: Governing AI-Assisted Delivery in the Enterprise

AI-assisted development has moved from experiment to production faster than most delivery frameworks were geared to handle. Across organizations, project managers are watching teams ship code generated by large language models and AI coding assistants. Organization policies on AI-assisted work might not have caught up, especially around change controls, audit trails, or risk assessments that govern any other production-bound work. The speed at which AI builds is exponentially faster than the speed at which a human can review. Glossing over control gates exposes the organization to risk.

This session is a working PM’s view of that risk and what to do about it. Drawing on real artifacts from a live financial-planning product built solo with AI assistance, the talk walks through the operating model that turns AI-assisted prototyping into production-grade delivery: data classification, stopping conditions, traceability, accuracy contracts, and the living registers that keep the controls honest as the system evolves. The discipline is not new. It’s the same flow and change-control thinking PMs have applied for decades, but it has to be re-articulated for a tool that moves faster than human review.

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