Mashrur Hossain

Getting an AI coding tool into developers’ hands is only the beginning. In large, regulated enterprises, sustained adoption depends on how well it fits the organization’s security controls, developer environments, engineering practices, and expectations for measurable value.

Drawing on my experience helping large financial-services organizations adopt AI-assisted development, I’ll share practical lessons about turning initial interest into everyday engineering use. We’ll explore how to identify focused, valuable use cases; align security, platform, and engineering teams; and build hands-on enablement around the work developers actually need to do.

We’ll also examine where adoption stalls: workshops without a clear follow-through plan, environment and access issues that interrupt momentum, and metrics that track activity without demonstrating outcomes. These experiences show why enterprise enablement is an ongoing organizational capability, not a one-time training event.

Attendees will leave with a practical approach to scaling AI coding adoption: establish technical readiness, define ownership, develop internal champions, connect learning to real workflows, and create feedback loops that improve both the developer experience and the rollout itself.