The Governance Gap
Why AI Adoption Outpaces Control, and What to Do About It
Watch nowMost engineering organizations can tell you exactly how many AI coding tools their developers use, with seat counts, adoption rates, and daily active usage all tracked and reported up to leadership.
The harder questions go unanswered. How much AI-generated code is in production right now, who reviewed it, whether it complied with component standards, and what changed between the prompt and the merge are questions most enterprises cannot answer with any precision.
That asymmetry is the governance gap, and it widens with every new tool deployed and every new role that starts generating code. The cost of leaving it open is higher than most leaders have priced in.
You'll take away:
- How design system drift surfaces as the most visible symptom of ungoverned AI development, in both directions
- Why pull request review buckles under multi-agent parallel volume
- What changes when authorship expands beyond engineering to product, design, and QA
- The opportunity cost of governance failure, and why it exceeds the downside risk for most organizations
- What enterprises running AI development at scale are actually building to close the gap
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