Work ยท Enterprise AI
Enterprise AI Adoption
The public version of a confidential story: how an organization can turn interest in generative AI into broad, responsible use without treating adoption as an afterthought.
The problem
Interest was not the hard part. The harder work was deciding where the technology could genuinely help, making experimentation approachable, and giving people enough confidence to use it responsibly.
What we tried
We treated adoption as product work. That meant making room for experimentation, learning from how people used the tools, and steadily connecting early lessons to reusable capabilities and responsible practices.
My role
I lead Data & AI work and help connect the organizational questions around adoption, technology, governance, and change. The work is less about a single tool than about creating the conditions for useful work to spread.
What happened
90%+ monthly active adoption of generative AI across the enterprise.
What I learned
Adoption is not a communications exercise after a technology decision. It is the work. Central capabilities and decentralized experimentation can reinforce one another, and governance is most useful when it gives people a clear way to move responsibly.