AI governance can't rely on blanket rules like avoiding sensitive data in AI tools. As AI becomes foundational infrastructure across business, companies need organization-wide governance that balances technology, risk, and business goals, not narrow policies that ignore real use cases.
Governance in AI, if you had asked me a couple of years ago when, you know, really the large language models started, we talked to a lot of folks, they said, "Oh yeah, we've got an AI policy, we've got governance, we're good to go." And what we've learned since then is that a policy saying don't put sensitive data in AI is not particularly practical, nor is it really solving the underlying issue of how we can use these tools holistically. AI has such broad reach into the enterprise, so many different use cases that it really requires the organization to come together in kind of a new way. It's, it's almost a new wave of compute, similar to desktop computers, similar to the rise of cloud. And now we have rise of AI. It's truly that level of transformation for the business.
