Why becoming AI-forward starts with data, governance, and an operating model, not with moving first
by Ramiz Bozai, Sailesh Kadam, Kriti Sen Sharma, Andrew Wallace-Jackson and Grace Crisp
The challenge for healthcare executives adopting AI is the noise when trying to advance an initiative. Between an inbox full of vendor pitches, competitors’ announcements, and strategic deadlines, figuring out where to start is a hurdle in and of itself.
Successful deployment of an AI strategy was never about being first. Many early adopters are now untangling technical debt and ungoverned pilots that a deliberate start would have avoided. The lesson is not that AI does not work; it is that an AI strategy without a foundation is not sustainable. Becoming AI-forward is about building the right foundation of data, governance, and business operating model. That foundation is more within reach than most leaders think.
An AI-forward healthcare organization is one designed to enable AI to be built, trusted, and scaled. Being AI-forward does not mean buying more tools or starting more long-running proof-of-concepts. At a high level, this means building a strong foundation of data and governance while designing a business operating model that unlocks the maximum potential of enterprise data. The goal is not a tool count, but an organization where the right people can build and answer their own questions.
