Over the past two years, healthcare leaders have shifted from questioning whether and where gen AI is relevant to focusing on how it can be used responsibly and at scale. Our latest survey of US healthcare leaders highlights several signals of gen AI’s maturation: Half of leaders report that their organizations have already implemented gen AI, more than 80 percent have deployed their first use cases to end users, and while AI safety risks remain top of mind, implementation barriers are now equally urgent (see sidebar, “Research methodology”).
Notably, half of respondents say their organizations deployed their first use cases more than six months ago. This cadence reflects increased confidence in both organizational capabilities and operational readiness, suggesting that healthcare organizations no longer view gen AI as experimental but increasingly as a core competency.
At the same time, the challenges that healthcare leaders face are evolving. Longstanding concerns around trust, safety, and governance now sit alongside the operational realities of integration. Against this backdrop, emerging interest in agentic AI points to the next stage of maturity—one in which organizations move from using gen AI to create content and support individual tasks to using agentic AI to take action and coordinate more complex processes end to end.
Taken together, our latest survey findings suggest that healthcare could be entering a more consequential phase of AI adoption—one defined less by novelty and more by discipline. As organizations continue to implement gen AI at scale, competitive advantage will increasingly hinge on how well they integrate AI into core workflows, measure and capture value, and manage residual risks as applications expand in scope and autonomy. The growing interest in agentic AI underscores this shift: Moving from isolated applications to orchestrated systems will raise the stakes for design, governance, and execution.
For healthcare leaders, the challenge ahead is not simply to adopt AI faster but to build the organizational capabilities required to sustain and scale it. Those that do will be better positioned to translate technological progress into lasting operational and clinical impact.
