Many health care leaders are leaning into agentic AI as adoption hurdles ease

The Deloitte report highlights that a majority of healthcare leaders anticipate agentic AI will fundamentally change their operating models, moving beyond traditional and generative AI by planning tasks, adapting to conditions, and coordinating with various systems to deliver outcomes across clinical, administrative, and financial domains. Key findings from a survey of 100 US healthcare technology executives and focus groups indicate that long-standing challenges to AI adoption, such as technical talent shortages, resistance to change, and data quality concerns, are becoming less significant. As a result, 85% of healthcare leaders plan to increase investments in agentic AI over the next two to three years, with 61% already implementing initiatives. An emerging 'AI divide' is noted, with early adopters expecting substantial cost savings, potentially exceeding 20%, by integrating agentic AI into core operating models rather than isolated pilot programs. This technology is expected to enhance consumer engagement, rethink care delivery by orchestrating complex tasks, and transform workforce capabilities by shifting from manual processing to oversight. However, successfully scaling agentic AI requires more than just technology deployment; it necessitates addressing governance, workforce readiness, and data integration challenges to unlock long-term value and ensure responsible implementation with human oversight and explicit guardrails.