Most organizations remain stuck in early-stage AI maturity
59% of organizations are still in early or developing AI maturity, exposing a widening gap between AI ambition and organizational readiness.
Developed by Emids in collaboration with ServiceNow, this research captures the perspectives of 75 senior healthcare executives on the state of AI adoption, readiness and investment across healthcare.
Healthcare organizations are accelerating AI investment, but most still lack the operational foundations required to scale it effectively. The gap is no longer about awareness or intent. It is about readiness.
This pre-summit industry assessment, conducted by Emids and ServiceNow, captures how payer, provider, and health-tech executives are navigating AI maturity, capital allocation, workforce constraints, interoperability challenges, and enterprise transformation priorities heading into 2026.
The findings reveal a clear pattern: organizations investing in governance, data infrastructure, and enterprise operating models are moving beyond pilots and creating measurable enterprise value. Those pursuing disconnected AI initiatives without foundational readiness remain stuck in costly cycles of experimentation.
Inside the report, healthcare leaders will uncover the structural barriers slowing AI adoption, the investment gaps shaping strategic decisions, and the imperatives organizations must address to compete in the next phase of healthcare transformation.
59% of organizations are still in early or developing AI maturity, exposing a widening gap between AI ambition and organizational readiness.
65% rank AI and automation as their #1 investment priority, yet 64% believe the domain remains underfunded and fragmented across silos.
50% of executives identified payer-provider-patient incentive misalignment as the single largest systemic obstacle to progress.
Three in four organizations are actively transforming or scaling capabilities rather than delaying modernization initiatives.
This report was produced in collaboration with ServiceNow, whose team contributed to the research and authored its closing chapter on AI execution at enterprise scale.