The state of AI in healthcare: closing the intent-capacity gap
Buying AI before you can run AI is a sequencing problem, not a technology problem. See where 75 healthcare executives stand on AI maturity, the barriers in their way, and how they’re allocating capital into 2026.
AI now ranks as the number one investment priority for healthcare executives. The ambition is real; the capacity to act on it is not. 75% of leaders are on offense, actively scaling or rebuilding core capabilities. Yet 69% sit in early-stage or developing AI maturity. That gap between intent and capacity is what this report measures.
The diagnosis is the same across the data: organizations buy disconnected point solutions before they build a unified data layer, and the ROI never materializes.
The benchmark report “Health Enterprise AI Readiness: The State of AI in Healthcare 2026” is built on an assessment of 75 senior payer, provider, and HealthTech executives. Co-authored by Emids and ServiceNow, it lays out a tested sequence for the decisions that separate scaled AI from stalled pilots: data governance, technical debt, and operating-model change.
What’s inside the report
- The maturity landscape: why 41% of healthcare organizations stall in the pilot trap and never reach enterprise scale.
- The 6 barriers: how technical debt, talent shortfalls, and shifting regulation multiply the cost of AI initiatives.
- The priority gap: why 64% of executives say their automation domains are underinvested, a budget-allocation problem more than a funding problem.
- The threat surface: why 81% confidence in traditional cybersecurity leaves modern LLM risks unaddressed.
- 6 strategic imperatives for 2026: boardroom-ready moves to align payer, provider, and patient incentives and build data partnerships that last.
Stop funding disconnected silos. Get the sequence that turns stalled pilots into AI running at enterprise scale, securely.
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