How Healthcare Differentiates on Core AI Practices

Author: Beth Schultz, VP of Research and Principal Analyst

From risk management to model adoption, a comparative look at how healthcare approaches foundational AI strategies

In our second-quarter 2026 global artificial intelligence (AI) research study, AI Technology Foundation & Strategy: 2026-27, Metrigy has found that companies overall are highly positive about AI’s impact for them. This includes 97.3% of the 79 healthcare companies that participated, even as their CX and IT leaders face unique perils in navigating today’s world of AI everywhere. Challenges for healthcare companies range from the onus of supporting life-or-death decision making, the need to adhere to strict patient privacy regulations, the complications of working with deep-seated legacy systems and processes, and more. Because of these distinct pressures, healthcare CX and IT leaders approach AI implementations differently than their peers in other industries, Metrigy finds.

This report delves into exactly where healthcare organizations diverge from the overall study base of 759 companies. By understanding these specific operational and strategic differences, healthcare CX and IT decision makers can evaluate their own progress and adjust their technology roadmaps to align with vertical-specific best practices. This report explores:

• What healthcare organizations do to support model flexibility and ensure a smooth plan for moving from one model to another
• Why healthcare organizations lag others in tracking their AI model inventories
• How healthcare organizations are embracing the AI Center of Excellence (CoE)
• Why small language models (SLMs) deliver unmatched task optimization for healthcare organizations

Table of Contents

• How Healthcare Stands Apart on AI
  • What’s Included in a Model Exit Plan
  • Governance Blind Spot
• Elevating AI Leadership to Combat Pilot Failure
• The Unexpected Reality Of SLMs
• Conclusion & Recommendations
• Working With Metrigy