of healthcare organizations have adopted AI in some capacity
Artificial intelligence is no longer experimental—most organizations now leverage it in at least one area of operations or care delivery.
That means nearly 3 in 4 health systems are already running AI somewhere in their organization today.
Nearly half of organizations have integrated AI into care delivery and operations
Clinicians and clinical leaders report AI is actively embedded in clinical workflows, decision support, or operational systems in at least some departments—moving beyond pilots into real-world use.
organizations plan to use AI to advance patient-centered care
Identifying care gaps and supporting chronic disease management are among the top planned use cases—highlighting how organizations aim to strengthen patient-centered strategies with AI.
or Disparities
(AI-based population health tools)
Management
(AI-driven remote monitoring and alerts)
Care Plans
(based on predictive models)
Outcomes & Feedback
(AI-enabled capture and response)
Adoption is outpacing preparedness
of leaders say their organization has the resources to manage AI-related legal & regulatory requirements
are confident their data is accurate
say their data is fully leveraged for clinical & operational decision-making
AI adoption is accelerating—but readiness is lagging. Only about half of organizations feel equipped to manage regulatory requirements, and fewer than half trust their data—revealing a readiness gap that extends beyond access to AI itself.
say high-quality data is critical for successful AI adoption
Data quality isn't a nice-to-have — it's the foundation everything else is built on.
Each chip = 1% of respondents
are implementing interoperability standards to support digital transformation
Standards such as HL7® FHIR® are helping enable more connected health data, allowing systems to share and use information more effectively.
Interoperability helps connect fragmented data environments—supporting more scalable and AI-ready healthcare ecosystems.
of leaders are highly concerned about AI-powered cyberattacks
As AI capabilities grow, so does the attack surface. Healthcare leaders point to emerging risks such as AI‑driven phishing, deepfake impersonation, and other evolving attack methods.
Organizations are fighting back
The top reason for adopting additional AI security tools: detecting emerging threats that traditional systems may miss.
of organizations report workforce burnout as a challenge to digital health transformation initiatives
It's not just about technology adoption—this reflects the human impact of ongoing digital transformation efforts.
plan to invest in cybersecurity infrastructure in the next 1–2 years
As part of their digital transformation journey, the vast majority of organizations are doubling down on security, recognizing that security is foundational to scaling digital health and AI initiatives.