Healthcare organizations are accelerating their use of artificial intelligence to improve efficiency and ease administrative burden, but most remain cautious about deploying AI in high-risk clinical scenarios, according to a Dec. 29 report from KLAS Research.

The perception-based report draws on interviews and surveys with 3,370 respondents across 1,742 provider and payer organizations conducted throughout 2025. Rather than evaluating vendor performance or market share, the research highlights which AI use cases and vendors are most commonly used or considered by healthcare organizations.

Report Shows 4 Key Areas of AI Adoption in Healthcare

1. AI Is Improving Operational Efficiency More Than Reinventing Care Delivery

• Nearly all organizations reported piloting or using AI in 2025, but most deployments remain limited in scope.
• AI is primarily used in lower-risk, operational workflows such as documentation, coding, meeting transcription, and administrative support.
• Higher-risk clinical applications, including clinical decision support and agentic AI, are largely confined to pilot phases.
• Key barriers to broader adoption include a lack of governance frameworks, uncertainty around measurable ROI, and challenges integrating AI into existing workflows.

2. Microsoft and Epic Lead AI Use and Consideration

• Microsoft is the most frequently cited vendor, driven by the adoption of ambient speech and generative AI tools across clinical and administrative settings.
• Epic follows closely, with AI capabilities embedded across chart summarization, automated patient messaging, and revenue cycle workflows.
• OpenAI, Abridge, and third-party ambient documentation vendors are commonly considered, particularly where organizations prefer best-of-breed solutions.
• Vendor selection is often influenced by integration with existing EHR systems and enterprise technology stacks.

3. Ambient Speech Remains the Top Clinical AI Use Case

• 79% of organizations reported using ambient speech technology to support clinical documentation.
• Respondents cited improvements in clinician documentation efficiency and EHR usability as key benefits.
• EHR vendors, including Epic, are rolling out competing ambient solutions, prompting organizations to evaluate options based on pricing and integration.
• Adoption of other clinical AI tools with direct patient impact remains limited due to safety, regulatory, and liability considerations.

4. AI Investment Plans Focus on Revenue Cycle and Patient Engagement

• Revenue cycle use cases — including claims adjudication (24%), coding automation (24%), and denials management (17%) — are among the most commonly adopted.
• Organizations view revenue cycle AI as a lower-risk opportunity with clearer ROI compared to clinical applications.
• Patient engagement use cases, such as automated messaging and digital communication workflows, are gaining momentum.
• Imaging AI, particularly in neurology and breast imaging, remains well established due to its longer history of use in healthcare.

Overall, the findings indicate that healthcare organizations are adopting AI cautiously, prioritizing operational efficiency, lower-risk use cases, and strong EHR integration. As governance and ROI clarity improve, these foundational deployments are expected to pave the way for broader clinical and patient-facing AI applications.

Read our latest articles for more on healthcare’s adoption of AI and the importance of staying HIPAA-compliant.

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