What are examples of agentic AI in healthcare?

Agentic AI is commonly used in operational workflows such as patient access, intake, prior authorization, revenue cycle management, documentation follow-ups, and remote monitoring escalation. These systems execute approved actions within defined boundaries and escalate uncertainty rather than making independent clinical decisions.

How do healthcare organizations prepare for agentic AI?

Preparation focuses on readiness, not experimentation. Organizations define where AI can act, enforce disciplined data access, ensure secure system integration, establish governance and escalation paths, and start with operational use cases where outcomes are measurable.

What risks does agentic AI introduce in healthcare?

The primary risks come from uncontrolled autonomy, including improper data access, silent execution, unclear accountability, and regulatory exposure. Without strong governance and traceability, these risks increase as agentic AI scales.

When will agentic AI be widely adopted in healthcare?

Agentic AI adoption is expected to accelerate in 2026, beginning with administrative and operational workflows. Organizations that prepare early will scale safely, while others will face pressure to adopt without adequate controls.