Health systems are giving more and more duties to AI agents — though don’t expect them to replace physicians or nurses anytime soon.
Agentic AI, which autonomously determines and executes the steps needed to achieve defined goals, is one area where healthcare hasn’t been left behind in its digital transformation, with the most scaling use cases of almost any industry, according to McKinsey & Co. Most, however, have been administrative in nature, health system executives told Becker’s.
“We’re seeing real traction with AI agents across our organization,” said Ryan Smith, senior vice president and chief information and digital officer of Salt Lake City-based Intermountain Health. “What began as a set of targeted experiments has quickly become a set of tools that people rely on every day.”
The biggest impact at the 34-hospital system has been on IT and operational support, with an enterprise AI agent triaging all incoming IT incident tickets. The tool has saved an estimated 20,000 staff hours through automated intake and routing, triaging over 150,000 incidents in the past five months.
Meanwhile, Intermountain’s AI-enabled human resources front door has resolved about 35,000 employee inquiries without the need to open a case, executing the work of about 40 full-time positions. Usage has grown more than tenfold year over year.
Another Intermountain agent continuously optimizes job postings based on performance and hiring outcomes, reducing recruitment marketing by over 25% while maintaining efficacy. An internally developed financial impact tool uses AI agents to analyze clinical documentation against payer-specific requirements, driving a 50-percentage-point improvement in post-claims denial outcomes. In the call center, AI agents cancel, reschedule and confirm appointments.
“Together, these solutions improve the patient experience while enabling staff to support more complex, higher‑value interactions,” Mr. Smith said.
AI agents have been slower to arrive on the clinical side — for obvious reasons. Unlike generative or assistive AI, agentic works independently rather than simply producing outputs.
“When it comes to high-stakes clinical workflows where patient safety is paramount and error tolerance is essentially zero, we’re still in the first inning,” said Eric Shelley, vice president of information services at Chicago-based Northwestern Medicine. “The technology shows tremendous potential, but we need to be methodical about validation, integration with clinical decision-making processes, and building the necessary guardrails before we can responsibly scale in those environments.”
The 11-hospital academic system has had early success with AI agents in areas such as administrative workflows, documentation support and coding — what Mr. Shelley called “lower-stakes operational/technical environments where we can accommodate a reasonable error tolerance.”
“Across healthcare, adoption of AI agents is advancing with intention rather than speed,” noted Jane Moran, chief information and digital officer of Somerville, Mass.-based Mass General Brigham. “Because these tools can influence patient care, strong governance, security and monitoring have to come first, so we haven’t broadly deployed autonomous clinical agents yet.”
Meanwhile, Scottsdale, Ariz.-based HonorHealth has been using agentic AI for postdischarge follow-up and preadmission testing before surgeries. “We are learning from these events but are not yet scaling outside of their departments,” said Chief Transformation Officer Jim Whitfill, MD. “We have seen both surprising acceptance by our patients as well as increases in capacity of our staff to care for more patients with the same resources.”
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