Where AI Adoption Is Growing for Health Systems

These are the areas seeing the biggest jump in implementation and producing the highest return on investment.

Health systems are getting more comfortable with AI adoption, allowing them to ramp up deployment in meaningful areas.

Eliciting Insights’ recent report reveals how quickly that shift is happening. According to the survey of 120 health systems across the U.S., 75% are now using at least one AI application, up from 59% in 2025. The growth is even more pronounced among organizations using at least three AI solutions, with half of respondents meeting that criteria this year, compared to 30% in the prior year.

It’s notable where that adoption is taking place, with the biggest uptick observed in areas tied to workforce and financial performance.

Clinical note-taking/ambient listening tools remain the most widely adopted AI applications across health systems, reaching 68% adoption, resulting in 62% year-over-year growth.

Other documentation-related tools are also expanding. AI-based clinical documentation improvement has reached 43% adoption after 59% year-over-year growth, reflecting continued investment in reducing administrative burden for clinicians.

Several revenue cycle use cases are gaining traction as well. AI coding solutions are in use at 36% of health systems after 29% year-over-year growth, while tools that support appeals and denial management are spreading. Prepopulated technical appeal adoption is up from 14% to 21%, and clinical appeals adoption has similarly trended upwards from 15% to 19%.

Patient-facing use cases are taking hold, particularly in communication. Draft replies to patient messages have reached 36% adoption and showed 80% growth, one of the fastest increases in the report.

Administrative automation is also moving forward, with AI chatbots in use at 25% of health systems, supporting front-end operations and access.

Despite the growth, adoption remains uneven across organizations. Executives reported a mix of experiences with implementation, including governance challenges and hesitation among staff, which continue to shape how quickly tools are rolled out.

What's driving ROI

At the same time, financial impact is becoming clearer. Among health systems that are measuring performance, more than half report at least a twofold return on investment from their AI deployments.

AI-based clinical documentation improvement and denial prediction are leading the way, with 71% and 70% of health systems, respectively, reporting at least a twofold ROI. These tools are closely tied to revenue integrity, which helps explain their strong performance.

Other applications are also showing solid results. AI coding solutions follow closely, with 66% of organizations reaching at least a twofold ROI, while ambient listening tools are not far behind at 61%. The data shows that health systems are getting the most bang for their buck from AI in areas that either capture revenue more effectively or reduce the administrative burden tied to care delivery.

The next phase of AI adoption will likely follow along the same path as organizations commit to deeper investment in use cases that have already proven their value for creating operational efficiency and maximizing returns.