Adoption of artificial intelligence tools in health care lags other industries; within health care, nursing and residential care is even further behind. 

This is a finding of an analysis recently published in JAMA Health Forum. The study compared AI use in health care to other sectors from 2023 to 2025.

The authors examined the U.S. Census Bureau’s Business Trends and Outlook Survey (BTOS) to see how health care respondents answered, “In the last two weeks, did this business use … [AI] in producing goods or services? (Examples of AI: machine learning, natural language processing, virtual agents, voice recognition, etc.).” More than 1 million companies across business sectors responded.

The authors found that health care is adopting and using AI at a slower rate than other sectors. Between 2023 and 2025, the mean adoption AI rate was 5.9% and increased over time. By 2025, AI use in health care stood at 8.3%. This was lower than in other sectors, such as finance and insurance (11.6%); education (15.1%); professional, scientific, and technical services (19.2%); and information services (23.2%).

Nursing facilities are adopting at an even slower rate. Adoption grew from 3.1% in 2023 to 4.5% in 2025, compared to ambulatory surgery centers, which grew to 8.3% adoption by 2025.

One reason for the lag may be the lack of funding for modernizing IT in nursing homes and residential care facilities, explained Scott Code, VP, Center for Aging Services Technologies (CAST) at LeadingAge, the association of nonprofit providers of aging services:

“Unlike hospitals and physician practices, nursing homes never received meaningful use dollars or other major federal incentives to modernize health information technology,” Code told Skilled Nursing News. “As a result, many providers are still catching up on basics like electronic health record optimization, interoperability and staffing capacity to support new tools. That limited foundation makes it more difficult to layer in emerging technologies like AI – even as interest grows.”

Tech to help skilled nursing headaches

Still, companies are releasing AI tools that assist skilled nursing providers with their biggest hurdles, which could be setting the stage for increased adoption.

As one example, ExaCare AI recently raised $30 million in Series A funding for software that helps streamline admissions. The company is in more than 1,500 facilities and has tools to highlight clinical risks, standardize criteria and streamline communications with the goal of reducing administrative burden, according to a press release.

Many providers are adopting tools to help with revenue cycle management, virtual nursing appointments and real-time patient monitoring. Matt Nieukirk, director of operations for SNF practice and home health at OSF Healthcare, previously told Skilled Nursing News that AI adoption is critical to bridge gaps between hospitals and post-acute care providers.

Even in 2023, when the BTOS first asked about AI adoption, skilled nursing providers were examining their options for improving patient care through AI. Lisa Chubb, chief clinical officer at Brickyard Health, told Skilled Nursing News at the time that the company was incorporating AI into the electronic health record to improve clinical decision making and patient monitoring.

“Today, most AI use in nursing homes comes through features embedded in existing systems, such as fall detection, clinical decision support and revenue cycle workflows, rather than broad adoption of generative AI or advanced analytics,” Code said. “As vendors integrate AI into core platforms and providers face mounting workforce and documentation pressures, adoption will accelerate. But the sector is starting from a very different baseline because it was never part of the meaningful use era.”

More research needed

A previous study found hospitals are adopting AI technology at a rapid pace, with 90% of responding health systems reporting some degree of success in AI adoption for imaging and radiology. However, the JAMA Health Forum authors pointed out the BTOS captures responses from a wider range of businesses, including small firms.

Additional research is needed into why AI adoption in health care, and nursing facilities in particular, is behind and what this might mean in terms of clinical implications, concluded the study’s authors. They also called for effective regulations to ensure the safe and efficient use of AI in health care.