Adoption of Artificial Intelligence in Health Care
Original Title: Adoption of Artificial Intelligence in the Health Care Sector
Journal: JAMA health forum
DOI: 10.1001/jamahealthforum.2025.5029
Overview
This study investigated the adoption of artificial intelligence (AI) in the US health care sector compared to other industries from September 2023 to May 2025. Using data from the US Census Bureau's Business Trends and Outlook Survey, which included responses from about 119,300 health care firms, the researchers analyzed biweekly trends in AI use. They found that while AI adoption in health care is increasing, it remains lower than in other sectors. In 2025, 8.3% of health care firms reported using AI, compared to 23.2% in information services and 19.2% in professional, scientific, and technical services. The mean AI use in health care over the study period was 5.9%. A key finding was the identification of an acceleration point in adoption around late December 2024 and early January 2025. Before this point, the biweekly growth rate was minimal at 0.005%; afterward, it increased significantly to 0.03%, representing a 481.5% change in the slope. Within health care, outpatient and ambulatory care firms showed the most substantial growth, increasing from 4.6% adoption in 2023 to 8.7% in 2025, while nursing and residential care facilities saw more limited growth from 3.1% to 4.5%.
Novelty
The study's novelty lies in its use of near real-time, large-scale national survey data to provide a dynamic and comparative view of AI adoption. Unlike previous research that often focused on well-resourced hospitals or specific AI applications, this analysis includes a broad range of organizations of varying sizes across multiple economic sectors. This approach offers a more grounded estimate of AI integration into routine business operations. Furthermore, the application of an interrupted time series analysis to identify a specific inflection point where the rate of adoption accelerated is a distinct contribution. This quantitative evidence of a shift from a nearly flat to a gradually increasing adoption slope provides a data-driven timeline of AI's expanding footprint in the health care industry.
Potential Clinical / Research Applications
The findings have direct implications for future research and policy. Researchers should now investigate the specific types of AI being adopted and the factors driving the disparity between outpatient clinics and residential care facilities. Studies are needed to assess the impact of this rising AI use on clinical outcomes, workforce productivity, and health care costs. It is also important to explore the barriers preventing wider adoption in settings like nursing homes. For policymakers and health care administrators, this study underscores the urgent need for governance frameworks to ensure AI is deployed safely and ethically. It also points to the necessity of developing targeted support programs and financial incentives to help under-resourced subsectors adopt beneficial AI technologies, thereby preventing a widening of care quality gaps. Furthermore, the accelerating trend calls for the proactive development of training curricula for the current and future health care workforce.