An umbrella review of the facilitators and barriers to implementing Artificial Intelligence (AI) solutions within hospital settings: through the lens of the NASSS framework (spread, scale-up and sustainability)

Advancements in artificial intelligence (AI) are revolutionising the healthcare sector, but challenges exist in AI adoption and its long-term use. This umbrella review aimed to identify the facilitators and barriers of AI implementation within hospitals and was registered on PROSPERO. Five databases (MEDLINE, HMIC, CINAHL Plus, Web of Science and Cochrane Reviews) were searched in January 2025, 763 articles were screened, with 13 included. The inclusion criteria encompassed studies implementing AI that were conducted within the hospital setting. The quality of the data were assessed using the ROBIS checklist and data were extracted using the NASSS (Nonadoption, Abandonment, and challenges to the Scale-up, Spread, and Sustainability) framework, to demonstrate how AI implementation was affected by: whether the AI solution had been technologically validated to ensure generalisability across departments; evidence the AI solution brings measurable gains; a lack of trust or understanding among hospital staff; the budgets and resources available to onboard the AI solution, train staff, and maintain the solution; the need for national policies on funding and regulating AI solutions. These factors affected the adoption, spread, scalability and sustainability of AI implementation and could be considered in future implementation efforts. The study was funded by the NIHR (NIHR205439).