An umbrella review of facilitators and barriers to the adoption, spread and sustainability of AI solutions within hospital settings.

Abstract

There is a growing use of artificial intelligence (AI) in healthcare settings, but challenges exist with AI adoption and its long-term use. This umbrella review funded by the NIHR (NIHR205439), 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 and re-run in February 2026, 1184 articles were screened, with 20 included. The inclusion criteria encompassed reviews implementing AI within hospital settings. The quality of the data were assessed using the ROBIS checklist and data were synthesised using the NASSS (Nonadoption, Abandonment, and challenges to the Scale-up, Spread, and Sustainability) framework. We found AI implementation was affected by: whether an AI solution as an intervention had been externally validated to ensure generalisability across different settings; evidence that the AI solution brings measurable gains; the level of trust in and understanding of the AI solution 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 should be considered for future implementation.