Tracking the Evolving Role of Artificial Intelligence in Implementation Science: Protocol for a Living Scoping Review of Applications, Evaluation Approaches and Outcomes
Year: 2026
Type: article
Abstract: Background: Artificial intelligence (AI) offers significant opportunities to improve the field of implementation science by supporting key activities such as evidence synthesis, contextual analysis, and decision-making to promote the adoption and sustainability of evidence-based practices. This living scoping review aims to: (1) map applications of AI in implementation research and practice; (2) identify evaluation approaches, reported outcomes, and potential risks; and (3) synthesize reported research gaps and opportunities for advancing the use of AI in implementation science. Methods: This scoping review will follow the Joanna Briggs Institute (JBI) methodology and the Cochrane guidance for living systematic reviews. A living scoping review is warranted to keep up with the rapid changes in AI and its growing use in implementation science. We will include empirical studies, systematic reviews, grey literature, and policy documents that describe or evaluate applications of AI to support implementation science across the steps of the Knowledge-to-Action (KTA) Model. AI methods and models of interest include machine learning, deep learning, natural language processing, large language models, and related technologies and approaches. A search strategy will be applied to bibliographic databases (MEDLINE, Embase, CINAHL, PsycINFO, IEEE Xplore, Web of Science), relevant journals, conference proceedings, and preprint servers. Two reviewers will independently screen studies and extract data on AI characteristics, specific implementation task according to the KTA Model, evaluation methods, outcome domains, risks, and research gaps. Extracted data will be analyzed descriptively and synthesized narratively using a mapping approach aligned with the KTA Model. Discussion: This living review will consolidate the evidence base on how AI is applied across the spectrum of implementation science. It will inform researchers, policymakers, and practitioners seeking to harness AI to improve the adoption, scale-up, and sustainability of evidence-based interventions, while identifying areas for methodological advancement and risk mitigation. Review registration: Open Science Framework, May 2025: https://doi.org/10.17605/OSF.IO/2Q5DV.
Source: F1000Research
Authors: Guillaume Fontaine, Olivia Di Lalla, Susan Michie, Byron J. Powell, Vivian Welch, James Thomas, Jeffery Chan, Samira Abbasgholizadeh-Rahimi, France Légaré, Janna Hastings, Sylvie D. Lambert, Justin Presseau, Sharon E. Straus, Ian D. Graham, Ruopeng An, Daniel N. Elakpa, Meagan Mooney, Alenda Dwiadila Matra Putra, Rachael Laritz, Natalie Taylor
Institutions: Ottawa Hospital Research Institute, Lady Davis Institute for Medical Research, McGill University, University College London, Washington University in St. Louis, University of Ottawa, Bruyere Health Research Institute, UNSW Sydney, Mila - Quebec Artificial Intelligence Institute, Université Laval, SIB Swiss Institute of Bioinformatics, University of Zurich, University of St.Gallen, St Mary's Hospital Centre, St. Michael's Hospital, University of Toronto, Unity Health Toronto, New York University, Jewish General Hospital
Language: English
Subfield: General Health Professions
Field: Health Professions
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,350
OpenAlex ID: W7128678094