AIM-IS
AIM-IS: AI Methods for Implementation Science
Artificial intelligence is arriving quickly in implementation science, from evidence synthesis to the analysis of program roll-outs. AIM-IS asks how the field can use these tools rigorously and responsibly, and gives researchers and practitioners the means to report what they did.
Map the landscape of AI applications, outcomes and gaps across implementation science.
Develop a framework for the responsible use of AI in implementation practice and research.
Build a practical toolkit for teams applying AI methods.
Establish a reporting standard so that AI-supported implementation work can be appraised and reproduced.
The protocol is published in Implementation Science (2026). The scoping review of AI applications in implementation science is complete. The framework, toolkit and reporting standard are in development, led in the lab by Dr. Priyanka Shrestha with an international author group.
AIM-IS combines a living scoping review with expert consensus methods, convening an international group of implementation and behavioural scientists to co-develop the framework, toolkit and reporting standard.
- Scoping review of AI in implementation science · complete
- AIM-IS framework · in development
- AIM-IS toolkit · in development
- AIM-IS reporting standard · in development
An international author group whose members are based at UCL, Northwestern University, Washington University in St. Louis, the Ottawa Hospital Research Institute, UNSW Sydney and other institutions. These are authors' affiliations, not formal institutional partnerships.
SELECT-IT is listed because the lab's work on choosing and using theories, models and frameworks informs how AIM-IS structures its guidance.
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Collaborations, consensus-panel participation and trainee projects on AI methods.