Part 5: The Use of AI in Systematic and Scoping Reviews (2026)

Artificial intelligence is reshaping the landscape of evidence synthesis — but knowing where and how to use it makes all the difference. This workshop offers a practical exploration of AI's role in systematic and scoping reviews, from database searching and title/abstract screening to data extraction and synthesis. Participants will leave with a clearer picture of which tools fit which tasks, and a realistic understanding of the opportunities and limitations AI brings to evidence synthesis research. In this workshop participants will: Describe how AI can support certain stages of the systematic and scoping review process Select appropriate AI tools for specific review tasks Critically evaluate the benefits and risks of integrating AI into evidence synthesis workflows This workshop is part of the Systematic Review Workshop Series. Presenter(s): Mê-Linh Lê, Health Sciences Librarian John Bryans, Health Sciences Librarian 00:00:00 - Welcome & introductions 00:06:55 - Setting the stage — reviews require rigor, replicability, transparency; AI *augments*, never replaces expertise 00:10:00 - Guidance & position statements (NICE, Cochrane, JBI, RAISE recommendations) 00:12:03 - Defining "AI" — generative AI vs. machine learning/automation 00:14:45 - Disclosing AI use & transparent reporting standards 00:16:43 - How to choose an AI tool — evaluation criteria 00:19:06 - Visual maps of tools by review stage: 00:23:35 - Stage 1 — Developing your research question 00:27:44 - Stage 2 — Assembling your team 00:29:11 - Stage 3 — Writing your protocol 00:34:39 - Stage 4 — Searching 00:43:55 - Stage 5 — Screening 00:48:27 - Stage 6 — Assessing quality / risk of bias 00:49:45 - Stage 7 — Data extraction 00:53:00 - Stage 8 — Analysis / critical appraisal 00:54:35 - Stage 9 — Disseminating results (journal selection, translation tools) 00:57:15 - Summary — where AI is most vs. least helpful across the review process Learn more at https://umanitoba.ca/libraries/