Abstract
To inform implementation recommendations for novel or emerging technologies, Research Information Services at Canada's Drug Agency conducted a multimodal research project involving a literature review, a retrospective comparative analysis, and a focus group on 3 Artificial Intelligence (AI) or automation tools for information retrieval (AI search tools): Lens.org, SpiderCite, and Microsoft Copilot. For the comparative analysis, the customary information retrieval practices used at Canada's Drug Agency served as our reference standard for comparison, and we used the eligible studies of 7 completed projects to measure tool performance. For searches conducted with our usual practice approaches and with each of the 3 tools, we calculated sensitivity/recall, number needed to read (NNR), time to search and screen, unique contributions, and the likely impact of the unique contributions on the projects' findings. Our investigation confirmed that AI search tools have inconsistent and variable performance for the range of information retrieval tasks performed at Canada's Drug Agency. Implementation recommendations from this study informed a "fit for purpose" approach where Information Specialists leverage AI search tools for specific tasks or project types.