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Artificial Intelligence Search Tools for Evidence Synthesis: Comparative Analysis and Implementation Recommendations.
Robin Featherstone1, Melissa Walter1, Danielle MacDougall1
1Canada's Drug Agency Ottawa Ontario Canada.
Cochrane Evidence Synthesis and Methods
|September 11, 2025
Summary
Artificial Intelligence (AI) search tools show variable performance for information retrieval tasks. A "fit for purpose" strategy is recommended, where specialists use AI tools for specific needs.
Area of Science:
- Health Sciences
- Information Science
- Computer Science
Background:
- Novel technologies like Artificial Intelligence (AI) require careful evaluation for implementation.
- Canada's Drug Agency's Research Information Services sought to assess AI tools for information retrieval.
Purpose of the Study:
- To evaluate the performance of three AI search tools: Lens.org, SpiderCite, and Microsoft Copilot.
- To develop implementation recommendations for AI tools in information retrieval.
Main Methods:
- A multimodal approach including literature review, retrospective comparative analysis, and focus groups.
- Compared AI tool performance against Canada's Drug Agency's standard information retrieval practices.
- Measured sensitivity/recall, number needed to read (NNR), time, unique contributions, and impact on project findings using data from 7 completed projects.
Main Results:
- AI search tools demonstrated inconsistent and variable performance across different information retrieval tasks.
- Performance metrics varied significantly between the evaluated AI tools and standard practices.
Conclusions:
- AI search tools are not universally superior and exhibit performance limitations for complex information retrieval.
- A 'fit for purpose' approach is advised, guiding Information Specialists to leverage AI tools strategically for specific tasks or project types.
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