Artificial intelligence (AI), particularly large language models (LLMs) and AI-powered research assistants, is rapidly changing the landscape of knowledge synthesis. This information session will provide an overview of the opportunities and limitations of using AI throughout the knowledge synthesis process, from refining research questions and developing eligibility criteria to building search strategies, screening studies, conducting quality assessment and data extraction, synthesizing findings and supporting scientific writing.

Through practical examples drawn from presenter experience and published literature, participants will explore where AI can improve efficiency, where caution is warranted and how to critically evaluate AI-generated outputs. The session will also discuss emerging best practices for documenting and reporting AI use in knowledge synthesis to promote transparency, reproducibility and research integrity.

By the end of this workshop, participants will be able to:

• Describe current and emerging applications of AI, including LLMs and AI-powered research assistants, across the stages of the knowledge synthesis process
• Recognize the potential benefits, limitations, and sources of bias associated with using AI to support knowledge synthesis tasks
• Identify current recommendations and best practices for the transparent and responsible reporting of AI use in knowledge synthesis projects

Must be a Waterloo student, staff or faculty member to attend. It is highly recommended that participants attend the Systematic and Scoping Review Methods workshop on October 27, 2026 to understand the foundational steps of the knowledge synthesis process.

This is an online event, please register to receive the event link. If you have accommodation requests or questions, reach out to libevents@uwaterloo.ca with your needs.

Please note: This is the fourth of a four-part workshop series on systematic and scoping reviews. You do not need to attend all four; please register for each workshop separately.