2026-06-04 –, Room #3 Language: English
AI agents and agentic AI systems represent a new architectural paradigm for applying Generative AI in workflows that require reasoning, information retrieval, and decision support. Unlike earlier forms of GenAI that focused primarily on text generation, agentic systems integrate retrieval, ranking, planning, and tool-use to deliver more reliable, verifiable, and domain-specific outputs. Their potential impact on information access and evidence synthesis is rapidly expanding.
In this 90-minute workshop, participants will first develop a foundational understanding of key terminology, core concepts, and the current landscape of agentic AI. We will then explore real-world examples demonstrating how agentic AI systems are being used in systematic reviews—including eligibility criteria development, search strategy, citation screening, data extraction, and validation workflows. We will focus on the application of search strategy creation and showcase how the audience can build a search strategy with the assistance of AI agents.
Finally, we will examine practical frameworks for critically appraising these systems, focusing on validity, performance claims, biases, and evaluation methodologies.
Participants will leave with:
- A clearer understanding of what AI agents and agentic systems are (and what they are not)
- Realistic expectations about their potential value and limitations in health libraries and evidence synthesis
- Practical skills to evaluate claims, ask informed questions, and support decision-making in their institutions
This session is designed for health librarians, information specialists, and anyone interested in the future of AI-supported evidence synthesis.
Yuhong Yuan, PhD, is a former gastroenterologist, former Cochrane information specialist, and former Cochrane managing editor. Dr. Yuan is currently an adjunct professor at Western University, a part-time assistant professor at McMaster University, and a senior research associate at London Health Sciences Centre. She has been involved in numerous research projects and has contributed extensively to clinical guideline development as a health research methodologist and guideline methodologist. Dr. Yuan has co-authored over 280 peer-reviewed medical publications and more than 190 conference proceedings, with an h-index of 74 on Google Scholar.
Ghayath Janoudi: MBBS, MSC, PHD (AI EPI) Dr. Ghayath Janoudi, MBBS, MSc, PhD (AI Epidemiology) is the CEO of Loon and a global speaker and expert in AI for clinical research. He spent over 15 years in leadership and executive roles at Canada's Drug Agency and various clinical research organizations where he worked in Health Technology Assessment (HTA) and Health Economics & Outcomes Research (HEOR). Dr. Janoudi has pioneered Cognitive Ensemble AI Systems and authored numerous publications, including using AI in clinical discovery, outlier analysis, drug therapy assessment, and outcomes-based healthcare. His extensive work in the field has brought him recognition as Canada Emerging Healthcare Leader in 2024.