PROVISIONAL PROGRAMME   THURSDAY 29 OCTOBER 2026 (AFTERNOON)   DAY 1 / Foundations of Artificial Intelligence: Understanding, Trust and Data     Opening Keynote   AI: What Are We Talking About? Concepts, Methods and Limitations     An introductory lecture providing a common understanding of artificial intelligence, its different methodological approaches, current capabilities and limitations, and the challenges associated with its use in scientific and regulatory contexts.   SESSION 1 / Validation, Explainability and Trust     This session will explore the conditions required for trustworthy AI in scientific and regulatory applications. Contributions are expected to address model validation, explainability, robustness, reproducibility, uncertainty and performance evaluation, as well as broader issues related to transparency and confidence in AI systems.   SESSION 2 / Data and Omics as the Foundation of AI     AI is only as reliable as the data on which it is built. This session will focus on data infrastructures, omics technologies, data quality and interoperability, highlighting how high-quality datasets enable effective AI applications for surveillance and risk assessment.   FRIDAY 30 OCTOBER 2026 (FULL DAY)   DAY 2 / From Models to Decision-Making   SESSION 3 / AI for Surveillance and Early Detection     This session will present AI applications supporting surveillance activities, including early warning systems, outbreak detection, information extraction and the integration of heterogeneous data sources for improved situational awareness.   SESSION 4 / AI for Risk Assessment     This session will examine how AI can complement existing risk assessment methodologies through predictive modelling, hybrid approaches combining mechanistic and machine learning models, scenario analysis and uncertainty characterization. Particular attention will be given to the added value of AI alongside established risk assessment frameworks.   SESSION 5 / Case Studies and Implementation     The final scientific session will focus on practical implementation. Speakers are encouraged to present operational experiences, successful applications, challenges encountered and lessons learned from deploying AI in food safety, animal health or plant health.   CLOSING ROUNDTABLE / AI in Risk Analysis: What is Realistic in the Next 5–10 Years?     A forward-looking discussion bringing together keynote heads of the institutes, speakers, session chairs and participants to identify priorities for future collaboration and methodological development.   Copyright © 2026 Ptolémée.