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A path to a productive, resilient, and sustainable agricultural future lies in the successful integration of disruptive AI-driven agritechnology into decision-making processes across the food supply chain. These advanced solutions are crucial for assessing trade-offs and risks in a world increasingly affected by climate volatility. However, these solutions cannot come without a deeper understanding of the underlying appetite for such solutions.

This seminar explored the pathway towards developing a trusted AI agronomist, combining the Agricultural Production Systems sIMulator (APSIM) with human-centered design principles and stakeholder engagement. APSIM is a globally recognised process-based crop modelling system that allows users to capture the complex dynamics of crop production, yet its uptake by industry has been limited. To enhance adoption, the speakers proposes a new architecture that captures the cropping dynamics but in a simpler representation via an APSIM-based emulator, built using machine learning. This emulator, when coupled with user-centered studies, aims to create a novel, impactful tool that interprets crop growth and its uncertainties effectively and rapidly, bridging the gap between research and practical application for farmers.