Artificial intelligence is moving rapidly beyond traditional machine learning and standalone large language models (LLMs). We are entering a new era of foundation models, multimodal AI, digital twins, and agentic AI. The real value of these technologies will come not simply from building larger AI models but from applying them to solve our everyday problems, including human and animal health and agriculture.

This keynote will explore these technologies through real-world applications. Multimodal foundation models can integrate diverse data types, including medical images, health records, wearable and physiological signals, livestock images and sensors, satellite and drone imagery, and weather, soil, and crop data. By connecting these different sources, Foundation AI can provide a more complete understanding of a patient, an animal, a crop, or a farm.

In human health, these technologies can support earlier disease detection, medical image analysis, personalised risk prediction, remote monitoring, and clinical decision-making. In cattle and livestock farming, AI can monitor animal health, behaviour, growth, welfare, reproduction, and nutrition. In agriculture, AI can support crop monitoring, disease detection, yield prediction, precision irrigation and fertilisation, and sustainable farm management.

A key focus will be AI-enabled Digital Twins for the dynamic digital representations of patients, animals, crops, or farms that are continuously updated with real-world data. Digital twins can help understand current conditions, predict future outcomes, and test possible interventions before they are applied in the real world.

The keynote will also discuss agentic AI, where intelligent AI agents can analyse information, use specialised tools, recommend actions, and adapt as conditions change. Together, foundation models, digital twins, and agentic AI can create practical intelligent systems that improve human health, animal welfare, agricultural productivity, sustainability, and the resilience of the planet.

Prof. Dr. Mohammad Ali Moni is a leading global scientist in AI and Digital Health Technology. He completed his PhD in AI and Digital Health at the University of Cambridge and worked as a postdoctoral fellow at world-renowned universities including Oxford, Cambridge, and the University of Sydney.

Prof. Moni has published 550+ journal articles, receiving 86,000+ citations with an h-index of 114. He is the recipient of numerous prestigious awards and fellowships, including the Commonwealth Fellowship, USyd Fellowship, UoW Distinguished Engineering Award, Certara Fellowship, and Researcher of the Year Award. Since 2021, he has consistently been ranked among the top 0.1% of scientists worldwide.