This session focuses on AI and data driven methods for CCUS and energy transition across subsurface and integrated energy systems. It includes applications in CO2 EOR, carbon storage, and low carbon energy systems, using physics informed surrogate modeling, transformer based methods, and mixture of experts frameworks for optimization and decision making under uncertainty, along with machine learning approaches for emissions prediction and carbon intensity optimization. These approaches aim to improve prediction, reduce uncertainty, and enable more efficient and sustainable energy operations.