The first wave of AI infrastructure centred on large-scale training environments, but the next phase will be defined by where AI delivers real-world outcomes. As AI becomes embedded across buildings, healthcare, manufacturing and critical infrastructure, inference will increasingly happen closer to where decisions are made. From autonomous buildings and digital twins to robotics and industrial automation, distributed AI is enabling faster, more resilient and personalised experiences while reshaping infrastructure requirements. This session explores how AI is moving beyond centralised campuses to a more distributed future, and what that means for the next generation of AI-ready infrastructure. Join this episode to discover:

• Why autonomous buildings, digital twins, robotics and industrial automation represent the next frontier for AI
• Where AI inference is likely to be deployed, from centralised campuses to regional and edge facilities
• What infrastructure is needed to support distributed AI workloads while balancing performance, resilience and latency
• What the next five years of AI deployment will look like, and where the biggest opportunities will emerge