Panel – Power, Compute and Connectivity: building the infrastructure for the inference era

The AI market is entering a new phase. As workloads shift from training to large-scale inference, the challenge is no longer simply deploying GPUs, but orchestrating the power, connectivity and compute infrastructure required to serve billions of AI-driven interactions. Recent industry research found that 64% of executives have demand visibility of 12 months or less, highlighting just how difficult capacity planning has become in a rapidly evolving market. The ability to secure power, connect infrastructure and rapidly deploy compute is emerging as the defining factor that will determine who can deliver AI capacity fastest and capture the greatest share of growing inference demand.

• As inference becomes the dominant AI workload, how will infrastructure requirements differ from the training-centric AI market of today?
• Can distributed and edge-based inference unlock stranded power, reduce latency and create new opportunities outside traditional AI hubs?
• What combination of power access, network connectivity and compute deployment will define the next generation of AI infrastructure leaders?

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