AI has entered a new phase. The race is no longer about smarter models or more GPUs. It’s about infrastructure. Power, networking, data readiness, governance and cost are now the real constraints shaping what AI can deliver at scale.

This RCRTech report starts from a simple idea: AI advantage comes from execution. The winners won’t be those who build the most intelligence, but those who can operate it reliably, efficiently and in production. As AI moves beyond pilots, its foundations look less like software and more like industrial systems — with major implications for enterprises, cloud providers, telcos, data center operators and policymakers.

Based on insights from RCRTech’s AI Infrastructure Week, the report cuts through false binaries like cloud versus edge or centralized versus distributed. Instead, it focuses on how compute, networks and energy systems are converging — and how organizations are orchestrating AI workloads across environments shaped by latency, regulation, sustainability and cost.

Drawing on interviews with infrastructure vendors, operators, analysts and technology leaders, the report examines how AI is being operationalized today, where cloud-era assumptions are breaking down and where the next infrastructure bottlenecks are already emerging.