The Edge Is the New Data Center, According to Cisco

Global demand for AI computing is outpacing supply at every level of the stack.

The race has shifted from building larger models to finding where those models can actually run, where power is available and latency is low. That search is pushing compute outward from the cloud to the edge.

Power defines the new geography

The scale of the build-out is unprecedented. Amin Vahdat, Google Cloud’s vice president for systems infrastructure, said this cycle is “100 times what the internet was.” Cisco’s Jeetu Patel compared it to “the space race and the Manhattan Project all put into one.” Both point to a common constraint: power. “Data centers are being built where the power is available,” Vahdat said in the same interview. The old rule of locating compute near population centers no longer applies.

Cisco’s AI Readiness Index quantified the gap. Only 13 percent of companies have infrastructure capable of scaling AI workloads, and just 21 percent report sufficient access to GPUs. More than half say their networks can’t meet AI bandwidth or latency requirements. Most face what Cisco calls "AI infrastructure debt", that is, aging data centers, inconsistent governance, and limited visibility across systems. The problem is structural: power and networking costs are rising faster than compute efficiency, while demand for localized inference keeps accelerating.