AI infrastructure has a networking problem, zero-trust overlays can help

Gartner projects worldwide AI spending will hit $2.52 trillion in 2026. The five largest US cloud providers have collectively committed up to $690 billion in capital expenditure this year alone. Everyone's talking about compute. But beneath all of this investment sits a problem that doesn't get nearly enough attention: the network. AI workloads are fundamentally distributed. Training runs span GPU clusters across providers. Inference happens at the edge. Agents call APIs across cloud boundaries. The networking approaches most organizations rely on (traditional VPNs, security groups, manual firewall rules) were designed for a simpler era. Where things are breaking down Ninety-two percent of enterprises now operate multi-cloud environments. AI teams spread GPU workloads across AWS, GCP, Azure, and specialized providers like CoreWeave or Lambda Labs, often because no single provider has the capacity they need. But each cloud comes with its own VPN tooling, addressing scheme, and firewall