Enterprises are racing to deploy AI pilots, but the jump to production is stalling. IDC‘s 2026 AI in Networking Special Report Survey, sponsored by Google Cloud, identifies the core bottleneck as infrastructure, not models. 32.6% of respondents cite security concerns as AI workflows become more distributed and autonomous. 26.8% point to automation challenges from manual operations and fragmented controls, while 24.7% blame limited staff skills and bandwidth. Agentic AI compounds these issues with dynamic interactions across diverse agent frameworks, model providers, clouds, APIs, and internal applications, dramatically expanding the security and governance surface area.

Networking emerges as the primary enabler for agentic interactions, extending beyond connectivity into service-centric controls that govern how distributed services identify, communicate, and exchange data securely. The article argues for an infrastructure-level approach that weaves policy, observability, and governance into the network control plane, rather than relying solely on framework-level controls that break down across different runtimes and clouds. This vision balances the tension between platform and best-of-breed solutions: among respondents favoring platforms, the main reasons were stronger security (32.9%), reduced complexity (27.7%), and faster deployment (24.2%). The ideal platform must be modular, open, and extensible, allowing integration of third-party tools without architectural rework.

For builders, the takeaway is clear: agentic AI at scale demands a networking strategy that is foundational, not bolted on. The infrastructure must provide consistent policy enforcement and observability across fragmented, multi-cloud environments. Organizations should avoid the lure of pure best-of-breed point solutions that create governance gaps and operational complexity. Instead, they need an open, extensible infrastructure platform that can evolve with the technology, enabling end-to-end trust and control as agentic systems become more autonomous and distributed.