• AI & Machine Learning IT Infrastructure Commentary Insight and analysis on the information technology space from industry thought leaders. • Agentic AI Starts with Infrastructure That Can Act Outdated network architectures are becoming the critical limitation that prevents AI from delivering on its promise. • September 2, 2025 By Darren Wolner, GTT Most enterprise conversations aroundagentic AIstill revolve around models and data - e.g., how to structure them, govern them, and get them into production. • And rightly so: Agentic AI depends on a strong foundation of real-time, trustworthy data and flexible model delivery. • But those layers don’t operate in isolation. • Behind every action an AI system takes, whether it’s rerouting a delivery, flagging a fraud attempt or scheduling maintenance, there’s infrastructure moving that data, executing the decision, and enforcing access policies in real time.
Article Summaries:
- Summary
Darren Wolner of GTT argues that agentic AI’s promise hinges on the underlying network, not just models or data. As AI systems push decisions to the edge-integrating cloud, on‑prem, and IoT resources-high‑performance, low‑latency connectivity becomes critical. GTT’s research shows private‑cloud spending outpaces public cloud, reflecting a need for tighter control over performance, cost, and security. Traditional network architectures, designed for batch workloads, struggle with the distributed, latency‑sensitive, and machine‑to‑machine traffic of agentic AI, leading to stalled inference and access gaps. The article calls for network upgrades that treat the network itself as the “computer” enabling true autonomy.
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