When one datacenter is no longer enough

As AI training scales beyond the power and capacity of a single site, organizations are being pushed toward multi-datacenter GPU clusters, turning networking into a core constraint rather than a back-end utility. For CIOs and IT leaders, the strategic implication is that AI infrastructure planning now has to account for deterministic low-latency traffic, tighter synchronization, power efficiency, and security across geographically distributed environments to keep large model training jobs efficient and reliable.