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[ARTICLE · art-121037] src=koreatimes.co.kr ↗ pub= topic=ai-infrastructure verified=true sentiment=· neutral

[CONTRIBUTION] Why AI infrastructure planning must happen now

A contributed article argues that AI infrastructure planning must begin earlier as AI workloads become more distributed across cloud, data center, and edge environments, warning that delays can slow deployment and postpone productivity gains. The piece emphasizes the need for balanced infrastructure—compute, networking, software, memory, and operations—and notes that organizations are prioritizing early planning to secure compute capacity for long-term AI growth.

read1 min views1 publishedSep 4, 2026

As adoption of artificiall intelligence (AI) accelerates across industries, one thing is becoming clear: infrastructure planning cannot wait. AI workloads are becoming more interconnected, distributed and operationally integrated across cloud, data center and edge environments. Infrastructure planning now requires organizations to align compute, networking, software, memory and operational requirements across increasingly complex environments. The cost of delaying AI infrastructure planning is becoming more apparent. Modern AI workloads require more than raw compute performance. They require balanced infrastructure where compute, networking, software, memory and operational workflows work cohesively at scale. Delays can slow deployment readiness and postpone AI-driven benefits such as productivity gains and operational automation. As AI demand continues to rise, organizations are prioritizing earlier planning to secure the compute capacity needed to support long-term AI growth. As AI infrastructure becomes more complex, infrastructure planning needs to begin earlier than traditional IT up

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