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Preparing Enterprise Data Centers for AI Adoption

A 2025 McKinsey forecast puts AI‑related IT infrastructure spending at nearly $7 trillion through 2030, with $3 trillion earmarked for data‑center capacity. Enterprises must juggle this surge with traditional workloads, requiring distinct strategies for power‑intensive AI training and latency‑critical AI inference. Training favors massive, liquid‑cooled cabinets often placed in remote mega‑campuses, while inference pushes compute closer to corporate data, sometimes at the edge. Most large firms remain unprepared—only about a third consider their facilities AI‑ready—prompting a shift toward hybrid cloud and colocation models that blend flexibility, security, and cost control.