For the past several years, enterprises have spent heavily on AI. Facing pressure to keep pace, IT leaders acquired hardware components quickly. In many cases, they did so before working out how all the pieces would fit together. It’s now clear that this kind of ad hoc AI procurement isn’t good enough. Organizations that keep buying GPUs without a plan for how to integrate them often end up with expensive hardware that sits underutilized. This challenge is growing as AI infrastructure becomes increasingly distributed. Enterprises now routinely combine hyperscale clouds, private infrastructure, specialized GPU providers, AI model platforms and edge environments…

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