Every enterprise AI strategy eventually runs into the same question: not just which models to use, but where to run them. That question is getting harder to answer as inference scales across more models, more providers and more geographies. According to Gartner®: “In 2026, global spending on inference ($23.3 billion) will surpass that of training ($19 billion).” Yet total AI costs keep climbing even as the models themselves grow cheaper, because the model invoice is only one part of the bill. Token consumption is rising fast, and that’s driving up overhead costs. Gartner predicts that “AI inference costs per agentic workflow…

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