AI is a Compensation Scale Expense
About this episode
Ray Rike and Peter Buchanan discuss the rising costs of enterprise AI and the shift in funding sources from IT budgets to labor.
Token prices have fallen 98 percent since GPT-4, but enterprise AI bills are up 320 percent. In this week's Big Story episode, Ray Rike and Peter Buchanan trace where that money is actually coming from, and the answer is not the software budget. Drawing on Gartner, Oxford Economics, Zylo, Challenger Gray and Christmas, and Goldman Sachs data, the two lay out why labor, not IT, is becoming the primary funding source for AI at scale, and why almost no company has the measurement infrastructure to manage it. The price paradox. Per token costs have collapsed, but usage has grown faster than costs have fallen. Ray walks through the math behind average enterprise AI budgets rising from $1.2 million to $7 million in two years. Three cautionary tales. Uber consumed its entire annual Claude Code budget in under four months, Microsoft revoked thousands of Claude Code licenses over cost, and one unnamed enterprise ran up a $500 million bill in a single month. Ray and Peter break down why each was a governance failure rather than a technology failure. Only two budget pools are big enough. The IT and software budget represents just 3 to 4 percent of revenue, while labor represents 25 to 40…
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