The next wave of AI governance is economic: leaders need to know which workflows consume resources and what business result they produce. This matters now because agent loops can hide repeated inference and tool work behind one user-visible result.
BCG describes token consumption as a material new cost that CFOs, CIOs, and CTOs must measure as AI enters production. The article argues that token price alone misses orchestration, tools, retrieval, storage, evaluation, observability, and human oversight. The mechanism is workload attribution that records every resource and exception required to reach an accepted outcome, then routes models and controls according to value and risk.
Teams should optimize cost per resolved outcome under quality and risk thresholds rather than reward the lowest nominal token rate. The evidence is BCG's management framework and examples; independent comparisons still require consistent workload and accounting boundaries. Watch whether organizations publish stable fully loaded unit costs and use them to stop, redesign, or scale agent workflows.