Over the past years, the price per token – the unit in which AI providers meter and bill every request and every response – has declined significantly as models, hardware, and inference infrastructure have improved. At first glance, this suggests that AI should become an increasingly inexpensive resource for organizations.
However, focusing on unit economics alone misses the bigger picture – token consumption is growing much faster than token prices are falling. Whichever industry and AI maturity level, the direction is the same: token cost becomes a major line item that every organization will need to start actively managing.
The time to start is now, before the growth ahead outpaces the ability to control it.
There is no single fix for rising token costs. Instead, companies need to address three complementary pillars: how individual behavior shapes AI usage, how the underlying infrastructure governs that usage, and how AI capacity is sourced and contracted.
In this report, we take a closer look at how to properly address these.
