AI costs exceed expectations, forcing CFOs to choose between tokens and headcount
As token costs for AI use rise more than expected, finance chiefs are adjusting priorities between tokens (model usage costs) and headcount. The increase is weighing on corporate profits and budgets, and the market appears not to have fully priced in this risk.
The cost of “tokens,” which measure AI model usage, has exceeded the levels companies anticipated. Rising token costs are leading to higher charges for cloud services and model API use. Finance teams are including these costs as quarterly budget items.
Here, “tokens” means the units of input and output sent to an AI model. The more tokens are used, the more API call costs and cloud computing costs rise. These costs are variable, so a surge in usage translates directly into higher spending.
Corporate finance chiefs are considering where to allocate more of their budgets: token costs or labor costs. Some companies are considering reducing model calls or changing usage patterns. Others are reviewing changes to their workforce structure resulting from automation.
The report points out that the market has not adequately factored in these increased AI costs when assessing risk. The impact of changes in cost structure on profit margins can become apparent quickly in quarterly results. The possibility has been raised that investors may need to pay attention to cost items in upcoming earnings announcements.
Companies are considering reallocating budgets, renegotiating cloud contracts, and introducing cost-efficiency tools. Some are strengthening their cost-tracking systems and setting usage-based alerts. Quarterly cost volatility could increase in this process.
The article is dated 2026-05-29. The report addresses this issue based on remarks from finance executives at several companies and trends in corporate costs. The relevant cost items need to be examined in detail in quarterly results.
Sources: CNBC,CNBC Top News
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