For much of 2025 and into 2026, some engineering teams measured AI success by tokens burned rather than value created, and a handful of companies even built internal leaderboards to track who used AI the most. According to a Washington Post Intelligence report by columnists Dan Gallagher and Kendrick Frankel, that era, nicknamed “tokenmaxxing,” is fading. Airbnb Chief Technology Officer Ahmad Al-Dahle described the shift on LinkedIn, as the Post’s coverage noted: his team tracked throughput and quality instead of token counts, and “usage took care of itself.”
That correction is good news for finance teams tired of chasing a moving number. It does not solve the harder problem underneath it. Most enterprises still cannot say, with confidence, who owns the AI bill, or what it will cost three months from now, a year from now, or three years from now. Token economics, or tokenomics for short, is the discipline meant to answer those questions: managing what AI, and especially agentic AI, actually costs to run, priced per million tokens processed rather than per software seat.
The Bill Nobody Planned For
The Post’s reporting makes the governance gap concrete. It reports that Uber’s chief technology officer told The Information the ride-share company had already exhausted its full-year AI budget by mid-April. It also cites data from a fintech firm showing blended token prices down roughly 50 percent year-over-year, a decline that hasn’t lowered bills so much as fed continuous reasoning loops behind the scenes, so cheaper tokens simply invite more of them.
What IDC’s Own Research Shows
IDC’s research shows the same pattern from the inside, not only from press coverage. In Effective Agent Cost Management: A Practitioner’s Framework for Planning, Sourcing, Implementation, and Operations (IDC #US54644126, June 2026), IDC found that engineering teams typically spot cost anomalies in real time but lack the budget authority to act on them, while finance holds that authority but often can’t detect a problem until a vendor invoice arrives weeks later. “Every dollar of wasted AI agent spend is a governance failure,” says Shari Lava, group vice president, AI, at IDC.
That gap is real, but governance can contain it. IDC’s most recent global cloud AI spending survey, fielded in April 2026 across the Middle East, Türkiye, and Africa, found that 61 percent of organizations exceeded their 2025 cloud AI budget, yet 83 percent of those overruns landed under 15 percent, evidence that early governance narrows overspend even when it can’t prevent it entirely (IDC #META54767326, August 2026). Visibility remains the harder half of the problem. IDC’s Worldwide Technology Buyer and Spending Outlook, based on a May 2026 survey of more than 1,400 IT leaders, found that difficulty budgeting for token- and inference-based pricing is now the single largest barrier organizations report when evaluating AI vendor pricing, ranking above even the unpredictability of usage costs itself (IDC #US54051126, July 2026). The problem is getting worse, not better.
Closing the Ownership Gap
Closing that gap is a shared job. IDC research on CFO-CIO dynamics finds the two roles hold converging influence over technology decisions but distinct, still-unreconciled mandates, and only one in five CEOs have created a separate AI budget line in the first place (IDC #US53393425, July 2025). Most AI spend is still sitting inside a budget category that was never built to isolate it, in the seam between whoever built the model and whoever has to answer for the invoice.
IDC’s governance framework treats that seam as fixable. It calls for naming a single accountable owner per AI workload before the first dollar is spent, building an ownership structure with real authority attached rather than a chart for the board deck, and reviewing token-volume variance as a standing agenda item in the quarterly FP&A cycle instead of waiting for a surprise. The Post’s own recommendations land in a similar place: treat AI spend like any other major budget category, actively monitored, with accountability clearly assigned.
CFOs who want the full framework, including the RACI model and budget governance checklist IDC built for practitioners, can find it in IDC’s ongoing AI Economics and Token Control research, available to IDC Quanta subscribers.
This piece references reporting from “AI tokenomics: Using the technology without busting the budget,” Washington Post/WP Intelligence, August 21, 2026.
