Corporate Executives Blindsided by Metered AI Pricing Models

A significant portion of corporate leadership is struggling to understand and manage AI costs as technology providers abandon subsidized flat-rate pricing in favor of usage-based billing models, according to new research from KPMG.

The accounting firm surveyed 2,145 senior executives across 20 countries and found that 29 percent had no clear understanding of where their AI expenses were coming from. An additional third identified their own lack of AI economics knowledge as a barrier to successful workplace deployment, as first reported by The Register.

The shift to metered billing

The findings reflect a broader industry transition. Where enterprises once relied on AI companies to subsidize large language model costs through predictable flat-rate contracts, rising computational expenses are forcing technology vendors into defensive pricing strategies. Usage-based models—where organizations pay based on actual consumption rather than fixed fees—are becoming the new standard.

"As usage-based pricing models become more common, many organizations are still building the capabilities required to forecast, monitor, and manage AI spending effectively," the KPMG report authors wrote. The data suggests that roughly one-third of executives had no concrete plan for productive AI deployment before costs became transparent through metered billing.

Planning gaps exposed

The survey results indicate that many corporate leaders approached AI as a straightforward solution for reducing overhead without fully understanding implementation mechanics. This pattern aligns with observations from workers required to use AI tools, who have noted that leadership often treats the technology as plug-and-play rather than as systems requiring strategic integration.

The disconnect between AI adoption mandates and cost management capabilities raises questions about the business case calculations that drove initial deployment decisions. Organizations now face the challenge of building forecasting and monitoring infrastructure while simultaneously managing unexpected expense growth.

Why it matters

The shift from subsidized to metered AI pricing is forcing a reckoning with actual deployment costs that many enterprises were unprepared to manage. This transparency gap has significant implications for AI ROI calculations and may slow adoption rates as organizations develop the financial controls needed to justify continued investment. For technology vendors, the transition tests whether enterprise demand can sustain profitability without subsidies—a critical question for the sector's long-term viability.

The KPMG findings were initially reported by The Register and highlight the gap between AI adoption enthusiasm and operational readiness across global enterprises.