Enterprise·Europe

KPMG Survey Reveals Companies Lack AI Cost Transparency

Global AI Watch · Editorial Team··5 min read
KPMG Survey Reveals Companies Lack AI Cost Transparency
Editorial Insight

AI token billing today mirrors early cloud adoption stages, driving mid-term strategy shifts by end-2026.

Key Points

  • 150% report limited visibility; 26% have full control over AI costs.
  • 2Prediction models have become central to enterprise financial strategy post-2025.
  • 3AI cost transparency issues echo early cloud adoption challenges.

What Changed

KPMG's latest survey highlights a significant oversight in AI expenditure management among businesses. With only 26% of companies having a full understanding of their AI costs, the rest face various levels of ambiguity. This scenario recalls the early challenges of the cloud adoption wave during the COVID-19 pandemic when companies initially invested heavily but later cut back on spending, leading to market turbulence.

Strategic Implications

The lack of cost transparency gives rise to significant strategic challenges for CFOs, particularly as enterprises increasingly integrate AI into their operations. The shift towards token-based billing complicates financial management, altering how costs are predicted and controlled. These changes empower technology advisory firms like KPMG while posing obstacles for companies striving for financial stability amidst accelerating technological growth.

What Happens Next

Expect further scrutiny on AI budgeting practices, with more companies likely confronting budget overruns, similar to historical cloud cost issues. By Q3 2026, anticipate policy adjustments within organizations to enhance transparency and accountability. Both internal audits and external advisory services will play a pivotal role in navigating these fiscal challenges.

Second-Order Effects

The current situation may lead to reevaluations of vendor pricing models. This scrutiny could ripple into AI supply chains, driving more negotiations for cost predictability. Regulatory oversight might increase, prompting a closer look at how AI utility metrics are determined, mirroring past regulatory approaches to IT expenditure controls.

Free Daily Briefing

Top AI intelligence stories delivered each morning.

Subscribe Free →

Explore Trackers