News
AI Costs · CFO Challenges · Enterprise AI · Usage-Based Pricing
Finance chiefs face significant challenges in accurately tracking artificial intelligence usage and associated costs, as an unreleased KPMG survey reveals only 26% of companies possess a comprehensive view, with 50% having some visibility and 22% reporting no visibility until after billing.
This struggle stems from a fundamental shift in vendor pricing models, moving from traditional flat fees to usage-based charges measured by "tokens," the basic unit of AI computing. This new token-based system introduces significant unpredictability, making it exceedingly difficult for even experienced finance teams to model costs for ambitious AI investments and agent development.
Companies risk experiencing substantial "sticker shock" as they scale their AI adoption without clear cost oversight, potentially leading to budget overruns and misallocated resources. The lack of transparent, real-time cost metrics impedes strategic planning, accurate budgeting, and effective resource allocation for enterprise AI initiatives, thereby hindering the full economic benefits of AI integration and potentially slowing broader AI adoption across industries.
