KPMG's research shows that nearly 30% of corporate executives find it difficult to understand the cost of AI on a pay-per-use basis, and nearly half have delayed deployment

According to KPMG's latest survey report involving 2,145 executives from 20 countries, as technology companies like Anthropic, OpenAI, and GitHub recently shifted some of their AI services from fixed subscription models to usage-based billing, businesses are facing challenges in cost forecasting and management during the scaling of AI deployment.

The report indicates that 29% of corporate executives find it difficult to understand and control operational costs when scaling AI deployment, and one-third of executives believe that insufficient understanding of AI economics hinders the deployment of AI entities. Due to costs exceeding expected value, nearly half (about 49%) of corporate organizations have chosen to delay or readjust their AI deployment plans; meanwhile, low-cost, high-fidelity large models are accelerating their impact on corporate AI strategies.

In addition, tech giants are increasing capital expenditures to build AI capacity. Amazon plans to spend about $200 billion on capital expenditures this year and is investing $1 billion in its AWS frontline engineering organization to assist customers in adopting AI entities; Microsoft's total capital expenditure is expected to reach $190 billion this year, with $2.5 billion allocated to the new entity Microsoft Frontier Company. KPMG emphasizes that, in addition to cost pressures, accountability in AI governance, employee engagement rules, and the prevention of system "hallucinations" remain core challenges faced by businesses today.