Ninety-three percent of enterprises surveyed by McKinsey reported exceeding their artificial intelligence budgets, a finding published in the firm's July 2026 analysis of enterprise AI cost management from its QuantumBlack practice.

The survey covered 120 enterprise participants with 75 qualified respondents across five major industries. It found that 62% of organizations have moved past experimentation into active AI deployment, and that spend climbs nearly fourfold as companies shift from isolated use cases to enterprise-wide rollout.

Pressure on those budgets is set to increase. A majority of firms in the survey expect AI spend to rise by at least 25% over the next twelve months. McKinsey reports that some companies have exhausted annual AI budgets within a few months, which forced contract renegotiations and unplanned funding requests.

Cost visibility remains thin. Only 20% to 25% of companies have mature AI financial operations practices in place, and McKinsey estimates that 20% to 30% of AI spend often goes unaccounted for because purchases scatter across cloud providers, model vendors, software features, experimentation environments, and individual business units.

Savings are available to firms that measure consumption. About one-third of organizations surveyed have already captured savings of 20% to 30% through active optimization, and organizations with high forecasting maturity save 10% more on AI spend than peers on average. Prompt caching alone can cut repeated input-token costs by as much as 90% for retrieval-augmented generation and for agents that reuse large stable prefixes.

Source: McKinsey and Company - https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-cost-of-intelligence-how-cios-can-manage-ai-demand-at-scale