Use of artificial intelligence by big companies is exploding—and the soaring cost has some of them pumping the brakes in a way that could complicate AI’s triumphal march across the economy.
Executives across industries this year have urged employees to integrate AI tools into their work, spending freely to encourage experimentation and seeking to send a message to Wall Street that their companies won’t be left behind in a coming wave of disruption.
All that enthusiasm has resulted in skyrocketing costs for so-called tokens, the basic unit of measurement for AI computing, as AI model providers seek to balance supply and demand and manage their own costs. Some enterprises have hit their annual budget in just three months or reported seeing their AI spending bills double or triple.
Higher costs may eventually steer users toward cheaper models that cost a fraction of the price, but many companies remain wary of such AI systems because several of the cheapest options were developed in China, according to executives. Anthropic, OpenAI, Google and others also offer cheaper versions of their flagship models, and Factory and others have developed systems to help companies triage queries and steer some tasks to cheaper options.
Token use continues to grow immensely. Google said at a recent event that it now processes over 3.2 quadrillion tokens a month, seven times as much as a year ago. The company and others are seeking to reduce the cost of AI use in a variety of ways, including increasing computing efficiency.
That shift to usage-based pricing has forced enterprise customers to reckon with their consumption. An Uber executive said by March, the company had blown through its annual budget for “agentic,” or autonomous, AI use. Microsoft limited access to an Anthropic program for some employees who can use an internal coding assistant instead. Salesforce introduced a new system for tracking how token use ultimately contributes to positive business outcomes.
“It has been great to let people experiment but now we have too many overlapping tools,” Meta Chief Technology Officer Andrew Bosworth said in an April memo to employees. “Nobody should be using AI tools just for the sake of using them. All motion is not progress and token usage alone is not a measure of impact of any kind.”
A Microsoft spokesman said the company’s decision to reduce access to Anthropic’s Claude Code program wasn’t rooted in cost but stemmed from a desire to standardize what employees use across its organization.
An Anthropic spokeswoman said the company’s models help customers achieve greater productivity, such as completing complex tasks in less than two weeks that would have taken more than seven months in the past.
“As with any new technology and way of working, teams are still discovering where the biggest gains are and how best to measure them,” she said. “We’re working with customers to give them the tools to make sure the return is something they can see, not just feel.”
Software engineers and startup executives warn that even though it’s possible to complete tasks far more quickly, spending on debugging, reviewing and rewriting AI-generated code remains high, indicating that the models still need to be improved.
For companies using advanced AI coding tools, only 18% of spending on tokens is translating into shipped coding products that reach real users, according to EntelligenceAI, a startup that aggregated data on more than 2,000 companies using advanced AI tools for coding.
Write to Bradley Olson at bradley.olson@wsj.com