Several companies had been going all in on artificial intelligence use, striking deals with top AI companies in order to use their tools. However, their costs seem to have caught up with them.
Microsoft, which recently expanded access to Claude Code from Anthropic, encouraged thousands of developers, project managers, designers, and other employees to experiment with coding using the tool. However, as the use of the tool grew rapidly, the company decided to scale back, canceling most of its direct Claude Code licenses, according to The Verge. Microsoft directed employees towards using GitHub Copilot CLI as an alternative.
Canceling Claude Code licenses won’t affect Microsoft’s Foundry deal, which includes investing up to $5 billion in Anthropic and giving Foundry customers access to Claude models, as well as Anthropic’s $30 billion commitment to purchase Azure compute capacity, according to the report.
READ: Big tech and government joins forces to police AI risks (May 6, 2026)
Microsoft is not the only company facing issues with AI costs. Bryan Catanzaro, vice president of Applied Deep Learning at Nvidia, recently suggested that AI use isn’t saving companies from labor costs, instead it is costing them more than the humans they employ.
“For my team, the cost of compute is far beyond the costs of the employees,” Cantazaro said.
Uber’s CTO Praveen Neppalli Naga told The Information in April that the firm had already burnt through its entire 2026 AI coding tools budget in just four months. That comes after the company had actively incentivized adoption through internal leaderboards ranking teams by AI tool usage.
According to reports, the main reason for these high costs is the way large language models are priced. Providers charge per token, the small text units models read or generate. With this structure, higher productivity and heavier experimentation both produce more tokens. Efficient work and wasteful queries can look almost identical from a billing standpoint, since each token still adds to the invoice.
READ: Big Tech partners with kids’ brands on digital moderation campaign amid controversy (May 14, 2026)
Many tech companies have actually pushed employees to use more tokens, not less. At Amazon, internal guidance has reportedly advised employees to use as many AI tokens as possible. Within Meta, one employee created a dashboard called “Claudeonomics” so teams could see who generated the greatest AI usage, turning consumption into a competitive metric.
As consumption increases, the cost of individual AI tokens is expected to fall sharply. A recent report from research firm Gartner found that by 2030, inference on a one-trillion-parameter LLM — in simple terms, a highly sophisticated AI model — will cost AI firms nearly 90% less than it did in 2025. However, this does not guarantee less expensive enterprise AI costs. This is because agentic models require far more tokens per task than standard models, increased consumption can outpace falling unit costs, and AI providers won’t fully pass through lower costs to consumers. In turn, inference costs are likely to push higher.