Enterprise AI Users Decry Spiraling Costs of Coding Tools

Microsoft and Uber have put a face on a problem spreading through corporate America: AI tools that work but cost much more than anyone planned. The former began phasing out its Claude Code subscriptions in mid-May, with the bulk expiring at the end of June. Uber CTO Praveen Neppalli Naga confirmed the ride-share company had burned through its entire 2026 AI budget by April, just months after Uber rolled out Claude Code to approximately 5,000 engineers.

Claude Code and similar tools charge per token used, rather than a flat monthly rate, so bills scale with every task. Costs per engineer at Uber reached anywhere from $500 to $2,000 a month, according to Forbes, and AI tools now account for close to 70% of code committed at Uber. Both firms have also reported significant productivity gains, which is part of why neither company has made a clean break.

Mavvrik’s 2025 survey noted that 85% of firms ran over their AI budgets, most by over 10%. A further 84% said AI spending had shrunk their gross margins by more than six points. Across the industry, AI capital expenditure hit $650 billion in the first quarter of 2026 alone. Over the same stretch, the share of companies with dedicated AI cost teams doubled to 63%.

Behind all this is a fact that rarely gets aired plainly: the AI companies themselves are not profitable despite investing hundreds of billions in the technology.

Anthropic closed 2024 with losses of $5.3 billion, while OpenAI posted a loss of $5 billion over the same year. Both remained loss-making heading into 2025, with OpenAI projected to lose upward of $8 billion and Anthropic around $3 billion. Running these models costs more than the industry expected, and those costs are rising rather than falling. The latest models need substantially more computing power per response, and that overhead gets passed down the chain.

AI search company Perplexity burned through 164% of its 2024 revenue on compute bills across AWS, Anthropic, and OpenAI. Cursor, reportedly Anthropic’s largest customer, sends essentially all its revenue back in compute fees. Additionally, most AI users use the free tiers, pushing the entire cost burden onto a relatively small base of paying customers. Heavy enterprise usage also costs AI providers more to serve, creating pressure to raise prices on the relatively small pool of AI customers on the enterprise tiers.

Both OpenAI and Anthropic have raised enterprise prices in response, further squeezing the margins of companies building on their models. Companies are now scrambling to add the controls that were absent when deployments accelerated through late 2025.

Usage limits, role-based access tiers, and redirecting routine queries to lower-cost models are among the guardrails now being applied to rollouts that previously had none. Anthropic’s $10.9 billion Q2 revenue forecast would mark its first profitable quarter, a sign that what hurts its customers is, for now, helping its bottom line.

As entities like D-Wave Quantum Inc. (NYSE: QBTS) work to develop the next tech frontier, quantum computing, they could be watching AI firms and taking notes on how best to ensure they remain profitable while keeping their solutions within reach of the vast majority of their target clientele.

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