HomeU.S. Tech Giants Rethink AI as Token Costs Surpass Programmer Wages
The AI industry today presents a stark contrast, with extremes on both sides. Major AI companies have surpassed the trillion-dollar valuation mark, and large language models are now widely used in coding. Yet many businesses that hoped to cut labor costs through AI have been surprised to discover that it actually ends up being more expensive than hiring human programmers.
This unexpected turn has left numerous tech companies in an awkward position. AI coding tools, once expected to lower costs and boost efficiency, now generate enormous bills for finance departments due to their incredible consumption speed.
Even Major Companies Must Reckon with Skyrocketing Budgets
Uber's chief technology officer recently acknowledged that the company had already exhausted its entire 2026 Claude Code budget by April. To cover these excessive AI costs, Uber had to slow down its annual hiring plans—prompting management to deeply rethink the blind rush toward internal AI adoption.
Unsurprisingly, cash-rich Microsoft is also grappling with the same financial drain. CEO Satya Nadella recently ordered a switch from Claude Code to the company's own GitHub Copilot for internal development starting in June. The core intention: strictly control spending and prevent runaway costs from large models.
24/7 Operation Turns into a "Money-Guzzling Beast"
While AI programming tools write faster than humans, in practice human developers earning a few thousand dollars per month are often more cost-effective than token-based AI. Particularly when teams deploy AI agents to run around the clock, money drains away like water released from a dam.
Beyond the heavy financial burden, the quality of AI-generated code also faces industry criticism. Several experts note that AI often "mass-produces garbage," with many hidden defects in the output. Subsequent review, testing, and deployment still require human cleanup. Replacing human programmers in the near term remains an unfulfilled promise.
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The AI industry today presents a stark contrast, with extremes on both sides. Major AI companies have surpassed the trillion-dollar valuation mark, and large language models are now widely used in coding. Yet many businesses that hoped to cut labor costs through AI have been surprised to discover that it actually ends up being more expensive than hiring human programmers.
This unexpected turn has left numerous tech companies in an awkward position. AI coding tools, once expected to lower costs and boost efficiency, now generate enormous bills for finance departments due to their incredible consumption speed.
Even Major Companies Must Reckon with Skyrocketing Budgets
Uber's chief technology officer recently acknowledged that the company had already exhausted its entire 2026 Claude Code budget by April. To cover these excessive AI costs, Uber had to slow down its annual hiring plans—prompting management to deeply rethink the blind rush toward internal AI adoption.
Unsurprisingly, cash-rich Microsoft is also grappling with the same financial drain. CEO Satya Nadella recently ordered a switch from Claude Code to the company's own GitHub Copilot for internal development starting in June. The core intention: strictly control spending and prevent runaway costs from large models.
24/7 Operation Turns into a "Money-Guzzling Beast"
While AI programming tools write faster than humans, in practice human developers earning a few thousand dollars per month are often more cost-effective than token-based AI. Particularly when teams deploy AI agents to run around the clock, money drains away like water released from a dam.
Beyond the heavy financial burden, the quality of AI-generated code also faces industry criticism. Several experts note that AI often "mass-produces garbage," with many hidden defects in the output. Subsequent review, testing, and deployment still require human cleanup. Replacing human programmers in the near term remains an unfulfilled promise.
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