Jensen Huang has a test for whether an engineer is worth keeping, and it comes with a token budget attached. On the All-In Podcast at the close of GTC 2026, the Nvidia chief executive said that if a US$500,000 engineer’s annual AI token consumption came in under US$250,000, half their salary, “I am going to be deeply alarmed.” Nvidia, he confirmed, is working toward a US$2 billion yearly token bill for its engineering force.
It’s a memorable provocation from the man who sells the compute. It’s also a tidy description of the trade-off now being made in corporate budgets everywhere, usually with less candour: money that once paid people is increasingly being paid for tokens. The question the industry has been slower to ask is whether that trade is actually working, and the honest answers arriving from the companies that moved first suggest it often isn’t.
Where the money went
The reallocation itself is not in dispute. The four largest hyperscalers have guided roughly US$700 billion in combined 2026 capital expenditure, nearly double last year, while Gartner projects AI agent software spending will reach US$207 billion, up 139%. On the other side of the ledger, Challenger, Gray & Christmas data shows AI as the most-cited reason for US job cuts for a record fourth straight month, with tech accounting for 31% of first-half layoffs.
An internal Meta memo obtained by Reuters described May’s cuts of 8,000 roles as offsetting the company’s substantial investments, even as revenue grew 33% that quarter. Oracle’s filings show headcount down 21,000 as savings feed its data centre buildout. These are highly profitable companies. The layoffs aren’t survival measures. They’re financing.
Andy Challenger’s summary of his firm’s data is the plainest available: “Companies are shifting budgets toward AI investments at the expense of jobs.” The task a worker performed may not have been automated at all. The budget that paid for it has simply moved.
What the money bought
Here, the record turns awkward. Gartner surveyed 350 executives at companies with over US$1 billion in revenue, all deploying AI agents or automation, and found roughly 80% had cut headcount, with no correlation between the cuts and improved returns. Analyst Helen Poitevin’s verdict: “Workforce reductions may create budget room, but they do not create return.”
Her research found the organisations that did improve ROI were those using AI to amplify their people rather than remove them. The token side of the ledger has its own reckoning underway.
Uber gave 5,000 engineers AI coding tools in December and exhausted its entire 2026 AI budget by April. Chief operating officer Andrew Macdonald conceded that despite 70 per cent of committed code being AI-generated, the connection to anything customers experience is missing: “That link is not there yet.” Uber’s engineers are now capped at US$1,500 a month in AI spend.
Walmart…
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