Business · Tom's Hardware
Talent over tokens: AI models are becoming more expensive to run, and productivity gains are limited — efficient workers might be the solution to strained budgets
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Earlier this month, it was reported that almost 80,000 workers were laid off in the first quarter of 2026, with companies pinning the blame on the rise of artificial intelligence.
Key facts
- Recently, Anthropic doubled the expected price tag for individual developers to spend on tokens, from $6 per active day to $13
- Uber's CTO said that the company used its annual AI budget in a few weeks, and the CEO of GetSwan shared that the company spent over $113,000 on AI with a four-person team in one month
- Anthropic's much-hyped and still-internal Mythos model is reportedly several times more costly per million tokens than Claude Opus 4.7, or even the newer Claude Capybara
- While Catanzaro's team is involved in making foundation models for Nvidia, AI usage is increasing among workers, with a reported 50% of U.S. employees using AI in some form, according to data
Summary
Whether through improved task efficiency or cost savings through automation, deployment of AI within the workforce is supposed to be the economically smart decision — even if it didn't necessarily turn out to be true. While Catanzaro's team is involved in making foundation models for Nvidia, AI usage is increasing among workers, with a reported 50% of U.S. employees using AI in some form, according to data released in mid-April. If the most useful AI models become too expensive without generating a return in productivity, their use in workplaces could fall dramatically, as token costs begin to pile up. If you asked Nvidia CEO Jensen Huang how much companies should spend on AI, his answer would probably be at least 50% of what you're paying your workers.