OpenAI and Anthropic Feel the Pinch as AI Budgets Get Leaner
Businesses are cutting AI spending and demanding real ROI, which could slow growth for top AI labs like OpenAI and Anthropic.
If you've ever left an AI chatbot running on a task way longer than necessary, you're not alone — but companies are now doing the math and realizing that approach is expensive. The trend, sometimes called 'tokenmaxxing,' basically means throwing as many AI tokens (the units AI models process) at a problem as possible without worrying about cost. That era appears to be winding down fast.
Businesses are increasingly focused on squeezing actual returns out of their AI investments rather than just experimenting freely. That shift in mindset — from 'let's try everything' to 'show me the ROI' — puts pressure on AI heavyweights like OpenAI and Anthropic, whose growth has been fueled in large part by companies spending generously to explore what AI can do for them.
Read more China's Zhipu AI Closes Gap With OpenAI and Anthropic on Cost →
When corporate budgets tighten around any technology, the companies selling that technology feel it pretty quickly. For AI labs, fewer tokens processed means less revenue, and slower revenue growth can complicate everything from product development to the eye-watering infrastructure investments these companies need to stay competitive. Both OpenAI and Anthropic have been burning significant cash to build and maintain the computing power behind their models.
The bigger question here is whether this efficiency push is a temporary belt-tightening or a more permanent recalibration of how businesses value AI tools. If companies get better at using AI more precisely — doing more with fewer tokens — that could actually reshape pricing models and competitive dynamics across the entire industry. Efficiency, it turns out, isn't always a friend to top-line growth.
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