The AI industry has spent the last two years in a frenzy of hardware investment, but a new analysis from Epoch AI asks the uncomfortable question: is all that silicon actually enough? Researchers Luke Emberson and Jaime Sevilla built a bottom-up model of global inference capacity and stacked it against the best available proxies for token demand. The verdict is sobering , demand appears to be outrunning supply by a wide margin, and the gap is widening.

The trillion-dollar question

Hyperscalers have been racing to build massive data centers, spending hundreds of billions in the process. The St. Louis Fed estimates that AI-related investment contributed about 1 percentage point , nearly 40% of the total , to US real GDP growth in the first three quarters of 2025, exceeding the IT investment contribution at the height of the dot-com boom. Whether the current AI buildout constitutes a bubble depends largely on whether there will be sufficient demand for the computing infrastructure being built.

Epoch AI estimates supply is growing 3 to 4 times per year, while demand for tokens is growing roughly 10 times per year , suggesting a compute crunch is nearing, if not already here.