The AI industry is about to hit an inflection point. According to Epoch AI, a nonprofit that tracks artificial intelligence trends, the compute power dedicated to running AI models will grow faster than the compute power used to build them by 2030.
The numbers behind the shift
Epoch AI’s projections paint a picture of an industry where the economics of deployment will increasingly dominate the economics of development. The organization estimates that nearly half of all inference compute will migrate to ASICs, or Application-Specific Integrated Circuits, by the end of the decade. These are chips designed to do one thing extremely well, as opposed to the general-purpose GPUs that currently power most AI workloads.
Meanwhile, the share of training compute in total AI operations is projected to hold steady at roughly 5%. Training compute for frontier AI models is currently growing at an annual rate of 4 to 5 times. The total installed AI compute base is expanding at a similar pace.
Historically, inference has already represented 60% to 80% of compute in actual deployments.
