AI inference capacity to 2030 (~35% CAGR) vs training 23.1 → 62.2 GW (~22%)
20.9 → 93.3 GWforecast
| Value kind | forecast — Forecasts are time-bound outlooks, not specifications; test decisions across plausible scenarios. |
|---|---|
| Scope | McKinsey base-case scenario for AI workload capacity growth to 2030, not observed capacity. Compare it only against other capacity forecasts on the same denominator. |
| As of | 2026 |
| Source | McKinsey, 'The next big shifts in AI workloads' · Workload-capacity chart: inference grows from 20.9 GW to 93.3 GW at 35% CAGR; training grows from 23.1 GW to 62.2 GW at 22% CAGR |
| Review | checking…review by 2026-11-07 · standard cadence |
| Recorded changes | last 2026-06-29 |
| Claim id | ai-inference-capacity-to-2030-35-cagr-vs |
Where the guide uses it
← Full numbers register — every date-stamped figure in the guide, with revision history.