# AI’s hidden storage bill: What inference leaves behind

Digest AI · Enterprise & Industry · published 2026-10-22T08:41:18Z

Canonical: https://digestai.news/story/ais-hidden-storage-bill-what-inference-leaves-behind

## Summary

The article notes that as inference scales, this hidden storage footprint can grow into hundreds of gigabytes per clip for higher‑resolution content.

McKinsey projects AI inference demand to grow at a 35% compound annual growth rate through 2030, compared with 22% for training, and to account for more than 40% of total data‑center demand by the decade’s end. A WD‑sponsored IDC white paper surveying 763 IT and business decision makers found nearly 95% reporting an increase in data volume due to generative AI in the past year, about 61% seeing growth of 25% or more, and 96% anticipating a need for faster archive retrieval. A senior product manager of a hyperscale cloud service provider warned that storage bottlenecks can cause GPU idle time, inflating costs.

## Key points

- McKinsey forecasts AI inference demand to grow 35% CAGR through 2030, outpacing training and reaching >40% of data‑center demand.
- IDC survey of 763 IT and business leaders found 95% see AI data volume rise, 61% report ≥25% growth, and 96% need faster archive retrieval.

## Why it matters

Hidden storage costs can outpace compute budgets as inference scales, forcing enterprises to allocate spend to scalable, tiered storage solutions.

## Sources

1. [AI’s hidden storage bill: What inference leaves behind](https://technologyreview.com/2026/10/22/1146948/ais-hidden-storage-bill-what-inference-leaves-behind) (MIT Technology Review AI, 2026-10-22)

## Cite

Digest AI, "AI’s hidden storage bill: What inference leaves behind", 22 October 2026, https://digestai.news/story/ais-hidden-storage-bill-what-inference-leaves-behind

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