AI’s hidden storage bill: What inference leaves behind

This WD-sponsored article argues that AI infrastructure planning overlooks data storage costs, since inference runs continuously and leaves back-end data behind—citing an internal measurement where an 8-second 720p video clip returned as a 3.97MB file left more than 500MB of associated data. It cites McKinsey's projection that inference demand will grow at a 35% CAGR through 2030 and a WD-sponsored IDC survey of 763 IT and business decision makers in which nearly 95% reported data volume increases from generative AI over the past 12 months. It recommends planning storage around the full AI data life cycle, with HDDs as a cost-effective high-capacity foundation for retained data.