This ESG research paper analyzes how storage infrastructure directly affects AI success. Survey data shows organizations facing bottlenecks in data pipelines, GPU utilization, and scalability due to legacy storage. The report explains the need for unified high-bandwidth architectures, real-time data access, automated management, and hybrid-cloud flexibility. It highlights how modern storage can increase GPU efficiency, reduce data-processing delays, and simplify scaling for training and inference workloads. It concludes with strategic recommendations for choosing AI-ready storage that supports long-term innovation.

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