AI has rewritten the enterprise data playbook. Workflows no longer just create temporary operational data, but vast amounts of high-value assets, from LLM training datasets and model outputs to logs, metadata and archived knowledge that may need to be preserved for years.
Storage infrastructure will underpin post-quantum security
AI has rewritten the enterprise data playbook. Workflows no longer just create temporary operational data, but vast amounts of high-value assets, from LLM training datasets and model outputs to logs, metadata and archived knowledge that…
TechRadar
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Sep 11, 2026 at 9:54 AM UTC · 4 Min. Lesezeit

Director of EMEAI Field Engineering at WD (Western Digital).
As enterprise tech leaders seek to scale infrastructure to meet these demands, storage requirements are undergoing a fundamental shift. Capacity and performance remain critical, but data security has become equally important. Today, long-term data integrity and absolute cyber resilience carry equal weight.
Protecting this data, however, is no longer just about defeating today’s threat vectors. It requires preparing storage infrastructure for a significant shift: the arrival of quantum computing.
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AI is accelerating data growth, but it can also extend the useful life of information. Data recorded today will be harvested for compliance, advanced analytics and model retraining for years to come.
To manage this economically, enterprise architectures rely heavily on high-capacity HDDs. While flash technologies dominate performance-critical hot tiers, HDDs remain the undisputed backbone of large-scale storage, providing the capacity, economics and longevity needed to archive data at scale.
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