Odaily Planet Daily reports: Ahmed Shihab, Chief Product Officer at Western Digital (WD), stated that as AI infrastructure expands rapidly, the core competition in storage should not be simplistically framed as a battle between flash and hard disk drives (HDDs), but rather on the ability to build AI storage architectures with long-term economic scalability. The AI industry currently faces a critical question: Will the storage architecture chosen this year be able to support future data growth reaching petabyte or even exabyte scales? He believes that many AI infrastructure designs fail not due to insufficient performance, but because they encounter cost challenges as data volumes expand.
Ahmed Shihab believes that AI data continues to grow, including model training data, inference data, user interaction logs, compliance data, and synthetic data. While adopting an all-flash architecture in the early stages may be appealing for small-scale deployments, storage costs will become a significant burden as data volumes increase. Flash and HDD are not competing technologies but complementary solutions tailored to different workloads. High-performance scenarios—such as model weights, GPU overflow, and KV caching—require low-latency flash storage; whereas long-term storage needs like training datasets, logs, checkpoints, compliance records, and large-scale historical data are better suited to HDDs, which offer superior cost efficiency.
“The winner in AI storage will be whoever can provide economically scalable capacity,” said Shihab, noting that customers choosing storage solutions care not just about speed, but about being able to scale their AI businesses reliably and sustainably.
Shihab noted that storage architectures in the AI era will become more layered, rather than relying on a single storage medium. “Flash handles performance at critical moments, while HDDs manage the data lifecycle.” During the scaling phase of AI infrastructure, storage costs are no longer merely an operational expense—they have become part of the architectural design. Every dollar spent on high-cost, high-performance storage means fewer resources available for compute, networking, power, and other infrastructure.
Additionally, reliability must be considered from the earliest stages of architectural design. For large-scale AI systems, hardware, software, network, and power failures are the norm; an excellent storage system must be capable of continuous operation, fault isolation, and rapid recovery. He concluded that the future direction of AI storage is not “flash replacing HDD,” but rather precise tiering based on different data lifecycles and business requirements. “True infrastructure is not about chasing flashy performance, but about building a reliable foundation that can support long-term AI growth.”