As artificial intelligence transitions from experimentation to core business operations, enterprise storage is no longer just a supporting infrastructure. It is becoming a strategic enabler of agility, innovation, and business outcomes. In an exclusive conversation with Digital Terminal, Ajeya Motaganahalli, VP of Engineering and MD – India R&D at Pure Storage, explains how enterprise storage strategies are evolving in 2026 to meet the demands of AI-driven organizations.
Data Management Takes Center Stage
Highlighting the shifting priorities for storage in AI-driven environments, Motaganahalli said, “As AI moves from experimentation into core business operations, enterprise storage strategies will shift in several fundamental ways. First, data management will matter more than raw capacity. AI success will increasingly depend on how effectively organisations can access, govern, and move data across environments.
In 2026, enterprises will focus less on simply storing more data and more on building coherent, trusted datasets that can be reused across training, inference, analytics, and governance. Fragmented data silos will become a clear disadvantage to achieving meaningful AI outcomes.”
Performance predictability is also a key focus. “Second, performance predictability will become critical. AI workloads are highly sensitive to latency and throughput, especially as enterprises run mixed workloads such as training, inference, and analytics on shared infrastructure. This is accelerating the shift toward all-flash platforms that can scale consistently from gigabytes to petabytes without disruption, while keeping GPUs fully utilised,” he explained.
Motaganahalli emphasized that storage must also meet higher expectations for security and compliance. “Third, storage will be evaluated through the lens of resilience and data sovereignty. As cyber threats intensify and regulatory scrutiny increases, enterprises will expect cyber resilience and data governance to be built into storage platforms by design not added as bolt-on features. Recovery assurance, immutable data protection, and clear control over data residency will become board-level priorities rather than IT preferences,” he said.
He noted that consumption models are reshaping how enterprises buy storage. “Finally, consumption models will reshape buying behaviour. In 2026, flexibility will outweigh ownership. Subscription-based, outcome-driven models will allow enterprises to adapt capacity, performance, and cost as AI demands evolve without locking themselves into long-term infrastructure bets in a rapidly changing technology landscape,” Motaganahalli added.
Treating Storage as a Strategic Data Platform
Looking ahead, Motaganahalli believes CIOs must stop treating storage as infrastructure to be managed. He said, “CIOs need to stop viewing storage as infrastructure to be managed and start treating it as a strategic data platform that directly influences business agility, innovation, and time-to-value. The next phase of digital transformation will be led by organisations that can unlock insights from data faster, more reliably, and at greater scale and storage sits at the centre of that equation.”
“First, CIOs should shift from storage-centric to data-centric architectures that are cloud-aware and hybrid by design,” he said. “Modern enterprises operate across on-premises, cloud, and edge environments, using block, file, and object data simultaneously. Managing these environments in silos increases cost, risk, and operational complexity. Unified platforms that provide consistent performance, visibility, and governance across the entire data estate allow data to move where it’s needed, without compromising security or control, while freeing IT teams to focus on higher-value initiatives.”
“Second, storage strategy must be aligned with AI and analytics roadmaps from day one. This means investing in scalable, high-throughput platforms that can support AI pipelines end to end – from data ingestion and preparation to training, inference, and real-time analytics – without constant re-architecting,” Motaganahalli explained.
Resilience, Security, and Sustainability as First Principles
Motaganahalli also stressed that modern storage cannot compromise on cyber resilience or sustainability. “Third, resilience, security, and sustainability must be built into the data layer as first principles. As cyber risks intensify and power and space constraints grow, enterprises can no longer treat cyber resilience, immutable data protection, and energy efficiency as optional. CIOs must evaluate storage not only on performance and cost, but also on assured recovery, regulatory compliance, and the ability to scale AI responsibly within real-world operational limits,” he said.
Removing Data Bottlenecks to Drive AI-Driven Outcomes
“Ultimately, reimagining enterprise storage is about removing data as a bottleneck. When data is accessible, governed, resilient, and adaptable, CIOs are better positioned to control risk, accelerate innovation, and deliver measurable business outcomes in an AI-driven future,” he concluded.
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