PodChats for FutureCIO: Architecting storage to power AI agility

APAC enterprises face data sovereignty fragmentation, IT talent shortages, and sustainability mandates. Enterprise storage is now pivotal to AI success—reshaped by engines like IBM's 5th Generation FlashCore Module (FCM5) that autonomously handle deduplication, encryption, and compression. Yet CIOs must secure data end‑to‑end, from ransomware recovery to quantum‑safe archival, procuring storage that adapts, protects, and optimizes relentlessly for the AI era.In this PodChats for FutureCIO, Barry Whyte, Principal Storage Specialist and Master Inventor at IBM, to talk about the forgotten technology that is core to the continuing development and use of AI in the enterprise.1.       What are the three most critical pain points facing APAC enterprises as AI transforms storage from passive repository to active computational engine? 2.       How do you see data sovereignty regulations, skills shortages, and sustainability mandates compound these challenges across the data lifecycle?3.       How is AI fundamentally reshaping storage technology development—from computational offload (deduplication, compression, encryption) to autonomous performance tuning?4.       Where do autonomous AI agents deliver maximum value in the storage lifecycle—real-time ransomware recovery, predictive capacity planning, or dynamic workload optimization? 5.       What does this mean for CIOs architecting infrastructure that must adapt to unpredictable generative and agentic AI workloads?6.       How can APAC CIOs prioritize use cases that address region-specific constraints like space-limited datacentres and carbon neutrality deadlines?7.       As post-quantum cryptography transitions from "decades away" to "plan now," how should APAC’s financial and government sectors rethink storage security architecture to protect AI training data and models across their entire lifecycle—from ingestion to archival—against "harvest now, decrypt later" threats?8.       Given that AI is compressing hardware refresh cycles while demanding greater capital efficiency, how should APAC CIOs and storage architects balance cloud-adjacent consumption models with on-prem computational storage investments to optimize TCO across the AI data lifecycle?9.       What is your recommendation for CIOs architecting storage to power AI agility?