In 2026, APAC CIOs are under intense pressure. GenAI and agentic AI workloads are surging, talent is scarce, and strict data-sovereignty rules are non-negotiable. Yet according to the latest IBM Institute for Business Value research, only 8% of organizations say their current infrastructure fully meets AI needs, just 42–46% believe they can handle advanced models or real-time inferencing at scale, and privacy, security, and compliance remain among the top reasons AI investments fall short.

That’s where the conversation turns to storage. Today we explore how flash storage is evolving from a simple high-performance tier into something far more intelligent: Agentic Flash — systems with embedded autonomous AI that self-provisions, tunes, migrates workloads, detects threats, and optimizes costs in real time.

We’ll examine how this autonomous intelligence is changing enterprise storage demands, how flash can integrate with content-aware capabilities to make RAG pipelines dramatically more efficient, what new governance guardrails are required between humans and autonomous AI, and how organizations can define SLAs and FinOps practices that keep pace with production agentic AI.

Joining us to unpack all of this is Craig McKenna, Vice President - Storage Sales, IBM Technology, Asia Pacific. 

1. What is the current state of AI adoption in APAC in 2026, and how has the shift to autonomous agentic AI changed the demands placed on enterprise storage infrastructure?

2. Beyond GPUs and accelerators, how is the rapid adoption of agentic AI workloads transforming enterprise storage requirements, and how have flash technologies evolved to support these workloads at scale?

3. How can flash storage integrate with content-aware storage capabilities to improve RAG pipeline efficiency as AI adoption drives explosive growth in unstructured data?

4. According to the IBM Institute for Business Value, 83% of executives view effective governance as essential yet only 8% have embedded risk frameworks. What governance guardrails and trust boundaries should exist between human oversight and autonomous agentic AI in intelligent flash storage systems?

5. How can embedded agentic AI in flash arrays help deliver measurable ROI as organizations scale AI workloads?

6. As organizations move agentic AI into production, what changes in SLAs will be needed to guarantee the performance, resilience, and compliance required by these workloads?

7. What FinOps policies and real-time dashboards are needed when autonomous AI in flash storage dynamically moves data between tiers and object storage during unpredictable AI workload spikes in hybrid environments?

8. In Asia’s regulatory environment, how can flash storage systems ensure that autonomous workload placement and data-mobility decisions remain fully auditable and compliant with privacy, security, and data-localisation requirements?