Leaders Roundtable: From Fragmentation to Control: Evolving Hybrid Cloud Operations for AI

Hybrid cloud is now the default operating model for most organisations in Hong Kong. At the same time, AI adoption is accelerating, but infrastructure and operating models are lagging behind. As organisations move beyond pilots, the constraints are becoming clearer. Many environments remain fragmented, loosely integrated, and not built for real-time, AI-driven workloads. 

Ecosystm research highlights where the gaps are most visible: 

• 47% cite infrastructure limitations across compute, storage, and network as a barrier to scaling AI 

• Only 40% are deploying AIOps, despite increasing operational complexity 

• Just 11% report seamless integration across cloud and on-prem environments for AI workloads 

What’s emerging is not just a scaling challenge, but an operating model problem. Organisations are starting to rethink how hybrid environments are structured and managed shifting toward more integrated, consistent, and automated approaches to operations. AIOps is beginning to play a more defined role, enabling teams to move beyond reactive issue management toward more predictive and adaptive operations. 

At the centre of this shift is a more unified CloudOps model that brings governance, observability, automation, and cost visibility into a single operating layer. The goal is not just efficiency, but greater control and clarity across increasingly distributed environments. 

Join us for an invitation-only executive roundtable to examine how organisations are modernising infrastructure and evolving operations to support AI at scale. In a closed discussion with peers, we will focus on practical approaches to reducing fragmentation, improving operational control, and making hybrid environments more workable. 

Key Takeaways: 

• Modernising for AI Scale. Addressing infrastructure constraints across compute, storage, and hybrid integration 

• From Fragmentation to Integration. Managing hybrid environments through more consistent operating models 

• Operationalising AIOps. Moving toward more predictive and automated IT operations 

• Closing the Integration Gap. Improving consistency across cloud and on-prem environments 

• Cost, Control & Visibility. Strengthening oversight across distributed hybrid estates