Spend a morning navigating any Asian megacity, whether Bangkok at rush hour or Jakarta on a rainy Monday. You will see a system that stays in motion despite constant congestion. It works because the infrastructure underneath is built to handle strain and variability.
Enterprise technology environments across Asia Pacific and Japan (APJ) are facing a similar dynamic. Artificial intelligence (AI) adoption is accelerating, digital services are expanding, and regulatory expectations are tightening. Yet many organizations are modernising in fragments. The result? Environments that are distributed but not coherent.
This raises a critical question for every CIO: how do you stay agile and secure when your digital “city” is expanding faster than your ability to govern it?
From distributed to coherent
In today’s rapidly evolving IT landscape, fragmentation, and the resulting loss of coherence across environments, has emerged as a critical challenge. This often leads to what experts describe as ‘architectural drift’: when environments evolve faster than an organization can govern them, causing platforms and workloads to behave inconsistently across locations.
The organizations navigating this most effectively plan for resilience from the outset. They simplify their architectures, build for portability, and proactively reduce operational risk.
AI at the edge
This challenge is most visible at the edge. Fuelled by the Internet of Things (IoT), 5G and AI-driven applications, APJ’s edge computing market is expanding rapidly. It is expected to more than triple from roughly US$9.5 million in 2022 to over US$33.4 million by 2028. Retail networks, hospitals, logistics hubs, and industrial facilities are generating vast volumes of real-time data. With generative and increasingly autonomous AI emerging, this data is becoming more valuable and far more sensitive.
Tim Hope, Chief Technology Officer at Versent, noted during our APJ roundtable that enterprises have moved well beyond curiosity about AI pilots. They are now dealing with practical questions on how to scale AI responsibly across markets. They must also meet differing data residency requirements and keep performance consistent across distributed edge environments.
These challenges are symptoms of fragmented and drifting environments, not of limitations in technology. Without a consistent platform strategy, AI deployments do not behave the same way across environments. That inconsistency drives overhead and compliance issues. It also makes scaling AI difficult.
A platform-led approach ensures governance, scalability, and performance remain consistent wherever workloads run. As AI becomes part of daily operations, this consistency will shape how well the technology performs and how much value it delivers to the business.
Closing protection gaps in a cloud-native landscape
Cloud-native adoption offers agility, but it also increases the number of components teams must manage across data centres, public cloud, and the edge. As environments expand, gaps in visibility, compliance, and control widen.
A 2024 global study found that 48 percent of organizations saw an increase in compliance violations. Around half said they would update or refactor their applications if they were migrating to the cloud for the first time. It is a reminder that many workloads are not cloud-ready and require additional work to perform reliably.
Leaders also highlighted a growing concern. Cloud-native architectures are maturing faster than the operational models that support them. Enterprises are realising that tool sprawl and siloed skills are now structural barriers created by fragmentation and architectural drift, preventing teams from operating consistently at scale.
What leaders want instead is clarity. Unified platforms that consolidate visibility, strengthen governance, and streamline operations are becoming central to restoring predictability and managing costs.
Ensuring continuity amid market volatility
External shifts are amplifying these pressures. Hyperscaler costs are becoming more volatile. Data sovereignty rules continue to evolve, while long-standing vendor licensing models are changing. As a result, many organizations are reassessing long-held infrastructure assumptions. Continuity and control now matter as much as speed.
Australian mining and civil services company Golding’s recent transformation provides a clear example. The company undertook a co-design process with Nutanix and Versent to rebuild its infrastructure strategy with flexibility and control at the core. The move to Nutanix Cloud Clusters (NC2) on Amazon Web Services (AWS) helped Golding regain operational confidence, strengthen disaster recovery, and achieve the portability required for rapid growth.
Equally significant was the trust built throughout the process. Meaningful change relies on alignment and collaboration just as much as it does on the technology itself.
Designing what comes next
Resilience has to be designed in from the start. For APJ enterprises, that means building for portability, embedding AI responsibly, and reducing complexity so teams can focus on innovation.
As AI and cloud-native adoption accelerate, the real differentiator will be how quickly an enterprise’s architecture can adapt. Organizations that invest in this adaptability today will be better positioned for whatever comes next.
Jay Tuseth is Vice President and General Manager of Asia-Pacific and Japan (APJ), Nutanix.
Jay is a seasoned enterprise executive who has lived in Singapore since 2013. Prior to joining Nutanix, he served as Conviva’s vice president of sales for APAC SaaS applications and general manager of customer experience, based in the company’s Singapore office.
At Conviva, Tuseth led all operations in the APJ region, helping digital businesses and their operations teams shift from a focus on quality of service to one centred on quality of experience. He drove continuous growth, challenging teams to push boundaries, take ownership, and ensure that great contributions were recognized.
Before Conviva, Tuseth served as vice president of cloud applications at Oracle. He also spent 12 years at Dell Technologies and EMC in multiple executive leadership roles, leading diverse teams across APJ and helping customers use data to maximise their competitive advantage.
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Featured image: Ning Shi on Unsplash
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