Building a sovereign and resilient digital state with multicloud partnerships

The early years of government cloud adoption were defined by the imperative to migrate.

Moving workloads off-premises, cutting costs and scaling capabilities were necessary first steps.

But in 2026, the conversation has matured considerably. The government's cloud strategy is no longer just a tech refresh exercise, but one that has become far more strategic.

That shift has translated into a growing embrace of multicloud and distributed operating models across the region.

According to Chin Ying Loong, Regional Managing Director for ASEAN and SAGE (South Asia Growing Economies), Oracle, governments have the imperative to ensure that critical services remain available, even under cyberattacks, infrastructure failures, or geopolitical disruption.

Chin adds that governments also want flexibility to run across different environments, jurisdictions, and providers without being constrained.

For public officers managing critical public infrastructure, the question is no longer whether to adopt cloud, but how to do so in a way that preserves sovereignty, ensures continuity, and avoids vendor lock-in.

Beyond the lock-in conversation

Vendor lock-in has long been a concern for procurement and IT teams in government, focusing on cost and negotiating leverage.

But today, Chin says that the stakes are higher, with mission continuity as the focus. Governments cannot afford to be in a position where critical services depend entirely on a single provider.

This is why Oracle has designed its multicloud strategy around this concern.

He explains that the company enables government agencies to run Oracle workloads natively across multiple hyperscalers, including AWS, Azure, and Google Cloud, while maintaining a consistent architecture and performance standard.

In practice, this means agencies are not forced into a costly re-platforming exercise or left managing fragmented, incompatible environments.

“They can deploy the same database services, with the same performance characteristics and service levels, across clouds,” he explains, underlining the importance of operational flexibility for public agencies to maintain service continuity.

Taming complexity

Another concern for many agencies managing a multicloud infrastructure is complexity.

Managing data and workloads across multiple providers introduces potential points of failure and raises questions about operational stability, which Chin acknowledges.

Oracle's response has been to engineer that complexity out through deep, tightly integrated partnerships with hyperscalers.

This is achieved by running Oracle services in close proximity to application workloads in other clouds. The result is reduced latency, secured connectivity, and more predictable data movement.

“From a public service perspective, multicloud becomes more stable, not more fragmented,” he says.

Bringing AI to the data

Traditionally, implementing artificial intelligence (AI) requires moving large volumes of data to where the compute or models are running.

For governments handling sensitive citizen data, this approach creates both governance risk and operational latency.

Oracle's multicloud approach flips this model by bringing AI to where data already resides.

Chin explains that this brings about two key advantages.

First, reduce latency and operational risks associated with moving data across networks. Second, align governance requirements to ensure that sensitive data remain in a controlled environment.

For public agencies, this means that they can more easily tap into AI closer to where the data already sits, while maintaining stronger control, faster response times, and more reliable operational outcomes.

Multicloud strategy as a strategic safeguard

Governments are also grappling with a longer-term risk: What happens when a key cloud platform undergoes significant changes, pricing shifts, or regulatory restrictions?

Chin cautions against tying one’s AI strategy to a single platform, as any significant change can create disruption.

A multicloud approach functions as a strategic safeguard, ensuring that data, models, and core platforms are built on a foundation that can operate across multiple environments, such as public cloud, sovereign deployments, and partner hyperscalers.

The broader AI strategy needs not to be redesigned from scratch when the cloud environment changes.

Chin notes that it gives governments the ability to pivot or redistribute workloads with minimal disruption, preserving both continuity and compliance.

Designing for both sovereignty and resilience

For public sector agencies, this is not about choosing between sovereignty and resilience, Chin explains, emphasising the need to design both from the start.

In Oracle’s experience, he shares that a model that works well is one where “sensitive or regulated data remains in sovereign or in-country environments, while other workloads—applications, analytics, or AI services—can run on public hyperscalers where it makes sense.”

Oracle's platform approach supports this across deployment models, without requiring agencies to sacrifice one objective for the other.

Less as a technical preference and increasingly as a governance imperative, a multicloud architecture serves as a foundational layer for states that need to be resilient, sovereign, and ready for whatever comes next.