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4 data management trends and predictions for 2026

By ernesto Alagos | Monday, December 22, 2025, 8:56 AM Asia/Singapore

4 data management trends and predictions for 2026

Shifts in AI models, dataset management, virtualization and isolated recovery environments will be some key developments in data management in the coming year.

By 2026, we’ll reach peak value from publicly available data, as AI models extract the last drops of signal from the open internet.

Enterprises will recognize that AI accuracy depends on data coherence. Virtualization will no longer be a product but an embedded capability, and several forces will converge to make isolated recovery environments (IREs) mainstream:

  1. AI models: 2026 marks the shift from mining the open internet to unlocking untapped internal data
    By 2026, we’ll reach peak value from publicly available data, as AI models extract the last drops of signal from the open internet. The next wave of AI progress will depend as much on discovering untapped data as on refining algorithms. Organizations will turn inward, racing to unlock data long trapped in legacy systems, mainframes, on-prem databases, and unstructured silos; though privacy and governance hurdles will slow progress.

    Synthetic data will emerge as a critical enabler, offering safe, scalable ways to train and test models without exposing sensitive information. Financial services will lead in simulations and risk modelling, while healthcare and other regulated sectors tread carefully. 2026 will mark an inflection point: a shift from mining what’s public to reimagining and reclaiming the hidden data within every organization.
  1. Managing datasets, not just data, becomes the new AI advantage
    Enterprises will recognize that AI accuracy depends on data coherence. Many large organizations still wrestle with multiple versions of truth; slightly different copies of the same data scattered across divisions and regions.

    In 2026, the focus will shift from collecting and cleaning data to governing datasets: curated, versioned, and contextual sources of truth that can be trusted across the business. Those who can eliminate fragmentation and maintain coherent, traceable datasets will see significant gains in model reliability and decision accuracy.

    In the era of enterprise AI, the true competitive edge won’t come from having more data—but from having consistent, managed datasets that everyone can trust.
  1. 2026: the virtualization revolt
    The decade-long dominance of proprietary hypervisors will finally fracture. While recent market consolidations have been a catalyst, the underlying drivers – cost, complexity, and the desire for greater control – have reached a breaking point. Enterprises across Asia Pacific, tired of rising license fees and shrinking flexibility, will begin rewriting their infrastructure playbooks.

    Virtualization will no longer be a product; it will be a capability, embedded natively into cloud, container, and edge platforms. Lightweight hypervisors, open-source technologies, and cloud-native orchestration will replace heavyweight virtual machine sprawl.

    The winners will be those who see this not as an exodus, but as an evolution: moving from managing virtual machines to virtualizing the entire stack – compute, storage, networks, and even AI workloads. By 2026, the infrastructure stack will become modular, programmable, and open. Vendor lock-in will give way to “infrastructure as code,” where the hypervisor quietly fades into the background.
  1. 2026: The year isolated recovery environments go mainstream
    In 2026, Isolated Recovery Environments (IREs) will move from a niche security measure to a boardroom mandate across Asia Pacific. As ransomware and destructive cyberattacks continue to escalate, organizations will recognize that traditional backups are no longer enough. The focus will shift from simply recovering data to assuring recovery itself, and secure isolation will become the new benchmark for cyber resilience.

    Several forces will converge to make IREs mainstream. Regulators will begin demanding demonstrable recovery integrity, insurers will link premiums to verifiable isolation, and boards who are still reeling from high-profile outages. They will push for architectural assurance rather than procedural promises. In response, enterprises will design recovery environments that are physically and logically segregated, automated, and continuously validated.

    Across APJ, IRE adoption will accelerate first in financial services, critical infrastructure, and manufacturing; sectors where downtime equals revenue loss or public risk. But the real shift will be cultural: IREs will redefine how organizations think about resilience, transforming backup from an operational afterthought into a core element of business continuity strategy.

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