AI and cloud reshape Asia-Pacific data software landscape

IDC forecasts a 15.7% CAGR for data management software in APeJC, reaching $13.7B by 2029, driven by AI automation, cloud adoption, and secure data governance.

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DQC Bureau
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AI and cloud reshape Asia-Pacific data software landscape

AI and cloud reshape Asia-Pacific data software landscape

Data management software in Asia-Pacific (excluding Japan and China) is undergoing rapid transformation, according to the latest IDC Worldwide Semiannual Software Tracker (2024H2). The market grew by 10.0% in 2024 and is projected to rise at a compound annual growth rate (CAGR) of 15.7%, reaching USD 13.7 billion by 2029.

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The driving force? A deepening reliance on automation, AI and GenAI-powered workflows across sectors. These capabilities demand real-time, scalable data pipelines — not just for speed, but for smarter decision-making. As businesses shift towards AI-first operations, they are investing in modern platforms that break down data silos and integrate diverse sources.

This transformation is also being shaped by regulatory pressures. Organisations are now rethinking data governance, opting for metadata-driven integration tools and frameworks that ensure compliance, auditability, and security. The pivot to intelligent governance is no longer optional; it’s foundational.

Cloud deployment continues to gain traction. While many organisations in the region maintain a hybrid IT environment, the pace of migration to public cloud services is accelerating. IDC expects public cloud-based deployments to grow at a robust 31.1% CAGR. By contrast, on-premises systems, especially in data lakes and NoSQL, are expected to remain relatively flat.

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Yet, it’s not a complete shift away from traditional infrastructure. Sectors like banking, government, and manufacturing still show a strong preference for on-prem setups, largely due to compliance requirements, latency constraints, and tighter operational control.

In essence, the region’s data software landscape is moving toward a mixed model: agile and cloud-optimised for innovation, yet grounded in on-premises reliability where needed. As AI and cloud-native architectures converge, the coming years will see enterprises reshaping their data foundations for flexibility, intelligence and control.

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