The economics of data sovereignty and data localisation mandates

As governments across Asia race to build digital economies, the question of where data lives has become one of the region’s most economically consequential policy debates. With the rise of Artificial Intelligence, the Internet of Things, and other data-intensive technologies, data has become the fuel of modern growth, yet the rules that govern how it moves across borders are ratcheting up.

Throughout Asia, concerns over privacy, security, and sovereignty have prompted governments to tighten their grip on data. In response, a wave of data sovereignty and data localisation mandates has emerged, rules that determine where and how data can be stored, processed, and shared. These policies are often well-intentioned, but their economic implications are poorly understood at a moment when competitiveness in the global digital economy hangs in the balance.

What do we mean by data sovereignty and localisation? 

Data sovereignty refers to the principle that data is subject to the laws of the country in which it is collected or stored. Data localisation takes this a step further, requiring that certain data categories remain physically within national borders. The aims range from protecting citizens’ privacy and ensuring government access, to promoting local industry and national security.

Yet the stringency of these mandates varies widely. Singapore and Japan have opted for relatively open, trust-based frameworks, while India and China have imposed more restrictive rules on critical and personal data. This diversity reflects not just policy choice, but different economic calculations about what governments stand to gain or lose from data openness.

The economic trade-offs are real

Data localisation mandates can function like a hidden tariff on the digital economy.

Firms face rising compliance and operational costs as they duplicate infrastructure, lease or build local data centres, and navigate complex regulatory regimes. These costs can weigh heavily on multinationals and start-ups alike — deterring foreign investment and raising barriers to innovation.

At the same time, the policy goals are not without merit. Governments view localisation as a way to spur domestic data infrastructure, job creation, and tax revenue, while strengthening economic resilience and digital sovereignty. In some cases, these policies have helped anchor thriving local tech ecosystems.

The challenge is that these effects do not balance evenly. While localisation may boost local cloud providers, it can also slow cross-border innovation, fragment regional digital markets, and erode the productivity gains that flow from global data networks — particularly for AI and advanced analytics that rely on large, diverse datasets.

A complex calculus for policymakers and businesses

For policymakers, the task is to navigate these trade-offs with eyes wide open — grounded in a clear understanding of the economic implications. 

• What are the real costs of localisation mandates — in lost investment, slower productivity, or reduced competitiveness? 
• Who bears those costs, and who benefits? 
• How do these impacts vary by sector, scale, or business model?

For businesses, the implications are equally significant. The economics of data localisation influence where firms choose to invest, how they deploy technology, and how they engage with regulators. Understanding these impacts — and being able to quantify them — is becoming a strategic necessity.

As the digital economy continues to evolve, finding the right balance between data security, innovation, and competitiveness will define Asia’s next chapter of growth. Policymakers and businesses alike will need clear, evidence-based analysis to navigate that path effectively.

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