AI in Social Protection: Data Sovereignty Considerations

Overview

Data is at the heart of artificial intelligence. For social protection systems, this raises fundamental questions: who controls the data that AI systems rely on, where is that data processed, and who has the power to determine how it is used?

The AI in Social Protection: Data Sovereignty Considerations publication examines these questions through the lens of social protection, where governments and institutions manage some of the most sensitive information about people and households.

The publication provides practical guidance for policymakers and social protection practitioners seeking to adopt AI while maintaining appropriate control over data, systems, infrastructure, and institutional capabilities.

Rather than treating data sovereignty simply as a question of where data is physically stored, the publication considers the broader dimensions of control, access, governance, infrastructure, and institutional capacity that shape whether countries can use AI on their own terms.

Why this publication matters:

Social protection systems depend on data. Information about people’s income, employment, household composition, health, disability, location, and use of public services can be essential for designing and delivering programmes.

AI can create new opportunities to make better use of this data. It can help institutions process large datasets, identify patterns, improve administrative processes, and support more responsive services.

But AI can also change the way data flows through social protection systems. Data may be transferred to external providers, processed through third-party applications or APIs, stored in foreign jurisdictions, or used within AI models that institutions have limited ability to inspect or control.

These questions become particularly important when social protection agencies use cloud-based AI services or rely on external technology providers. The choice of deployment model can have significant implications for data sovereignty, accountability, security, and institutional autonomy.

The challenge is therefore not simply to protect data from unauthorised access. It is to ensure that governments and social protection institutions retain meaningful control over the data and AI systems on which essential public services depend.

What you’ll find inside:

• A conceptual framework to understand data sovereignty
• A dive into sovereignty readiness and the dimensions of sovereignty risk
• Examples illustrating current patterns in AI use
• An integrated framework for mitigating data sovereignty risk

Who is this publication for?

This publication is designed for:

• Policymakers
• Social protection practitioners
• Researchers
• AI developers and technology partners
• International organizations and development partners

Required citation:

DCI AI Hub for Social Protection, AI in Social Protection: Data Sovereignty Considerations, Deutsche Gesellschaft für Internationale Zusammenarbeit, Germany, 2026.