What Is Data Sovereignty?

Cloud computing has helped businesses, especially small enterprises, reduce the high costs of establishing physical IT infrastructures. However, this shift has led to decentralized data storage across the globe, raising concerns about data protection and regulatory compliance.

The storage of sensitive data in foreign jurisdictions poses potential risks to national sovereignty and citizen well-being. In response to these concerns, governments are increasingly implementing laws to protect personally identifiable information (PII). These measures are particularly necessary in a time when artificial intelligence (AI) is accelerating the use and exploitation of data.

Recent legal challenges highlight these concerns. For example, OpenAI has faced lawsuits alleging unauthorized use of user data to train its GPT models. Similarly, DeepSeek, an AI startup, has faced allegations of data misuse, leading to bans in Texas and Australia. These incidents highlight the ongoing debate surrounding data privacy and the need for robust data protection laws.

As digital identity frameworks and protective measures evolve, ensuring that user data remains within national borders, under well-established laws, is critical. Enforcing these regulations and holding non-compliant companies accountable is essential to safeguarding privacy and ensuring geopolitical stability.

What Is Data Sovereignty?

Data sovereignty refers to the principle that data generated within a country’s borders is subject to its laws and governance structures. This means that governments, organizations, and individuals have control over how their data is collected, stored, processed, and shared.

With the growth of cloud computing, businesses are increasingly storing data across multiple jurisdictions, raising concerns about who controls and protects that data. Countries are responding with stricter regulations to ensure that data remains under national jurisdiction. These regulations aim to protect national security, privacy, and economic interests. Examples of such laws include the General Data Protection Regulation (GDPR) in the European Union, the California Consumer Privacy Act (CCPA) in the U.S., and the Clarifying Lawful Overseas Use of Data (CLOUD) Act, which addresses law enforcement access to data across borders.

For example, if a UK-based financial services firm stores transaction data in the U.S., questions arise about the UK government’s ability to protect its citizens’ financial information, especially during geopolitical shifts. This uncertainty has led many nations to mandate local storage or impose data transfer restrictions, ensuring control over sensitive data.  According to the United Nations Conference on Trade and Development (UNCTAD), 71% of countries have enacted data privacy and protection regulations, many of which relate to data sovereignty.

Difference Between Data Sovereignty, Data Localization, Data Residency

These three terms are often confused but are distinct and important to understand in the context of global data management:

Terms	Definition	Key Requirement	Example
Data Localization	Requires that data must be stored or processed within a specific country’s borders.	Data cannot be transferred or stored outside the country.	Russia requires that citizens’ data be stored within Russia.
Data Residency	Refers to the physical location of data storage, without a legal mandate.	Organizations can choose where to store data, as long as regulations are followed.	A U.S. company stores EU customer data in Germany to comply with regulations.
Data Sovereignty	Concerns the legal authority over data, regardless of where it is stored.	The country of origin has authority over the data, even if stored elsewhere.	A company in France must comply with GDPR, even if its data is stored in the U.S.

Why Is Data Sovereignty Important?

Data sovereignty goes beyond legal technicalities—it impacts privacy, cybersecurity, national security, economic growth, and global business operations. Here’s why it matters:

1. Strengthening National Privacy Protection

Data sovereignty helps ensure that personal data remains protected under local laws, preventing unauthorized access by external entities. With growing concerns over data breaches, citizens feel safer when their data is governed by their own country’s regulations.

2. Supporting Legal and Regulatory Compliance

Countries around the world have specific laws to protect data, and businesses must comply with these rules. Data sovereignty ensures that businesses follow national regulations like the EU’s GDPR or California’s CCPA, which lay out clear guidelines on how personal data should be handled. Storing data within a country’s borders helps companies comply with these regulations, avoiding fines and other legal issues.

3. Enhancing Cybersecurity and National Security

When foreign companies store or manage critical data, it can increase the risk of cyberattacks or unauthorized access. By enforcing data sovereignty, countries protect themselves from cyber threats and safeguard their national security interests. For example, countries like China have strict data sovereignty laws to keep sensitive data within their borders, which reduces reliance on foreign providers and enhances security.

4. Increasing Consumer Trust

Consumers are becoming more aware of how their personal data is handled, with 86% saying data privacy is a growing concern. By prioritizing data sovereignty, businesses can build trust with their customers. Ensuring that data is stored and processed in line with local privacy laws shows customers that their information is safe. Take Estonia, for example—its strong data sovereignty laws have helped build trust in its digital services, making citizens feel secure about how their data is managed.

5. Ensuring Ethical Data Use and AI Development

Data sovereignty also plays a key role in ensuring that AI systems are developed ethically. When data stays within national borders, it’s easier to monitor how it’s used to train AI models. This helps ensure AI development is guided by local ethical standards and reduces the risk of biases introduced by foreign data manipulation.

Key Principles of Data Sovereignty

The principles of data sovereignty guide how nations and organizations manage, protect, and control data within their jurisdiction. These include:

1. Jurisdictional Control

Jurisdictional control means that a country has legal authority over the data generated, stored, and processed within its borders. Governments enforce national data protection laws to ensure that data remains safe and complies with local regulations.

2. Data Localization

Data localization requires that data collected within a country remains within that country’s borders, either fully or partially. This helps protect sensitive data from foreign access. However, it can create economic challenges, including increased costs and trade barriers. A paper by the Centre for Information Policy Leadership (CIPL) outlines these potential drawbacks.

3. Data Governance

Data governance ensures that data is handled responsibly. This involves creating policies and frameworks to manage its collection, storage, and processing. It also includes setting up accountability, compliance, and security measures to protect privacy and maintain data integrity.

4. Data Minimization

Data minimization is about collecting only the necessary data needed for a specific purpose. By focusing on what’s required, businesses reduce the amount of data that crosses borders or needs processing. This also limits exposure to data breaches. Companies like Apple implement this principle by processing data on devices rather than storing large amounts on servers.

5. Cross-Border Data Transfer Restrictions

This principle controls how organizations move data across national borders, ensuring that sensitive or personally identifiable information (PII) is not transferred to countries with weaker data protection laws. For example, Article 45 of the EU’s General Data Protection Regulation (GDPR) requires companies to assess whether the destination country offers adequate data protection before transferring data.

Challenges of Implementing Data Sovereignty

Implementing data sovereignty introduces several challenges for businesses, including:

1. Navigating Complex Jurisdictions

Companies operating across borders face a complex regulatory landscape, as different countries have their own laws regarding data storage, processing, and transfer. This can create significant compliance challenges, especially when regulations evolve or conflict, increasing operational risks and costs for multinational businesses.

2. Infrastructure and Cost Challenges

Data sovereignty often requires local data storage, leading to high infrastructure costs. Businesses often need to build or lease data centers, hire additional staff for compliance, and implement new data management systems, all of which can be expensive. Data transfers and processing fees can also rise due to regional restrictions, further increasing compliance-related expenses. According to a 2025 report by NorthRow, companies spend, on average, 25% of their revenue on compliance-related expenses, with new data laws further escalating these costs.

3. Technology and Resource Barriers

In many regions, particularly developing countries, the lack of infrastructure to meet data sovereignty requirements creates operational obstacles. Businesses may have to invest in building local facilities or depend on less secure local providers, which can affect reliability and security. These infrastructure constraints pose a challenge to companies striving to meet data sovereignty regulations.

4. Cross-Border Legal Conflicts

Conflicts between data sovereignty laws in different countries can create legal uncertainty for businesses. For instance, the US CLOUD Act allows the government to access data stored abroad, which may clash with the EU’s GDPR restrictions on data transfers. Such discrepancies can lead to legal disputes, diplomatic tensions, and trade barriers, complicating global operations.

5. Privacy vs. Innovation

Striking a balance between protecting privacy and fostering innovation is a key challenge. While data sovereignty laws aim to protect privacy, they can also limit data flow, hindering technological research and development in sectors such as AI. The restrictions on cross-border data transfers can stifle collaboration, slowing innovation in industries reliant on large datasets.

6. Operational and Administrative Complexity

Managing data across multiple jurisdictions adds significant complexity to IT operations. Businesses must implement country-specific policies for data storage, transfer, and security, requiring them to navigate multiple regulatory environments simultaneously. Global enterprises, in particular, face the burden of ensuring compliance with various national regulations, such as GDPR in the EU and PIPEDA in Canada, which can lead to administrative and operational overhead.

How to Balance AI and Data Sovereignty

Balancing AI’s need for vast data sets with the principles of data sovereignty is one of today’s biggest challenges. AI thrives on access to large amounts of data to learn, improve, and make decisions. However, data sovereignty laws, which protect national security and privacy, often require that sensitive data stay within specific borders. This creates a tension: while AI needs a lot of data to be effective, those laws limit how freely data can flow across countries.

The need for vast, diverse datasets is especially critical for AI in areas like healthcare, finance, and autonomous vehicles. The more data AI has, the better it can learn and provide valuable insights. But the stricter data sovereignty laws make it harder to gather and use data across borders, complicating AI development.

So, how can we balance these two competing priorities? Solutions like federated learning and privacy-preserving technologies offer a way forward. For example:

Federated Learning

Federated learning allows AI models to be trained on local data, without the need to send it across borders or centralize it. This way, data stays within its local jurisdiction, complying with data sovereignty laws while still allowing AI to learn from the data. For example, healthcare organizations can train AI models using patient data stored in local hospitals, but the data never leaves the facility. This ensures the privacy of individuals while enabling the use of valuable data for AI training.

Privacy-Preserving Technologies

Privacy-preserving technologies like differential privacy and homomorphic encryption help businesses protect data while using it for AI.

• Differential Privacy adds noise to data, so individual data points can’t be identified, even when the data is analyzed in aggregate. This ensures that companies can use and share data without compromising user privacy.
• Homomorphic Encryption allows computations to be done on encrypted data, meaning the raw data never has to be exposed during the AI training process. This ensures the data remains secure while still contributing to AI’s learning process.

These technologies provide a way to respect data sovereignty laws, protect privacy, and still allow AI to access the data it needs. By using federated learning and privacy-preserving techniques, it’s possible to strike a balance where AI can continue to evolve, while data privacy and sovereignty are maintained.

Utilizing Decentralized Systems to Achieve Data Sovereignty

Decentralized systems provide effective solutions for enhancing data privacy, security, and sovereignty. Designed to give individuals greater control over their data, these technologies can also scale to meet the needs of nations and organizations. When implemented properly, decentralized systems offer resilient, transparent, and tamper-proof data governance, ensuring sovereignty at all levels—from individual users to entire nations.

1. Blockchain

Blockchain is a distributed ledger technology that records data across a network, eliminating single points of failure and control, making data tampering nearly impossible. For example, Estonia’s e-residency program uses blockchain to secure digital identities, ensuring citizen data stays under strict local control. Blockchain enhances data privacy by providing a tamper-proof system for storing sensitive information, allowing individuals to maintain control over their data. Its transparency and immutability improve accountability, while facilitating auditable consent that strengthens data sovereignty and privacy.

2. Decentralized Identifiers (DIDs)

Decentralized Identifiers (DIDs) enable individuals and organizations to create self-managed digital identities without relying on a central authority. Stored on decentralized networks, DIDs give users full control over their personal data. In the EU, pilot projects are utilizing DIDs to enable secure, self-sovereign identity verification. This reduces reliance on traditional identity providers and empowers users to decide which information to share and with whom, fully aligning with the principles of data sovereignty.

3. Verifiable Credentials

Verifiable credentials complement DIDs by providing a secure way to issue, store, and verify digital credentials without disclosing excessive personal information. These credentials are tamper-proof and cryptographically verified, enhancing both security and compliance. Universities and employers are adopting verifiable credentials to issue and confirm certifications. For example, universities issue degrees as verifiable credentials, ensuring authenticity while allowing the student to retain control over their personal data. This approach helps organizations comply with data sovereignty laws by limiting the sharing of personal data and maintaining jurisdictional control.

4. Smart Contracts

Smart contracts are self-executing agreements that run on blockchain networks. These contracts automate data access, processing, and sharing, ensuring compliance with jurisdictional laws. Governments could use smart contracts to restrict access to citizen data, granting access only under specific legal conditions, such as compliance with GDPR. The EU is considering using smart contracts to facilitate cross-border data transfers while ensuring compliance with regional data sovereignty frameworks. By automating the process, smart contracts ensure that data privacy is respected, while still enabling the free flow of information necessary for innovation and international collaboration.

The Future of Data Sovereignty

The future of data sovereignty will be shaped by technological advancements like quantum computing, edge computing, and the growing demand for international cooperation. As data continues to play a critical role in the global economy, it is essential for countries to update their data sovereignty frameworks to address these emerging challenges and ensure robust privacy and security.

Quantum Computing and Data Protection

Quantum computing has the potential to disrupt current encryption methods, making data more vulnerable to security breaches. As quantum technology advances, it will be crucial for data sovereignty laws to evolve in order to protect sensitive information. Nations must adopt quantum-resistant encryption techniques and rethink their data protection strategies to safeguard against quantum-powered threats, ensuring the security of data within their jurisdiction.

Edge Computing and Decentralized Data Management

Edge computing, which processes data locally on devices rather than relying on centralized servers, aligns closely with the principles of data sovereignty. By keeping data within specific geographic regions, edge computing can support local data storage and processing, ensuring compliance with data sovereignty laws. However, the decentralized nature of edge computing introduces complexities in maintaining consistent data protection standards. Governments will need to adapt regulations to address the unique challenges of edge devices and decentralized data flows while ensuring privacy protections are upheld.

International Cooperation for Unified Data Sovereignty Frameworks

As data sovereignty laws continue to become more fragmented across different regions, there will be an increasing need for international cooperation. Currently, varying regulations on data storage, privacy, and cross-border transfers create compliance challenges for businesses operating globally. A unified global framework for data sovereignty would help standardize data management practices, making it easier for businesses to comply with laws across jurisdictions. Such frameworks could ensure that countries uphold data protection while facilitating the free flow of data across borders, fostering innovation, and supporting economic growth.

How Identity.com Prioritizes Data Sovereignty

At Identity.com, data privacy and user control are at the core of our platform. We provide solutions that empower individuals to manage their digital identities, ensuring full compliance with data sovereignty principles. Below are a few ways we prioritize data sovereignty:

1. Use of Decentralized Identity Tools

Identity.com leverages decentralized identity tools such as DIDs and verifiable credentials to give users complete control over their data. Our platform ensures that users can manage their digital identities without relying on centralized authorities, keeping personal data under their control. By using cryptographic methods for secure authentication and validation, our secure mobile app ensures that users share only the necessary information for a given transaction, minimizing the risk of data breaches.

2. Compliance with Global and Regional Data Regulations

Our solutions are designed to meet global and regional data regulations, ensuring that our services comply with diverse legal requirements. This commitment to compliance not only helps us meet legal standards but also fosters trust among our users, especially those operating across different jurisdictions.

3. Empowering Users with Control Over Their Personal Data

Through the Identity.com mobile app and our developer tools, we empower users by giving them full control over their personal data. Our platform allows individuals to decide what information to share, with whom, and for how long, fully aligning with the principles of data sovereignty. This user-centric approach promotes transparency and accountability, ensuring users are active managers of their digital identities rather than passive recipients of data handling decisions.

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