How to Plan for Data Sovereignty in the Age of AI
Modern companies are built on data, which is their most valuable asset. This data must be protected and comply with the regulations of the countries where these companies operate. Many governments forbid sensitive data from residing on systems outside of their legal control, creating the challenge of data sovereignty. Examples include the EU General Data Protection Regulation (GDPR) and Canada’s Consumer Privacy Protection Act (CCPPA).
AI compounds this challenge as it utilizes vast amounts of data, often consuming data that was previously restricted. Generative AI services, used in business applications, must limit the use of data outside the country-specific data sovereignty boundaries.
As AI technology grows, it confronts established and emerging privacy and data sovereignty regulations globally, like GDPR and CCPPA. Businesses must balance compliance with the need to use the latest data technologies, often maintaining data in multiple countries to better serve customers and employees. This introduces complexities due to varying regional data protection laws.
Fortunately, a blend of mindset, policy, and tools can help achieve a balance. Five considerations for protecting data sovereignty when integrating AI include:
- Mindset: It’s crucial that everyone in the company understands the fundamentals of data sovereignty and the business risks of non-compliance.
- Inventory: As data grows and fragments, businesses must maintain an inventory of their data and understand the vendors that act on this data.
- Internal Policies and Governance: Companies must comply with regional data residency laws and manage data anonymization and pseudonymization effectively.
- Vendor Dialogs: Enforce vendor compliance by ensuring they adhere to company policies and the regulatory frameworks of the regions they operate in.
- Data Unification Technologies Using AI: Modern tools leverage AI to enhance data unification and ensure internal consistency, which aids in managing data sovereignty compliance.
Healthcare systems face stringent data sovereignty requirements but illustrate the possibility of maintaining flexible and compliant data management systems. For example, a patient’s data can be kept locally and processed without transmitting personally identifiable information.
Speed, agility, and compliance need not be sacrificed with the right tools and partners. Managing data within the varying and complex sovereignty regulations globally is essential for every international organization today.
