How governments can deal with data sovereignty

In today’s fast-paced global digital economy, data has become an invaluable resource, driving advancements, and enabling digital trade.

Governments worldwide face the challenge of maintaining data sovereignty while fostering economic growth and technological innovation.

Achieving this balance requires a nuanced approach to managing data flows across borders, ensuring security, privacy, and accessibility for law enforcement, without stifling economic and technological progress.

The economic impact of data sovereignty

Data sovereignty, defined as a nation’s ability to exercise jurisdiction over its data within and beyond its borders, significantly impacts economic growth. Countries typically adopt one of two models: free data flow or restricted data flow. Each model offers distinct economic implications.

Free data flow model: Countries such as Japan and those in the European Union embrace the free data flow model, allowing data to move across borders under certain conditions. This model fosters international collaboration, innovation, and competitive pricing.

By enabling access to large, diverse datasets, it supports the development of artificial intelligence (AI) and other advanced technologies.

Benefits of the free data flow model include:

Innovation and customisation: Companies can leverage aggregated data from foreign markets to develop new, targeted services for international customers.

Collaboration: Relaxing restrictions on data flow facilitates cross-border collaboration among innovators and researchers, driving the development of new products.

Affordability: Reducing data restrictiveness can open markets to competition, leading to lower prices in relevant sectors.

Service quality: The free flow of data enhances service quality by increasing competition and access to higher-quality services from local and foreign providers.

Service availability: Reducing regulatory hurdles makes markets more attractive for businesses, increasing the number and diversity of services offered.

Despite these benefits, the free data flow model requires robust data security measures to protect sensitive information from cyber threats and breaches. Countries must weigh these advantages against the potential costs and ensure they invest in effective security mechanisms.

Restricted data flow model: Conversely, countries such as China and Russia adopt a more restricted data flow model, imposing rather stringent regulations on data transfer. While this model aims to protect national interests, it may incur significant economic costs.

Drawbacks of the restricted data flow model include:
Economic contraction: A restricted model can lead to a 1.7 per cent contraction in GDP per year and a decrease in employment rates.

Reduced investment: Foreign direct investment may decrease by 1.7 per cent to 3.4 per cent, and sectors relying on cross-border data transfers can shrink by 3.5 per cent.

Service access and affordability: Localisation measures increase costs and reduce service availability, raising prices and limiting market competition.

Innovation: Restricting data flow hinders companies’ ability to innovate and expand, as additional resources are required to build local capabilities.
Despite these challenges, countries with large populations and mature technology markets may mitigate some negative impacts by reducing reliance on foreign data flows and fostering domestic innovation.

Balancing data sovereignty and AI development

AI development relies on access to diverse and large datasets, which can be hindered by stringent data localisation measures. Governments must find a balance that ensures data security and privacy without stifling innovation.

Options to mitigate the stifling effects of data localisation measures include:
Cross-border data agreements: Countries can establish agreements that facilitate data flow while ensuring adequate protection. Bilateral or multilateral agreements can set conditions for data transfer, safeguarding privacy and security.

Robust data protection laws: Implementing comprehensive data protection laws, like the EU’s General Data Protection Regulation (GDPR), can protect personal data while permitting cross-border transfers.

International cooperation: Engaging in international frameworks, such as the Budapest Convention on Cybercrime, can enhance regulatory interoperability and address challenges in investigating crimes involving cross-border data.

Achieving effective data sovereignty

To balance data sovereignty with economic and technological advancements, governments should consider the following actions:
Enable free data flow with trust: Limit cross-border data transfer restrictions to safeguard national security interests or serve specific national objectives.

Elevate personal data protection: Adopt robust personal data protection laws that align with global standards, ensuring that the data of citizens and residents is protected.

Protect intellectual property: Enact necessary legislation, improve enforcement mechanisms, and ratify international treaties to safeguard intellectual property within and outside borders.

Enforce cybersecurity standards: Implement best-in-class cybersecurity measures to protect data from cyberattacks and ensure resilience against natural or man-made disasters.

Establish international frameworks: Enhance international cooperation with like-minded countries to build trust and address challenges in cross-border data management (For example, Budapest Convention, US CLOUD Act).

In conclusion, data sovereignty is a complex and evolving issue that requires careful consideration of economic, technological, and political factors. By adopting a balanced approach, governments can ensure data security and privacy while fostering innovation and economic growth, ultimately benefiting their digital economies and societies.

Rob Van Dale is a partner and lead – Digital and Analytics Practice, Elias Abi Aad is a consultant and Africa, and Carl Ghanem is a consultant at Kearney Middle East and Africa.