Below is guest posting and analysis by Trevor Koverko, co-founder of Sapien.
The advent of internet-enabled technologies has changed world trade and economics as citizens, governments and businesses joined exchanges without borders. Data has since become the lifeline and major fuel for businesses and societies around the world, driving economic growth through shared values.
In this digitally connected world, data sovereignty has emerged as an important concept for organizations, state actors, and internet users to control data collection, storage and utility systems. Data sovereignty determines global trade rules, but it should not hinder industry growth and innovation while protecting individual data privacy rights.
Protecting national interests
Global trade relies on data sharing and processing across national borders, so multiple territories and extraterritorial legal measures control the flow of data. Some countries deploy localization methods to limit cross-border data exchange, conduct extensive assessments prior to outbound transfers, and interfere with international trade, industrial output, and foreign direct investment (FDI).
Such data sovereignty measures strengthen national markets and help mature industries provide high-performance services within state jurisdiction. In particular, it helps countries where companies can maximize revenue generation streams by leveraging the vast data reserves.
However, excessive reliance on national data sovereignty can have a negative impact on the domestic economy, with an estimated 1.7% decline in GDP, a 2% decline in employment, and a contraction of up to 3.4% decline in FDI. This leads to detrimental effects on silent global economic ecosystems and international trade.
While localization of services is required, hyperlocalization can prevent companies from accessing international services for data processing, labeling and analysis. This has particular implications for emerging AI industries that rely heavily on large datasets for model training, thereby increasing overhead costs.
Hyperlocalization of data-dependent industries such as AI and cloud service providers can affect free cross-border trade and hinder scaling operations. At the same time, it can reduce revenue diversification channels, cause disruption and generate suboptimal yields for companies relying on foreign data storage units and overseas processing facilities.
In addition to requesting additional capital reserves to manage workloads, Hypersorber’s data management could undermine cross-border trade agreements and data sharing treaties. Therefore, governments and organizations must find a balance to balance the digital economic ecosystem and data sovereignty measures.
Balancing innovation and sovereignty
In some countries, receiving the optimal level of data protection security bound by legal contracts will encourage cross-border data exchange. These bilateral or multilateral contracts help a country maintain the data sovereignty of its citizens by setting specific terms for data use.
Such a data sovereignty model will enhance international trade, global industrial productivity, and cross-border joint projects, leading to a vibrant domestic economy. Data show that GDP has increased by 0.6% and employment rates from the country’s free data exchange increased by 1%.
As digital native companies rely on large aggregate data sets, access to foreign data reserves helps to build innovative and customized services for international customers. In addition to catering to global markets, the unique cross-country exchange of data will encourage researchers and scientists to tackle new data-driven products.
Estimates then show that low data limits for International Technology and Innovation Foundation Data Index could reduce overhead costs by 0.6%. This will allow global and domestic markets to participate in more competition and help businesses improve user-oriented services through high quality data accessibility.
Free data flows can make national markets an attractive destination for data-driven companies, with more domestic and foreign companies offering SAAS and AI solutions. As business diversification occurs, businesses and governments need to remember citizen centrality and user-generated data when operating global markets.
Individuals are sovereign
User data forms the core of the global digital economy. Therefore, protecting user data sovereignty is the best in building market trust and creating long-term value. First of all, Personal Data Protection Act requires protecting citizens’ data during cross-border transfers.
For example, the EU General Data Protection Regulation (GDPR), the Asia-Pacific Economic Cooperation (APEC) Cross-Border Privacy Rules System, and the Privacy Enforcement Agreement (CPEA) are the regulations necessary to maintain individual data sovereignty. Despite these legislative measures, Schrems II’s decision to invalidate the EU-US Privacy Shield contract has posed a major challenge for transatlantic data transfer.
Currently, the EU-US Data Privacy Framework provides provisions for data protection measures for EU citizens within their US jurisdiction, with US intelligence restricting access to data for European users. However, in the pressing Schrems III case, a better transatlantic data transfer approach is needed to balance data protection, innovation, and information flows across borders.
In the data economy, trust and reliability are important to encourage users to participate in data sharing systems. As a result, the user-centered data sovereignty model begins a trust building exercise by implementing robust data usage policies and contracts to instill trust among stakeholders.
If users are confident that they will share their data for strong security measures, it will lead to more innovative products, cross-national knowledge sharing, joint exercises, and global economic growth. Therefore, user-focused data sovereignty allows interoperability as organizations and governments can seamlessly share data across national domains without regulatory hurdles. Data sovereignty ensures responsible and sustainable growth over the long term, as data intensive industries like AI continue to evolve.
