Dr. Mark Nasila, Chief Data and Analytics Officer in FNB Chief Risk Office.

At its simplest, sovereignty refers to power and control. That is, who or what has control over who or what. It’s where the idea of a king or queen as sovereign stems from — in a monarchy, power rests with the monarch. 

In modern democracies, sovereign power lies with parliament or congress, or the bodies elected to create and enact laws. But sovereignty can also refer to power over assets or resources.

One contemporary African example is the Lesotho Highlands water project. Lesotho, a nation wholly surrounded by South Africa, sought to assert sovereignty over its natural resources, particularly its abundant water supply, by leveraging the strategic value of its water in negotiations with South Africa.

Recognising that water was its most valuable asset, Lesotho aimed to maximise its benefits by charging South Africa for the use of water flowing from the Orange River, which originates in Lesotho’s Maluti Mountains. 

This led to the establishment of the Lesotho Highlands Water Project (LHWP) in 1986 between Lesotho and South Africa, a large-scale initiative designed to transfer water to South Africa while simultaneously generating significant revenue for Lesotho through royalties.

This arrangement allowed Lesotho to gain significant economic benefits, with royalties from the water transfers contributing approximately 4% of its GDP and 10% of government revenues, funding critical development projects within the country. 

By asserting control over its water resources, Lesotho not only ensured a steady stream of revenue but also reinforced its sovereignty over a key natural asset.

The LHWP represents a strategic partnership where Lesotho’s water, a vital resource that the country itself uses sparingly, becomes a powerful tool for economic development. 

This initiative underscores how smaller nations can leverage their natural resources to assert sovereignty and foster economic growth, even when partnered with larger neighbouring countries.

What is sovereign AI?

Sovereign AI refers to the concept of countries harnessing and processing their own data to build artificial intelligence domestically, rather than relying on external entities to do so. 

In the past, countries would export raw materials, such as minerals or agricultural products, to be processed elsewhere, losing a significant portion of the potential value. 

Similarly, if nations allow external entities to handle and process their data, they risk missing out on the transformative benefits that AI can offer.

Data, in today’s digital age, is increasingly viewed as a vital resource — comparable to traditional resources like oil or minerals. Just as industrialisation brought value to countries by enabling them to process raw materials into valuable products domestically, developing AI capabilities requires similar investments in infrastructure and expertise.

This ensures that the value derived from data, such as new technologies and AI-driven innovations, stays within the country. By treating data as a strategic resource and focusing on developing AI in-house, nations can transform their raw data into valuable insights and applications that benefit their own economies.

Around the world, many governments are now focusing on this idea of retaining data sovereignty through domestic AI production. They are investing in building the necessary infrastructure, from hardware to skilled workforces, to create a robust AI ecosystem.

These efforts aim to develop the capacity to process their data locally, ensuring that they can fully capitalise on the economic and strategic opportunities that AI presents. 

By doing so, countries avoid exporting their “raw” data, instead transforming it domestically through their own AI “factories,” much like how they would process raw materials like minerals or oil to retain greater control over the resulting value.

Sovereign AI is part of the broader concept of digital sovereignty, which emphasises the importance of national control over digital technologies to ensure security, economic growth, and strategic resilience. 

It is not about isolating from global cooperation but building local capabilities to address unique challenges while preserving autonomy and independence.

Regulatory control is another critical factor, as governments aim to ensure AI safety, ethics, and accountability through tailored regulations. 

Ultimately, the pursuit of sovereign AI reflects a balance between national interests and international cooperation, as countries collaborate on AI initiatives and establish global partnerships to advance AI capabilities while protecting their sovereignty.

The AI factory

The concept of an AI factory, as discussed by NVIDIA CEO Jensen Huang, draws a parallel to the factories of past industrial revolutions, which transformed resources like water into electricity. 

In the current era, data centers serve as modern AI factories, where data and electricity are processed to create valuable “data tokens” that can be distributed globally. 

This shift signifies a new phase in industrial production, where the focus has moved from the generation of software to the creation of intelligence.

An AI factory functions by seamlessly integrating various technical components such as compute power, storage, and networking. This integration is designed to optimise the entire system for handling complex AI tasks. 

Unlike traditional software development, which involves creating static applications, an AI factory produces dynamic intelligence. This intelligence, in the form of adaptable tokens, can be applied across various types of data and contexts, making it versatile and potent.

Huang highlighted this evolution by stating that we have transitioned from manufacturing electricity to creating software and now, to manufacturing intelligence itself. 

This development emphasises the role of AI factories as the next step in technological advancement, positioning data centers as hubs for producing the intelligence that powers a wide range of digital applications.

How AI affects economies and international trade

Research from the McKinsey Global Institute explores the potential economic impact of AI by simulating how AI adoption might play out across countries, companies, and sectors.

The study first analyses the behaviour of firms and sectors to develop a bottom-up view of AI integration. It also considers the disruptions workers, companies, and countries might face during the transition to AI. 

The distribution of economic gains and losses could affect how well AI benefits are captured globally. Lastly, the research clusters countries with similar characteristics to provide a comprehensive global perspective.

Key findings include that AI has vast potential to drive global economic growth, and a major challenge is that AI adoption could widen inequalities between countries, companies, and workers. Early adopters will benefit because their earlier adoption will give them advantages that may be hard to compete with.

Various factors affect AI-driven productivity, including labour automation, innovation, and new competition. Both micro factors (like the speed of AI adoption) and macro factors (such as global interconnectedness and labour market structures) influence the overall impact of AI.

While AI could stimulate economic activity, the benefits are expected to be uneven. Developed nations, where wage levels are high and ageing populations limit GDP growth, are more likely to adopt AI rapidly, gaining a 20-25% boost in economic benefits.

In contrast, developing countries may only capture 5-15%, potentially widening the existing digital divide. Different countries will need tailored strategies for AI adoption to address this disparity.

Artificial intelligence (AI) is poised to significantly impact international trade by lowering barriers and enhancing efficiencies in areas such as data analytics and translation services. However, challenges remain, such as the need for global access to data to train AI systems.

AI could boost productivity growth, leading to stronger economic growth and new trade opportunities. AI is already improving global value chain (GVC) management by enhancing trend prediction, risk management, and operational efficiency. 

For example, businesses can use AI to optimise warehouse management, predict demand, and streamline manufacturing processes. AI is already driving international trade through digital platforms such as eBay. 

Small businesses are benefiting from AI-driven tools like machine translation, which has significantly increased cross-border trade, particularly in markets like Spanish-speaking Latin America.

AI could improve trade negotiations by analysing economic trajectories and predicting outcomes under various trade scenarios. Brazil has already implemented AI in its Intelligent Tech & Trade Initiative to enhance trade negotiation strategies.

In summary, while AI offers promising benefits to international trade, its impact may vary depending on how quickly economies adapt and address challenges such as data access and workforce skills.

Changing how we work

A recent IMF analysis explores the potential impact of artificial intelligence (AI) on the global labour market, revealing that nearly 40% of jobs worldwide are exposed to AI.

Historically, automation has primarily affected routine tasks, but AI has the capability to impact both low- and high-skilled jobs. 

This makes advanced economies more vulnerable to disruption, with about 60% of jobs in these regions potentially affected by AI. In these economies, half of the exposed jobs could benefit from AI by increasing productivity, while the other half might see reduced demand for human labour, potentially leading to lower wages or job losses.

In contrast, emerging markets and low-income countries face less immediate disruption from AI, with 40% and 26% of jobs exposed, respectively. However, the lack of infrastructure and skilled labour in these regions could hinder the ability to benefit from AI, potentially increasing inequality between nations.

AI and the sovereign state

AI is transforming the world, affecting economic, social, and political spheres, and reshaping the concept of state sovereignty. 

A study by Hazrat Usman and colleagues explores how AI challenges and reinforces state sovereignty. On one hand, AI-enabled technologies such as autonomous weapons and cyberattacks can bypass state borders and undermine traditional state authority, giving power to non-state actors. 

On the other hand, AI strengthens state control, especially through enhanced surveillance, border control, and immigration policies, allowing states to exert greater control over their territories and populations.

The rise of AI introduces new forms of power, especially through social media and online platforms, where non-state actors like corporations and even machines influence global affairs. 

5reAutonomous weapons pose a significant threat to sovereignty as they operate without human intervention, raising questions about states’ ability to control force and prevent conflicts. However, AI can also reinforce state sovereignty by improving efficiency in governance, enhancing public services, and regulating populations more effectively.

Policymakers face the challenge of harnessing AI for public good while mitigating risks like job displacement, privacy invasion, misinformation, and national security threats. 

Smart regional and national AI strategies are crucial to attracting talent, investment, and ensuring AI’s safe and ethical use. Regulations on accountability, privacy, and transparency, alongside workforce upskilling, will be essential to foster an AI-powered future that benefits all. 

The involvement of legal, ethical, and philosophical experts in shaping AI policies is critical to address its broader societal impacts and ensure that AI serves the greater good.

As countries recognize the dual-use nature of AI — its potential to drive economic growth and its risks to national security — they are actively developing their own AI infrastructures to boost competitiveness and protect their sovereignty. 

This concept of “Sovereign AI” reflects the need for nations to maintain control over AI development and its implications for governance.

A strategic roadmap for sovereign AI

The goal of AI sovereignty is to avoid reliance on foreign nations or corporations for critical AI technologies while still participating in global cooperation. It advocates for a balance between national control and international collaboration, recognising that global partnerships can be beneficial.

To develop sovereign AI, the World Economic Forum (WEF) recommends nations must focus on six strategic pillars: Digital Infrastructure, Workforce Development, Research, Development, and Innovation (RDI), Regulatory and Ethical Framework, Stimulating the AI Industry, and International Cooperation.

The path toward sovereign AI requires long-term, coordinated efforts to secure a competitive advantage in the global digital race while safeguarding national interests. This balanced approach promotes strategic resilience rather than isolationism, enabling countries to protect their autonomy while engaging in global AI development.

AI sovereignty is poised to become a central issue in international relations, raising questions about balancing national interests with global collaboration and shaping future AI governance.