1. Introduction
For most of human history, societies that mastered the defining technologies of their age often gained significant advantages over those that did not. Agricultural innovations supported larger populations and more complex institutions. Maritime technologies expanded trade and influence across continents. Industrialization transformed production and wealth creation. More recently, the Information Age reshaped economies through digital networks, data, and communication systems.
History reveals a recurring pattern: technology does not simply transform economies; it reshapes the distribution of power between societies. Importantly, societies do not need to be at the centre of a technological revolution to be affected by it. Many regions that played little role in the development of maritime, industrial, or digital technologies nevertheless experienced profound economic and political consequences as a result. Technological revolutions often redraw the rules of competition for everyone.
The world is already living through another such transformation. According to McKinsey Global Institute (2023) and the Stanford AI Index (2025), AI is increasingly being integrated into business operations, production systems, logistics, research, and decision-making. Unlike many previous technologies, AI has the potential to augment not only physical labour but also aspects of human cognition, allowing intelligence itself to be deployed at unprecedented scale.
The implications extend far beyond technology. Like the revolutions that preceded it, AI is likely to favour those with the capital, infrastructure, data, research capacity, and institutions necessary to develop and deploy it effectively
For Africa, the challenge is not simply whether the continent adopts AI, but whether African enterprises will possess the capabilities necessary to compete in an economy where intelligence is becoming an increasingly important source of value creation and competitive advantage.
To understand what this transformation may mean for African enterprise, it is first necessary to examine a lesson history has repeatedly demonstrated: technological revolutions reshape not only economies, but the distribution of power itself.
2. Technology and the Rise of Civilizations
Power has rarely remained with a single civilization for long. Throughout history, dominance shifted between societies such as Ancient Egypt, Mesopotamia, China, Greece, Rome, and the Islamic Caliphates. Mokyr (1990) argues that technological advantage has been a recurring factor in the rise of many of history's most influential civilizations.
One of the earliest examples emerged with the agricultural revolution. As communities transitioned from hunting and gathering to organized agriculture, societies capable of producing reliable food surpluses gained significant advantages. Along the Nile, agricultural systems supported the growth of Ancient Egypt. In Mesopotamia, irrigation enabled some of the world's earliest urban settlements (see Figure 2).
The consequences extended far beyond food production. Agricultural surpluses supported larger populations, specialized occupations, and more complex systems of governance. What began as an agricultural advantage gradually evolved into an economic, political, and military one, a relationship highlighted by Diamond (1997).
Technological superiority did not necessarily make a civilization more enlightened, morally advanced, or culturally sophisticated, but it often made it more capable of producing wealth, organizing society, defending territory, and expanding influence (Acemoglu & Johnson, 2023).
Across different regions and eras, technological advantage repeatedly translated into economic and political influence, a pattern that continues to shape global competition today (Mokyr, 1990).
3. Navigation, Empire, and the Globalization of Power
Before oceans became highways of commerce and empire, geography largely determined the limits of power. Mountains, deserts, forests, and oceans constrained the reach of kingdoms and empires, allowing many societies to develop largely independent of one another (Diamond, 1997; Morris, 2010). This began to change as advances in shipbuilding, navigation, cartography, and astronomy transformed the oceans from barriers into pathways. For the first time, civilizations could move people, goods, information, and military power across vast distances with increasing efficiency.
Long before European expansion, maritime technologies were already reshaping regional influence. Between roughly 1200 BCE and 300 BCE, the Phoenicians established extensive trading networks across the Mediterranean.
From the seventh to the fifteenth centuries, Arab merchants connected Africa, Asia, and Europe through commercial routes that facilitated the exchange of goods, ideas, and technologies. In the early fifteenth century, the voyages of Zheng He demonstrated the remarkable maritime capabilities and influence of Ming China across the Indian Ocean.
Portugal pioneered long-distance oceanic exploration, while Britain later combined naval superiority, commerce, and industrial capacity to build one of history's largest empires. Maritime technology had expanded the reach of economic and political influence beyond anything previously possible (see Figure 3).
Control of maritime networks generated wealth, and wealth financed further expansion, creating a self-reinforcing cycle of technological and economic advantage. For some societies, this brought prosperity. For others, it facilitated conquest, slavery, resource extraction, and colonial rule on an unprecedented scale, reinforcing what McNeill (2009) describes as the far-reaching influence of maritime power.
Perhaps the most important lesson from this period is that societies did not need to be at the centre of maritime innovation to be affected by it. Many regions that played little role in developing these technologies nevertheless experienced profound economic, political, and social consequences.
From this point onward, geographical distance ceased to provide the protection it once had against the far-reaching effects of technological change.
4. Industry, Information, and the Acceleration of Global Power
If maritime technology connected the world, industrial technology transformed it.Beginning in Britain during the eighteenth century, advances in mechanized production, steam power, and transportation fundamentally changed how economies functioned. Goods could be produced faster, transported farther, and sold more efficiently than ever before (see Figure 4)
Economic power increasingly depended not only on industrial production but also on ownership of digital infrastructure, software platforms, communication networks, and information systems. As Castells (2011) argues, this marked the emergence of a network society in which information flows became a major source of economic and political power.
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| Figure 5. Visualization of global undersea fiber-optic cable networks, illustrating how digital infrastructure concentrates information flows, economic power, and geopolitical influence within a few continental corridors. Image Credit: Ben Pollock, Submarine Cable Networks (2017) |
5. The Intelligence Revolution
Artificial intelligence belongs to a long line of the transformative technologies that have expanded human capability throughout history. What separates artificial intelligence from many earlier technological revolutions is not its scale, but the nature of the capability it amplifies. While many previous technologies amplified human physical capabilities, AI increasingly amplifies cognitive capabilities.For centuries, intelligence remained one of humanity's most important constraints. Every government, enterprise, and institution depended on human beings to process information, interpret situations, and make decisions. While knowledge could be accumulated, intelligence itself could not easily be scaled.
AI is beginning to change that reality. Many forms of analysis, prediction, communication, and problem-solving can now be performed faster, cheaper, and more consistently than before. Intelligence is increasingly becoming a resource that can be deployed at scale, extending capabilities that were once constrained by the availability of human expertise, as observed by Brynjolfsson and McAfee (2014) .What makes this development particularly significant is that AI is not merely another digital tool. Like agriculture, steam power, electricity, and the internet before it, Trajtenberg (2018) describes AI as a general-purpose technology with applications across almost every sector of society. It is already influencing healthcare, finance, warfare, manufacturing, transportation, education, scientific research, and business operations. As a result, AI is not simply creating new industries; it is transforming existing ones.The countries and private organisations leading this transformation are investing heavily in advancing it. According to the Stanford AI Index Report (2026), AI development is increasingly driven by substantial investments in computing resources, data centres, research, and specialized talent. As illustrated in Figure 6, these computing resources are concentrated in a relatively small number of countries, highlighting the unequal global distribution of the physical infrastructure that underpins the AI economy.
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| Figure 6. Featured in the Stanford University 2026 AI Index report using Cloudscene data, the "Global Distribution of Data Centers, 2025" map exemplifies how the network society concentrates compute capacity. The visualization highlights how physical compute infrastructure is intensely concentrated within North American and Western European corridors. Image Credit: Stanford University AI Index report (2026) |
Just like in previous technological revolutions, those who develop and control the foundational technologies are likely to acquire significant economic and strategic advantages.
6. When Intelligence Becomes Infrastructure
Artificial intelligence is often viewed as a tool, comparable to a search engine or advanced software application. While useful, these comparisons may underestimate its significance. The growing integration of AI into economic systems suggests that it is becoming less a standalone technology and more a foundational layer of modern infrastructure, a development noted by Brynjolfsson and McAfee (2017).Throughout history, technologies such as roads, electricity, and the internet evolved from innovations into essential infrastructure.Artificial intelligence appears to be following a similar path. Today, AI is already embedded in search engines, navigation systems, financial platforms, logistics networks, cybersecurity systems, and customer service operations. In many cases, people interact with AI daily without even realizing it.
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| Figure 7. An illustration of Artificial Intelligence operating as an invisible, foundational infrastructure—seamlessly embedded directly into daily digital interactions, processing complex data behind the scenes across search, logistics, and financial systems without the user even realizing it. Image Credit: unssc.org
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A particularly important development is the emergence of AI agents. Unlike traditional software that performs predefined tasks, AI agents are increasingly capable of interpreting goals, making decisions, coordinating activities, and executing complex workflows with limited human intervention. In effect, intelligence becomes embedded within the infrastructure of the enterprise
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| Figure 8. AI agents coordinating software development and workflow automation, illustrating how artificial intelligence is becoming embedded within enterprise operations. Image Credit: ChatGPT, modified by the author.
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Historically, economic growth required larger workforces and increasingly complex management structures. Organizational intelligence was constrained by the availability of skilled human labour. AI is changing that reality by enabling certain forms of intelligence to be deployed at a scale beyond what human labour alone can provide.The result is not merely automation, but the emergence of intelligent enterprises. Businesses that successfully integrate AI into their operations can become more productive, responsive, and efficient than those that do not. As with previous technological revolutions, early adopters are likely to gain significant advantages over those that fall behind (Perez, 2002). The implications extend beyond individual firms. As intelligence becomes embedded in digital infrastructure, access to advanced AI capabilities is emerging as an increasingly important source of competitive advantage.
7. The Transformation of Economic Power
For centuries, competitive advantage depended mainly on a combination of labour, capital, natural resources, and geography. These factors remain important, but AI is beginning to alter their relative significance. The ability to deploy intelligence at scale across analysis, forecasting, logistics, automation, and decision-making is transforming how organizations compete. A small firm equipped with advanced AI tools may perform functions that once required much larger teams, while large corporations can use AI to strengthen existing advantages.
History suggests that such transitions often concentrate power before they distribute it. During the Industrial Revolution, nations that industrialized first gained significant advantages over those that industrialized later. During the Information Age, a relatively small number of companies came to dominate digital platforms, cloud infrastructure, and global data networks.
Similar asymmetries are now visible in artificial intelligence, where leadership remains concentrated among organizations with access to vast datasets, computing resources, research ecosystems, and capital.
The implications of AI extend beyond the digital realm. Advances in robotics, computer vision, sensors, and autonomous systems are enabling intelligent machines to perform an increasing range of physical tasks. The significance of this development should not be underestimated.
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| Figure 9. EVST Modern embodied AI systems in a manufacturing facility, showcasing a humanoid robot for industrial operations, a dexterous robotic hand for precision manipulation and data collection, and a quadruped robot for autonomous inspection and monitoring in complex environments. Image Credit: evsint.com
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Many previous waves of automation primarily affected routine or repetitive tasks. The merging of AI and robotics has the potential to challenge both cognitive and physical forms of work (Ford, 2021).
AI is reducing many of the barriers that once limited competition across borders. Translation systems reduce language constraints. AI-powered analytics provide deep insights into consumer behaviour. Intelligent customer service systems can operate continuously across multiple markets. As Baldwin (2016) notes, digital technologies increasingly enable firms to operate across borders with fewer geographic and organizational constraints.
Advances in robotics and embodied AI are also reducing dependence on local labour for certain operational, manufacturing, logistics, and service functions (see Figure 10). Increasingly, firms can enter distant markets with fewer physical, organizational, and labour-related constraints than in previous eras, a trend that Ford (2021) argues is likely to accelerate as intelligent systems become more capable.
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| Figure 10. (a) Shows the RealBOT Embodied Open Platform developed by RealMan Robotics. A technician uses an external motion-tracking rig to physically guide the wheeled humanoid robot through a folding task, generating real-world training data (b) End-to-end neural network learning to operate a Keurig coffee machine solely by observing approximately 10 hours of human demonstration videos. Image Credit: newsghana.com.gh
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This development carries an important implication. Just as maritime technologies enabled powers to project influence across oceans, AI may enable firms to project economic influence across borders with unprecedented efficiency. Geography remains important, but it will become less protective than it once was.
Competition in the twenty-first century may therefore be defined increasingly by access to intelligence itself, whether through software, algorithms, data systems, or intelligent machines.
8. African Enterprise at a Crossroads
Artificial intelligence is emerging at a pivotal moment in Africa's economic development. The continent is home to one of the world's youngest and fastestgrowing populations (see Figure 11). Its cities are expanding rapidly, entrepreneurship is increasing, and digital technologies have already transformed sectors such as finance, commerce, communication, and transportation. Across Africa, a new generation of businesses is emerging to address local challenges and participate in global markets.
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| Figure 11. Global median age distribution showing Africa as the world's youngest continent, highlighting its demographic significance and long-term economic potential. Image Credit: Credit: boydinstitute.org
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Many African economies still remain in the process of industrialization. According to the World Bank (2023), small and medium-sized enterprises continue to form the backbone of economic activity, while sectors such as agriculture, manufacturing, construction, transportation, and services remain critical sources of employment and income.
This context makes the rise of artificial intelligence particularly significant for many African countries and raises important questions about the continent's future development pathway. For decades, industrialization and labour-intensive sectors provided pathways for employment creation, productivity growth, and economic transformation. The possibility that intelligent systems may alter these traditional development pathways is a concern emphasized by UNCTAD (2025).
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| Figure 12. Small and medium-sized enterprises (SMEs) and labour-intensive sectors that continue to underpin employment, entrepreneurship, and economic activity across much of Africa. Image Credit: ellegagne.com
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AI is weakening many of the traditional barriers that once limited foreign competition in African markets. The challenge, therefore, is not simply technological adoption but also ensuring that African enterprises remain active participants in the value created by the intelligence revolution rather than becoming passive consumers of technologies, platforms, and services developed elsewhere.
Whether this transition becomes a source of empowerment or dependency will depend largely on who develops the capabilities, controls the systems, and captures the value created by artificial intelligence.
9. The Risk of a New Form of Digital Imperialism
As intelligent systems reduce the importance of distance, language, and operational complexity, the foundations of competition are changing. It is within this changing landscape that a new risk of digital imperialism emerges.
Although Kwet's (2019) concept of digital imperialism shifts attention from the control of territory to the control of technology, artificial intelligence may represent a new phase in which technological control increasingly translates into economic influence across territories, enabling foreign enterprises to dominate strategic sectors without exercising formal political control.
Whereas earlier forms of digital imperialism centered primarily on platforms, software, data, and digital infrastructure, artificial intelligence extends these capabilities by enabling firms to automate decision-making, coordinate complex operations, and increasingly participate in physical industries through robotics and embodied AI. The result is not simply greater digital influence, but the possibility of deeper economic penetration into sectors that were previously constrained by geography, labour, and physical presence.
The issue is not that foreign companies operate in African markets. Competition, trade, and investment have long been important drivers of economic development. Rather, artificial intelligence may fundamentally alter the conditions under which this competition takes place.
This concern is not emerging in a vacuum. Across much of Africa, many of the largest and most profitable sectors of the economy are already characterized by significant foreign participation. Telecommunications markets are often led by companies such as MTN Group, Orange, and Vodacom.
The extraction of strategic resources such as gold, copper, cobalt, and other minerals frequently involves multinational firms such as Glencore and Barrick Gold. Consumer markets across the continent are heavily influenced by global brands including Nestlé and Unilever (see Figure 13).
The digital economy displays a similar pattern. According to UNCTAD (2025), much of the world's digital infrastructure and platform economy is concentrated among a small number of global technology firms, including Microsoft, Google, Amazon, Meta, Apple, and OpenAI. As a result, millions of African individuals, businesses, universities, and governments already depend on technologies developed and controlled outside the continent.
Foreign investment and technology transfer have undoubtedly contributed to economic growth, employment, connectivity, and innovation. However, they also highlight a recurring challenge: local enterprises often compete against organizations possessing greater capital, stronger technological capabilities, larger networks, and easier access to global markets.
This asymmetry may become more pronounced in the age of artificial intelligence, a pattern consistent with the historical relationship between technology and power examined by Acemoglu and Johnson (2023).
Now, foreign firms located thousands of kilometres away can analyze local markets, communicate across languages, automate operations, and coordinate business activities with unprecedented efficiency. Combined with robotics and other forms of embodied AI, they may extend their economic reach into foreign markets with fewer constraints than ever before.
The result is a new form of competitive imbalance. Local enterprises may increasingly compete against firms with superior data, computing infrastructure, research capacity, automation systems, and AI capabilities.
In such an environment, the challenge will not merely be keeping pace with technological change but remaining competitive long enough to adapt to it. If AI enables technologically advanced firms to overcome many of the barriers that once limited foreign competition on the continent, local enterprises may face pressures unlike any they have encountered before. The risk is not simply that foreign companies gain market share. The risk is that domestic industries are displaced before they have the opportunity to mature, innovate, and become globally competitive.
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| Figure 14. Conceptual illustration of multinational corporations leveraging artificial intelligence to coordinate strategic expansion into African markets, strengthen their competitive position, and extend their influence into sectors that were previously more difficult to enter due to geographical, operational, and labour-related constraints. ChatGPT, modified by the author.
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This possibility should not be mistaken for inevitability. Technological revolutions do not determine outcomes on their own. Policies, institutions, and strategic decisions remain critical in shaping who benefits from technological change and the conditions under which competition occurs.
10. Africa's Structural Disadvantages in the Age of AI
Technological revolutions create opportunities, but those opportunities are rarely distributed equally. Throughout history, societies have entered technological transitions from different starting positions. Some possessed the resources, institutions, infrastructure, and expertise necessary to capitalize on emerging technologies. Others were forced to adapt to systems largely designed and controlled elsewhere.
The age of artificial intelligence is unlikely to be different. While AI has the potential to unlock enormous opportunities across Africa, it also threatens to expose and amplify a series of structural disadvantages that already exist across the continent. Understanding these disadvantages is essential because they explain why African enterprises may require time to compete on equal terms in the age of artificial intelligence. They also demonstrate why unrestricted competition may produce outcomes very different from those predicted by conventional free-market theory.
Among the most significant structural disadvantages facing Africa in the age of artificial intelligence are:
a. Capital
The scale of investment flowing into artificial intelligence highlights the growing importance of capital in the AI economy. According to the Stanford AI Index Report (2025), leading AI firms are investing billions of dollars in computing infrastructure, research, data acquisition, talent, and model development, with some individual projects exceeding the annual budgets of many African institutions. By contrast, many African enterprises continue to face limited access to financing, affordable credit, and growth capital. Although entrepreneurial activity is increasing across the continent, limited financial resources constrain the ability of firms to develop, adopt, and scale AI technologies. As a result, many African enterprises may struggle to develop, adopt, and scale AI technologies at the pace required to remain competitive.
b. Computing Infrastructure
Unlike previous digital technologies, modern AI systems require vast computational resources. Data centres, cloud infrastructure, advanced processors, and high-speed connectivity have become foundational to AI development and deployment. The Stanford AI Index Report (2025) and UNCTAD (2025) highlight the concentration of this infrastructure within a relatively small number of countries and corporations (see Figure 6). Consequently, many African enterprises rely on infrastructure they neither own nor control, increasing their dependence on external providers for critical AI capabilities.
c. Research Capacity.
The organisations leading the AI revolution have spent decades building strong universities, research institutions, engineering ecosystems, and innovation networks. According to the Stanford AI Index Report (2025), these investments have enabled them to produce much of the world's AI research, attract leading talent, and shape the direction of the technology. By contrast, the UNESCO Science Report (2021) notes that Africa's research ecosystems remain comparatively underfunded and underresourced, limiting the continent's ability to contribute to AI innovation and increasing its reliance on technologies developed elsewhere
d. Data
In the Industrial Age, oil was one of the world's most strategic resources. In the AI Age, data is rapidly assuming a similar role. UNCTAD (2025) emphasizes the growing importance of large datasets as a source of competitive advantage in the development and commercialization of advanced AI systems. Although African businesses generate valuable data every day, much of the infrastructure used to collect, process, and monetize it is owned by external platforms. This limits Africa's ability to capture the economic value of its own data while strengthening the competitive position of external AI platforms.
e. Industrial Capacity
As discussed earlier, the rise of embodied AI is extending artificial intelligence into the physical economy. Ford (2021) notes that robotics, autonomous vehicles, intelligent manufacturing systems, drones, and smart construction equipment are rapidly moving toward widespread commercial deployment. The countries leading these developments already possess strong manufacturing bases, reliable energy systems, advanced supply chains, engineering expertise, and industrial ecosystems. Together, these capabilities place them in a stronger position to develop and deploy the next generation of AI-powered technologies, potentially leaving African enterprises increasingly dependent on imported AI-enabled products rather than participating in their design, manufacture, and commercialization.
f. Market Power
The concentration of AI leadership among some of the world's largest and most valuable corporations reflects a broader pattern identified by Acemoglu and Johnson (2023). These firms combine established global brands, vast customer networks, extensive distribution systems, substantial financial resources, and access to cuttingedge technologies. Such advantages allow them to deploy AI at a scale that many smaller enterprises, particularly in developing economies, may struggle to match. This may leave African enterprises increasingly dependent on imported AI-enabled products and technologies rather than participating in their design and manufacture.
g. regulatory preparedness.
Technological revolutions often move faster than institutions. According Stanford AI Index Report (2024), the rapid advancement of artificial intelligence has created governance challenges that many governments are still working to address, particularly in areas such as digital infrastructure, data protection, competition policy, labour markets, and technological sovereignty. Meanwhile, the technology continues to advance. This creates a situation in which markets may be transformed before regulatory frameworks are fully prepared to respond.
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| Figure 15. Global distribution of AI-related legislative activity by country (2016–2024), illustrating disparities in AI regulatory preparedness and comparatively lower legislative activity across much of Africa. Image Credit: Stanford University AI Index Report (2025)
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This does not mean failure is inevitable. Nor does it imply that African enterprises cannot compete. However, it does suggest that the continent faces a fundamentally different challenge than many previous technological transitions.
The Global AI Summit on Africa held in Kigali represented an important step in shaping the continent's approach to artificial intelligence. Discussions focused heavily on digital sovereignty, AI governance, talent development, local innovation ecosystems, data governance, infrastructure investment, and ensuring that Africa participates meaningfully in the emerging AI economy. These priorities reflect a growing recognition that Africa must build its own technological capabilities rather than rely solely on systems developed elsewhere (Global AI Summit on Africa, 2025).
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| Figure 16. The Global AI Summit on Africa held in Kigali, Rwanda (2025), bringing together policymakers, industry leaders, researchers, and innovators to advance continental discussions on AI governance, innovation, and Africa's technological future. Image Credit: techreviewafrica.com.
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While the summit emphasized innovation and AI adoption, it did not directly confront the possibility that technologically superior foreign firms could use AI to expand into African markets with unprecedented efficiency, potentially outcompeting local enterprises before they develop comparable capabilities. This leaves an important policy question unresolved: how can Africa encourage innovation and openness while ensuring domestic enterprises retain a meaningful opportunity to survive, adapt, and compete?
11. Protecting African Enterprise from Digital Imperialism
History offers little evidence that technological isolation leads to long-term prosperity. Societies that successfully navigate technological revolutions are rarely those that reject change. More often, they are those that create the conditions necessary to benefit from it (Perez, 2002).
The challenge is not whether Africa should embrace AI, but how it can do so without allowing African enterprise to be overwhelmed during the transition. This distinction is crucial. As Chang (2002) argues, many of today's advanced economies protected and nurtured strategic industries during their own periods of technological transformation.
Britain, the United States, Germany, Japan, South Korea, and China all used varying combinations of industrial policy, strategic protection, and state support during critical stages of their technological and industrial development.
None of these countries developed under conditions of unrestricted competition from more advanced rivals. They were given time to learn, adapt, build, and compete. Africa deserves the same opportunity.
Indeed, debates about protecting strategic industries are not confined to developing economies. In recent years, the United States has adopted a range of measures aimed at strengthening domestic manufacturing, securing critical supply chains, promoting American AI leadership, and reducing dependence on foreign competitors. The rationale behind many of these measures is outlined by the Office of the United States Trade Representative (2025), which emphasizes the protection of American workers, industries, technological leadership, and national competitiveness.
Another factor that may intensify pressure on African enterprises is the growing attractiveness of African markets in an increasingly AI-driven global economy. As Baldwin (2016) observes, many firms in North America, Europe, and parts of Asia already operate in highly competitive and relatively mature markets where opportunities for rapid expansion are becoming more limited. By contrast, the African Development Bank (2024) highlights Africa's rapidly growing population, expanding urban centres, rising digital connectivity, and significant unmet demand across numerous sectors.
As artificial intelligence reduces the costs of market research, localization, customer acquisition, administration, and service delivery, firms can increasingly expand into foreign markets with greater speed and efficiency than was previously possible.
For many companies, future growth may depend less on competing for marginal gains in saturated markets and more on capturing opportunities in emerging ones. This may make Africa an increasingly important destination for foreign enterprises seeking new customers, new data, and new sources of growth. While such investment can bring significant benefits, UNCTAD (2025) highlights that it may also intensify competitive pressures on disadvantaged firms that are still building the capabilities needed to compete in the intelligence economy.
As AI discussions continue through initiatives such as the Global AI Summit on Africa in Kigali and forthcoming summits in Ghana and South Africa, greater attention should be given not only to AI adoption but also to the policies needed to strengthen African enterprise and long-term economic competitiveness.
Building AI capabilities remains essential, but so too is ensuring that African enterprises can participate meaningfully in the markets that AI will help shape.
Achieving this objective will require a coordinated set of policies aimed at strengthening the competitiveness, resilience, and long-term growth of African enterprises in the age of AI.
a. Domestic Enterprise:
African enterprises can participate meaningfully in the markets AI will shape. Governments may therefore encourage firms benefiting from African markets to contribute to local development through employment, skills transfer, technology partnerships, research collaboration, local procurement, and investment in domestic innovation ecosystems.
b. Labour and Automation:
AI should improve productivity without weakening employment opportunities. As Ford (2021) argues, advances in AI and automation may challenge traditional patterns of job creation, making it important to balance technological progress with employment in economies where large youth populations continue to enter the labour market.
c. Digital Taxation:
Taxation will also become increasingly important. Foreign firms generating substantial value from African markets while employing relatively few local workers should contribute fairly to the economies from which that value is derived. Traditional tax frameworks were designed for a world in which economic activity was closely tied to physical presence. The age of AI may require new approaches that reflect the realities of digital and automated enterprise.
d. Capability Building:
Revenues from such mechanisms should be reinvested in Africa's competitive capabilities. Strategic investment in AI research, digital infrastructure, cloud computing, data centres, entrepreneurship, universities, technical education, and local technology enterprises can strengthen the continent's capacity to innovate and compete (Mazzucato, 2013).
e. Strategic Sectors:
Particular attention should be given to industries likely to shape future competitiveness, including AI, cloud infrastructure, robotics, advanced manufacturing, cybersecurity, digital platforms, and semiconductors. Like railways, steel, electricity, and telecommunications in earlier eras, these technologies are likely to underpin future economic development.
Perhaps most importantly, Africa must recognize that time itself is a strategic resource. The continent does not need to become a global leader in artificial intelligence overnight. What it needs is sufficient space to build capabilities before competition becomes overwhelming. The objective should be gradual integration rather than immediate exposure; learning rather than dependency; capability building rather than passive consumption.
Protecting African enterprise is not about resisting the future. It is about ensuring that Africa has a place within it. For the first time in centuries, the continent finds itself at the early stages of a technological revolution whose final shape has not yet been determined. The decisions made today may influence Africa's economic trajectory for generations to come.
12. Conclusion
Artificial intelligence may become one of the most transformative technologies in human history. Like the technological revolutions that came before it, it will influence how economies compete, how value is created, and how power is distributed.
Africa enters this transition with immense potential, but also with a number of structural disadvantages that could make adaptation more difficult. The long-term success of African enterprise will depend not only on access to artificial intelligence, but also on the ability to build the capabilities, infrastructure, institutions, and competitive firms necessary to thrive in an increasingly intelligence-driven economy.
The risk of digital imperialism is therefore not about technology itself. It is about dependency. It is about a future in which intelligence is increasingly controlled elsewhere while African enterprises struggle to participate in the value it creates.
The age of artificial intelligence is still unfolding, and the decisions made today will help determine who benefits from it tomorrow.
If Africa is to avoid becoming merely an exploitable market for foreign intelligence systems and a consumer of value created elsewhere, it must create the conditions for its own enterprises to survive, adapt, and compete.
Protecting African enterprise is not about resisting technological change. It is about ensuring that African businesses have the time, space, and support necessary to develop the capabilities required to compete in the intelligence economy.
The future of African enterprise will not be determined by artificial intelligence alone. It will be determined by the choices made in response to it.
