Title: The United States, China, and AI Competition in Africa: Lessons for the Global South

Introduction

With its large youth population and abundant resources, Africa has become a crucial player in the ongoing U.S.-China AI competition. While Beijing has long prioritized AI expansion on the continent, private U.S. companies have increasingly relied on African labor and resources in their AI development. Recognizing AI’s transformative nature and its pivotal role in great power competition, the African Union has called for an “Africa-centric, development-oriented and inclusive approach” in its Continental AI Strategy.

While existing research has identified the benefits and risks of AI in Africa and the broader Global South, scholars have yet to explore how lessons from the former could benefit the latter. By comparing U.S. and Chinese AI initiatives in Africa and analyzing the diverse responses of African nations, this article draws insights from the continent’s evolving AI landscape to show how other regions of the Global South could harness great power competition to maximize benefits while minimizing associated risks.

Different Policy Approaches to AI Exports in Africa

In addressing competition with China, the second Trump Administration has prioritized innovation over safety, representing a significant departure from the Biden Administration’s previous approach. President Trump’s AI Executive Order seeks to “remove barriers to American leadership” by removing “unnecessarily burdensome requirements for companies.” The administration’s AI Action Plan and Genesis Mission focus on ways to “accelerate AI innovation,” “build American AI infrastructure,” and “lead in international AI diplomacy and security.” These goals coincide with the launch of Stargate—an initiative by OpenAI, Oracle, and Softbank to deploy $500 billion to expand AI infrastructure.

While U.S. government policy has focused on domestic AI development, efforts to export AI to the Global South remain limited. Instead, private companies have assumed a leading role through research and development (R&D) initiatives and open-source platforms in Africa. The map below highlights several significant AI R&D initiatives undertaken by major U.S. tech companies, including Google, IBM, and Nvidia.

Figure 1. Map illustrating examples of U.S. private sector AI initiatives in Africa.

In contrast, China’s AI strategy employs a top-down approach with two primary goals: strengthening domestic industries and exporting AI to the Global South. To strengthen domestic industries, China’s 2017 Next Generation AI Development Plan outlines its ambition to become a global AI leader by 2030. Since then, China has since employed a plethora of federal and provincial policy mechanisms across the AI tech stack. For example, Beijing designated 11 cities as major high-tech zones for the AI industry through its Zhongguancun initiative; state-led AI funds have invested heavily in select private sector players such as DeepSeek’s parent company, High-Flyer; and provincial governments such as Shanghai, Chongqing, and Qinghai have invested in specialized AI applications in financial services, the service industry, and environmental protection, respectively. Soon after the United States launched Stargate, the Bank of China announced its $138 billion AI Development Plan to bolster its AI supply chains.

Unlike the United States, China leverages established foreign policy roadmaps like the Belt and Road Initiative (BRI) and Digital Silk Road (DSR) to export its technology. Emphasizing “South-South cooperation,” China’s DSR offers a digital infrastructure investment package that includes 5G, payment architecture, and surveillance technologies to countries in the Global South. By March 2025, 52 African countries and the African Union had signed agreements with China, resulting in more than $700 billion in Chinese engineering deals in the past decade. State-led initiatives, like the Forum on China-Africa Cooperation (FOCAC), Chinese universities, and private sector players, have further expanded China’s footprint on the continent.

Overall, the United States’ focus on domestic policy and corporate activity and China’s focus on state strategy and infrastructure have presented unique opportunities and risks for African countries.

Dual Engagement with the United States and China in Agriculture

Across Africa, a small group of countries—Mauritius, South Africa, Nigeria, Rwanda, Kenya, and Egypt—lead in AI preparedness, adoption, and entrepreneurship, consequently attracting a disproportionate amount of U.S. and Chinese AI investment. Agriculture, a sector central to economic development, offers a clear window into how these states navigate external partnerships. By tracing select U.S. and Chinese AI partnerships across state-level, private sector, and higher education projects, we observe that these countries employ a “mix and match” technique to maximize mutual benefits.

U.S. capital investments and research partnerships have fostered a burgeoning agricultural startup ecosystem in Kenya and South Africa. For example, in Kenya, Plantvillage Nuru, developed by researchers at Penn State University, helps farmers diagnose diseases and infections in crops such as Cassava. In Kenya, IBM employs geospatial AI technologies to support reforestation projects. Through Nvidia’s Inception Program, which supports AI local startups by offering technical and financial support, South Africa’s Aerobotics provides AI solutions for crop monitoring, irrigation management, and pest and disease management.

Chinese engagements, in contrast, are most mature in state-led and higher education partnerships, though private sector activity has also accelerated. At the 2024 FOCAC Summit, China and Africa announced a plan to undertake 20 digital infrastructure projects between 2025 and 2027, many of which have agricultural applications. Several Chinese and African universities, such as China Agricultural University, Fujian Agriculture and Forestry University, and Cairo University, have also partnered to develop AI solutions for pest and disease detection. Meanwhile, private sector initiatives such as DeepSeek have advertised their potential to modernize agriculture, and genomics company BGI Group spoke in Nairobi about using AI to digitize seed systems.

Together, these examples demonstrate how African governments selectively engage with U.S. and Chinese partners across different layers of the agricultural sector to leverage strengths from both sides. Specifically, they have drawn on U.S. startup ecosystems and technical innovation while leveraging Chinese infrastructure, training, and applied research.

Extant Challenges and Risks

While the dual-engagement strategy has enabled African countries to leverage complementary strengths from both U.S. and Chinese AI initiatives, the same competitive dynamics that create these opportunities also generate significant risks. The race between the United States and China for AI dominance extends three critical vulnerabilities across the entire Global South: labor exploitation, data colonialism, and digital authoritarianism.

Competition, particularly between U.S. companies racing towards building artificial general intelligence, could entrench exploitative labor practices in the Global South through a race to the bottom for cheap labor. U.S. AI companies already use Global South laborers for the important “janitorial” role of data labeling, sometimes to the detriment of these laborers. In addition to OpenAI, which previously employed Kenyan workers to label traumatizing content like child sexual abuse, bestiality, and murder to develop its ChatGPT safety system, other U.S. AI firms like Samasource, Scale AI, and Mighty AI have also adopted this lucrative business model. For African nations with large youth labor forces, reliance on data-cleaning jobs could trap individuals in “low-skills” jobs and cause widespread psychological harm.

Second, the Trump Administration’s prioritization of innovation at the expense of safety risks further practices of data colonialism. U.S. and Chinese reliance on Global North data in AI training can lead to algorithmic bias, discrimination, and models that perform worse when applied to the Global South. The underrepresentation of Global South demographics in data-driven AI healthcare solutions can also lead to more inaccurate diagnoses and ineffective treatments, making these technologies potentially dangerous.

Finally, competition may enable China to disseminate digital authoritarianism further. Notably, Deepseek’s rise could amplify Chinese propaganda and normalize censorship, as the chatbot avoids politically sensitive topics such as the 1989 Tiananmen Square protests and Uyghur repression. Lower media literacy rates and weaker data protection regulations also make AI-generated misinformation more potent in the Global South. Instances of AI-generated content distorting public opinion have been reported in Burkina Faso, South Africa, Rwanda, and the Congo, though this risk is not limited to Africa. AI’s role in abetting authoritarian practices is further exemplified by reported uses of AI-powered surveillance systems by autocratic governments to monitor citizens illegally.

Policy in Practice and the Broader Lessons for the Global South

The present-day African AI landscape offers two overarching policy lessons for the wider Global South.

First, African frontrunners demonstrate the value of early articulation of national AI strategies that establish investment-friendly policies, establish predictable regulatory frameworks early, and detail clear regulations to address associated AI risks. For example, Mauritius first detailed its AI Strategy in 2018 and has since been ranked highest within sub-Saharan Africa for AI readiness according to the Oxford Insights Government AI Readiness Index 2024. South Africa’s National AI Policy Framework details a commitment to talent and digital infrastructure development—two pillars that were addressed by Microsoft’s $285 million investment in the country. Detailed policy frameworks that delineate sectoral priorities and key areas of focus provide clear pathways for the United States and China and expand their AI footprint through investments. These policy frameworks should also include data governance frameworks to mitigate risks, but they should resist the exclusive adoption of U.S. or Chinese AI regulation.

Second, these countries highlight how deliberate hedging strategies can harness both U.S. and Chinese strengths while mitigating the extant challenges and risks associated with AI competition. Kenyan startups, for instance, have attracted U.S. capital and research partnerships, including engagement with Nvidia, to build a dynamic AI-driven innovation ecosystem. At the same time, African governments have leveraged China’s “South–South cooperation” narrative to secure increased digital infrastructure investments and sovereign-led R&D collaborations in agriculture, fintech, and health. For the broader Global South, this dual-track approach requires a sophisticated understanding of the risks on both sides. Given the policy volatility of the current U.S. administration, countries should avoid over-reliance on U.S. capital and diversify funding sources where possible. Likewise, when working with China—whose data-governance practices remain weaker—countries should anchor negotiations in strong data-protection rules, localization requirements, and explicit AI-risk-management provisions. Embedding these safeguards at the outset enables Global South governments to retain strategic agency while navigating great-power competition.

Taken together, Africa’s experience underscores a powerful lesson for the Global South: agency comes from preparation and diversification. Countries that articulate their own AI priorities early and engage both U.S. and Chinese actors on their own terms are best positioned to harness the benefits of AI competition while mitigating the associated risks.

. . .

Alice Chen is a current analyst at Kobre & Kim LLP, a law firm focused on cross-border disputes and investigations. She was previously a Fritz Fellow at Georgetown University’s Tech & Society, where she researched the implications of AI for the Global South. She also has experience working in national security, government relations, and public policy within both the private and public sectors. Alice received her B.S. in Foreign Service at Georgetown University’s Walsh School of Foreign Service, where she specialized in International Economics.

Neel U. Sukhatme is the David A. Breach Dean of Law and Professor of Law at the University of Michigan Law School. Previously, he served as the Associate Dean for Research and Academic Programs, the Anne Fleming Research Professor, and a Professor of Law at Georgetown University Law Center. Neel received his Ph.D. in Economics from Princeton University and his J.D. from Harvard Law School. He received his B.S. in Computer Engineering from the University of Illinois and frequently writes on issues related to law and technology.

Image Credit: Sdkb, CC BY-SA 4.0, via Wikimedia Commons