Artificial intelligence holds the potential to transform economies globally, yet the extent to which developing nations will reap benefits or lag behind hinges on today’s decisions. The African Union’s landmark Continental AI Strategy, adopted in July 2024, embodies both ambitious goals and stark realities. While AI could contribute $1.5 trillion to Africa’s GDP by 2030, the continent currently accounts for a mere one percent of global AI compute capacity, despite hosting 15 percent of the world’s population. This contradiction underscores the key challenge for underdeveloped nations, especially in Africa and South America, as they navigate the AI landscape. With global AI investments hitting $100-130 billion annually, African AI startups have garnered only $803 million over five years.
The critical question is not whether AI is essential for development but whether these regions can tap into its transformative power before opportunities diminish. The stakes are exceedingly high. The mobile revolution that empowered Kenya’s M-Pesa to serve millions without traditional banking now presents a model for AI advancement. However, unlike mobile technology, AI demands substantial computational resources, consistent electricity, and specialized skills that are still lacking in many areas of the Global South. Africa is beginning to recognize AI’s strategic significance. The growing momentum across the continent challenges the notion of AI’s relevance in developing economies.
Sixteen African nations are now developing national AI strategies or policies, with Kenya unveiling its comprehensive strategy for 2025-2030 in March and Zambia following suit in November 2024. This marks a 33 percent increase in strategic planning within just two years, indicating that African leaders perceive AI as a crucial infrastructure rather than a luxury. The African Union’s Continental AI Strategy is the most extensive development-focused AI framework globally, estimating that optimal AI adoption could boost the continent’s GDP by six percent by 2030. Unlike the Western focus on innovation for its own sake, Africa’s strategy prioritizes agriculture, healthcare, education, and climate adaptation—vital sectors for its 1.3 billion inhabitants.
A senior AU official involved in the strategy’s development notes, “We’re not trying to copy Silicon Valley. We’re creating AI that addresses African needs.” This Africa-centered approach stems from sobering lessons from previous technology eras, where developing nations often became consumers rather than creators of digital solutions. South America is taking a distinctly different yet equally strategic route, utilizing existing regional integration frameworks to steer AI development. The Santiago Declaration, ratified by more than 20 nations in October 2023, established the Regional Council on Artificial Intelligence, with Chile emerging as the leader in the region. Chile ranks first in the 2024 Latin American Artificial Intelligence Index (ILIA), followed by Brazil and Uruguay.
This leadership position reflects significant investments, with Chile committing $26 billion for its 2021-2030 National AI Policy, while Brazil’s 2024-2028 AI Plan allocates $4.1 billion for 74 strategic initiatives. Brazil’s approach exemplifies how developing countries can mobilize resources for AI advancement. The anticipated Santos Dumont supercomputer is set to become one of the five most powerful globally, and six Applied Centers for AI will focus on agriculture, healthcare, and Industry 4.0 applications. This marks a fundamental shift from perceiving AI as an imported solution to fostering local capabilities. The relevance of AI in development is underscored by the success of Hello Tractor’s platform in African agriculture.
Founded in Nigeria, this ‘Uber for tractors’ service employs AI for demand forecasting and fleet optimization, benefiting over 2 million smallholder farmers across more than 20 countries. The outcomes are remarkable: farmers experience income increases of 227 percent, accelerate planting by 40 times, and achieve three-fold yield improvements through precision timing. Apollo Agriculture in Kenya and Zambia illustrates how AI can tackle long-standing financial inclusion issues in agricultural development. By utilizing machine learning for credit scoring and satellite data for precision recommendations, the company supports over 350,000 previously unbanked farmers with non-performing loan rates below 2 percent, outperforming traditional banks in high-risk demographics. These are not mere pilot projects but profitable enterprises addressing real challenges with quantifiable impacts.
The investment landscape starkly highlights the development hurdles hindering AI adoption. Global AI funding reached $100-130 billion annually, whereas African AI startups secured only $803 million over five years. Latin America saw venture capital investment plummet to $3.6 billion in 2024, marking a five-year low, with early-stage funding dominating 80 percent of transactions. This investment pattern perpetuates technological dependence. The United States and China hold 60 percent of all AI patents and contribute one-third of global AI publications. A mere 100 companies, primarily from these nations, account for 40 percent of global AI R&D expenditure, while 118 countries—mostly in the Global South—are excluded from major AI governance discussions. The risks of digital colonialism are significant.
Current trends indicate a widening divide rather than a closing one. Major tech firms like Apple, Nvidia, and Microsoft boast market values that rival the total GDP of the African continent. This concentration of AI capabilities within a handful of corporations from wealthy nations fosters dependency reminiscent of colonial resource exploitation. Digital colonialism arises when developing nations become consumers instead of producers of AI technologies. Most AI training relies on Western datasets, resulting in cultural and linguistic biases that inadequately serve non-Western populations. For instance, search results in diverse nations such as Brazil predominantly display white faces when querying images of babies, reflecting biases in training data.
Moving toward inclusive AI futures necessitates recognizing both AI’s potential for transformation and the enduring barriers to equitable access. Challenges such as infrastructure deficits, skill shortages, and funding inequalities present substantial obstacles, yet successful applications in agriculture and healthcare show that progress is attainable. Regional cooperation frameworks like the African Union’s Continental AI Strategy and Latin America’s Santiago Declaration serve as models for coordinated development capable of competing with the concentrated resources and expertise of established tech hubs. These strategies prioritize development needs over mere technological progress, potentially fostering more inclusive AI ecosystems. The precedent set by the mobile revolution inspires optimism regarding leapfrogging opportunities, but achieving success requires consistent political will, adequate funding, and international collaboration.
Nations that strategically invest in AI foundations while nurturing local innovation can position themselves to benefit from the AI transformation rather than be left behind. The global AI divide embodies both the greatest risks and the most significant opportunities for international development in the 21st century. Whether AI serves to bridge or exacerbate global inequalities will depend on the choices made today by governments, international organizations, and private sector entities. The stakes, quantified in trillions of dollars of economic value and billions of lives impacted, necessitate urgent, coordinated action to ensure that AI advances human development rather than merely technological progress.
The African farmer utilizing Hello Tractor’s AI platform to enhance crop yields and the Brazilian patient receiving AI-driven diagnostic services exemplify AI’s relevance in development. The future of such success stories hinges on the policy frameworks being established in developing nations today. The AI revolution is relentless, but its benefits need not be dictated by geographical or financial circumstances. The opportunity for inclusive AI development remains, but it will not be available indefinitely.
