The Future of AI in the Global South: Trends, Challenges, and Opportunities

Introduction 

The Global South, comprising developing nations in Asia, Africa, Latin America, and Oceania, has evolved from a history of imperialism into a hub of economic potential. Home to over 85% of the world’s population, key maritime routes, 42% of global GDP, and over 60% of foreign direct investment, it is marked by rapid growth, cultural diversity, and ongoing development challenges.

In the contemporary geopolitical landscape, a noticeable shift in the balance of power has occurred, accompanied by an emerging transition in AI technological advancements from the Global North to the Global South. AI is defined as the study of how to make computers do things which, at the moment, people are better at. This transition reflects not just technology transfer but a broader redistribution of knowledge and innovation capacity. Nations in the Global South are increasingly becoming active participants in AI research, deployment and development rather than remaining passive consumers.

This shift is enabling developing countries to leverage AI technology to reform development systems, tackle inequality, and promote inclusion and self-reliance, making significant impacts on social and economic developments, while addressing local challenges in areas such as healthcare, education, agriculture, finance and governance in such a resource-constrained environment. In addition, as most of the AI is designed and developed in the Global North, its adaptation and impact differ significantly due to its application in vastly different social contexts, raising digital inequality and ethical concerns.

However, this technological shift bolsters the Global South's standing at the forefront of an AI revolution. With AI's transformative potential shaped by distinct social, economic, cultural, and infrastructural factors, it is vital to explore how AI can be effectively harnessed to maximise benefits, address challenges, and navigate future efforts to ensure equitable and responsible AI development in the Global South from the local perspective.

Potentials of AI in the Global South

The Global South has the potential to strategically leapfrog traditional development hurdles. By leveraging emerging AI technologies, these nations can drive inclusive and sustainable development across key sectors such as healthcare, education, agriculture, and public services. With the right investments in digital infrastructure, education, and policy frameworks, the Global South can accelerate AI adoption and establish itself as a vital contributor to the global AI landscape.

AI's Economic Impact: The rapid conveyance of information and deepening globalisation have opened new avenues for embracing AI and other emerging technologies across these regions.  It is estimated that by 2023, artificial intelligence will contribute up to $15.7 trillion to the global economy, with North America and China expected to experience the largest gains in GDP growth. AI has become deeply embedded in daily life, from shaping interactions on social media to serving as a tool in modern warfare. AI is not just a technology, its development and application are influenced by the human actors, policies and regulatory structures, making it a complex system of human and technology assemblage.

AI in Warfare: AI is used in unmanned aerial vehicles (UAVs), autonomous drones, and cyber warfare, raising significant global security concerns. It enhances military capabilities by enabling faster decision-making, improved targeting accuracy, and efficient resource allocation. These advancements allow all military personnel to respond swiftly, make strategic choices, and strengthen overall defence operations. A clear example is the 2025 India-Pakistan drone war. In response to the Pahalgam attack, India launched Operation Sindoor, targeting terrorist sites with missiles and kamikaze drones. The newly deployed “Akash Teer” air defence system played a crucial role, neutralising over 100 terrorists and highlighting India’s growing reliance on intelligence-driven warfare. While the drone role in such conflicts remains limited and largely symbolic, it offers a low-escalation military option. They have now become central to both international conflicts and domestic security strategies, underscoring AI’s growing influence in modern military operations.

AI in Healthcare: There is some evidence of AI-based technology aimed at supporting communities in the Global South. Notable projects include AI to detect bananas or cassava disease and creating an imaginary observing system for precision agriculture and forest monitoring in Brazil. The healthcare project includes predictive models for engaging expecting mothers in rural India, clinical decision support against antimicrobial resistance in Ghana, and fetal ultrasound interpretation in Zambia. The education projects include identifying at-risk students in Colombia, improving English learning in Thailand and developing teaching assistants for science education in West Africa.

AI in Energy Management: Additionally, AI is also being used in intelligent energy management. Twin transition has led to convergence of the AI revolution and energy transition that is enhancing innovation, transforming the Global economy and addressing urgent environmental challenges. As AI accelerates the energy transition, clean energy investment boosts AI growth. The resource-rich Global South is well-positioned to seize this momentum by promoting inclusive and sustainable green AI initiatives. With tech giants like hyperscale, Microsoft and Google investing heavily in renewable energy, such as Microsoft’s $10 billion project and Google’s leadership in procurement, there is growing potential for the Global South to attract investment, create jobs, and upgrade infrastructure.

AI in Investment and Growth: Over the years, major tech companies have entered the Global South Market. IBM was among the first major companies to launch a research lab in the global south, starting in India in 1998, later expanding to Rio de Janeiro and Nairobi in 2013. India has been a gateway for high-tech research, with Microsoft launching its research lab in Bangalore in 2005, later expanding to Africa with development centres in Nairobi and Lagos. With such initiatives, AI growth in the Global South is promising, sustaining this ecosystem calls for stringent regulatory frameworks that build skilled talent and foster digital inclusivity, while advancing in clean energy and development goals.

Challenges of AI in the Global South

Limited Access to Critical Infrastructure: Despite the significant opportunities represented by AI in the Global South, several challenges persist. Wealthy nations and high-income developing countries are better positioned to reap AI’s economic benefits, thanks to robust AI digital infrastructure, abundant resources, and advanced data systems, leading to the Digital Gap. A key driver of the “AI divide” is structural limitations, as many developing countries struggle to manage the vast data and computing resources required for training AI systems. For the successful implementation of AI-driven solutions, a sound technical AI infrastructure is essential, but often out of reach. This includes high capacity computing resources, large storage capacity, skilled talent and a mature network and cyber security infrastructure. This is evident as the Global South hosts only 1% of the world’s top computers, with Africa at just 0.04%.

These high-performance machines are crucial and expensive for AI development, yet remain scarce. Such critical AI research and development infrastructure is largely monopolised by a handful of companies based in the Global North, limiting access to advanced models and stifling broader global participation in innovation. Recent advances like DeepSeek demonstrate the Global South's potential to build efficient, affordable AI without substantial investment or Western dependence, raising concerns among the West about accelerating economic and military capabilities. However, replicating and sustaining such breakthroughs across the resource-constrained Global South remains a formidable challenge without support and prolonged investments.

Information Warfare and Manipulation: Additionally, AI is increasingly exploited in information warfare, particularly during elections, with paid troll campaigns, often run from Global South countries, used to manipulate online discourse. This underscores the urgent need to regulate social media recommendation algorithms, which prioritise virality over truth. Tech companies often invoke free speech to avoid responsibility. For example, while large numbers of users in the Global South use platforms like Facebook, tech companies allocate minimal budgets for content moderation in these regions. Simultaneously, the rise of data brokers is alarming, as they sell personal data to corporations that influence user behaviour. What began as a trade-off for personalised services now fuels a global economy built on data monetisation.

Risk of Exclusion: As developed nations lead in AI regulation, innovation, and infrastructure, the benefits of AI remain heavily concentrated in the Global North. The U.S. and China currently dominate the AI landscape, controlling nearly half of the world’s AI chips. In contrast, the Global South faces a “compute desert,” with limited access to high-performance computing, energy-intensive infrastructure, and capital. This stark imbalance hampers the region’s ability to participate in the AI-driven global economy and the broader clean energy transformation. Simultaneously,  AI systems rely on diverse, localised data to function effectively, yet much of the Global South lacks the digital infrastructure and skills needed to generate and harness this data. With 2.6 billion people still lacking internet access, many remain digitally invisible and vulnerable to exclusion or manipulation. Low digital literacy, limited skilled professionals, and limited investment further deepen the divide by restricting data access, increasing the risk of biased AI systems that entrench existing inequalities.

Adding to the challenge, voices from the Global South are often sidelined in global AI dialogues, limiting their influence over the technology shaping their future. With little inclusion and growing challenges, governments in the Global South may divert public spending away from digital innovation, further delaying inclusive development.. Without urgent action to bridge these, it risks undermining the AI revolution and deepening existing inequalities.

Exploitative Labour Practices: At the same time, concerns grow over exploitative labour practices, such as low-paid data annotation outsourced to countries like Kenya, where workers filter harmful content and label datasets. These conditions reveal deep global inequalities and fuel fears of “AI colonialism,” where the Global North accelerates AI progress by relying on undervalued labour from the global South. This mirrors historical exploitation, extracting economic value from the Global South to enrich the North. This rapid AI industrialisation is driven partially by this cheap labour, often at the expense of workers’ mental health, deepening technological dependency and reinforcing existing global inequality. While policymakers often argue that innovation moves too fast to regulate, it’s vital to recognise that this rapid progress is often driven by the exploitation of labour and resources in developing countries.

Privacy and Ethical Concerns: As AI expands, weak data protection and rising misuse have intensified privacy and ethical concerns. Strong policies and governance frameworks are crucial to ensure safe, trustworthy AI that attracts investment to develop inclusive, locally adapted AI governance based on global best practices.

Conclusion

AI offers the Global South a chance to accelerate development, foster innovation, and bridge digital divides. However, without strong governance, ethical safeguards, technical infrastructure, skilled talent, and inclusive policies, it risks deepening global inequalities. The dominance of a few tech giants and limited infrastructure in developing countries highlights the shortage of AI professionals and limited training opportunities, leading to brain drain and an urgent need for local capacity-building, fair labour practices, and regional cooperation.

Investing in digital education, indigenous  AI systems, and context-driven innovation can help reduce poverty and close the global development gap. The path forward depends on our collective commitment to ethical principles, inclusive innovation, and equitable access. In the 21st century, these are not optional aspirations but necessary foundations for a fair and sustainable AI future.