Will AI Leave Developing Economies Behind?

Every major technological revolution has transformed economies, but not all have reduced inequality. From mechanisation during the Industrial Revolution to the rise of the Internet, technological progress has often rewarded those best positioned to adopt it first. Artificial Intelligence may be no different. Because its benefits depend on capital, digital infrastructure, skilled workers, and strong institutions—resources already concentrated in wealthier countries—AI risks widening global inequality by amplifying existing advantages. For developing economies still climbing the ladder of industrialisation, the greater danger is that the ladder itself may be dismantled before they reach the top.

Economic development has historically depended on technology diffusion, the process through which innovations spread from richer economies to poorer ones. As countries adopt new technologies, they become more productive, attract investment, and gradually close the income gap with richer economies. The Organisation for Economic Co-operation and Development (OECD) describes technology diffusion as “a critical driver of productivity growth,” while the World Intellectual Property Organization (WIPO) has found that the pace of diffusion has accelerated dramatically over recent years. But unlike earlier technologies, AI is not something countries can simply import. The International Monetary Fund (IMF) explains that a key determinant of AI adoption is “the availability of the specialized technologies, data, and infrastructure.” These resources remain heavily “concentrated and retained in a small number of developed economies”. WIPO’s research highlights this growing divide: the United States reuses 70% of Chinese-originated novel technologies within 5 years, whereas China reuses less than 5% of US technologies in the same timeframe. Meanwhile, India takes an average of 11 years to re-invent based on an Indian-originated breakthrough, while the US takes just 3. The gap is possessing the capacity to absorb and improve technology.

As a result, wealthy nations, large technology corporations, and highly skilled workers in advanced economies stand to benefit the most from AI. The IMF explains that “advanced economies are better positioned to benefit from AI because of higher exposure, advanced digital infrastructure, AI-ready labor pools, and stronger institutions”. This is reflected in the IMF’s AI Preparedness Index, where advanced economies score 0.68, compared with 0.46 for emerging markets and just 0.32 for low-income countries. Advanced economies “constantly emerge as early adopters,” as high-income countries account for 87% of notable AI models and receive 91% of venture capital funding, while low- and middle-income countries account for less than 1% of AI innovation. Meanwhile, annual global spending on computing capacity exceeds $300 billion, but “these investments are unevenly spread,” the International Labor Organization reports. Rather than creating entirely new advantages, AI is reinforcing existing ones, creating a “winner-take-most” dynamic in which countries already at the technological frontier continue pulling further ahead.

Those least prepared to adopt AI are the ones most vulnerable to being left behind. WIPO identifies Sub-Saharan Africa as having the world’s largest technology gap, followed by Latin America and then Asia. Africa holds less than 1% of global data capacity and hosts only about 160 data centres, with nearly half located in South Africa, Nigeria, and Kenya. An IMF report on Sub-Saharan Africa warns that without policy action, many countries may see productivity gains of just 0.2% over the next decade, leaving the region last on the IMF’s AI Preparedness Index.

This risk extends beyond countries to workers. The ILO has found that clerical support workers face the highest exposure to AI automation, “with 24% of the tasks in these jobs associated with high level of exposure to automation”. For countries like India and the Philippines, where call centres and business process outsourcing employs millions—”an important source of formal and relatively well-paid employment, particularly for women”—the implications are serious. If AI automates many of these jobs, developing economies risk losing a sector that has historically driven industrialisation. The policy gap also reinforces the technology gap. According to the UN, fewer than “one third of developing countries have AI strategies.” Without national strategies, developing countries cannot guide AI development toward their priorities or attract AI investment.

However, the future is not inevitable. A WIPO report emphasises that “deliberate policy choices remain essential for translating diffusion into growth, development and actual impact,” identifying technology characteristics, information speed, absorptive capacity, and public policy and institutions as the key determinants of successful technological diffusion. The ILO similarly emphasises that governments can promote more inclusive growth by using proactive strategies, some of which involve investing in “digital infrastructure, promoting technology transfer, building AI skills, and ensuring that all jobs along the AI value chain are of good quality”. Improving AI preparedness could significantly narrow the growth gap between advanced and developing economies.

So, will AI leave developing economies behind? The evidence suggests it could, but only if today’s inequalities in infrastructure, skills, investment, and institutions remain unaddressed. Whether AI becomes another force widening global inequality or a force for shared prosperity will depend more on how successfully its benefits are made accessible to the countries that need them most.

by Mikaela Dinh

Bibliography

Technology diffusion. (2024). In OECD. https://www.oecd.org/en/topics/sub-issues/technology-diffusion.html

Technology on the Move World Intellectual Property Report. https://www.wipo.int/edocs/pubdocs/en/wipo-pub-944-2026-en-the-world-intellectual-property-report-2026-technology-on-the-move.pdf

Cerutti, E., Garcia Pascual, A., Kido, Y., Li, L., Melina, G., Mendes Tavares, M., & Wingender, P (2025). The Global Impact of AI – Mind the Gap. https://doi.org/10.5089/9798229008570.001.a001

https://www.imf.org/external/datamapper/datasets/AIPI. In Mind the AI Divide: Shaping a Global Perspective on the Future of Work. (2024). In International

Labour Organization. https://www.ilo.org/publications/mind-ai-divide-shaping-global-perspective-future-work (1)AI’s $4.8 Trillion Future: UN Trade and Development Alerts on Divides, Urges Action; 2025. https://unctad.org/news/ais-48-trillion-future-un-trade-and-development-alerts-divides-urges-acti.