Written by: Giulia Materazzo
Since the launch of ChatGPT in November 2022, the issue of artificial intelligence has been brought to the global limelight. Countless think pieces, studies, and protests have arisen since then on the topic. Many worry about potential human disempowerment and job loss (Gratton, 2026), while supporters argue for a future of boundless possibilities and increased efficiency (Baker, 2024). On a wider scale, nations are fighting to establish dominance in the new digital economy (Ostrovsky, 2026). While controversy erupts over AI art, geopolitical experts weigh in on the race between the US and China in developing AI models, there remains one area that has been significantly neglected: the impact AI will have on the developing world.
A focus specifically on underdeveloped nations may seem irrational, as the impact of AI on many first-world countries is evident and immediate, while poorer countries appear to be safe from its reach. After all, a computer science graduate in Germany surely has more to fear from a coding bot than a subsistence farmer in Sierra Leone. However, this argument masks a potentially debilitating future for developing countries. This article will first introduce a long-run view on the impacts of AI, and the widening global wealth gap that may result from it, and secondly, an analysis of how developing countries have already been inextricably tied to AI supply chains. The impact of AI on the developing world is understudied and under-researched, and any discussion on the future of artificial intelligence and a future digital global landscape should center on these nations in its analysis.
As mentioned above, low-income and emerging economies are less threatened by AI in the short run compared to their advanced counterparts. While the IMF predicts that around 60% of jobs in advanced economies are at risk of being impacted by AI, only 40% of jobs will be affected in emerging economies, and 26% in low-income economies (Cazzaniga et al., 2024). Focusing specifically on jobs that will be directly harmed by AI, the brunt of the impact is once again borne by advanced economies— 33% of jobs compared to 24% and 18% in emerging and low-income economies, respectively (AI’s $4.8 Trillion Future, 2025).
However, just as the number of jobs and industries that will be affected by AI in developing economies is lower, so is the number of those that stand to benefit from it. Roughly half of the jobs affected in advanced countries are considered complementary to AI, meaning enhanced productivity as industries learn to harness the new tool (Cazzaniga et al., 2024). This leaves developing and emerging economies with two challenges: higher barriers to benefit and the risk of being left behind by an increasingly efficient world (Tavares et al., 2025). An additional issue is that while the jobs harmed by AI are far fewer in developing economies, they may be among the most profitable. The reason why developing countries thrive in certain areas, such as IT services in India or call centers in the Philippines, is that they can offer those services at a significantly lower cost than in advanced economies. By reducing the labor intensity of those industries, AI would effectively wipe out the competitive edge of many developing countries (Schellekens & Skilling, 2024).
Furthermore, developing nations face a risk not just from the adoption of AI into the global economy, but from the cost of running its systems. Even if developing economies managed to remain completely sheltered from AI, it would be impossible for them to remain separated from the struggle for the raw minerals required to run it, because it is playing out on their soil. Every chatbot, every calculation, every code run by AI requires the physical extraction of resources, many of them from some of the most economically and politically unstable states in the world (Raw Material Extraction). Conversations around AI devote ample time to its consequences, but they neglect to mention the costs it already has.
Large-scale mining operations in areas like the Democratic Republic of the Congo, Mongolia, and Latin America pose a serious environmental threat. After years of increased AI use, contamination of local water sources will accumulate, potentially destroying industries and ways of life centered around farming, fishing, or herding (Raw Material Extraction). This establishes an obvious flaw within existing data on the impact of AI in developing countries. The impact of AI on jobs in the digital sector can be measured, but how can one appropriately take into account the degradation of natural resources that impoverished populations depend on? The aforementioned farmer from Sierra Leone will not be harmed by an immediate artificial intelligence model, but he will suffer when coltan mining pollutes the water supply and ruins his crops. To accurately estimate AI’s true global impact, increased attention to the countries in its supply chain is imperative.
Besides environmental impact, the governments of developing countries may struggle to protect their populations from the economic inequality and labor injustice that will result from these booming resource markets (Alnafrah, 2025). Instances of forced labor and child labor have already been documented in the Democratic Republic of the Congo, and local indigenous communities in South America’s lithium triangle complain of deepened inequalities and disruption of traditional ways of life (Raw Material Extraction). Considering past and existing cases of countries afflicted with resource curses, it is possible that the rise of AI may lead to increased civil conflict and authoritarianism (Hunter et al., 2023). Discounting domestic issues, perhaps an even larger threat might be foreign interference. As the US and China compete with each other for global dominance, and China has established a strong presence in the developing world through its Belt and Road Initiative programs, the threat of neocolonialism looms closer than ever for many countries (Kleven, 2019).
Current critiques of AI largely focus on vulnerable groups and industries within advanced economies, such as older workers, or the arts and media, but in doing so, they neglect the most vulnerable of all among the global population. As advanced economies adjust to AI in the long-term, developing economies will most likely be largely unable to reap benefits from it, worsening overall inequality (Georgieva, 2024). In the meantime, the race for domination between superpowers will make resources more valuable than ever, leaving the developing countries in which they are found prone to exploitation, labor injustice, and environmental ruin.
To prevent this, not only should developing countries be the subject of far more empirical research than is presently dedicated to them, but international economic policy should focus on mitigating the harm they will face. Some countries, such as Ghana through its One Million Coders initiative, are already beginning to prioritize developing their digital infrastructure and skills (Synaepa-Addison, 2025). Other countries, like Indonesia and Bolivia, are passing laws to assert more dominance over their mining industry and protect themselves from exploitation (Huld, 2025). In order to ensure the developing world keeps pace in the new global economy, such initiatives should be encouraged by international organizations such as the IMF. In a future economy shaped by AI, a lack of meaningful research and preventative measures will result in a wider wealth gap than ever before.
References
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