artificial intelligence<\/a> is already reshaping human development. For instance, AI-powered mobile apps are helping rural health workers interpret symptoms in places where doctors are scarce. Meanwhile, adaptive learning platforms are personalizing lessons for students in under-resourced schools. In climate-vulnerable regions, AI models are forecasting floods, droughts, and crop failures days or weeks in advance, giving communities valuable time to prepare.<\/p>\n\n\n\nHowever, these gains are not automatic. They depend on choices about who builds the technology, whose data trains it, and who has a say in governing it. As a result, the benefits of the global AI market are far from evenly distributed.<\/p>\n\n\n\n
Currently, a small group of economies and around 100 firms control the bulk of AI research, patents, and computing power. Meanwhile, fewer than one-third of developing countries have a national AI strategy. Among least developed countries, that figure drops to just 12%. Additionally, about 65% of people in least developed countries remain offline, which puts AI out of reach from the start.<\/p>\n\n\n\n
At the same time, up to 40% of jobs worldwide could be affected by AI-driven automation. This threatens to erode the low-cost labour advantage that many developing economies rely on for growth and poverty reduction. Furthermore, 118 countries, mostly in the Global South, are absent from major AI governance forums. Consequently, norms on safety, transparency, and accountability are being written without their input.<\/p>\n\n\n\n
According to UNCTAD, these are not just technical gaps. Rather, they are human development gaps that affect livelihoods, public services, and countries’ capacities to meet their citizens’ needs.<\/p>\n\n\n\n
Still, AI can deliver the greatest human development impact where needs are most acute, namely, agriculture, primary healthcare, disaster management, and public administration. Success, however, depends on three interdependent factors: infrastructure such as electricity, broadband, and computing; locally relevant data; and workforce skills.<\/p>\n\n\n\n
For most developing countries, the report notes, the realistic entry point is adapting existing or open-source models to local conditions, rather than building proprietary systems. Moreover, aligning these efforts with national development plans, and treating data governance as central to readiness, separates countries that capture AI’s gains from those where the technology stays confined to urban centres.<\/p>\n\n\n\n
Notably, inclusive AI is not a slower path. Instead, it is one that ensures technology leaves no one behind. For developing countries, the window to act remains open, but it is narrowing.<\/p>\n\n\n\n
To address these gaps, UNCTAD is calling for global cooperation to steer AI toward shared goals and values. Its key priorities include:<\/p>\n\n\n\n
An industry commitment, through a public disclosure mechanism for AI similar to the environmental, social, and governance (ESG) framework, to improve accountability and turn global commitments into impactful outcomes.<\/p>\n\n\n\n
Shared infrastructure, in the form of a global shared facility, to provide equitable access to AI infrastructure and lower entry barriers for countries that cannot build such infrastructure alone.<\/p>\n\n\n\n
Open innovation, through open data and open-source models, to broaden access to knowledge and resources and support inclusive AI innovation, while coordinating fragmented open-source AI resources to make them more accessible.<\/p>\n\n\n\n
And capacity building, especially through South\u2013South cooperation, to strengthen developing countries’ ability to seize AI benefits and address shared challenges.<\/p>\n\n\n\n
Ultimately, as the global AI market continues its rapid rise toward $4.8 trillion by 2033, UNCTAD argues that inclusive policies now will determine whether its gains reach everyone, or only a privileged few.<\/p>\n\n\n\n
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