Key Details
An UNCTAD article, Ensuring AI Benefits Everyone Is Key to Development in the Global South, identifies the capabilities and international arrangements needed to prevent AI from widening existing development gaps.
Area | What UNCTAD Highlights |
|---|---|
Concentrated capacity | A small group of economies and around 100 firms control much of global AI research, patents and computing power |
Limited national preparedness | Fewer than one-third of developing countries have a national AI strategy; the share falls to 12% among least developed countries |
Connectivity divide | About 65% of people in least developed countries remain offline |
Labour-market exposure | Up to 40% of jobs worldwide could be affected by AI-driven automation |
Governance gap | 118 countries, mostly from the Global South, are absent from major AI-governance forums |
Development priorities | Progress depends on infrastructure, locally relevant data and workforce skills |
The AI Divide Extends Beyond Access to Technology
The global AI market is projected to reach US$4.8 trillion by 2033, around 25 times its 2023 size. Yet UNCTAD argues that market growth will not automatically produce widely shared development gains.
AI can help rural health workers interpret symptoms, personalise learning in under-resourced schools and provide earlier warnings of floods, droughts and crop failures. Whether these applications reach underserved populations depends on electricity, broadband, computing capacity, suitable data and trained users.
The concentration of these capabilities can leave developing countries dependent on systems built elsewhere using priorities and datasets that may not reflect local conditions.
Adaptation Offers a More Realistic Entry Point
For most developing economies, UNCTAD considers adapting existing or open-source models more practical than building proprietary AI systems from the ground up.
This approach can direct scarce resources towards:
Adapting models to local languages and operating conditions;
Building datasets relevant to agriculture, healthcare and public administration;
Improving access to computing for researchers and domestic enterprises; and
Training workers to use and evaluate AI systems effectively.
The article cautions that AI may otherwise remain concentrated in urban and technologically advanced centres rather than becoming a broadly available development tool.
Four Pathways for More Inclusive AI
UNCTAD proposes action at both national and international levels:
Public disclosure: An accountability mechanism modelled on environmental, social and governance reporting could require greater transparency about the impacts of major AI systems.
Shared infrastructure: A global facility could give countries access to computing resources they cannot afford to build independently.
Open innovation: Better coordination of open data, open-source models and technical resources could lower entry barriers for local innovators.
Capacity building: Knowledge-sharing, joint research and South–South cooperation could help developing countries address common technological and governance challenges.
Policy Relevance
For India, the article’s value lies less in diagnosing domestic AI readiness and more in sharpening the choices around who can participate in the AI economy.
India is investing in computing infrastructure and domestic AI models, but inclusive adoption will also require affordable access for start-ups, universities, MSMEs and public institutions. Local-language and sector-specific datasets will determine whether AI serves Indian users beyond the largest firms and metropolitan markets.
UNCTAD’s governance warning also gives India a potential international role. India can use its technological capacity and position within the Global South to press for wider representation, shared infrastructure and fairer access to AI knowledge and resources.
The labour dimension deserves equal attention. If AI affects tasks underpinning India’s services and labour-intensive sectors, skilling policy must prepare workers to work with the technology and move into new roles, rather than treating AI capability only as a question of engineers and model developers.
Relevant Question for Policy Stakeholders: How should India balance investment in frontier AI capabilities with the wider task of making computing, data and AI skills accessible across firms, regions and public services?
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