The October 2026 Annual Meetings of the World Bank and the International Monetary Fund, held in Bangkok, Thailand, highlighted the growing importance of artificial intelligence (AI) in shaping the global economy. The choice of the location was particularly relevant given the economic and technological transformations underway across Asia and the Pacific. The region is playing an increasingly important role in global AI-related production, while governments and businesses are exploring how to harness emerging technologies to strengthen productivity and economic growth. Unsurprisingly, AI featured prominently in discussions at the Annual Meetings and in the World Bank's broader development agenda, with the institution consistently encouraging developing countries to adopt existing AI technologies and adapt them to their local needs. Yet, alongside the opportunities AI offers, its expansion also presents significant challenges for developing economies, including potential job displacement and growing dependence on foreign technologies. While AI is opening new opportunities for economic development and enabling businesses, including smaller enterprises, to improve their operations, its implications for labour markets and the distribution of economic gains remain uncertain. Understanding how developing countries can harness these opportunities while addressing the risks will therefore be essential to ensuring that the AI transformation contributes to more inclusive and sustainable development.
A United Nations Development Programme (UNDP) report released in December 2025, titled The Next Great Divergence: Why AI May Widen Inequality Between Countries, finds that East Asia and the Pacific are at the very centre of the AI transition. The report finds that ‘the region now hosts more than half of global AI users and is rapidly expanding its innovation footprint, from China’s rise to nearly 70% of global AI patents to over 3,100 newly funded AI companies across six economies.’ However, the region is deeply diverse within itself, and some countries are better placed to extract the most value out of the AI transition while others may fall behind given their lack of infrastructure or institutional capacity. For example, connectivity is a central part of unleashing AI potential but it remains highly unequal among developing countries; in fact, a report by the United Nations Conference on Trade and Development (UNCTAD) highlights that internet use in lower-middle-income and low-income countries can be as low as 54% and 27%, respectively.
Nonetheless, the World Bank sees AI as a central component for growth in the region. Just a few days before the Annual Meetings of the IMF and the World Bank in Bangkok, the World Bank released an East Asia and Pacific Update, titled Riding the AI Wave. The report examines the adoption of AI across the East Asia and Pacific region, arguing that AI adoption, especially in the industrial sector, has become one of the key drivers of the sustained, albeit slowing, economic growth in the region. However, the implications of AI adoption for labour markets remain less clear, leaving important questions about its potential effects on employment unanswered. As the report shows: ‘there is not yet a discernible impact on AI-automatable jobs in EMDEs [Emerging Markets and Developing Economies] in East Asia and Pacific, in contrast with emerging evidence of negative impacts in advanced economies and other EMDE regions.’ This evidence seems to contrast with the UNDP report, which found that women and young people in Asia face particular vulnerabilities. ‘Jobs held by women are nearly twice as exposed to automation, and youth employment is already declining in high-AI-exposure roles, especially for those aged 22–25, threatening early-career pathways.’
Apart from the growing divide between and within countries, the increasing reliance of Asian countries on AI-related production and investment may also pose further sources of vulnerability. As the World Bank’s regional Chief Economist, Franziska Ohnsorge, explained in an event dedicated to the launch of the report Riding the AI Wave, ‘the region's reliance on AI-related goods production, AI-related industrial sectors, has been a source of strength but could become a source of weakness if global AI-related activity slows.’ A vulnerability associated with the AI transformation concerns access to reliable electricity, which remains a critical challenge for countries across the region. Expanding investment in renewable energy and strengthening electricity supply capacity could help address this challenge while also reducing exposure to extreme climate events, including unusually strong El Niño patterns, and limiting dependence on imported fossil fuels.
The World Development Report 2026, published by the World Bank in August, had already addressed some of the implications of AI for economic development, urging developing countries to recognise AI as a significant tool for advancing their development agendas. In the foreword, Indermit Gill, Senior Vice President and Chief Economist of the World Bank Group, stressed the importance of looking beyond the widespread concerns surrounding AI, arguing that: ‘Developing economies should tune out much of this noise. […] AI has thrown them a lifeline they should grasp before it slips away.’ This perspective reflects the World Bank's view that AI represents a potentially transformative opportunity for developing economies. Unlike their more advanced counterparts, developing countries may be better positioned to harness some of the benefits of AI while facing less immediate disruption to established labour markets and economic structures. The challenge, therefore, is to seize this opportunity and integrate AI into development strategies before the technological gap between countries widens further. The most practical starting point for developing countries is to adopt AI tools that are already available while adapting them to their specific needs and local contexts.
Similarly, at the 2026 Annual Meetings of the World Bank and the IMF, the President of the World Bank, Ajay Banga, in his speech suggested that developing countries focus on ‘practical, or small AI’ rather than ‘Big AI’ systems. Developing countries would need to invest heavily and pool resources to build their own Big AI models from scratch, while practical applications of existing AI models could have a more direct effect on developing countries’ populations. For example, farmers could use AI to improve yields, teachers could do the same to improve their classes and provide better education, health workers could make better-informed decisions, and entrepreneurs could reach new customers.
However, this approach also entails important challenges. As the World Bank acknowledges in the World Development Report 2026, ‘on the political side, the world’s most advanced AI systems are controlled by a small number of companies, mainly in the United States and China. This means developing countries could become dependent on technology they do not control. Like all countries, they also face risks from unexpected consequences of AI.’ The adoption of existing AI technologies therefore presents a double-edged opportunity: while it can accelerate development and help bridge technological gaps, it may also create new forms of technological dependence and expose developing economies to risks associated with systems over which they have limited control.
Ultimately, the AI transformation presents both significant opportunities and considerable challenges for East Asia and the Pacific. While the region is already benefiting from the expansion of AI-related production and the growing adoption of emerging technologies, these gains risk being unevenly distributed across and within countries. Differences in digital infrastructure, institutional capacity and access to skilled workers may further widen existing economic disparities. Addressing these inequalities will require governments to prioritise investment in affordable digital connectivity, education and skills development, while strengthening institutional capacity to support the effective adoption of AI. Particular attention should also be devoted to groups that may be disproportionately affected by technological change, including women and young workers, through targeted training programmes and measures that facilitate their participation in evolving labour markets. These policies would help ensure that the benefits of AI adoption extend beyond the most technologically advanced economies and reach smaller businesses and more vulnerable segments of the population.
A second challenge concerns the structural vulnerabilities associated with increasing reliance on AI technologies and production. As developing countries in Asia and beyond adopt existing AI tools, they must also strengthen their capacity to adapt these technologies locally, and most importantly to govern them, rather than becoming entirely dependent on systems developed and controlled elsewhere. This calls for investment in domestic technological expertise, appropriate regulatory and institutional frameworks, and regional cooperation to share knowledge, resources and expertise. At the same time, governments should strengthen the resilience of their energy systems by expanding renewable energy production, modernising electricity grids and improving supply capacity. Such measures would help address the growing energy demands associated with AI while reducing exposure to external shocks and dependence on imported fossil fuels.
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