By Dr. Gyan Pathak
Asia and the Pacific stands as the world’s most diverse region, where wealth and deprivation, stability and fragility, technological leadership and digital exclusion coexist side by side. This diversity makes it the ultimate testing ground for artificial intelligence (AI), a new UNDP report says. With surge in adoption of AI in wealthy nations, millions of jobs in the region could be at risk. The worst sufferers are likely to be women and young adults.
The report titled “The Next Great Divergence: Why AI may widen inequality between countries” show AI unfolds here will not only determine the region’s development trajectory but also signal whether the technology becomes a force for greater inclusion or a driver of deeper inequality.
The data indicates that the technology juggernaut is expected to inject nearly $1 trillion in economic gains over the next decade across Asia alone. The report says that entry-level workers in may South Asian nations face “significant exposure” to changes already underway, including automation.
To prevent a looming jobs crunch, UNDP has urged the governments to consider the ethics of AI before rolling it out further – and to ensure this is done so in as inclusive a way as possible. It is important since the Asia-Pacific region is home to more than 55 per cent of the world’s population, putting it at the centre of AI transition. The region hosts more than half of global AI users and is rapidly expanding its innovation footprint; China alone holds nearly 70 per cent of global AI patents, while six countries host more than 3,100 newly funded AI companies.
The region brings together high- and low-income economies, strong and struggling education systems, long and short life expectancies, and resilient democracies alongside fragile states. Health and gender equality outcomes are equally uneven, with some countries achieving global bests and others lagging far behind.
The economic gaps are stark. In 2024, Afghanistan’s GNI per capita was less than $400 dollars, while Singapore’s exceeded $70,000, a difference of nearly 200 times. In purchasing power terms, Singapore is around 70 times richer than Afghanistan.
Similar divides exist within countries. According to the World Inequality Database, the bottom 50 percent of the population in Asia and the Pacific typically receive less than 20 percent of income and hold under 6percent of wealth, while the top 10 percent capture between 35 and 70 percent. In China, India, Thailand, and Iran wealth concentration among the top decile is particularly stark.
These inequalities translate directly into human development gaps: South Asia, for example, loses over a quarter of potential development value once inequality is factored into UNDP’s Human Development Index.
Despite decades of rapid growth, high inequality also coexists with absolute deprivation on a massive scale. Around 196 million people in the region still live in extreme poverty (below $3.00/day, 2021 PPP); about483 million are multi-dimensionally poor; some 770million women are out of the labour force; and an estimated 1.3 billion people work in the informal sector, often without protections.
To put it bluntly, the GDP per capita of Kuala Lumpur and Shanghai are similar ($30,000) while the GDP of the poorest Malaysian state, Kelantan, would rank in the lower half of an Asia-Pacific countries list. In Asia and the Pacific there are “many countries within countries.”
The Asia-Pacific region is already investing heavily in AI, signalling that leaders recognize both the opportunity and the urgency. South-East Asia, for example, attracted over $30 billion in AI-ready data-center commitments in the first half of 2024, as global tech firms and local investors funded AI startups, data centres and digital platforms. ASEAN as a bloc is projected to see AI boost GDP by 10–18 percent by 2030, adding roughly$1 trillion.
AI is already being applied to solve persistent development challenges. Governments and businesses across Asia and the Pacific are turning to AI in areas like healthcare, education, finance, agriculture, and public services. The promise driving this rush is that AI could help “leapfrog” development constraints – for example, using telemedicine powered by more effective and powerful current and forthcoming AI systems to deliver health services in remote islands that lack doctors, employing AI tutors to improve education in understaffed schools in Pacific islands, protect vulnerable ecosystems through continuous monitoring and intervention, increase state capacity and make governments more efficient, and offer new opportunities to spur economic growth.
In short, there is a widespread hope that AI will be a game-changer for development, allowing countries to tackle old problems in new, more efficient ways.
However, not all countries are equally prepared for the AI transition. A few economies—such as Singapore, the Republic of Korea, and China – stand at the global frontier of AI research and adoption. They benefit from robust digital infrastructure, advanced STEM education systems, and dynamic technology ecosystems that attract investment and talent. These foundations enable them to experiment, scale, and integrate AI across industries at a pace comparable to leading global innovators.
Many others, however, are not yet positioned to participate in this transformation. In several lower-income and fragile contexts, even reliable access to electricity, connectivity, and data systems remains a challenge.
Evidence from Latin America shows that nearly half of all GenAI-exposed jobs – equivalent to 17 million, that could realize productivity gains – are hindered by gaps in digital access. Digital divides also affect women’s AI readiness as well as their underrepresentation – as AI developers or users – risking furthering gaps and divides. Limited institutional capacity and skill shortages compound these structural gaps, creating barriers to both public- and private-sector adoption.
The IMF’s AI Preparedness Index underscores this regional divide. Asia-Pacific countries collectively span the full range of global readiness – from world leaders to those among the least prepared. This divergence in preparedness makes the region alive laboratory for the global AI transition. (IPA Service)
