UNDP Warns: AI Surge Risks Entrenching Asia’s Inequality Divide

The United Nations Development Programme’s warning issued in December 2025 highlights a growing fault line running through the Asia-Pacific region as artificial intelligence adoption accelerates unevenly. With more than half of the world’s AI users now located in Asia-Pacific, the region stands at the forefront of technological transformation. Yet this leadership masks stark disparities in readiness, investment capacity, and institutional resilience that threaten to harden existing inequalities rather than alleviate them.

UNDP’s Chief Economist Philip Schellekens cautioned that countries investing early in digital infrastructure, advanced skills, and governance frameworks are positioning themselves for long-term gains. Others, he noted, risk falling into a structural lag that becomes increasingly difficult to reverse. This warning arrives as regional projections suggest AI could generate close to one trillion dollars in economic value over the coming decade, even as it places millions of lower-skill jobs under pressure.

Disparities In AI Exposure And Adoption

Wealthier Asia-Pacific economies are moving rapidly to embed AI across industries. China alone accounts for roughly 70 percent of the region’s AI patents, while six Asia-Pacific countries have produced more than 3,100 AI firms over the past few years. In technology-forward economies such as Singapore, South Korea, and Japan, studies indicate that up to half of all jobs are exposed to AI-driven transformation, either through automation or augmentation.

By contrast, emerging and lower-income economies face a narrower set of outcomes. While adoption rates may be high in absolute terms, particularly in large labor markets such as India, the quality of integration differs sharply. AI deployment in these contexts often targets routine and labor-intensive tasks in manufacturing, services, and agriculture, sectors that employ vast numbers of workers but offer limited pathways for reskilling or mobility. International Monetary Fund estimates suggest AI could lift annual GDP growth by around two percentage points, yet those gains are likely to concentrate in urban centers with access to data infrastructure and specialized talent.

Vulnerability Of Specific Demographics

UNDP’s analysis underscores that the social costs of uneven AI adoption are not evenly distributed. Women and younger workers are disproportionately represented in entry-level and routine roles most susceptible to automation. By 2025, global surveys show that two-thirds of enterprises have already reduced entry-level hiring due to AI integration, with the trend accelerating in Asia-Pacific’s informal and service-heavy economies.

UN Assistant Secretary-General Kanni Wignarasa has noted that AI is improving at a speed that is putting many nations at the starting blocks, especially regarding ethical implementation and inclusion of data. Devoid of conscious precautions, she cautioned, digital exclusion will become another dimension of inequality that will be superimposed on pre-existing income and gender disparities.

Economic Opportunities Amid Displacement Threats

These risks notwithstanding, the economic potential of AI in Asia-Pacific has been immense. According to consulting and development institutions, the region is the global leader in the use of AI in the workplace, advancing the development of industries, including fintech, logistics, and healthcare. Assessments of the World Bank that will be released in mid 2025 have parallels to the previous technological waves in East Asia where productivity gains were later translated to net employment growth under favorable policy provisions.

Timing and distribution is the challenge. According to PwC 2025 Global AI Jobs Barometer, routine jobs are being eliminated at a higher rate than the new jobs complementary to AI are being created. This delay is adding an additional burden on already stressed labor markets due to post-pandemic adjustments and falling global demand, leading to more chances of short-term displacement being converted into long-term exclusion.

Reskilling Imperatives And Policy Gaps

There are disproportionate responses to policy in the region. The developed economies have invested a lot in AI education and workforce transition schemes and the poorer states face financial limitations and organizational inadequacies. The paradox in India is seen in the fact that despite the high levels of use of AI, there is a lack of a social safety net and a disjointed reskilling system.

UNDP suggests that it is only through joint public and private efforts that the benefits of AI will be enjoyed by companies and employees who are already at a position of taking advantage of it. Failure to have inclusive governance systems poses a threat of strengthening elite capture, where technological benefits end up in the hands of vast masses of people.

Geopolitical And Developmental Ramifications

The AI wave is transforming the intra-regional relations as a replica of the global North-South schism. Such technology centers as Singapore and Seoul keep moving ahead, and areas of South Asia, Southeast Asia and the Pacific fight to keep up. According to UNDP analysts, such a deviation would result in propagating secondary impacts, such as pressures in labor migration and societal upheaval, as well as emergent types of trade friction.

The dominance of China in the development of AI adds more complexity. Despite the benefits of Chinese technology alliances in the form of infrastructure and scale, there is still worry that such an arrangement will be biased towards deployment instead of local capacity-building, which would further entrench dependency instead of encouraging autonomous innovation.

Global Supply Chain Vulnerabilities

The role of Asia-Pacific as the manufacturing base of the world is also changing due to AI. The assembly lines, ports and logistics networks automation offer potential efficiency benefits, but they pose a risk to low-skill hub jobs. According to IMF forecasts, the performance of the results will be quite different: exporters who can implement AI in higher-value production can gain, whereas those economies dependent on inexpensive labor will lose their competitive edge.

Such changes overlap with the broader 2025 potential trade tension and tariff resettlements, increasing the uncertainty in governments to strike the balance between competitiveness and social stability.

Policy Responses And Implementation Challenges

There are various dominant economies which can serve as an example of adaptation. South Korea and Japan have incorporated the requirement of reskilling in their national AI plans and have allocated multibillion of funds in their 2025 budgets. The SkillsFuture initiative in Singapore has gained more than its share of attention due to its emphasis on lifelong learning and AI-complementary skills with evidence of productivity improvements in services and high-tech manufacture.

Such models are however difficult to scale. The transferability of these approaches is constrained by fiscal pressures and institutional gaps in emerging economies, which strengthens a cycle where AI is increasing divergence and not convergence.

Regional Cooperation And Multilateral Push

The regional forums have acquired new significance as the magnitude of the challenge is becoming transparent. The framework of the digital economy of ASEAN and APEC discourses in 2025 are increasingly focusing on common standards, mobility of talent, and data regulation. UNDP has recommended more equity in computing resources with the warning that otherwise the AI boom will make it easier to establish barriers across borders.

Nonetheless, coordination is challenged by the barriers such as regulatory disintegration and incentives by the private sector that is more concerned with speed and profitability rather than inclusivity. The nationalization of regional interests is still in process.

Navigating Uncertainty In AI’s Trajectory

With 2025 coming to an end, Asia-Pacific is at a critical crossroad wherein the rate of AI adaptation is going faster than the creation of an inclusive policy framework. Economies enjoying the benefit of good patent holdings and infrastructure are establishing high standards that others have not been able to match, leading to calls to leapfrog through open-source AI and shared data commons.

Finally, the future of AI in Asia will be an issue of more human than algorithm-driven decisions. The ability of the governments to preempt disruption, the investment in people by institutions, and regional partners working together will be the factors that lead to reduced or increased divides over time due to technological acceleration. The UNDP warning has a wider scope that is not limited to Asia-Pacific: can world governance be able to work fast enough not to make the upcoming wave of innovation tear social cohesion, but to make it test its boundaries?