Reprogramming trade in Asia for an automated future
Reprogramming trade in Asia for an automated future
The growing adoption of robotics and artificial intelligence (AI) is rapidly reshaping Asia’s industrial capacity and trade dynamics. Asian countries, in particular those that are not robotics leaders, must actively invest in human capital, institutions and innovation to future-proof the region for automation.
Asia has seen rapid growth in robotics and AI with China, Japan and South Korea leading industrial robot adoption. China holds Asia’s largest robot stock, surpassing Japan and South Korea combined. India, Turkey, Thailand and Vietnam have the highest growth rates in robot delivery. In robot density, South Korea remains far ahead, followed by Japan and China. Among lower-income economies, India leads in robot stock, followed by Vietnam, the Philippines and Pakistan. Given the high absolute number of new deliveries in China, Japan and South Korea, there has been a widening gap in robot adoption between these robotics leaders and other Asian countries.
Increasingly, robotics and AI are intertwined in their development. According to McKinsey and Company’s 2024 firm survey, AI adoption among firms rose in Asia and the Pacific from 58 per cent in 2023 to 72 per cent in 2024.
During this period, AI adoption dramatically increased in Greater China, from 48 to 75 per cent. North America and Europe led AI adoption at 82 and 80 per cent, respectively. Since 2013, the United States has led private AI investments (US$470.9 billion), followed by China (US$119.3 billion) and the United Kingdom (US$28.2 billion). In 2024, the most AI start-ups emerged in the United States, followed by China, India, South Korea, Japan and Singapore.
Automation in robotics-leading economies could raise domestic supply and reduce demand for imports from other economies. But it may also boost import demand from other countries due to the increased need for imported intermediate inputs in sectors undergoing robotisation.
This offshoring-versus-reshoring debate continues.
A 2023 World Bank working paper — ‘Does Automation Adoption Drive Reshoring? A Cross-Country Investigation’ — uses empirical data collected between 2008–19 from 60 countries to show how the short-term effects of automation reduce reshoring and encourage continued offshoring. A one per cent increase in automation correlates with a 0.28 per cent decrease in reshoring, especially in high- and lower-middle-income countries. This process supports continued regional trade and growing opportunities for lower-wage Asian economies within global value chains.
In contrast, the authors of a 2023 MERIT Working Paper — ‘Automation-induced reshoring and potential implications for developing economies’ — use a theoretical model to demonstrate how longer-term large-scale automation causes reshoring and harms lower-income Asian exporters. Their simulation suggests that developing economies face major risks unless they rapidly adopt automation or shift to non-routine services.
Robotics development is also changing global and regional market competition landscapes. Robot adoption could strengthen the market power of firms with initially high mark-ups, reinforcing existing market concentration. But if utilised effectively, it could also enable smaller and younger firms to survive, compete and grow their market power faster.
For example, Robots-as-a-Service is emerging as a flexible and scalable model that reduces upfront costs and increases access to automation. Instead of purchasing robots outright, firms can subscribe to use them. Countries that are not robotics leaders could consider utilising this new business model to create innovative products and services that serve both local and global demand, thereby carving out new development pathways.
Asian economies will need to invest in education and reskilling to help workers adapt and seize new business opportunities arising from robotics and AI. The aim is to empower workers to use new technologies as productivity tools. Global frameworks, like UNESCO’s 2019 Beijing Consensus, emphasise inclusive, AI-enhanced education by 2030. Without education and reskilling, workers may view automation and AI as a threat, increasing political demand for protectionist or anti-tech policies. Experimental evidence predicts that domestic automation shocks lead to support for redistribution, while foreign automation shocks increase support for regulations and tariffs which harms productivity growth in the long run.
While some countries mention AI in national curricula, actual implementation is rare. As of late 2024, only ten countries — including Australia, Japan, South Korea and the United States — had issued specific guidance for AI in education.
For Asian economies that are not yet leaders in robotics and AI, it is crucial to invest in human capital that is capable of adapting to and thriving in new modes of production, innovation and business. Equally important is the maintenance of open, resilient and robust policies and market institutions.
South Korea has been leading in these policies. Its national initiative, the Digital New Deal, is a multi-year US$53.5 billion commitment from 2020–25 focused on digital infrastructure, data and AI innovation. The government is working closely with chaebols including Samsung and Hyundai, start-ups and institutions like Korea Institute for Robot Industry Advancement to drive innovation. Seoul is also focusing on data openness and cross-border digital trade agreements with countries like Singapore.
Indonesia has ambitions for AI development as well, but its policies require strengthening. Indonesia’s AI National Strategy 2045 lacks sufficient budget, interministerial coordination and clear legal frameworks for data governance. Other issues that could also hinder international AI collaboration and cloud services include strict data localisation rules and inconsistent digital trade policies.
At this pivotal moment of rapid technological transformation, countries in Asia must act strategically to prepare the region for automation. Investment in education and reskilling is essential to empower workers. It would also be wise to invest more in infrastructure to bring the AI ecosystem closer to home, so more people could utilise AI and robotics to build power plants, transmission lines and wiring data centres together.
Countries that are not robotics leaders should avoid trying to replicate China, Japan or South Korea’s industrialisation and development paths but instead invest in human capital, institutions and innovation. To balance out the reshoring risks, they could explore shifting comparative advantage from labour-intensive to technology-intensive sectors. In doing so, non-robotics leaders could find ways to make smart use of automation in new modes of economic development.
Yixiao Zhou is Associate Professor of Economics and Director of the China Economy Program in the Arndt-Corden Department of Economics at the Crawford School of Public Policy, The Australian National University.
This article appears in the most recent edition of East Asia Forum Quarterly, ‘Asia’s new trade politics’, Vol 17, No 3.
https://doi.org/10.59425/eabc.1757509200
Source: East Asia Forum
