ADB economists Roshen Fernando and Ed Kieran Reyes explain why artificial intelligence readiness is important, identifying the main challenges and showing what their recent research means for growth and jobs in the region.
Generative AI tools are changing how people learn and work across Asia and the Pacific. By creating content and solving problems from simple prompts, these tools can help workers do more in less time and offer new ways for businesses to grow. Yet the scale of their impact will depend less on technological promise than on how effectively countries close widening gaps in AI readiness—gaps that risk driving uneven economic growth and employment prospects between advanced and developing economies.
AI readiness is an economy’s capacity to use and benefit from artificial intelligence, which depends on digital infrastructure, skilled workers, innovation, and strong institutions, as well as the economic structure that determines the share of tasks that can be performed with AI, thereby boosting productivity. Data shows a significant gap between advanced and developing economies in the region.
Our recent analysis suggests that these factors interact, but digital infrastructure and skilled workers are usually the biggest challenges for the region’s developing economies. Poor infrastructure makes it hard to access computing power and cloud services, while a lack of skilled workers makes it hard for firms to adopt AI effectively. Job postings show that advanced economies are hiring more AI skills than developing ones, highlighting gaps in firms’ readiness. Innovation, institutions, and economic structure also affect how fast AI adoption leads to productivity gains beyond the leading firms.
Trading in AI enabling goods, like electronics, computers, and other digital hardware, helps spread technology and speeds up AI adoption. The analysis finds that these goods account for a much bigger part of trade in advanced economies than in most developing economies in the region. Firms that are part of these value chains can more readily access key supplies and tap into global knowledge, boosting innovation. Limited trade slows the spread of AI and makes adoption more expensive. This uneven participation increases the differences in AI readiness and how quickly economies see productivity gains.
Simulations using an economic model suggest that AI increases economic growth more quickly and to a greater extent in advanced economies because they are better prepared and have higher shares of tasks that can adopt AI. In advanced Asia and the Pacific, AI is estimated to lift gross domestic product growth by about 0.6–2.1 percentage points (pps) by 2030, with the gains easing to 0.5–1.5 pps by 2040. In contrast, developing Asia and the Pacific experiences smaller but more persistent gains, at around 0.2–1.8 pps in 2030 and 0.1–1.6 pps in 2040. The simulations also show that if developing economies improve their AI readiness, their growth can increase by up to 0.4 pps, with the People’s Republic of China (PRC) having the largest possible gain. Improving readiness through policy interventions is key to closing growth gaps, not just adopting AI.
AI is most widely used in the service sector, where tasks can be performed more productively with digital tools. For example, in Singapore, AI is used in logistics and port operations to allow workers to remotely supervise and coordinate multiple cranes and vehicles, changing how work is organized and performed. Sectors like agriculture, and construction are less affected for now. Even in agriculture, where AI adoption remains limited overall, some early applications are emerging—for instance, farmers are using AI powered tools to map farmland and forecast rainfall to cope with shifting weather patterns. This trend affects jobs. In better-prepared economies, AI helps services grow and enables workers to move more easily across jobs. In many developing economies, smaller productivity gains from AI-led automation could slow business growth and lead to job losses. However, because fewer tasks can be automated, job losses may be less severe in the short term and may provide workers more time to adapt and acquire skills.
The analysis shows that improving digital infrastructure, skills, innovation, and institutions is key to wider AI use. Services have the most to gain from AI, so targeted investments and incentives can help these sectors grow and make it easier for workers to move to new jobs. Building industries that make AI enabling goods and joining global value chains can also increase industrial output and jobs. Policies that support AI skills, employability, and social protection are important to help workers adjust in the short term.
Source: blogs.adb.org
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