Lee Jong-wha: An economics professor at Korea University, he is a former chief economist at the Asian Development Bank and a former chief advisor to the South Korean president on international economic affairs.
Current discussions about the global artificial intelligence race usually focus on competition between the creative leaders – the United States and China – while the rest of the world remains largely an observer. However, while the United States and China push the boundaries of AI development, from foundational models to advanced semiconductor design, they will not solely dictate the economic impact of this technology. Instead, it will be those who implement it who will have that influence.
While the invention of general-purpose technologies like AI creates new opportunities, the diffusion of these technologies across industries and economies is what leads to transformation. Inventions such as electricity, the internal combustion engine, and the internet took decades to realize significant productivity gains because companies had to reorganize production, invest in infrastructure, and develop new skills.
Preliminary evidence suggests that AI is likely to follow a similar trajectory. Last year, approximately 16% of the global working-age population used generative AI tools on a monthly basis. However, adoption rates varied significantly from one country to another, and the fastest adopters of this technology were not necessarily those leading in AI innovations. In fact, while the U.S. and China race to develop the strongest algorithms, a much larger group of countries is competing to achieve wider and faster integration of AI into their economies.
According to the AI Readiness Index for 2025, which assesses nearly 200 countries based on political capability, governance, infrastructure, and adoption of applications in the public sector, the United States ranks first in AI readiness, followed by France, the United Kingdom, the Netherlands, and South Korea. Germany, Singapore, China, Australia, and Norway complete the top ten. The AI Readiness Index published by the International Monetary Fund ranks Singapore, the United States, the Netherlands, Finland, New Zealand, and Germany among the most prepared economies globally based on digital infrastructure, human capital, innovation, and regulation.
The multipolar nature of the AI adoption race partially reflects the fact that technologically capable economies in Europe and Asia have launched ambitious national strategies to accelerate AI diffusion. In Europe, policymakers aim to combine industrial AI adoption with regulatory frameworks that enhance trust and responsible innovation.
In Asia, Singapore is heavily investing in digital infrastructure, workforce training, and experimentation in the public sector. Japan has adopted an “innovation first” approach to AI governance, encouraging experimentation and close collaboration between government and industry. South Korea has set an ambitious goal to become one of the world’s top three AI powers. Initiatives like the “AI in Manufacturing Transformation Strategy” aim to integrate AI into key industries – including semiconductors, automobiles, robotics, and shipbuilding – while also expanding computational infrastructure and nurturing AI talent.
In addition to these leading countries, others are also working to accelerate the adoption of AI applications. India, home to a small number of leading AI companies, is striving to establish itself as a leader in AI applications and services. Malaysia has launched a national action plan aimed at creating an AI-driven economy, with the goal of becoming a regional AI hub by 2030.
These efforts partially reflect policymakers’ recognition in Asia and Europe that achieving massive productivity gains is crucial for compensating for rapid population aging, shrinking workforces, and increasing financial pressures. Under these circumstances, AI presents one of the few realistic pathways to achieve such gains and maintain long-term growth.
Ultimately, the most effective strategies will be those centered around three mutually reinforcing pillars. The first pillar is human capital. Equipping workers with stronger digital skills and problem-solving abilities is essential for enabling them to collaborate effectively with AI systems. This requires substantial improvements in education and lifelong learning.
The second pillar involves technological capabilities. Countries must strive for continuous investment in computational infrastructure, data systems, and research networks that support experimentation and innovation.
The final pillar is industrial transformation, which includes reorganizing production processes, introducing new mechanisms for work completion, and adopting complementary technologies. Recent simulations of AI’s macroeconomic impact suggest that economies combining strong digital infrastructure with advanced manufacturing or data-intensive services are particularly well-positioned to benefit from this technology.
In this context, countries like Finland, Germany, Singapore, South Korea, and the Netherlands, alongside the United States and China, enjoy a competitive advantage. Europe’s vast industrial base, from advanced machinery to energy systems, particularly facilitates widespread AI adoption, which helps to stimulate sluggish productivity growth. However, some analysts warn that Europe’s ambitions will remain constrained unless it works to reduce its dependence on foreign digital infrastructure and cloud platforms.
The success of such strategies will heavily depend on the institutions and governance frameworks that encourage technological advancement while ensuring the responsible use of AI. Priorities should include maintaining competition, attracting global talent, supporting startups, and implementing regulatory controls that address risks such as data misuse, algorithmic bias, and excessive market concentration.
The transformation of AI into a transformative engine for global productivity growth will depend not only on the pace and direction of innovation but also on how effectively countries worldwide adapt their institutions, labor markets, and production systems to seize the opportunities created by this technology. It will not be those achieving breakthroughs in Silicon Valley or Hangzhou alone who win the “AI race,” but also – and perhaps more so – those who deploy these strategies most effectively.
