Which Countries Are Positioned to Benefit From the AI Revolution?

Artificial intelligence (AI) has the potential to give a similar boost to workforce productivity growth as the information and communication technology (ICT) revolution in the late 1990s. But a range of factors will determine which countries can reap the most benefits.

The extent of productivity gains will depend on the development of complementary innovations to harness the power of AI, as well as effective regulation and policymaking. And once the technology is in place, economies will need to adapt so that displaced workers and capital can be redeployed, analysts at Capital Economics argue.

So, which countries are best positioned to make the biggest productivity gains from deploying AI?

Key Takeaways

  • The US leads in benefiting from AI, followed by Singapore, the UK, South Korea, Canada, and Hong Kong.
  • China lags behind due to regulatory restrictions on AI and a focus on domestic market protection.
  • Japan and the Eurozone face challenges in adopting and diffusing AI technology.
  • Emerging economies may experience slower AI diffusion, affecting productivity and services outsourcing.
  • Developed economies may gain more from AI, potentially widening the income gap with emerging economies.

Developed Countries to Take the Lead

The US is set to lead a pack of 33 major developed and emerging economies in benefiting from the effects of AI over the next two decades, according to Capital Economics.

Singapore and the UK come second and third in the analyst firm’s AI Economic Impact Index, with South Korea, Canada, and Hong Kong also in the top 10. Israel and parts of the Nordic region are also well-placed to capitalize on adoption.

The US leads the way, reflecting its size, private and public investment in research and development, and the talent nurtured by its higher education system.


The US channeled more private investment into AI and the largest number of AI start-ups than any other country – both outright and on a per-capita basis.

​Asian Tigers and the UK Strongly Positioned

Hong Kong, Singapore, and South Korea all rank highly, making the top 10 as they perform well on diffusion and adaptation. Their ability to adapt quickly to new technology has enabled them to develop export-led economies and move up the value chain, and this will serve them well in adopting AI.

For example, South Korea was nimble in developing its heavy industry in the 1970s and digital TV market in the 2000s, these are lessons they likely remember as technology enters another new era.

The UK ranks third despite a lack of investment, as its higher education system draws in talent that has contributed to its advanced R&D base. This boosts its standing in the Index for AI innovation. Global AI leaders such as Google DeepMind, BenevolentAI, and Signal AI are based in the UK, reflecting its position as an AI leader.

The fact that the UK economy is highly services-based and has a flexible labor market lends itself to a relatively rapid diffusion of AI tools and applications. This should also help it adapt to the challenges and opportunities presented by AI, according to Capital Economics.

Chinese Regulation Could Limit Diffusion

China ranks 18th in the AI Economic Impact Index, which could be considered low given that it leads the way in some areas of innovation owing to the public and private sectors channeling significant resources into AI development since it was identified as a national priority in the mid-2010s.

China scores lower on diffusion as government regulators have insisted on stronger oversight of generative AI tools developed by domestic firms than other countries, largely to ensure that they comply with censorship rules.

The government’s crackdown and ongoing restrictions on the technology sector indicate that it is unlikely to permit the adoption of AI technologies throughout the economy.

However, China is still likely to play a significant role in the global AI landscape. While it will likely wall off the domestic market as it does with internet services, it is nurturing an independent ecosystem of AI providers that may be able to successfully export technologies and services.

Japan, Eurozone to Lag

Japan and most eurozone economies rank between the US and China. Japan is placed 16th, as its history of technological innovation could support rapid AI adoption, however, it has recently lagged in diffusing new technology across the economy.

For instance, cash is more widely used in Japan than any other advanced economy, and most businesses still use fax machines.

There are several constraints facing significant economies in the eurozone. Historical, political, structural, and other factors limited the impact of the ICT revolution on the region, and the US received the more significant boost. Europe’s less developed venture capital industry, less flexible labor market, and relatively limited cloud infrastructure – a critical component in AI development and adoption – are likely to limit its potential for AI innovation. In addition, the region is expected to adopt more regulations than policymakers in other countries.

Within the region, countries that have workforces with more AI-related skills and technological infrastructure, such as Germany and France, will fare better than those with fewer AI skills and low network readiness, such as Italy and Spain.

How Will AI Adoption Affect Emerging Economies?

Less advanced IT sectors, a lack of dynamic private sector development, low R&D investment, and continued brain drain to developed economies will limit AI innovation and diffusion in emerging economies, according to Capital Economics.

There is also a possibility that AI applications will replace services currently outsourced to workers in developing economies. Tasks such as customer service responses, drafting documents, and producing market emails, which form part of the business process outsourcing (BPO) sector, could see a substantial increase in productivity from generative AI, particularly large language models (LLMs).

There is a risk that Western businesses could move this work into the cloud rather than paying for BPO services. A World Bank and the University of Oxford study on customer service businesses in India found that “AI adoption initially coincides with a small increase in general hiring, but then reduces demand for non-AI workers over the next few years, such that the overall effect is substantially negative”.

This could mean that India and the Philippines experience a loss of around 0.3-0.4 percentage points of annual gross domestic product (GDP) growth over the next decade from a shrinking BPO sector, Capital Economics estimates. Other countries such as Brazil, Mexico, and Poland could lose around 0.1-0.2% annually.

Slower diffusion of AI will likely mean that most emerging economies would see any potential productivity boost later than developed economies, from the mid-2030s onwards.

Productivity growth in economies with large services export sectors could experience slower growth if AI causes those sectors to be re-shored back to developed economies.

While there are opportunities to retrain workers to help meet demand for AI-related services, most low-income developing markets could lack the resources to invest in training. However, AI could create opportunities for low-income countries to implement AI in a way that has a material economic impact.

For instance, the mobile phone revolution in the late 2000s enabled countries in sub-Saharan Africa to leapfrog fixed telephony and provide citizens with access to low-cost devices and services that had far-reaching effects on economic development.

Use cases for AI in medicine and healthcare, such as in drug discovery, could offer significant benefits, such as developing new treatments for certain diseases or reducing infant mortality rates. AI can also address the skills gap in education by facilitating new methods of training and remote treatment.

And yet, AI will not be able to solve factors that have tended to limit advancement in underdeveloped economies, including weak institutions, poor governance, and lack of regional integration, Capital Economics notes.

Implications of the AI Revolution

What impact will all these dynamics have on the shape of the global economy?

If AI does boost developed economies more than emerging economies, this will amplify the ongoing slowdown in the rate at which incomes in developing countries are catching up with those in advanced economies – a trend that has emerged since the rapid growth in the “golden age” of the 2000s and early-2010s.

AI adoption is likely to help the US economy remain ahead of the Chinese economy in terms of GDP measured at market exchange rates. India could advance from the world’s fifth-largest economy currently to the third largest, although AI could hamper rather than help that growth over the next decade.

“AI is likely to become a new fault line in the fracturing of the global economy”, Capital Economics states. Large-scale AI adoption in developed economies could also make it more difficult to achieve the convergence of income in emerging markets, as richer economies are better equipped to deploy the technology.

The Bottom Line

The US, UK, and developed economies in Asia are the best positioned to realize the potential benefits of the AI revolution. While China is likely to limit the proliferation of AI applications and services at home, it could still become an important global player as it exports the results of its investment in technological innovation.

Adopting AI presents more complex challenges to emerging economies, which could benefit from innovations that contribute to their growth or be left behind as developed economies accelerate their advancement.


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Nicole Willing
Technology Journalist

Nicole is a professional journalist with 20 years of experience in writing and editing. Her expertise spans both the tech and financial industries. She has developed expertise in covering commodity, equity, and cryptocurrency markets, as well as the latest trends across the technology sector, from semiconductors to electric vehicles. She holds a degree in Journalism from City University, London. Having embraced the digital nomad lifestyle, she can usually be found on the beach brushing sand out of her keyboard in between snorkeling trips.