Artificial intelligence (AI) leadership remains concentrated in a handful of countries, with the United States and China continuing to dominate the global AI ecosystem, according to the World Bank’s World Development Report 2026: The Promise of Artificial Intelligence. The report says this concentration creates challenges for developing countries but also opens opportunities because they can benefit from AI without spending billions of dollars on building frontier AI systems from scratch.
The report says the world’s leading AI companies, advanced AI models, data centres, specialised chips and top AI talent remain clustered in only a few economies. It adds that the concentration of these critical parts of the AI value chain makes it increasingly difficult for other countries to compete at the highest level of AI development.
“The concentration of the most important building blocks of AI – such as advanced models, computing infrastructure, and specialized hardware – within a few companies and countries leaves developing countries potentially dependent on technologies they do not control,” the report says.
Why is AI leadership concentrated in only a few countries?
The World Bank says AI development depends on massive investments in computing infrastructure, semiconductors, data centres, large datasets and highly skilled researchers. Only a small number of countries have built these capabilities over many years. The report says most leading publicly listed AI companies are based in either the United States or China. These countries also host many of the world’s leading private AI companies.
According to the report, this concentration creates a powerful cycle. Countries with strong AI ecosystems attract more skilled researchers, more venture capital and more technology companies. Those advantages help them develop even better AI models, which in turn attract more investment and talent. The report says this makes it harder for other countries to catch up, which is why the San Francisco Bay Area remains the world’s leading AI hub.
The report also says AI differs from many previous technologies because the entire value chain is concentrated. Very few economies can build advanced AI chips, large-scale computing infrastructure and frontier AI models. While developing countries produce some minerals that support the AI industry, only a handful of countries control the technologies that power advanced AI systems.
What does this mean for developing countries?
The World Bank says developing countries should not try to copy the AI strategies of advanced economies. Instead of competing to build the world’s most powerful AI models, they should focus on adopting existing AI tools and adapting them to local needs. The report says this approach costs far less while still delivering significant economic and social benefits.
“The cost of adapting AI is far lower than building it from scratch,” the report says, adding that countries can build practical AI applications using existing models rather than investing billions of dollars in frontier AI development.
The report says developing countries can customise existing AI models for local languages, laws and business environments. Entrepreneurs can build applications for healthcare, education, agriculture and government services without creating large language models themselves. It says adapting AI to local conditions is likely to deliver the biggest gains because imported AI systems may not work well without local data and language support.
The World Bank also says countries should avoid becoming dependent on a single AI provider. Instead of pursuing complete “AI sovereignty”, governments should use AI models, cloud services and digital tools from multiple providers so they can switch technologies when needed without rebuilding their entire systems.
Although AI leadership remains concentrated, the report says developing countries still have a significant opportunity to benefit from the technology. Rather than trying to lead the global AI race, they should focus on solving local problems, improving productivity and expanding public services through practical AI applications. It says adopting, adapting and then advancing AI offers the most realistic path for long-term development.