The World Bank’s World Development Report 2026 argues that artificial intelligence (AI) offers a historic opportunity for developing economies such as Nigeria and the rest of Africa, provided they choose the right path. The report, titled The Promise of Artificial Intelligence, comes at a time when global development progress is moving at its weakest pace in 75 years. Growth in low- and middle-income countries has slowed to levels not seen in three decades, and the report says AI could help compress decades of development into years.

The World Bank’s core message is that this opportunity will not come from trying to build the most advanced AI models. Instead, it will come from adapting existing tools to local realities.

The technology is spreading faster than any previous general-purpose technology. The steam engine took about 80 years to reach lower-income countries. Electricity took 40 years, and the internet took 20. ChatGPT, by contrast, drew half of its global traffic from middle-income countries within just six months of launch. That pace, the report says, creates both urgency and possibility.

Expertise that once took generations to develop can now reach farmers, teachers, doctors, and administrators on a compressed timeline. The report says developing economies do not need to build trillion-dollar, all-purpose AI models to benefit from the technology. Instead, the emphasis should be on “Small AI” — low-cost, highly tailored tools that can work around the infrastructure bottlenecks common in the developing world.

At the same time, the report warns that simply importing ready-made AI products from Silicon Valley or Beijing is not enough. The biggest gains will come from adapting AI to local languages, weak connectivity, limited infrastructure, and the specific challenges individual countries face.

The report identifies three forces that determine AI’s value. First are its capabilities. AI can perform cognitive tasks that usually require scarce human expertise, including diagnosing disease, forecasting weather, designing lessons, and managing public records. In places where specialists are limited, that expands the effective supply of skilled support.

Second is concentration. A small number of companies in a handful of countries control the most advanced chips, models, and infrastructure. That creates dependency risks, but it also means poorer countries can customize existing systems without starting from scratch.

Third are the complements. AI works best where electricity is reliable, the internet is available, schools produce capable workers, institutions function well, and local data exist. Many developing countries still lack those foundations, which limits the technology’s potential and helps explain why the report ties AI adoption to broader investment in basic systems, not just software.

The World Bank therefore recommends a sequenced strategy: adopt, adapt, and only later advance. Adoption of existing tools is the practical starting point. Doctors can use diagnostic aids. Farmers can receive improved weather guidance. Businesses can improve operations.

But adoption alone is not enough. Adaptation is where the biggest gains are found. Tools need to work through text messages or voice calls for people without smartphones. They need to respect local farming practices, educational curricula, and administrative systems. By contrast, building frontier models — the “advance” stage — is the most expensive and least realistic option for most countries in the near term, because it requires massive computing power, huge datasets, and top talent that remain concentrated elsewhere.

The report points to early examples of adaptation already under way. In Bangladesh, AI-powered medical imaging has increased the number of patients screened each day for diabetes-related eye problems by 40%. In India’s Telangana state, artificial intelligence weather forecasts have produced savings of up to $560 per small farmer. In Ghana, a tutoring system designed for basic phones and weak connections produced nearly a full year of mathematics learning gains for as little as $5 per student. The report says these are not abstract possibilities, but examples of how modest, context-aware models can stretch limited expertise further.

The labour market evidence also supports the case for adaptation rather than disruption. Only 4.5% of jobs in low- and middle-income countries face high automation risk from generative AI, compared with 14.2% in high-income economies. At the same time, about 16.2% of jobs in developing countries could see meaningful productivity gains, close to the 18.7% figure for richer countries. Because many workers in the Global South still perform manual or less cognitive tasks, AI is more likely to amplify their efforts than replace them.

Governments play the decisive role, the World Bank says. As enablers, they must build the basics: reliable power, affordable connectivity, foundational education, and stronger data systems in local languages. Initiatives that expand electricity access, including those targeting hundreds of millions of people in Sub-Saharan Africa, become even more important in that context.

As users, governments can use their purchasing power to test and scale AI solutions in health, education, agriculture, and public administration. As regulators, they should begin with voluntary industry standards, apply existing laws to clear harms, and work internationally to avoid fragmented rules that could block access.

The report also warns about the risks of inaction. Without stronger complements, AI could widen gaps between countries and within them. Dependence on a few foreign providers may grow. Trust may weaken if systems embed bias or compromise privacy. Energy demand may also rise.

Even so, the World Bank remains cautiously optimistic. Under conservative assumptions, AI could lift potential growth rates in developing economies above the weak averages of recent years. The window is narrow, and the technology is moving quickly while also proving more context-specific than earlier technologies.

For policymakers and institutions, that means the near-term test is not whether they can join the frontier race, but whether they can make practical use of tools that already exist while putting in place the conditions those tools need. Countries that treat AI as a plug-and-play import will capture limited value. Those that make adaptation the central strategy, reshaping tools for their people, languages, and challenges, stand a better chance of solving problems that have resisted solutions for generations.

The World Bank’s 2026 blueprint is not a call to join an expensive global race to build the most powerful AI models. It is a practical invitation to make the technology work where it is needed most. For Africa and other developing markets, the report says the smartest move is not to advance at all costs, but to adapt with purpose, urgency, and a clear focus on local realities.

Source: World Bank World Development Report 2026