AI Could Lift Global Growth Beyond US and China, Report Says. Will Africa Benefit?

Artificial intelligence could become a source of growth for economies far beyond the United States and China, according to a new Financial Times survey of 94 economists. That is an encouraging prospect for countries that have spent the AI boom watching investment, chips and profits gather around a small group of technology powers. But the prediction also raises a harder question; will Africa capture a meaningful share of the gains, or mostly buy the tools that generate them?

The survey, published on October 18, points to the possibility of wider economic benefits over the coming decade. It is a forecast of what economists think AI can do, not evidence that a global productivity surge has already arrived. The distinction matters. Building expensive data centres and selling AI subscriptions can lift investment now; making a hospital, farm, factory or small business more productive takes adoption, training and reliable infrastructure.

The International Monetary Fund’s October World Economic Outlook projects global growth of 3.1% in 2026 and 3.4% in 2027. It identifies stronger AI investment and eventual productivity gains as possible upside drivers, while warning that expectations around AI could also be reassessed. In other words, the same technology can support a brighter outlook and create financial risk if investment races ahead of measurable returns.

There is another divide beneath the global numbers. Countries that supply chips, cloud services or power-intensive computing facilities can benefit immediately from the buildout. Economies outside those value chains have to work harder to turn imported AI tools into higher output and incomes. A forecast of broadly shared gains should not be confused with a guarantee that every region will benefit equally.

For Africa, success need not mean building a frontier model that rivals the largest American or Chinese systems. The near-term opportunity may be less glamorous and more useful; software that helps clinicians manage records, farmers obtain timely advice, banks detect fraud, teachers prepare lessons and small firms handle customers or accounts with less wasted time.

That is close to the World Bank’s argument in its 2026 report on AI and developing economies. The bank estimates that 16.2% of jobs in developing economies could see meaningful productivity gains from AI, while 4.5% face automation risk. These are estimates of exposure and potential, not a forecast of actual African jobs created or lost. The report stresses that power, connectivity, skills and institutional capacity determine whether the promise becomes real.

A World Bank study of firms in seven economies, including Kenya and Nigeria, offers a useful warning. AI use is spreading quickly, but sophisticated use cases remain concentrated. Signing up for a chatbot is easier than integrating one into a business process, checking its output and proving that it saves money or improves a service.

The basic infrastructure still decides

The World Bank’s Africa Economic Update argues that the continent’s immediate opening lies in adapting practical, lower-cost AI, backed by electricity, connectivity, data, computing access and skills. TechBooky has examined the power constraint facing African AI infrastructure. It applies to everyday adoption too such as unreliable electricity and expensive internet make it harder for a small firm to use a digital tool consistently, however capable the model itself may be.

There are promising local routes. African companies can adapt models to local languages and regulations, build tools for agriculture and health, or provide enterprise systems that keep sensitive data under tighter control. South African enterprise AI efforts illustrate that the commercial question is often whether a tool solves a specific operational problem, not whether it wins a global model benchmark.

Governments have a role beyond announcing national AI strategies. They can improve reliable power and broadband, make public data usable within privacy rules, help workers learn relevant skills and buy technology against clear service outcomes. Businesses, meanwhile, need to measure whether AI improves speed, accuracy or revenue rather than treat adoption as an end in itself.

The FT survey makes a credible case for optimism beyond the two largest AI powers. Africa’s share of that potential will be decided less by the existence of powerful models than by who can put them to work. The next measure of progress is not how many AI announcements the continent produces, but how many more productive firms, better public services and better-paid workers emerge from them.