The World Bank warned Tuesday that developing countries risk being left behind if they fail to adopt artificial intelligence tools, calling AI a potential boost for economies facing their weakest growth in three decades. The warning came with the release of the bank's annual World Development Report, which argues that low-cost, locally adapted AI can improve health, education, justice, and agriculture.
"AI has thrown developing economies a lifeline, and they should seize it," said Indermit Gill, chief economist of the World Bank Group. "They do not need large models or big data centers to reap its benefits."
Developing economies are in their weakest growth period in 30 years, according to the bank. The report said AI could "significantly boost that performance before the end of the 2020s while delivering tangible benefits to people." It called on countries to use AI to "help extend otherwise costly medical, legal, educational and agricultural services to underserved billions - doing in a decade what might otherwise take a century."
AI as a lifeline for struggling economies
The 2020s have been a difficult decade for lower-income countries, hit by successive shocks. The World Bank earlier this year called it a "lost decade" for their economic growth. The bank has lowered its 2026 global growth forecast to its lowest level since the pandemic, with the Iran war causing economic fallout that has hit low-income and developing countries hardest, particularly in Asia.
The report urges developing countries to begin working with localized AI tools, invest in electricity generation and distribution, expand access to computing power, and improve the availability of local data. Gaurav Nayyar, the report's director, said: "The window to get this right is narrow. AI presents a once-in-a-lifetime opportunity to solve problems that have resisted solutions for generations."
Adapting AI to local conditions
For the 6.8 billion people - 83% of humanity - who live in low-income and developing countries, AI tools must be adapted to local needs. The report highlights examples including increasing diabetes screening in Bangladesh and reducing costs for Indian farmers through advanced weather forecasts. It emphasizes that solutions need to meet people where they are. "For example, AI solutions will need to be delivered through voice calls on basic mobile phones for those who cannot read or afford smartphones," the report says. "Simply importing an AI model does not mean it will work well locally."
The report recommends that governments invest in infrastructure and adapt existing AI models rather than building large systems from scratch. That approach aligns with practical strategies for AI for Government that focus on incremental improvements to public services using available technology.
The risks of getting it wrong
The report also delivers a stark warning: "AI could widen gaps between countries, increase inequality within them, concentrate market power, weaken trust in public institutions, and create new risks for safety, rights, and social cohesion." It calls on policymakers to build public trust as they expand AI use. "Improved public services and better learning outcomes in schools will reinforce trust - but if AI embeds bias in government decisions or erodes data privacy, that trust will be difficult to recover," the bank said.
Although risks to employment in developing countries are currently low, the report warns that over the long term AI tools could reduce economic mobility by eliminating many of the middle-class jobs that make it possible. The report itself was written with the aid of several advanced AI tools, including products from OpenAI, DeepSeek, Google, and Anthropic, according to a disclosure.
Why this matters for IT & Development
For IT professionals working on development projects, the World Bank's report signals a shift toward smaller, more adaptable AI systems rather than massive data center builds. The emphasis on voice-based interfaces, offline-capable tools, and low-bandwidth solutions means developers will need to design for constraints that are different from those in wealthy countries. Building trust through transparent, privacy-preserving systems is also a core technical challenge - one that will determine whether these tools gain acceptance or face rejection. For professionals looking to build skills in this area, resources on AI for IT & Development offer practical guidance on implementing AI in resource-constrained environments.
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