Artificial intelligence could enable developing countries to compress decades of economic and social progress into just ten years, but only if governments move quickly to strengthen digital infrastructure, skills and institutions, according to the World Bank’s flagship World Development Report 2026.
The report argues that AI represents a rare opportunity for emerging economies to accelerate development without first replicating the expensive technology ecosystems built by advanced nations. Instead, countries can generate significant benefits by adopting affordable AI tools and adapting them to local challenges.
However, the World Bank warns that the window to capitalise on this opportunity is narrow. Without investment in electricity, connectivity, education and governance, many developing economies risk falling further behind as AI adoption accelerates.
A different AI story for developing economies
Contrary to concerns that AI will trigger widespread job losses, the report suggests automation risks are significantly lower across developing countries than in wealthier economies.
According to the World Bank, only 4.5% of existing jobs in low- and middle-income countries are highly exposed to automation by generative AI, compared with 14.2% in high-income economies.
Instead, AI’s greatest potential lies in enhancing workforce productivity.
The report estimates that 16.2% of jobs in developing economies could experience meaningful productivity improvements through AI, only slightly below the 18.7% projected for advanced economies.
Rather than replacing workers, AI is expected to augment human capability by helping professionals make better decisions, process information more effectively and deliver services at greater scale.
Public services stand to benefit
The report identifies significant opportunities for governments to improve service delivery using AI.
Potential applications include:
- improving healthcare diagnostics;
- supporting teachers and education systems;
- strengthening agricultural advisory services;
- enhancing tax administration;
- improving disaster response;
- expanding access to justice; and
- strengthening delivery of social protection programmes.
These applications are particularly valuable where shortages of skilled professionals, incomplete records and limited institutional capacity constrain public services.
According to the report, relatively simple AI systems adapted to local conditions could significantly improve outcomes without requiring the enormous computing infrastructure associated with frontier AI development.
Foundations matter more than frontier models
One of the report’s central messages is that developing countries should avoid trying to compete immediately in building cutting-edge AI models.
Instead, it recommends a phased strategy:
- Adopt proven AI technologies already available.
- Adapt them to local languages, sectors and public services.
- Advance towards developing domestic AI capabilities as digital ecosystems mature.
The report argues this approach allows countries to realise economic benefits more quickly while avoiding costly investments before essential foundations are in place.
Infrastructure remains the biggest barrier
Despite AI’s promise, the report highlights major infrastructure gaps that continue to limit digital transformation.
In Sub-Saharan Africa:
- nearly one-third of rural schools still lack reliable electricity; and
- more than two-thirds lack dependable internet connectivity.
Without addressing these fundamental constraints, AI adoption will remain limited regardless of advances in the technology itself.
The World Bank points to initiatives such as Mission 300, which aims to expand electricity access to 300 million people across Sub-Saharan Africa by 2030, as critical enablers of future AI adoption.
Building trust will be just as important
The report also argues that successful AI adoption depends on strong governance and public confidence.
Governments are encouraged to begin with voluntary industry standards while working internationally to avoid fragmented regulation. Existing laws should be applied where necessary to address emerging harms, including privacy breaches, discrimination and misuse of AI systems.
Maintaining public trust will be particularly important as governments increasingly deploy AI within public services.
Analysis
For project professionals, the report reinforces a shift that is becoming increasingly evident across both the public and private sectors: AI is moving from being viewed primarily as a technology initiative to becoming an enabler of large-scale transformation programmes.
The report’s emphasis on adoption before innovation also carries important lessons for project delivery. Rather than pursuing ambitious AI development programmes, many organisations and governments are likely to generate greater value by integrating existing AI tools into established processes, improving productivity before investing in frontier capabilities.
This phased approach mirrors established project management principles around capability maturity and incremental value delivery. It also highlights the importance of enabling projects that extend beyond software implementation. Investments in power infrastructure, broadband connectivity, digital skills and institutional reform become foundational programmes without which AI transformation cannot succeed.
Perhaps the report’s most significant message is that AI may prove less about replacing labour than expanding human capacity. For project leaders responsible for delivering national infrastructure, public services and economic development programmes, that distinction is likely to shape investment priorities over the coming decade.
