World Bank Warns That Without Investment in Skills, Infrastructure and Data Systems, Artificial Intelligence Risks Widening the Global Divide
Artificial intelligence has the potential to significantly raise productivity and living standards in developing economies within the next decade, but only if countries urgently invest in the basic building blocks required to harness the technology, the World Bank has cautioned. In a recent assessment, the institution warned that nations that fail to strengthen digital infrastructure, education systems and governance frameworks risk being left further behind.
The Promise of AI for Developing Economies
According to the World Bank, AI could help developing countries accelerate progress in agriculture, healthcare, education, public services and manufacturing. From precision farming and early disease detection to more efficient logistics and personalised learning tools, the technology offers practical applications that can address long-standing development challenges.
If adopted at scale and supported by the right conditions, AI-driven productivity gains could translate into higher growth, better jobs and improved service delivery within a ten-year horizon. For economies seeking to leapfrog traditional development stages, the opportunity is substantial.
The Critical Caveat: Foundations First
The World Bank’s central message is clear: AI is not a plug-and-play solution. Its benefits will accrue primarily to countries that have already invested — or begin investing now — in foundational enablers. These include reliable electricity, affordable and widespread internet connectivity, digital skills, quality data systems, and regulatory frameworks that encourage innovation while managing risks.
Without these basics, advanced AI tools risk remaining inaccessible or underutilised. In the worst case, the technology could amplify existing inequalities both within and between countries.
Key Areas Requiring Immediate Attention
Digital Infrastructure High-speed internet and stable power supply remain uneven across many developing regions. AI applications, especially those involving large models or real-time data processing, demand robust connectivity and computing capacity.
Human Capital Education systems need to prioritise foundational literacy, numeracy and digital skills. Workers will require continuous reskilling to adapt to AI-augmented jobs. Countries that invest early in training and adaptive learning systems will be better positioned to capture the gains.
Data and Governance AI systems rely on data. Developing economies must strengthen data collection, privacy protections and open-data initiatives. Clear rules on accountability, bias and transparency will be essential to build public trust and attract investment.
Public-Private Collaboration Governments alone cannot drive AI adoption. Partnerships with the private sector, universities and international organisations will be needed to finance infrastructure, develop use cases and scale successful pilots.
Risks of Inaction
The World Bank highlighted the danger of a new digital divide. Countries that move quickly to build enabling conditions could see accelerated development, while those that delay may face slower growth, reduced competitiveness and greater dependence on external technology providers.
There is also a risk that AI benefits concentrate in urban centres or among already privileged groups, leaving rural communities and informal workers further marginalised unless deliberate inclusion policies are adopted.
Opportunities Across Sectors
In agriculture, AI-powered advisory services and crop monitoring can improve yields and climate resilience. In healthcare, diagnostic tools and supply-chain optimisation can extend the reach of limited medical resources. In education, adaptive learning platforms can help address teacher shortages and learning gaps. Public administrations can use AI to improve targeting of social programmes and reduce leakages.
These applications, however, depend on the underlying infrastructure and skills base that many developing countries are still building.
Policy Recommendations
The World Bank urged policymakers to act on multiple fronts simultaneously:
- Accelerate investment in broadband and energy access
- Modernise education and vocational training systems
- Develop national AI strategies with clear priorities and ethical guidelines
- Foster local innovation ecosystems and support start-ups
- Ensure that AI deployment aligns with broader development goals, including poverty reduction and climate resilience
International cooperation, technology transfer and concessional financing will also play important roles in helping lower-income countries bridge the readiness gap.
Global Context
Advanced economies are already integrating AI across industries and public services. The speed of this transformation means that the window for developing countries to position themselves advantageously is relatively short. The next decade will likely determine whether AI becomes a force for global convergence or a driver of deeper divergence.
Outlook
The World Bank’s message is both optimistic and urgent. Artificial intelligence can help lift developing economies within a decade, but only if the hard work of building digital, human and institutional foundations begins now. Countries that treat AI readiness as a core development priority stand to gain the most. Those that postpone investment risk watching the opportunity pass them by.
