AI for All? World Bank Lays Out Roadmap to Help Developing Nations Catch Up

The World Bank’s Devising a Strategic Approach to Artificial Intelligence: A Handbook for Policymakers is a detailed and timely playbook aimed at helping governments, particularly in low- and middle-income countries (LMICs), navigate the fast-evolving artificial intelligence (AI) landscape. Developed with research input from institutions such as the Stanford Institute for Human-Centered Artificial Intelligence, UNESCO, the Global Center on AI Governance, and the Tony Blair Institute for Global Change, the handbook underscores that while AI technologies, especially generative AI (GenAI), are surging globally, their benefits are largely confined to higher-income nations. Low-income countries account for just one percent of global GenAI traffic, and over a third of the world’s population lacks daily internet access, threatening to deepen digital and socio-economic inequalities. Without deliberate and well-resourced AI strategies, the technological revolution may bypass much of the developing world, further marginalizing those already digitally excluded.

The report notes that “small AI” solutions, like mobile-based crop diagnostics or healthcare decision tools, are gaining traction in LMICs. Still, GenAI and large-scale systems remain inaccessible due to limited infrastructure, regulatory uncertainty, and underdeveloped innovation ecosystems. It warns that failure to engage strategically with AI could result in long-term structural challenges, including youth underemployment and missed opportunities in high-skill digital sectors. To respond effectively, the handbook proposes an adaptable framework that countries can tailor to their local realities, capacities, and development goals.

The Four Cs of AI Readiness

Central to the World Bank’s framework are four foundational pillars, connectivity, computing, context, and competencies, collectively dubbed the “Four Cs.” These represent the minimum requirements for any country to engage meaningfully with AI. Connectivity refers to reliable energy and high-speed broadband internet, both prerequisites for AI model deployment and digital services. Computing addresses the need for high-performance computing infrastructure, including access to data centers and cloud services that enable model training and inference.

Context, meanwhile, highlights the importance of having high-quality, well-governed local data to ensure that AI systems reflect local languages, cultures, and values. Finally, competencies encompass both general AI literacy and specialized STEM skills necessary to develop and apply AI systems across sectors. The report emphasizes that investing in these areas is not just about enabling AI, but also about supporting broader digital transformation. These “hard” and “soft” foundations are essential for any country looking to close the AI gap and benefit from the technology’s potential.

Aligning with Global Norms and Partnerships

The handbook encourages LMIC governments to actively engage with global AI governance frameworks and multilateral cooperation. It references the G7 Hiroshima Principles, the OECD’s AI Recommendations, and UNESCO’s Ethics of AI guidelines as critical tools for aligning domestic AI development with international best practices. It also points to the first legally binding international treaty on AI adopted by the Council of Europe and regional efforts such as the Cartagena Declaration, signed by 17 Latin American nations to promote ethical, inclusive AI.

While these principles promote transparency, safety, and fairness, the handbook warns against blindly importing foreign frameworks. Instead, it urges countries to contextualize international norms through inclusive, participatory policy design processes. Regional platforms like Smart Africa, ASEAN, and the African Union can also facilitate knowledge exchange and policy harmonization. International collaboration is not just about regulation; it’s also a gateway to technical assistance, investment, capacity building, and global partnerships that can accelerate AI maturity in developing countries.

From Use Cases to National Transformation

To make AI tangible, the handbook highlights real-world use cases from diverse countries. Togo used AI in its COVID-era social protection system to deliver emergency cash transfers to vulnerable citizens without formal identification. Nigeria has leveraged AI to accelerate tuberculosis diagnosis and pilot personalized education tools, showing dramatic learning gains. India is deploying AI in public banks to combat financial fraud, while Mauritius uses drone-fed AI systems for precision farming. Even in the UK, AI is powering automated government services and real-time public sentiment analysis.

These examples underscore the versatility of AI across sectors, including health, education, agriculture, finance, and public services. The handbook argues that AI should not be treated as a standalone sector but as a layer of innovation applied across the economy. However, governments must ensure that foundational conditions, political leadership, funding, stakeholder buy-in, and data readiness are in place before scaling pilots. Policymakers are encouraged to map local use cases, identify priority sectors, and develop sector-specific adoption strategies.

A Practical Seven-Module Blueprint for Action

The core of the handbook is a seven-module framework designed to guide governments from vision to implementation. It begins with setting up a capable, multidisciplinary task force empowered to coordinate across ministries. Next, countries are encouraged to assess their AI and digital landscape, using tools like AI readiness indexes and stakeholder maps. Modules three and four involve defining national objectives, drafting mission and vision statements, and selecting priority sectors and strategic pillars.

Subsequent modules cover shaping specific actions through SMART goals, conducting policy gap analyses, and designing risk mitigation strategies. The final steps involve launching the strategy, preparing communications plans, assigning institutional responsibilities, and establishing results tracking mechanisms. The framework is both sequential and modular; countries can use the full suite or focus on specific areas depending on their needs. Importantly, stakeholder engagement is embedded throughout, with templates for interviews, citizen consultations, and workshops provided to ensure inclusive policy design.

The World Bank handbook is not simply a guide to technological adoption; it is a strategic tool for embedding AI within broader development agendas. It is grounded in the idea that AI can be a powerful engine for inclusive growth, but only if countries act now to lay the groundwork. With careful planning, inclusive governance, and targeted investment, LMICs can shape an AI future that works for all.