The AI wave is global. Readiness is not. Here’s what the latest regional economic data show

The AI wave is reaching every region, but it is not impacting every economy equally. Developing countries are entering the AI era from radically different starting points, shaped by geography, infrastructure, skills, and institutions. Yet they share the same challenge: turning access to AI into higher productivity, more and better jobs, and improved public services. The Global Picture: Promise, Inequality, and Capacity Gaps Technology itself is no longer the biggest bottleneck. Corporate investment has surged, while cloud services have made powerful AI tools cheaper and more widely available. The bigger problem is whether countries can put those tools to work. Firms and governments need reliable infrastructure, well-organized data, digital skills, effective management, and institutions capable of deploying AI responsibly. Without these foundations, access will spread faster than meaningful adoption. For most developing economies, as the new World Development Report: The Promise of Artificial Intelligence has laid out, the biggest gains will come not from building expensive frontier models, but from adapting existing systems to local languages, data, industries, and constraints. Smaller, task-specific tools, often referred to as “small AI,” can already help farmers, teachers, health workers, and public agencies even where bandwidth and computing power are limited. Governments have three essential roles: build the foundations for adoption, use AI to improve public services, and set clear rules that encourage innovation while managing risk. Africa: Building AI-Readiness Sub-Saharan Africa’s economy is on a modest upswing, with growth projected to reach 4.3% in 2026, supported by domestic demand and rising demand for critical minerals, according to Africa: Building AI-Readiness. Yet its AI readiness gap is stark. The region has 18% of the world’s population, just 0.6% of global data-center capacity, and only 5% of those facilities are AI-ready. Some 900 million people remain offline. Even so, practical, low-cost applications are already improving education, health, agriculture, and logistics. Scaling them will require reliable electricity, better connectivity, affordable devices, local-language data, and regional cooperation to share the high fixed costs of digital infrastructure. South Asia: Adopting AI for Growth South Asia is the fastest-growing region, projected to expand by 6.8% a year in 2026–27, according to South Asia: Adopting AI for Growth. Its AI use is rising too, but it remains relatively basic. About 23% of formal firms in India report using some form of AI, compared with 43% in the United States, and the gap is wider for advanced applications. Unreliable electricity, slow broadband, and adult literacy gaps hold back deployment. Still, AI-exposed sectors are attracting more international partnerships and becoming more integrated into global value chains. The next step is to strengthen skills, infrastructure, and the business environment so firms can move beyond routine tasks and capture more value. Middle East, North Africa, Afghanistan, and Pakistan: From Divide to Opportunity: AI, Jobs, and Growth Few regions show a sharper divide in AI readiness than the Middle East, North Africa, Afghanistan, and Pakistan. Saudi Arabia and the United Arab Emirates rank among the global top 25 for AI development and computing capacity and are investing billions of dollars to become future hubs, according to Middle East, North Africa, Afghanistan, and Pakistan: From Divide to Opportunity: AI, Jobs, and Growth. Fragile and conflict-affected economies, by contrast, face severe shortages of electricity, broadband, and institutional capacity. The economic backdrop is also turbulent: conflict in the Persian Gulf and the effective closure of the Strait of Hormuz have contributed to a projected regional GDP contraction of 2.1% in 2026. Meanwhile, Arabic, Persian, Urdu, and other regional languages and contexts are underrepresented in training data. AI has the potential of augmenting the productivity of up to 20% of the jobs in the region, but closing gaps will be essential to realize these gains. Europe and Central Asia: Making AI Work Europe and Central Asia has considerable AI potential, but much of it remains untapped, according to Europe and Central Asia: Making AI Work. Data-center capacity stands at only 2.1 megawatts per million people, compared with 31.6 megawatts in high-income economies outside the region. Fewer than one in 10 firms use AI—about half the EU average. The quickest gains are likely to come from adapting existing technologies to local languages and business needs. That will require affordable computing power, accessible public data, and managers who know how to turn new tools into better processes and products. Latin America and the Caribbean: Harnessing the AI Transition Latin America and the Caribbean faces an “innovation paradox”: the returns to innovation are high, yet investment and the capacity to absorb new technologies remain low, according to Latin America and the Caribbean: Harnessing the AI Transition. Generative AI tools are spreading quickly, but many firms still use them for basic tasks rather than to transform core operations. More than four in 10 digitally connected workers cannot write a prompt that an AI system can usefully act on. Weak managerial know-how, organizational capital, and data capabilities are the main constraints. Governments can help by becoming anchor clients through agile public procurement and by offering technology-extension services to smaller firms. Short-cycle higher education, modernized vocational training, and proactive reskilling will also matter as automation pressures grow. East Asia and Pacific: Riding the AI Wave East Asia and the Pacific plays an outsized role in the global AI supply chain, according to East Asia and Pacific: Riding the AI Wave. Its economies produce many of the semiconductors, electronics, and hardware powering the AI revolution, helping lift projected growth to 4.4% a year in 2026–28. But making AI-related goods is not the same as using AI widely. Adoption by firms and individuals still trails advanced economies because of high costs, limited knowledge, and privacy concerns. Expanding use beyond the technology sector will require stronger workforce skills and wider access. The region must also prepare for AI’s growing energy demand by strengthening power grids and scaling renewable generation. Putting AI to Work AI’s development impact will depend less on who can access the technology than who can use it well. Electricity, connectivity, data, skills, capable firms, and effective institutions will determine which economies turn AI into higher productivity, better jobs, and improved services. The policy mix will vary. Some countries must first connect citizens and stabilize power supplies; others need better data, management, regulation, or advanced skills. But the central lesson is the same. The AI wave is global, but readiness is built economy by economy.