The Economic Impact of AI on Development
Artificial intelligence is reshaping economic growth, work, and public services, and the gains are not arriving evenly. This page sets out what the World Bank and IMF data show, with an interactive dashboard and an Arab-region lens.
- 01
AI capacity is concentrated. High-income countries account for about 87 percent of notable AI models, 86 percent of AI start-ups, and 91 percent of venture capital funding, while holding about 17 percent of the world's population.
- 02
Exposure to AI is broad and uneven. The IMF estimates that about 40 percent of global employment is exposed to AI, close to 60 percent in advanced economies and about 26 percent in low-income countries.
- 03
Use is shifting toward developing markets. By mid-2025, more than 40 percent of global ChatGPT traffic came from middle-income countries, led by Brazil, India, Indonesia, and Vietnam.
- 04
Readiness has four parts. The IMF AI Preparedness Index measures digital infrastructure, human capital and labor-market policies, innovation and economic integration, and regulation and ethics.
- 05
Smaller, local AI can fit better. The World Bank argues that affordable, purpose-built AI in local languages, running on basic devices, is a more realistic path for many developing economies than large-scale systems.
of the world's notable AI models come from high-income countries, which hold about 17 percent of the global population.
World Bank, Digital Progress and Trends Report 2025of global employment is exposed to AI, rising to about 60 percent in advanced economies.
IMF, Staff Discussion Note on generative AI and the future of work (January 2024)growth in generative-AI job vacancies from 2021 to 2024, with about one in five of those roles in middle-income countries.
World Bank, Digital Progress and Trends Report 2025economies measured by the IMF AI Preparedness Index across four dimensions of readiness.
IMF, AI Preparedness Index01Explore AI readiness and its economic context
Select an indicator and a region lens to see how economies compare on the foundations for AI. Readiness scores come from the IMF, context indicators from the World Bank.
Loading the interactive dashboard.
What does AI readiness measure?
AI readiness has four parts. The IMF AI Preparedness Index scores each economy on digital infrastructure, human capital and labor policies, innovation and economic integration, and regulation and ethics.
How wide is the global AI divide?
The capacity to build AI is concentrated. High-income economies account for most AI models, start-ups, and venture funding, while holding a small share of the world's population.
02How the World Bank and IMF use AI and large language models
Both institutions treat AI as central to development and to their own operations. They study its economic effects, and they apply it inside their work.
How does the World Bank use AI?
The World Bank treats AI as a general-purpose technology and gives it a developing-country reading. Its World Development Report 2026 addresses AI for development directly. Inside the institution, the International Finance Corporation built an AI-powered ESG analysis tool trained on years of emerging-markets data and opened it to free public access as a public good.
The development-impact unit built a generative-AI research assistant grounded on a curated database of validated studies, so it summarizes evidence for policymakers without fabricating results. The same unit developed a news-driven early-warning approach that forecasts food crises ahead of traditional systems.
The World Bank also tests AI in the field. A randomized controlled trial in Edo State, Nigeria, used a GPT-4 assistant as a supervised after-school tutor and recorded large learning gains at low cost, placing the program among the most cost-effective measured to improve learning. Across this work the Bank frames AI readiness around four foundations, connectivity, compute, context, and competency, and it argues for "Small AI": affordable, purpose-built tools in local languages that run on basic devices.
How does the IMF use AI?
The IMF measures readiness and analyzes AI's effect on work. Its AI Preparedness Index covers around 174 economies across four dimensions: digital infrastructure, human capital and labor-market policies, innovation and economic integration, and regulation and ethics.
IMF staff analysis on generative AI and the future of work produced the headline exposure figures: about 40 percent of global employment is exposed to AI, close to 60 percent in advanced economies, around 40 percent in emerging-market economies, and about 26 percent in low-income countries. The same analysis notes that AI can both displace and complement jobs, and warns it may widen inequality between and within countries without supportive policy. The IMF extends this work through analysis and capacity development with member countries.
What the two approaches share
Both institutions treat AI as a development question, not only a technology question. They pair public analysis with internal use, they ground their tools in validated data, and they place policy, skills, and infrastructure at the center of whether developing economies benefit. The common message is that capability without readiness widens gaps, and readiness is something governments can build.
03Common questions about AI and economic development
What is the impact of AI on economic development?
AI affects economic development unevenly. The capacity to build AI is concentrated in high-income countries, which account for about 87 percent of notable AI models and 91 percent of venture capital funding while holding about 17 percent of the world's population. At the same time, use is spreading to developing markets, and the IMF estimates that about 40 percent of global employment is exposed to AI. The economic result depends on whether developing economies build the infrastructure, skills, and governance to adopt AI on their own terms.
How are AI capabilities distributed between rich and developing countries?
AI capabilities are concentrated in high-income countries. According to the World Bank, high-income economies account for about 87 percent of notable AI models, 86 percent of AI start-ups, and 91 percent of venture capital funding, despite holding about 17 percent of the global population. This concentration is the central feature of the global AI divide.
How much of the labor market is exposed to AI in emerging markets?
About 40 percent of employment in emerging-market economies is exposed to AI, according to IMF staff analysis. The same analysis estimates exposure near 60 percent in advanced economies and about 26 percent in low-income countries, with roughly 40 percent of employment exposed worldwide. Exposure means a job overlaps with what AI can do, which can mean either displacement or support.
What is AI readiness and how is it measured?
AI readiness is a measure of how prepared an economy is to adopt and benefit from AI. The IMF measures it through the AI Preparedness Index, which covers around 174 economies across four dimensions: digital infrastructure, human capital and labor-market policies, innovation and economic integration, and regulation and ethics. A higher score signals stronger foundations for AI adoption.
How does the World Bank use AI?
The World Bank treats AI as central to development and uses it in its own work. Its World Development Report 2026 addresses AI for development. The International Finance Corporation released an AI-powered ESG analysis tool as a free public good. The development-impact unit built a research assistant grounded on a curated database of validated studies, and a news-driven early-warning approach for food crises. A randomized trial in Edo State, Nigeria, used a GPT-4 assistant as a supervised after-school tutor and recorded large learning gains at low cost.
How does the IMF use AI?
The IMF analyzes AI and applies it to its own analytical work. It publishes the AI Preparedness Index, which scores around 174 economies on four dimensions of readiness. Its staff analysis on generative AI and the future of work produced the headline exposure figures of about 40 percent of global employment, near 60 percent in advanced economies, and about 26 percent in low-income countries. The IMF also engages in analysis and capacity development on AI with member countries.
Data, vintage, and method
Every figure on this page carries a named source. Context indicators come live from the World Bank Indicators API and are cached for the site. Readiness scores come from the IMF AI Preparedness Index. Labor-market exposure figures come from IMF staff analysis. No figure is invented, estimated, or extrapolated. This page was last updated on 2026-06-21.
- World Bank Indicators API (live, 2010 to 2024): internet use, mobile subscriptions, R&D spending, GDP per capita, high-technology exports, labor productivity. data.worldbank.org
- World Bank, Digital Progress and Trends Report 2025: AI concentration, generative-AI vacancies, ChatGPT traffic, the four readiness foundations.
- World Bank, World Development Report 2026: AI for development.
- IMF AI Preparedness Index (2023): readiness scores and the four sub-indices, Arab economies in this build.
- IMF Staff Discussion Note (January 2024): AI labor-market exposure figures.
Source documents are named in full. The site owner confirms exact deep links to each document before publishing.
Shahzad Asghar
Shahzad Asghar leads data and digital solutions for a United Nations regional commission, with more than twenty years across the UN system in data, digital transformation, geospatial services, and cybersecurity governance. His work spans AI-enabled platforms, data engineering, and digital-government delivery across the Arab region.
Credentials include CISSP, PMP, TOGAF, and Azure Solutions Architect Expert.
Building AI policy or platforms for development?
If your work touches AI readiness, data systems, or digital government across the Arab region, start a conversation.
Connect with Shahzad Asghar