How can AI be used to deliver better public services? That’s one of the big questions for developing countries. Governments are already experimenting with AI in areas ranging from tutoring and medical diagnosis to weather forecasting and administrative tasks, and some applications are yielding tangible benefits. In Ghana, the Rori math tutor, delivered by text message on basic cell phones, produced nearly a full year of learning gains in mathematics at US$5 per student. In Bangladesh, AI-supported medical imaging increased the number of patients screened for diabetic retinopathy by 39.5 percent per day.
For most governments, the next step is the challenge: How to move from relatively small-scale experiments with AI to identifying the applications that create value and expand their rollout from a few hundred users to millions. Building that capacity requires improving systems to buy, test, evaluate, and integrate AI solutions into public service delivery – and that is what can help them move from pilots to scale. The World Development Report 2026: The Promise of Artificial Intelligence articulates a sequence of five steps.
Step 1: Match AI to the problem
AI is not the right answer to every problem. Putting AI on top of a poorly designed process can simply automate existing inefficiencies. Governments should start with three basic questions:
- What problem are we trying to solve?
- Would AI improve the outcome compared with simpler alternatives, and at what cost?
- What complementary changes, such as better data, redesigned workflows, skills, or connectivity, would be needed?
The right opportunity also depends on which type of AI is being considered. Revenue authorities around the world have used machine learning algorithms to analyze historical data on tax returns to uncover compliance risks that manual audits missed. Predictive AI models like this suit agencies that have large, structured data sets and clearly defined outcomes to predict. Generative AI can be better suited to language-intensive tasks, such as drafting, translating, or answering citizens’ queries.
Step 2: Build AI-ready data
In Brazil, the VICTOR system that converts scanned court documents into machine-readable text has reduced the amount of time it takes to determine eligibility for an appeal to the Brazilian Supreme Federal Court from 40 minutes to just 5 seconds. But this is the exception rather than the norm. Governments across developing economies identify data quality and availability as the most common barriers to using AI in their internal operations (see figure 1). Getting AI solutions off the ground will require investments to build AI-ready data: from digitizing information—drawing on censuses, tax records, birth and death registries, land records, and social programs—to improving the use of management information systems and connecting data across government agencies.
