The core of the story is that AI in emerging markets will be driven by a mix of hard and soft infrastructure, digital public infrastructure, and practical AI building blocks, with both proprietary and open-source approaches playing a role to reduce costs and boost local control.

AI-enabled vertical solutions are expanding from enhanced software to AI-native firms, including fintech credit scoring in Africa and agritech yield prediction in South America.

To capture value, emerging markets must look beyond model hype to the full operating environment, including digital infrastructure, data, skills, and the actors connecting them.

Publication date for the report is July 5, 2026.

The article is part of a longer report and includes a call to elevate knowledge and leadership skills, though this is supplementary to the main points.

The report outlines three impact horizons: short-to-medium term gains from local adoption, medium-to-long term gains from developing domestic ecosystems, and long-term systemic gains from global diffusion.

A consolidated framing mirrors the structure of short- to medium-term productivity and service gains, followed by ecosystem development benefits, and culminating in global diffusion and new industries.

AI is evolving toward generative and agentic capabilities, with rapid global adoption and the potential for emerging markets to leapfrog in education, healthcare, and finance through holistic, task-defined AI and large datasets.

The handbook advocates validating product-market fit early, investing in local adaptation, and using open tools where appropriate.

Major challenges include fragmented markets, low purchasing power hindering monetization, concentration among a few global players, and rapid commoditization of models and infrastructure; the recommended actions emphasize early product-market validation, local adaptation, and open tools.

Sustainable AI in emerging markets requires cross-sector coordination among governments, businesses, investors, communities, and entrepreneurs to enable long-term economic transformation aligned with local needs.

A World Bank Group report argues that AI’s benefits depend on building sustainable local ecosystems, not just importing AI models, requiring investment in infrastructure, data, and skills.