How to Boost AI Investment in Emerging Markets?

The International Finance Corporation published a new handbook in May 2026 outlining a practical framework for accelerating AI investment in emerging markets, as countries weigh the risk of being left behind in a technology transition that is moving faster and proving more technically complex than previous waves of digital disruption.

The handbook, authored by Lana Graf, Anastasia Nedayvoda, and Eveline Smeets from the World Bank Group's Digital and AI Vice Presidency, is directed at investors, policymakers, and AI ecosystem builders seeking to assess where AI investment in developing countries can compound and where constraints are likely to slow or block scaling.

According to the handbook, its central argument is that sustainable AI ecosystems in emerging markets require more than access to cutting-edge models.

They depend on the right combination of hard infrastructure, data centers, high-performance computing, connectivity, soft infrastructure such as digital skills, accelerators, and research labs, and foundational digital systems including national identity, payments, and data exchange platforms.

Two Frameworks for Investment Decisions

The handbook proposes two complementary analytical lenses. The Ecosystem Lens maps the actors and capabilities needed to build a functioning AI innovation pipeline, from foundational model providers and MLOps platforms to vertical AI companies building sector-specific solutions in fintech, healthcare, agriculture, and education.

The Structural Elements Lens identifies the system-level conditions required to make that ecosystem sustainable over time, with particular focus on data availability and the energy and construction infrastructure that AI data centers demand.

The report argues the two lenses work together: early ecosystem wins justify infrastructure investment, and infrastructure upgrades unlock the next wave of AI solutions.

Viewed in isolation, each lens produces incomplete conclusions, the Ecosystem Lens can overstate momentum from isolated successes, while the Structural Elements Lens can become overly focused on constraints and miss local adaptability.

The Market Concentration Risk

The most significant structural risk the report identifies is market concentration. The global AI landscape is trending toward dominance by a small number of well-capitalized international players that disproportionately capture economic benefits.

For local AI innovators in emerging markets, this dynamic restricts competitive opportunities and limits growth. The report argues that addressing this imbalance requires regulatory intervention, strategic investment, and a deliberate focus on local adaptation and proprietary data, the assets that cannot be replicated by incumbents leveraging global network effects.

IFC committed a record $71.7 billion to private companies and financial institutions in developing countries in fiscal year 2025. The handbook represents an extension of that investment thesis into AI, offering a framework designed to help emerging markets shape their position in the global AI landscape before the window for doing so narrows.