Developing countries should prioritize interoperable Artificial Intelligence (AI) systems rather than pursue costly ambitions of technological sovereignty, according to the World Bank, which argues that relying on multiple providers could reduce dependence on major powers while accelerating digital transformation.
In its World Development Report 2026, the World Bank said low- and middle-income economies should resist the temptation to build every layer of the AI supply chain domestically, warning that the enormous costs of developing frontier AI models and data infrastructure place such ambitions beyond the reach of most countries. Instead, governments should focus on ensuring that AI systems from different providers can work together and be replaced without disrupting entire networks.
“A more practical way to reduce dependence on a single country is to buy models, cloud services, and other AI tools from many countries and make sure they can work together and be swapped out without requiring the entire system to be rebuilt,” the report said.
The World Bank warned that the concentration of AI capabilities in a handful of countries and companies poses strategic risks for developing economies, potentially increasing dependence on foreign technology and forcing poorer nations to choose between competing systems. At the same time, the concentration of expertise allows developing countries to customize existing technologies without spending billions of dollars building frontier models from scratch.
For most developing countries, the costs of pursuing technological independence are prohibitive. The report noted that the amount major technology companies are expected to spend on AI infrastructure in 2026 exceeds the size of many national economies.
Instead of pursuing what the report calls “AI sovereignty,” policymakers are encouraged to adopt an approach similar to the digital-payment systems developed in India and Brazil.
The World Bank highlighted India’s Unified Payments Interface, or UPI, and Brazil’s Pix payment network as examples of interoperable infrastructure that connects banks, fintech companies and payment applications through a common platform. The systems promote competition by allowing multiple providers to operate on the same network, making it easier to replace or add participants without rebuilding the entire ecosystem.
The report suggests that a similar model could be applied to artificial intelligence, enabling governments and businesses to diversify their technology suppliers while avoiding dependence on a single foreign provider.
The World Bank argues that developing economies should concentrate on adopting existing AI tools and adapting them to local needs rather than investing heavily in frontier technologies. Building cutting-edge models requires advanced semiconductor capacity, massive datasets, data centers and world-class researchers, resources available to only a handful of countries and corporations.
The report warned that countries that delay adopting AI risk repeating the mistakes of previous technological revolutions. It noted that nations that failed to invest in the infrastructure and institutions required by earlier innovations, such as steam power and electricity, suffered widening economic gaps that persisted for generations.
For developing economies, the World Bank said, interoperability offers a middle path between technological dependence and the expensive pursuit of self-sufficiency, allowing countries to benefit from AI while preserving flexibility in an increasingly fragmented digital landscape.
