AI Adoption Depends on More Than Powerful Models

The global AI race is increasingly becoming a race for infrastructure as well as software. The World Bank's discussion of AI and inequality highlights a key issue: countries cannot fully benefit from advanced artificial intelligence simply by having access to the technology. They also need the digital foundations required to use it effectively. Reliable electricity, broadband connectivity, data systems and skilled workers all influence how quickly businesses can adopt new technologies. This creates an important distinction between access and adoption. A company may technically have access to an AI service through the internet, but that does not necessarily mean it has the data, employees or internal systems required to integrate AI into its operations. For developing economies, improving these foundations could produce benefits far beyond AI. Better digital infrastructure can support online education, electronic payments, remote work, e-commerce and government services. AI therefore has the potential to accelerate the return on investments already being made in digital infrastructure. But without those investments, countries risk falling behind. The same principle applies to education. AI tools can increase productivity, but workers still need enough knowledge to understand how to use them, evaluate outputs and incorporate them into real business processes. This means the global AI competition could increasingly resemble previous industrial transformations. Countries that build the necessary infrastructure early may attract investment and skilled workers, while those that fall behind may become dependent on imported technology. The World Bank's warning about inequality therefore has an infrastructure dimension. AI could become an engine of development, but only where the foundations exist to support it.