Ethiopia is among the world’s lowest-performing countries in artificial intelligence (AI) readiness, trailing on both scale and intensity of AI capacity, according to a World Bank assessment.
The 2025 edition of the Digital Progress and Trends Report places Ethiopia at the bottom tier globally, highlighting deep structural gaps in connectivity, computing power, data availability, and digital skills that threaten to widen economic and social inequality.
The report classifies Ethiopia as a low-income country underperforming on both dimensions of AI readiness, meaning it lacks not only the market size and infrastructure to develop AI technologies, but also the per-capita capacity needed to adopt and use AI across public services, businesses, and daily life.
“Low income countries such as Ethiopia and Kenya underperform on both scale and intensity, highlighting the need to invest in foundational enablers such as affordable and high-quality broadband, digital literacy, and workforce skills,” the report states.
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The World Bank warns that countries with limited AI foundations risk becoming permanent consumers of foreign AI platforms, rather than creators or shapers of technology suited to local needs. Ethiopia’s small and fragmented digital market, combined with limited computing infrastructure and skills shortages, places it firmly in this vulnerable category.
According to the report, countries that lack sufficient AI “intensity” often see adoption confined to elite institutions or a few urban centers, leaving most of the economy untouched by productivity gains. For Ethiopia, this means AI deployment risks deepening urban-rural and income divides rather than closing them.
A central barrier identified is Ethiopia’s limited access to compute, including both domestic data centers and affordable cloud services. The report notes that data centers are capital- and energy-intensive, requiring stable electricity and high-quality internet connectivity—conditions that remain unreliable in many low-income countries.
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More than 60 percent of developing countries face serious energy security challenges, undermining the viability of infrastructure investment, the report adds, citing International Energy Agency data. Without stable power and predictable regulation, Ethiopia risks being locked out of large-scale AI deployment.
Even where infrastructure exists, Ethiopia faces a scarcity of advanced digital and AI skills, according to the report’s analysis of workforce competency. Limited access to advanced training, under-resourced educational institutions, and ongoing brain drain to higher-income countries further weaken the country’s capacity to manage and adapt AI systems.
The World Bank cautions that AI systems require specialized, often tacit expertise to operate effectively, and without domestic capacity, countries risk dependency on external providers.
The report also flags language and data gaps as major constraints for countries like Ethiopia, where many local languages are underrepresented in global AI training data. Without localized datasets and models adapted to national contexts, AI tools risk excluding large segments of the population, particularly in education, agriculture, and public services.
“Without dedicated investments in local language models and culturally relevant interfaces, AI risks replicating and even reinforcing existing inequities,” the report warns.
The World Bank concludes that Ethiopia’s pathway to benefiting from AI lies not in frontier innovation, but in urgent investment in foundational enablers—reliable connectivity, affordable compute, robust data governance, and large-scale digital skills development.
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