Rethinking Automation Risk in Ethiopia’s Labor Market
85% of jobs in Ethiopia were once estimated to be at risk of automation in early studies on automation risk in Ethiopia and the future of work in developing countries. That was 10 years ago. Today, with rapid advances in AI and job automation in Ethiopia, and evolving evidence on the future of work in Africa, is the country’s exposure to automation actually increasing or decreasing?
Ten years ago, a widely cited study from the Oxford Martin School, using World Bank data, estimated that as much as 85 percent of jobs in Ethiopia were at risk of automation, shaping early debates on automation risk in Ethiopia and the broader future of work in developing countries. The finding helped popularize concerns about “premature deindustrialization,” where job automation in low-income countries could outpace industrial growth before it fully matures. A decade later, with rapid advances in Generative AI (GenAI), AI-driven task automation, and digital technologies, alongside new research on task-based automation vs occupation-based automation, the key question is whether Ethiopia’s exposure to automation has intensified or declined.
Recent evidence suggests the answer is more nuanced than the original headline implies. Early studies like The Future of Employment relied on occupation-level analysis, meaning they assessed entire jobs as automatable or not. Recent research has shifted toward task-level analysis and occupational exposure metrics, which yield lower, more realistic estimates. For example, a 2025 analysis, based on financial and central bank data, finds that less than 10 percent of core job tasks can currently be fully automated by AI systems. This distinction matters because most jobs consist of a bundle of tasks, many of which remain resistant to automation due to social interaction, non-routine cognitive adaptability, or physical context.
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