The Exposure of Workers to Artificial Intelligence in Low- and Middle-Income Countries

Investment Rating - The report does not explicitly provide an investment rating for the industry analyzed. Core Insights - The labor market impacts of artificial intelligence (AI) are expected to be more limited in low- and middle-income countries (LMICs) compared to high-income countries (HICs), with only 12% of workers in low-income countries and 15% in lower-middle-income countries experiencing high exposure to AI [3][74]. - AI exposure is higher among women, urban workers, and those with higher education levels, indicating a disparity in how different demographic groups are affected by AI advancements [3][12][75]. - The analysis suggests that while AI may enhance productivity and automate certain tasks, it does not necessarily lead to job losses, as it could also augment worker productivity [3][12]. Summary by Sections Introduction - The report highlights the rapid development of AI, particularly generative AI, and its potential to transform jobs and economic structures, similar to historical technological revolutions [8][9]. Measuring AI Exposure and Labor Market Impacts - The study employs the AI Occupational Exposure (AIOE) index to assess the potential impact of AI on various occupations across 25 countries, representing a population of 3.5 billion people [10][30]. - The AIOE index indicates that high-income countries have the highest exposure to AI, with an average score of 62, while low-income countries have an average score of 37 [11][41]. Stylized Facts about AI in Low-, Middle-, and High-Income Countries - The average AIOE across all countries is 47, with significant variations based on income levels. High-income countries show a right-skewed distribution of AI exposure, while low-income countries exhibit a left-skewed distribution [39][41]. - The report categorizes AI exposure into four levels and finds that high-skilled occupations are more exposed to AI than low-skilled ones, with white-collar industries being the most affected [61][64]. Conclusion - The findings emphasize the need for tailored policy responses to manage AI's impact on the workforce, particularly in LMICs, where infrastructure challenges such as lack of electricity may hinder AI adoption [74][76]. - The report concludes that fears of significant labor market disruptions in LMICs due to AI may be overstated, suggesting that the immediate effects may be more about improving access to services rather than widespread job losses [78].