人工智能能为拉丁美洲和加勒比地区停滞不前的生产力做些什么？（英）2024

Investment Rating - The report does not explicitly provide an investment rating for the industry under discussion. Core Insights - The productivity growth in Latin America and the Caribbean (LAC) has stagnated since 1980, with income levels showing no convergence with the US, unlike emerging Asia and Europe [8][21] - The sluggish productivity growth is attributed to limited technology diffusion and a large informal sector, which hampers overall economic growth [9][10][19] - Artificial intelligence (AI) has the potential to enhance productivity in the formal sector, reduce informality, and facilitate economic convergence with advanced economies [14][20] Summary by Sections Low Productivity Growth in Latin America and the Caribbean - Labor productivity growth in LAC has been only 0.5 percent annually since 1980, compared to 4.2 percent in East Asia and 1.4 percent in the US [21] - The informal sector remains large, with informal firms being only 15 percent as productive as formal firms, limiting overall productivity growth [25][31] The Important Role of Technology Diffusion in Growth - The limited diffusion of technology is a key reason for low productivity growth in LAC, with IT adoption lagging behind advanced economies [12][11] - Historical patterns show that technology diffusion can account for significant income disparities between countries [41] The Difference AI Can Make - AI is expected to boost labor productivity growth similarly to past IT innovations, with the potential for rapid adoption due to lower capital requirements [13][14] - AI could enable LAC to leapfrog technologies, as seen in Brazil's digital payment system, Pix [14] Labor Market Implications of AI - AI may not necessarily reduce overall employment; instead, it could create new jobs while also leading to job polarization [15][16] - Jobs at high risk of automation are primarily in sectors like call centers, while jobs that benefit from AI are in areas like healthcare [17][18] Adoption of AI in LAC - LAC's exposure to AI is below 40 percent of the labor force, compared to 60 percent in advanced economies, indicating a risk of falling behind in AI adoption [19] - Factors hindering AI adoption include weak competition, regulatory issues, and a large informal sector [19] Policies to Achieve the Full Potential of AI - Policies should focus on enhancing technology diffusion, supporting workforce transitions, and addressing skills gaps through education and training [20] - Investments in digital infrastructure and measures to reduce labor market informality are essential for maximizing AI benefits [20]