Template-Type: ReDIF-Paper 1.0
Author-Name: Leonardo Gambacorta
Author-X-Name-First: Leonardo
Author-X-Name-Last: Gambacorta
Author-Name: Enisse Kharroubi
Author-X-Name-First: Enisse
Author-X-Name-Last: Kharroubi
Author-Name: Aaron Mehrotra
Author-X-Name-First: Aaron
Author-X-Name-Last: Mehrotra
Author-Name: Tommaso Oliviero
Author-X-Name-First: Tommaso
Author-X-Name-Last: Oliviero
Title: Artificial intelligence and growth in advanced and emerging economies: short-run impact
Abstract: This paper investigates whether the positive effects of generative artificial intelligence (gen AI) on growth rate of value added differ across countries in the short run. Using an empirical strategy inspired by Rajan and Zingales (1998) and a dataset covering 56 economies and 16 industries, we find that the differential growth effects arise from variations in sectoral exposure to cognitive and knowledge-intensive activities, differences in production structures, and countries' AI preparedness. Our results suggest that, on average, gen AI is likely to benefit advanced economies more than emerging market economies, thereby widening global income disparities in the near term.
Creation-Date: 2025-12
File-URL: https://www.bis.org/publ/work1321.pdf
File-Format: Application/pdf
File-Function: Full PDF document
File-URL: https://www.bis.org/publ/work1321.htm
File-Format: text/html
Number: 1321
Keywords: generative artificial intelligence, emerging market economies, economic growth; productivity differentials, technological readiness, sectoral exposure to AI
Classification-JEL: E24, O47, O57
Handle: RePEc:bis:biswps:1321