AI and ESG - New Quality Productivity in Digital Economy

Da Huo (), Tianying Sun (), Wenjia Gu () and Aidi Tang ()
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Da Huo: International Business School, Beijing Foreign Studies University,No. 19, North Road, West Ring 3, Haidian District, Beijing, China, 100089
Tianying Sun: School of International Trade and Economics, Central University of Finance and Economics, No.39, South College Road, Haidian District, Beijing, China, 100081
Wenjia Gu: School of International Trade and Economics, Central University of Finance and Economics, No.39, South College Road, Haidian District, Beijing, China, 100081
Aidi Tang: School of International Trade and Economics, Central University of Finance and Economics, No.39, South College Road, Haidian District, Beijing, China, 100081

Journal for Economic Forecasting, 2025, issue 2, 5-23

Abstract: This research examines AI adoption’s impact on corporate ESG performance using Lasso-based empirical analysis and data science methodologies. Results confirm AI significantly enhances ESG performance, albeit with regional and sub-dimensional variations. AI technology based on 3D Unmanned Aerial Vehicle (UAV) programming is used to optimize pro-ESG development via single- and multi-objective approaches. Path simulations using Ant Colony Optimization (ACO), A*(Astar), and Rapidly-Exploring Random Tree (RRT) algorithms reveal regionally adaptive ESG patterns suited to hub-specific contexts, showing governance, efficiency, and demonstration effects. This study explores AI-driven sustainability, demonstrates interdisciplinary applications of 3D data and optimization technology in social computing science.

Keywords: AI; ESG; New Quality Productivity; Lasso; AI Computational Optimization (search for similar items in EconPapers)
JEL-codes: C61 F23 M14 O14 (search for similar items in EconPapers)
Date: 2025
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