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From algorithms to green growth: Can artificial intelligence drive enterprise energy transformation?

Year: 2025

Type: article

Abstract: As global priorities shift towards sustainability and climate change mitigation, the impact of artificial intelligence (AI) as an emerging technological force on enterprise energy transformation (EET) remains insufficiently explored. This study treats the “Smart Manufacturing Pilot Policy” as a quasi-natural experiment, uses data from A-share listed companies between 2007 and 2022, and applies the standard Difference-in-Differences model to examine the impact of AI on EET. The findings reveal that AI adoption significantly enhances EET, with more pronounced effects observed in state-owned enterprises, firms in eastern and coastal regions, and those with advanced digital transformation. Four key mechanisms are identified: fostering green technology innovation, enhancing human capital structure, improving environmental information disclosure, and reducing financing constraints. Overall, this study provides novel insights into the economic impact of AI and offers a framework for sustainable, energy-efficient development that can be applied to countries with similar economic structures and development trajectories.

Source: Economic Analysis and Policy

DOI: 10.1016/j.eap.2025.02.029

Authors: Meiying Huang, Quan Li, Bowen Li

Institution: Lanzhou University

Language: English

Topic: Energy, Environment, Economic Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Climate action, Affordable and clean energy, Decent work and economic growth

Open Access status: hybrid

Estimated APC paid: $2,890