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

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.

Authors

Institutions

Publication Details

Journal
Economic Analysis and Policy
Published
2025-02-21
DOI
https://doi.org/10.1016/j.eap.2025.02.029
Citations
19
Primary Topic
Economic and Technological Innovation
Type
article
Field-Weighted Citation Impact
59.49

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Meiying Huang, Bowen Li, Quan Li
19 citations
Economic Analysis and Policy
Economic and Technological Innovation
59.49
article

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

Meiying Huang, Bowen Li, Quan Li
article en
19 citations

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.

Economic Analysis and PolicyVol. 85
Lanzhou University (CN)
National Social Science Fund of China
Affordable and clean energy
Openalex Percentile: Top 0%
Economic and Technological Innovation
59.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.