About the Journal
In Memory of Professor Jerzy Radecki
Ownership and Management Statement
Editorial Office
Editorial Board
Scope
Impact Factor
Indexed by
Journal Impact Factor contributing items
Publication Frequency
Revenue Sources & Business Model
Contact
Subscription
Current issue
Online first
Instructions for Authors
Copyright & Licensing
Publication Fees
Editorial policies
Publication Policy Overview
Peer Review Policy
Research Ethics and Malpractice Policy
Plagiarism Policy
Conflict of Interest Policy
Open Access Policy
Instructions for Reviewers
Generative AI and AI-Assisted Technologies Policy
Advertising Policy
Direct Marketing & Manuscript Solicitation
Digital Archiving and Preservation Policy
CrossMark, Correction, and Retraction Policy
Archive
Publication Fees
Copyright & Licensing
Editorial policies
Publication Policy Overview
Peer Review Policy
Research Ethics and Malpractice Policy
Plagiarism Policy
Conflict of Interest Policy
Open Access Policy
Instructions for Reviewers
Generative AI and AI-Assisted Technologies Policy
Advertising Policy
Direct Marketing & Manuscript Solicitation
Digital Archiving and Preservation Policy
CrossMark, Correction, and Retraction Policy
eISSN: 2083-5906
ISSN: 1230-1485
ISSN: 1230-1485
ORIGINAL RESEARCH
Artificial Intelligence and Carbon Emission
Embodied in Manufacturing Production:
Effect and Impact Mechanism
1
School of Economics, Central University of Finance and Economics, Beijing 102206, China
2
School of Economics and Management, Yantai Institute of Technology, Yantai 264003, Shandong, China
Submission date: 2025-06-05
Final revision date: 2025-12-11
Acceptance date: 2026-02-08
Online publication date: 2026-05-21
Corresponding author
Chunlei Zhao
School of Economics and Management, Yantai Institute of Technology, Yantai 264003, Shandong, China
School of Economics and Management, Yantai Institute of Technology, Yantai 264003, Shandong, China
KEYWORDS
TOPICS
ABSTRACT
At present, the deep integration of artificial intelligence and manufacturing has become an important
engine for global green development. Based on data from 54 countries worldwide, this paper finds that
AI has a significant inhibitory effect on carbon emissions embodied in manufacturing production.
Mechanism analysis indicates that this abatement effect is realized by improving production technology
levels, promoting the optimization and upgrading of industrial structure, and strengthening industrial
agglomeration. Heterogeneity tests show that while these decarbonization benefits are particularly
pronounced in high-income economies and nations with advanced AI adoption, the impact varies
considerably across individual countries and different industries. Finally, the paper finds that “Industry
4.0” policies enhance the carbon reduction potential of AI, with the effect reaching its peak in the
fourth lag period. Therefore, only by fully leveraging the technological dividends of AI and enhancing
the transmission effect of production technology, industrial structure optimization, and industrial
agglomeration can the potential of AI in manufacturing carbon reduction be better released.
CONFLICT OF INTEREST
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
REFERENCES (55)
1.
JU S., ANDRIAMAHERY A., QAMRUZZAMAN M., KOR S. Effects of financial development, FDI and good governance on environmental degradation in the Arab nation: Dose technological innovation matters? Frontiers in Environmental Science, 11, 1094976, 2023.
2.
HUANG G., HE L Y., LIN X. Robot adoption and energy performance: Evidence from Chinese industrial firms. Energy Economics, 107, 105837, 2022.
3.
ZHOU W., ZHUANG Y., CHEN Y. How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology. Energy Economics, 131, 107355, 2024.
4.
OSUMI Y. Robotics, Skill-Biased Technology and Labor Shares: A Four-Factor Case. Structural Change, Market Concentration, and Inequality: A Multi-sector Analysis, 1st Ed.; Springer: Singapore, Singapore, pp. 75-88, 2024.
5.
XU X., SONG Y. Is There a Conflict between Automation and Environment? Implications of Artificial Intelligence for Carbon Emissions in China. Sustainability, 15 (16), 12437, 2023.
6.
LV H., SHI B., LI N., KANG R. Intelligent Manufacturing and Carbon Emissions Reduction: Evidence from the Use of Industrial Robots in China. International Journal of Environmental Research and Public Health, 19 (23), 15538, 2022.
7.
CHEN P., GAO J., JI Z., LIANG H., PENG Y. Do Artificial Intelligence Applications Affect Carbon Emission Performance? - Evidence from Panel Data Analysis of Chinese Cities. Energies, 15 (15), 5730, 2022.
8.
MA'RUF A., LEUVEANO R.A.C., RIZKY U. Product design cost estimation for make-to-order industry: a machine learning approach. Emerging Sci, 8 (3), 1167, 2024.
9.
ZHANG X., ZHU H. The Impact of Industrial Intelligence on Carbon Emissions: Evidence from the Three Largest Economies. Sustainability, 15 (7), 6316, 2023.
10.
FREITAG C., BERNERS-LEE M., WIDDICKS K., KNOWLES B., BLAIR G.S., FRIDAY A. The real climate and transformative impact of ICT: A critique of estimates, trends, and regulations. Patterns, 2 (9), 2021.
11.
LUAN F., YANG X., CHEN Y., REGIS P.J. Industrial robots and air environment: A moderated mediation model of population density and energy consumption. Sustainable Production and Consumption, 30, 870, 2022.
12.
LIU B., YANG X., ZHANG J. Nonlinear effect of industrial robot applications on carbon emissions: Evidence from China. Environmental Impact Assessment Review, 104, 107297, 2024.
13.
SHEN Y., YANG Z. Chasing Green: The Synergistic Effect of Industrial Intelligence on Pollution Control and Carbon Reduction and Its Mechanisms. Sustainability, 15 (8), 6401, 2023.
14.
CHENG Y., ZHANG Y., WANG J., JIANG J. The impact of the urban digital economy on China's carbon intensity: spatial spillover and mediating effect. Resources, Conservation and Recycling, 189, 106762, 2023.
15.
LI Z., WANG J. The dynamic impact of digital economy on carbon emission reduction: evidence city-level empirical data in China. Journal of Cleaner Production, 351, 131570, 2022.
16.
AHMAD T., ZHU H., ZHANG D., TARIQ R., BASSAM A., ULLAH F., ALSHAMRANI S.S. Energetics Systems and artificial intelligence: Applications of industry 4.0. Energy Reports, 8, 334, 2022.
17.
JIN W. Unveiling the impact of industrial robots on consumption-based embodied carbon intensity: A global perspective. Energy Strategy Reviews, 54, 101484, 2024.
18.
LI Y., ZHANG Y., WU X. Does the application of industrial robots reduce the intensity of CO₂ emissions embodied in manufacturing exports? Data Science and Management, 8 (2), 117, 2024.
19.
TANG Z., TANG S., ZOU J. Artificial intelligence and global embodied carbon flow: Evidence from the application of industrial robots. Habitat International, 165, 103560, 2025.
20.
GHOBAKHLOO M., FATHI M. Industry 4.0 and opportunities for energy sustainability. Journal of Cleaner Production, 295, 126427, 2021.
21.
LI Y., ZHANG Y., PAN A., HAN M., VEGLIANTI E. Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms. Technology in Society, 70, 102034, 2022.
22.
GENG W., LIU X., LIAO X. Mechanism analysis of the influence of intelligent manufacturing on carbon emission intensity: evidence from cross country and industry. Environment, Development and Sustainability, 26, 15777, 2024.
23.
ZHONG J., ZHONG Y., HAN M., YANG T., ZHANG Q. The impact of AI on carbon emissions: evidence from 66 countries. Applied Economics, 56 (25), 2975, 2024.
24.
CHEN Y., DU D., ZHANG Q., LI X. Global industrial robots trade network structure and its impact on manufacturing carbon intensity. Technology in Society, 102981, 2025.
25.
ZHANG Y., ZHU J., WANG S. Industrial robots reduce carbon emissions in manufacturing through global value chains. Scientific Reports, 15 (1), 27602, 2025.
26.
LONG G., DUAN D., WANG H., CHEN S. The impact of industrial robots on low-carbon green performance: Evidence from the belt and road initiative countries. Technology in Society, 79, 102712, 2024.
27.
YAO W., LIU L., FUJII H., LI L. Digitalization and net-zero carbon: The role of industrial robots towards carbon dioxide emission reduction. Journal of Cleaner Production, 450, 141820, 2024.
28.
LI X., TIAN Q. How Does Usage of Robot Affect Corporate Carbon Emissions? - Evidence from China's Manufacturing Sector. Sustainability, 15 (2), 1198, 2023.
29.
LIU Z., MA X., GONG J. AI-Powered Carbon Mitigation: Charting the Green Inflection Point of Manufacturing in the Intelligent Economy Era. Sustainability, 18 (4), 1971, 2026.
30.
BOGACHOV S., KWILINSKI A., MIETHLICH B., BARTOSOVA V., GURNAK A. Artificial intelligence components and fuzzy regulators in entrepreneurship development. Entrepreneurship and Sustainability Issues, 8 (2), 487, 2020.
31.
LI J., HERDEM M.S., NATHWANI J., WEN J.Z. Methods and applications for Artificial Intelligence, Big Data, Internet of Things, and Blockchain in smart energy management. Energy and AI, 11, 100208, 2023.
32.
YE Z.P., YANG J.Q., ZHONG N., TU X., JIA J.N., WANG J.D. Tackling environmental challenges in pollution controls using artificial intelligence: A review. Science of the Total Environment, 699, 134279, 2020.
33.
WANG L., LUO G., SARI A., SHAO X.F. What nurtures fourth industrial revolution? An investigation of economic and social determinants of technological innovation in advanced economies. Technological Forecasting and Social Change, 161, 120305, 2020.
34.
CHEN Y., JIN S. Artificial Intelligence and Carbon Emissions in Manufacturing Firms: The Moderating Role of Green Innovation. Processes, 11 (9), 2705, 2023.
35.
RAMMER C., FERNANDEZ G.P., CZARNITZKI D. Artificial intelligence and industrial innovation: Evidence from German firm-level data. Research Policy, 51 (7), 104555, 2022.
36.
DEHDAR F., SILVA N., FUINHAS J.A., KOENGKAN M., NAZEER N. The Impact of Technology and Government Policies on OECD Carbon Dioxide Emissions. Energies, 15 (22), 8486, 2022.
37.
TIAN X., BAI F., JIA J., LIU Y., SHI F. Realizing low-carbon development in a developing and industrializing region: Impacts of industrial structure change on CO₂ emissions in southwest China. Journal of Environmental Management, 233, 728, 2019.
38.
FAN G., ZHU A., XU H. Analysis of the Impact of Industrial Structure Upgrading and Energy Structure Optimization on Carbon Emission Reduction. Sustainability, 15 (4), 3489, 2023.
39.
GAO X., LI C., ELAHI E., ABRO M.I., CUI Z. Technological Innovation, Product Quality and Upgrading of Manufacturing Value Chain: Empirical Evidence from China. Sustainability, 15 (9), 7289, 2023.
40.
ZOU W.Y., XIONG Y.J. Does artificial intelligence promote industrial upgrading? Evidence from China. Economic Research-Ekonomska Istraživanja, 36 (1), 1666, 2023.
41.
WANG M., ZHANG M., CHEN H., YU D. How Does Digital Economy Promote the Geographical Agglomeration of Manufacturing Industry? Sustainability, 15 (2), 1727, 2023.
42.
DU M., ZHANG Y., DONG H., ZHOU X.J. Heterogeneous impact of artificial intelligence on carbon emission intensity: Empirical test based on provincial panel data in China. Frontiers in Ecology and Evolution, 11, 1058505, 2023.
43.
ANDREONI J., LEVINSON A. The Simple Analytics of the Environmental Kuznets Curve. Journal of Public Economics, 80 (2), 269, 2001.
44.
HOU J., TEO T.S.H., ZHOU F., LIM M.K., CHEN H. Does Industrial Green Transformation Successfully Facilitate a Decrease in Carbon Intensity in China? An Environmental Regulation Perspective. Journal of Cleaner Production, 184, 1060, 2018.
45.
FU Y., WANG Z. The Impact of Industrial Agglomeration on Urban Carbon Emissions: An Empirical Study Based on the Panel Data of China's Prefecture-Level Cities. Sustainability, 16 (23), 10270, 2024.
46.
HOSOE M., NAITO T. Trans-Boundary Pollution Transmission and Regional Agglomeration Effects. Papers in Regional Science, 85 (1), 99, 2006.
47.
WANG Q., HAN X. Is decoupling embodied carbon emissions from economic output in Sino-US trade possible? Technological Forecasting and Social Change, 169, 120805, 2021.
48.
GRAETZ G., MICHAELS G. Robots at work. Review of Economics and Statistics, 100 (5), 753, 2018.
49.
JURKAT A., KLUMP R., SCHNEIDER F. Tracking the Rise of Robots: The IFR Database. Jahrbücher für Nationalökonomie und Statistik, 242 (5-6), 669, 2022.
50.
BUSSE J. Trade, environmental regulations and the World Trade Organization: New empirical evidence. Journal of World Trade, 38 (2), 285, 2004.
51.
WANG E.Z., LEE C.C., LI Y. Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries. Energy Economics, 105, 105748, 2022.
52.
NUNN N., NANCY Q. US food aid and civil conflict. American Economic Review, 104 (6), 1630, 2014.
53.
ING L.Y., GROSSMAN G.M. Robots and AI: A New Economic Era, 1st Ed.; Routledge: London, UK, pp. 1-370, 2022.
54.
BUER S.V., STRANDHAGEN J.O., CHAN F.T.S. The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. International Journal of Production Research, 56 (8), 2924, 2018.
55.
MORALLES H.F., DO NASCIMENTO REBELATTO D.A. The effects and time lags of R&D spillovers in Brazil. Technology in Society, 47, 148, 2016.
Share
RELATED ARTICLE
| eISSN: | 2083-5906 |
| ISSN: | 1230-1485 |
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
