IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v83y2025ics0160791x25002192.html

Institutional adaptability, skill-bias technological shifts, and energy efficiency in global decarbonization pathways: Exploring the role of artificial intelligence patents

Author

Listed:
  • Bergougui, Brahim

Abstract

The catalytic role of artificial intelligence patents (AIP) in accelerating global decarbonization pathways—through structural reductions in CO2 emissions—remains underexplored. Leveraging a panel of 29 countries (2005–2023), this study explores the effect of AIP on carbon mitigation. We find robust evidence that AIP drives significant emissions reductions, with results persisting across instrumental variable regressions, sensitivity analyses, and alternative model specifications. Mechanism tests reveal three decarbonization channels: AIP drives technological shift by favoring skilled labor and automating carbon-intensive routine tasks; institutional adaptability magnifies these decarbonization benefits; and AIP enhances systemic energy efficiency, evidenced by substantial reductions in both primary energy intensity and per capita CO2 emissions. Heterogeneity tests demonstrate that AIP's decarbonization impact is most pronounced in economies geographically proximate to the USA (the global AI innovation hub), in lower-income nations, and in countries with high fossil fuel dependency. Within AIP categories, energy-management patents yield the highest decarbonization returns. These findings underscore AI patents as critical yet underutilized tools for achieving net-zero transitions, with policy implications for targeted intellectual property incentives, global technology transfer, and institutional reforms to amplify decarbonization synergies.

Suggested Citation

  • Bergougui, Brahim, 2025. "Institutional adaptability, skill-bias technological shifts, and energy efficiency in global decarbonization pathways: Exploring the role of artificial intelligence patents," Technology in Society, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:teinso:v:83:y:2025:i:c:s0160791x25002192
    DOI: 10.1016/j.techsoc.2025.103029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X25002192
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techsoc.2025.103029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Song, Malin & Pan, Heting & Shen, Zhiyang & Tamayo-Verleene, Kristine, 2024. "Assessing the influence of artificial intelligence on the energy efficiency for sustainable ecological products value," Energy Economics, Elsevier, vol. 131(C).
    2. Daron Acemoglu & David Autor & Jonathon Hazell & Pascual Restrepo, 2022. "Artificial Intelligence and Jobs: Evidence from Online Vacancies," Journal of Labor Economics, University of Chicago Press, vol. 40(S1), pages 293-340.
    3. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    4. Nahar, Sharmin, 2024. "Modeling the effects of artificial intelligence (AI)-based innovation on sustainable development goals (SDGs): Applying a system dynamics perspective in a cross-country setting," Technological Forecasting and Social Change, Elsevier, vol. 201(C).
    5. Liu, Jun & Liu, Liang & Qian, Yu & Song, Shunfeng, 2022. "The effect of artificial intelligence on carbon intensity: Evidence from China's industrial sector," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    6. Danish I. Godil & Zhang Yu & Arshian Sharif & Rimsha Usman & Syed Abdul Rehman Khan, 2021. "Investigate the role of technology innovation and renewable energy in reducing transport sector CO2 emission in China: A path toward sustainable development," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(4), pages 694-707, July.
    7. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    8. Yanqiao Deng & Minda Ma & Nan Zhou & Zhili Ma & Ran Yan & Xin Ma, 2024. "China's plug-in hybrid electric vehicle transition: an operational carbon perspective," Papers 2405.07308, arXiv.org, revised Aug 2024.
    9. Cao, Qingfeng & Chi, Chuenyu & Shan, Junhui, 2025. "Can artificial intelligence technology reduce carbon emissions? A global perspective," Energy Economics, Elsevier, vol. 143(C).
    10. Xuli Tang & Xin Li & Feicheng Ma, 2022. "Internationalizing AI: evolution and impact of distance factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 181-205, January.
    11. Robles Carrillo, Margarita, 2020. "Artificial intelligence: From ethics to law," Telecommunications Policy, Elsevier, vol. 44(6).
    12. Silvio Traverso & Massimiliano Vatiero & Enrico Zaninotto, 2023. "Robots and labor regulation: a cross-country/cross-industry analysis," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 32(7), pages 977-999, October.
    13. Emily Oster, 2019. "Unobservable Selection and Coefficient Stability: Theory and Evidence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(2), pages 187-204, April.
    14. Shadi, Mohammad Reza & Mirshekali, Hamid & Shaker, Hamid Reza, 2025. "Explainable artificial intelligence for energy systems maintenance: A review on concepts, current techniques, challenges, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
    15. Wang, Tianyi & Ma, Minda & Zhou, Nan & Ma, Zhili, 2025. "Toward net zero: Assessing the decarbonization impact of global commercial building electrification," Applied Energy, Elsevier, vol. 383(C).
    16. Gruetzemacher, Ross & Dorner, Florian E. & Bernaola-Alvarez, Niko & Giattino, Charlie & Manheim, David, 2021. "Forecasting AI progress: A research agenda," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    17. Teece, David J., 2018. "Profiting from innovation in the digital economy: Enabling technologies, standards, and licensing models in the wireless world," Research Policy, Elsevier, vol. 47(8), pages 1367-1387.
    18. Shang, Yunfeng & Yang, Qin & Pu, Yuanjie & Taghizadeh-Hesary, Farhad, 2024. "Employing artificial intelligence and enhancing resource efficiency to achieve carbon neutrality," Resources Policy, Elsevier, vol. 88(C).
    19. Wang, Yong & Zhao, Wenhao & Ma, Xuejiao, 2024. "The spatial spillover impact of artificial intelligence on energy efficiency: Empirical evidence from 278 Chinese cities," Energy, Elsevier, vol. 312(C).
    20. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769, December.
    21. Mohamed Khaled Al-Jafari & Hatem Hatef Abdulkadhim Altaee, 2023. "The Role of Labor Productivity in Reducing Carbon Emission Utilizing the Method of Moments Quantile Regression: Evidence from Top 40 Emitter Countries," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 15(3), pages 1-1, March.
    22. Zhou, Huilin & Wang, Linhui & Cao, Yutong & Li, Jincheng, 2025. "The impact of artificial intelligence on labor market: A study based on bibliometric analysis," Journal of Asian Economics, Elsevier, vol. 98(C).
    23. Ran Yan & Nan Zhou & Minda Ma & Chao Mao, 2024. "India's residential space cooling transition: Decarbonization ambitions since the turn of millennium," Papers 2412.06360, arXiv.org, revised Mar 2025.
    24. Feng, Fangfang & Li, Junjun & Zhang, Feng & Sun, Jinghuan, 2024. "The impact of artificial intelligence on green innovation efficiency: Moderating role of dynamic capability," International Review of Economics & Finance, Elsevier, vol. 96(PB).
    25. Murtaza Hussain & Shaohua Yang & Umer Sahil Maqsood & R. M. Ammar Zahid, 2024. "Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4375-4396, July.
    26. Ding, Tao & Li, Jiangyuan & Shi, Xing & Li, Xuhui & Chen, Ya, 2023. "Is artificial intelligence associated with carbon emissions reduction? Case of China," Resources Policy, Elsevier, vol. 85(PB).
    27. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    28. Bergougui, Brahim, 2025. "Industrial robots for a sustainable future: Uncovering the asymmetric effects of AI on ecological quality in G7 economies," Technology in Society, Elsevier, vol. 83(C).
    29. Buhari Doğan & Sunil Tiwari & Brahim Bergougui & Sudeshna Ghosh & Daniel Balsalobre‐Lorente, 2025. "Green Innovation and Fiscal Spending: Decoding the Path to Sustainable Development," Sustainable Development, John Wiley & Sons, Ltd., vol. 33(4), pages 6307-6327, August.
    30. Yan, Ran & Zhou, Nan & Ma, Minda & Mao, Chao, 2025. "India's residential space cooling transition: Decarbonization ambitions since the turn of millennium," Applied Energy, Elsevier, vol. 391(C).
    31. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    32. Yanqiao Deng & Minda Ma & Nan Zhou & Chenchen Zou & Zhili Ma & Ran Yan & Xin Ma, 2024. "Provincial allocation of China's commercial building operational carbon towards carbon neutrality," Papers 2412.14523, arXiv.org, revised Jan 2025.
    33. Zhang, Hongyuan & Ding, Yibing & Niu, Jing & Jung, Samuel, 2024. "How artificial intelligence affects international industrial transfer — Evidence from industrial robot application," Journal of Asian Economics, Elsevier, vol. 95(C).
    34. Ina Ganguli & Jeffrey Lin & Nicholas Reynolds, 2020. "The Paper Trail of Knowledge Spillovers: Evidence from Patent Interferences," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 278-302, April.
    35. Qiang Wang & Yuanfan Li & Rongrong Li, 2024. "Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-18, December.
    36. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    37. Milad Abbasiharofteh & Tom Broekel & Lars Mewes, 2024. "The role of geographic distance and technological complexity in U.S. interregional co-patenting over almost two centuries," Environment and Planning A, , vol. 56(7), pages 2003-2022, October.
    38. Zaizhou Hu & Zengdong Cao & Anran Du & Qin Tu, 2025. "Where does it matter? Revisiting the role of proximity in knowledge spillovers," American Journal of Economics and Sociology, Wiley Blackwell, vol. 84(2), pages 297-322, March.
    39. Daron Acemoglu, 2002. "Technical Change, Inequality, and the Labor Market," Journal of Economic Literature, American Economic Association, vol. 40(1), pages 7-72, March.
    40. Sergiusz Pimenow & Olena Pimenowa & Piotr Prus, 2024. "Challenges of Artificial Intelligence Development in the Context of Energy Consumption and Impact on Climate Change," Energies, MDPI, vol. 17(23), pages 1-34, November.
    41. Jiao, Anqi & Lu, Juntai & Ren, Honglin & Wei, Jia, 2024. "The role of AI capabilities in environmental management: Evidence from USA firms," Energy Economics, Elsevier, vol. 134(C).
    42. Junhao Zhong & Yilin Zhong & Minghui Han & Tianjian Yang & Qinghua Zhang, 2024. "The impact of AI on carbon emissions: evidence from 66 countries," Applied Economics, Taylor & Francis Journals, vol. 56(25), pages 2975-2989, May.
    43. Chan, Keith Jin Deng & Papyshev, Gleb & Yarime, Masaru, 2024. "Balancing the tradeoff between regulation and innovation for artificial intelligence: An analysis of top-down command and control and bottom-up self-regulatory approaches," Technology in Society, Elsevier, vol. 79(C).
    44. Deng, Yanqiao & Ma, Minda & Zhou, Nan & Zou, Chenchen & Ma, Zhili & Yan, Ran & Ma, Xin, 2025. "Provincial allocation of China's commercial building operational carbon toward carbon neutrality," Applied Energy, Elsevier, vol. 384(C).
    45. Qi, Jianhong & Tan, Yong & Zhang, Zhitong, 2024. "The influence of industrial robots on firm-level pollution emissions: Evidence from China," Economic Modelling, Elsevier, vol. 133(C).
    46. Adam Jaffe & Richard Newell & Robert Stavins, 2002. "Environmental Policy and Technological Change," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 22(1), pages 41-70, June.
    47. Lee, Chien-Chiang & Qin, Shuai & Li, Yaya, 2022. "Does industrial robot application promote green technology innovation in the manufacturing industry?," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    48. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    49. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    50. Stephen Machin, 2008. "An Appraisal of Economic Research on Changes in Wage Inequality," LABOUR, CEIS, vol. 22(s1), pages 7-26, June.
    51. Hyuk-Soo Kwon & Jihong Lee & Sokbae Lee & Ryungha Oh, 2022. "Knowledge spillovers and patent citations: trends in geographic localization, 1976–2015," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 31(3), pages 123-147, April.
    52. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    53. David Mhlanga, 2023. "Artificial Intelligence and Machine Learning for Energy Consumption and Production in Emerging Markets: A Review," Energies, MDPI, vol. 16(2), pages 1-17, January.
    54. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Qingfeng & Chi, Chuenyu & Shan, Junhui, 2025. "Can artificial intelligence technology reduce carbon emissions? A global perspective," Energy Economics, Elsevier, vol. 143(C).
    2. Bergougui, Brahim, 2025. "Industrial robots for a sustainable future: Uncovering the asymmetric effects of AI on ecological quality in G7 economies," Technology in Society, Elsevier, vol. 83(C).
    3. Arntz, Melanie & Genz, Sabrina & Gregory, Terry & Lehmer, Florian & Zierahn-Weilage, Ulrich, 2024. "De-Routinization in the Fourth Industrial Revolution - Firm-Level Evidence," IZA Discussion Papers 16740, IZA Network @ LISER.
    4. Genz Sabrina & Janser Markus & Lehmer Florian, 2019. "The Impact of Investments in New Digital Technologies on Wages – Worker-Level Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(3), pages 483-521, June.
    5. Wang, Yong & Zhao, Wenhao & Ma, Xuejiao, 2024. "The spatial spillover impact of artificial intelligence on energy efficiency: Empirical evidence from 278 Chinese cities," Energy, Elsevier, vol. 312(C).
    6. Cao, Qingfeng & Ni, Pengfei & Guo, Jing, 2025. "Broadband internet and income inequality among the floating population: Evidence from the “broadband China” strategy in China," China Economic Review, Elsevier, vol. 90(C).
    7. Zhu, Junda & Yang, Junhong & Peng, Mengbo & Liang, Xinyue & Ben, Chaoran, 2025. "Deep learning-driven heat load prediction: Investigating the impacts of optimizer and learning rate scheduler strategies," Energy, Elsevier, vol. 340(C).
    8. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    9. Zou, Yanchi & Li, Kun & He, Lilong & Guo, Jiapei, 2025. "The employment effects of ICT investment: Evidence from the U.S. Commuting Zones," Economic Modelling, Elsevier, vol. 151(C).
    10. Zhou, Chaobo & Zhang, Haikuo & Ying, Jinhuika & He, Shouchao & Zhang, Chong & Yan, Jiale, 2025. "Artificial intelligence and green transformation of manufacturing enterprises," International Review of Financial Analysis, Elsevier, vol. 104(PA).
    11. Anastasiia Pustovalova & Priit Vahter, 2024. "Automation-Skill Complementarity: The Changing Returns To Soft Skills In Different Stages Of Technology Adoption," University of Tartu - Faculty of Economics and Business Administration Working Paper Series 146, Faculty of Economics and Business Administration, University of Tartu (Estonia).
    12. Genz Sabrina & Janser Markus & Lehmer Florian, 2019. "The Impact of Investments in New Digital Technologies on Wages – Worker-Level Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(3), pages 483-521, June.
    13. Yang, Kunyu & Kuang, Jinsong, 2025. "How artificial intelligence applications enhance enterprise green total factor productivity? A perspective on human-machine matching and labor skill structure," Economic Analysis and Policy, Elsevier, vol. 87(C), pages 926-947.
    14. Janssen, Simon & Mohrenweiser, Jens, 2018. "The Shelf Life of Incumbent Workers during Accelerating Technological Change: Evidence from a Training Regulation Reform," IZA Discussion Papers 11312, IZA Network @ LISER.
    15. Christoph Riedl & Eric Bogert, 2024. "Effects of AI Feedback on Learning, the Skill Gap, and Intellectual Diversity," Papers 2409.18660, arXiv.org.
    16. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2025. "What workers and robots do: An activity-based analysis of the impact of robotization on changes in local employment," Research Policy, Elsevier, vol. 54(1).
    17. Martin Lábaj & Tomáš Oleš & Gabriel Procházka, 2025. "Impact of robots and artificial intelligence on labor and skill demand: evidence from the UK," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 15(4), pages 953-1001, December.
    18. Emilio Colombo & Alberto Marcato, 2021. "Skill Demand and Labour Market Concentration: Theory and Evidence from Italian Vacancies," DISEIS - Quaderni del Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo dis2104, Università Cattolica del Sacro Cuore, Dipartimento di Economia internazionale, delle istituzioni e dello sviluppo (DISEIS).
    19. Thomsen, Stephan L, 2018. "Die Rolle der Computerisierung und Digitalisierung für Beschäftigung und Einkommen," Hannover Economic Papers (HEP) dp-645, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    20. Pi, Jiancai & Zhang, Pengqing, 2018. "Skill-biased technological change and wage inequality in developing countries," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 347-362.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:83:y:2025:i:c:s0160791x25002192. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.