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AI vs. ESG? Uncovering a Bidirectional Struggle in China’s Sustainable Finance

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  • Zizhe Du

    (School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

  • Chao Chen

    (Faculty of Business, City University of Macau, Macau 999078, China)

Abstract

As global discourse increasingly centers on environmental, social, and governance considerations, ESG investment has become a major trend in financial markets. Artificial intelligence (AI), through its rapid evolution, has exerted a transformative influence that continues to reshape the fundamental structures of this domain. This study investigates the dynamic relationship between AI and ESG investment indices in China, aiming to reveal the bidirectional causal linkages and time-dependent interactions between these two critical areas. In methods, we used four different parameter stability tests to indicate that the Granger causality test based on the full-sample VAR model may produce biased results. Therefore, we employed a bootstrap rolling-window subsample Granger causality test using data from January 2013 to September 2024 in China. The results reveal a significant dynamic relationship between ESG investment and AI. In key findings, we find that AI exerts a negative impact on ESG investment. AI development attracts substantial capital inflows that favor technological advancement and commercialization over long-term ESG investments. Meanwhile, ESG investment shows both positive and negative effects on AI. The positive effect indicates that ESG investment promotes AI research and applications emphasizing energy efficiency, data privacy, and fairness, thereby supporting the sustainable development of AI technologies. However, driven by short-term economic returns, strict ESG standards and compliance requirements may, in the short term, constrain the development of certain energy-intensive or emerging AI technologies. In economic and political implications, our study provides policymakers with scientific evidence to improve the ESG investment environment and to design balanced policies that support both AI development and sustainable investment practices. It underscores the necessity of promoting coordinated development between AI and ESG investment to achieve global sustainability goals and recommends measures to align short-term economic interests with long-term ESG objectives. This study is expected to serve as a scientific basis for ESG goal-setting and contribute to the realization of China’s dual-carbon goals. In particular, it facilitates the convergence of artificial intelligence technologies with sustainable development initiatives and tells the importance of responsible technological progress for global sustainable development.

Suggested Citation

  • Zizhe Du & Chao Chen, 2025. "AI vs. ESG? Uncovering a Bidirectional Struggle in China’s Sustainable Finance," Sustainability, MDPI, vol. 17(9), pages 1-23, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:9:p:4238-:d:1650987
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    as
    1. Pesaran, M. Hashem & Timmermann, Allan, 2005. "Small sample properties of forecasts from autoregressive models under structural breaks," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 183-217.
    2. Boschetti, Fabio & Price, Jennifer & Walker, Iain, 2016. "Myths of the future and scenario archetypes," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 76-85.
    3. Chen, Lei & Li, Ke & Chen, Shuying & Wang, Xiaofei & Tang, Liwei, 2021. "Industrial activity, energy structure, and environmental pollution in China," Energy Economics, Elsevier, vol. 104(C).
    4. Fu, Tong & Li, Zijun & Qiu, Zhaoxuan & Tong, Xinle, 2024. "The policy gap between finance and economy: Evidence from China's green finance policy," Energy Economics, Elsevier, vol. 134(C).
    5. Hao, Pu & Alharbi, Samar S. & Hunjra, Ahmed Imran & Zhao, Shikuan, 2025. "How do ESG ratings promote digital technology innovation?," International Review of Financial Analysis, Elsevier, vol. 97(C).
    6. Chen, Yan & Zhang, Ruiqian & Lyu, Jiayi & Hou, Yuqi, 2024. "AI and Nuclear: A perfect intersection of danger and potential?," Energy Economics, Elsevier, vol. 133(C).
    7. Xing Zhao & Yuanyuan Qian, 2024. "Does Digital Technology Promote Green Innovation Performance?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 7568-7587, June.
    8. Su, Chi-Wei & Khan, Khalid & Umar, Muhammad & Zhang, Weike, 2021. "Does renewable energy redefine geopolitical risks?," Energy Policy, Elsevier, vol. 158(C).
    9. Liu, Yajun & Zhang, Xiuwu & Shen, Yang, 2024. "Technology-driven carbon reduction: Analyzing the impact of digital technology on China's carbon emission and its mechanism," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    10. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    11. David L. McCollum & Wenji Zhou & Christoph Bertram & Harmen-Sytze Boer & Valentina Bosetti & Sebastian Busch & Jacques Després & Laurent Drouet & Johannes Emmerling & Marianne Fay & Oliver Fricko & Sh, 2018. "Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals," Nature Energy, Nature, vol. 3(7), pages 589-599, July.
    12. Ludovic Cassely & Sami Ben Larbi & Christophe Revelli & Alain Lacroux, 2021. "Corporate social performance (CSP) in time of economic crisis," Post-Print hal-03513326, HAL.
    13. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Arslanturk, Yalcin, 2010. "Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window," Energy Economics, Elsevier, vol. 32(6), pages 1398-1410, November.
    14. Zhang, Weike & Zeng, Ming, 2024. "Is artificial intelligence a curse or a blessing for enterprise energy intensity? Evidence from China," Energy Economics, Elsevier, vol. 134(C).
    15. Joakim Sandberg, 2011. "Socially Responsible Investment and Fiduciary Duty: Putting the Freshfields Report into Perspective," Journal of Business Ethics, Springer, vol. 101(1), pages 143-162, June.
    16. Hafize Nurgul Durmus Senyapar & Ramazan Bayindir, 2025. "The Energy Hunger Paradox of Artificial Intelligence: End of Clean Energy or Magic Wand for Sustainability?," Sustainability, MDPI, vol. 17(7), pages 1-32, March.
    17. Buchanan, Bonnie & Cao, Cathy Xuying & Chen, Chongyang, 2018. "Corporate social responsibility, firm value, and influential institutional ownership," Journal of Corporate Finance, Elsevier, vol. 52(C), pages 73-95.
    18. 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).
    19. S. Leanne Keddie & Michel Magnan, 2023. "Are ESG performance-based incentives a panacea or a smokescreen for excess compensation?," Sustainability Accounting, Management and Policy Journal, Emerald Group Publishing Limited, vol. 14(3), pages 591-634, June.
    20. Diks, Cees & Panchenko, Valentyn, 2006. "A new statistic and practical guidelines for nonparametric Granger causality testing," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1647-1669.
    21. David L. McCollum & Wenji Zhou & Christoph Bertram & Harmen-Sytze Boer & Valentina Bosetti & Sebastian Busch & Jacques Després & Laurent Drouet & Johannes Emmerling & Marianne Fay & Oliver Fricko & Sh, 2018. "Author Correction: Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals," Nature Energy, Nature, vol. 3(8), pages 699-699, August.
    22. Huynh, Toan Luu Duc & Hille, Erik & Nasir, Muhammad Ali, 2020. "Diversification in the age of the 4th industrial revolution: The role of artificial intelligence, green bonds and cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    23. Ghazi Shukur & Panagiotis Mantalos, 2000. "A simple investigation of the Granger-causality test in integrated-cointegrated VAR systems," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(8), pages 1021-1031.
    24. Zeng, Ming & Zhang, Weike, 2024. "Green finance: The catalyst for artificial intelligence and energy efficiency in Chinese urban sustainable development," Energy Economics, Elsevier, vol. 139(C).
    25. Ren, Hao, 2025. "ESG rating disagreement and corporate digital transformation," Finance Research Letters, Elsevier, vol. 75(C).
    26. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    27. Qiongzhi Liu & Jing Ren, 2023. "Local Fiscal Pressure and Enterprise Environmental Protection Investment under COVID-19: Evidence from China," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    28. Evgeny Burnaev & Evgeny Mironov & Aleksei Shpilman & Maxim Mironenko & Dmitry Katalevsky, 2023. "Practical AI Cases for Solving ESG Challenges," Sustainability, MDPI, vol. 15(17), pages 1-15, August.
    29. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    30. Anh, Dao Le Trang & Quang, Nguyen Thi Thieu & Anh, Nguyen Tuan, 2024. "Investment decision and efficiency: Global insights on manufacturing firms amidst energy uncertainties," Energy Economics, Elsevier, vol. 137(C).
    31. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
    32. Amir Amel-Zadeh & George Serafeim, 2018. "Why and How Investors Use ESG Information: Evidence from a Global Survey," Financial Analysts Journal, Taylor & Francis Journals, vol. 74(3), pages 87-103, July.
    33. David Silver & Aja Huang & Chris J. Maddison & Arthur Guez & Laurent Sifre & George van den Driessche & Julian Schrittwieser & Ioannis Antonoglou & Veda Panneershelvam & Marc Lanctot & Sander Dieleman, 2016. "Mastering the game of Go with deep neural networks and tree search," Nature, Nature, vol. 529(7587), pages 484-489, January.
    34. Qiang Wang & Tingting Sun & Rongrong Li, 2025. "Does Artificial Intelligence (AI) enhance green economy efficiency? The role of green finance, trade openness, and R&D investment," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-22, December.
    35. Qian Zhao & Chi-Wei Su & Jun-Mo Guo, 2024. "Does Technological Innovation Promote Renewable Energy Investment?," SAGE Open, , vol. 14(1), pages 21582440241, February.
    36. Su, Chi-Wei & Qin, Meng & Tao, Ran & Shao, Xue-Feng & Albu, Lucian Liviu & Umar, Muhammad, 2020. "Can Bitcoin hedge the risks of geopolitical events?," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
    37. Ting-Ting Li & Kai Wang & Toshiyuki Sueyoshi & Derek D. Wang, 2021. "ESG: Research Progress and Future Prospects," Sustainability, MDPI, vol. 13(21), pages 1-28, October.
    38. Dahlke, Johannes & Beck, Mathias & Kinne, Jan & Lenz, David & Dehghan, Robert & Wörter, Martin & Ebersberger, Bernd, 2024. "Epidemic effects in the diffusion of emerging digital technologies: evidence from artificial intelligence adoption," Research Policy, Elsevier, vol. 53(2).
    39. Ludovic Cassely & Sami Ben Larbi & Christophe Revelli & Alain Lacroux, 2021. "Corporate social performance (CSP) in time of economic crisis," Sustainability Accounting, Management and Policy Journal, Emerald Group Publishing Limited, vol. 12(5), pages 913-942, June.
    40. Zi Li & Lingyun He & Zhangqi Zhong & Yufei Xia, 2024. "Financial–industrial integration, green technology innovation, and enterprise’s green development performance: an empirical analysis of 625 listed industrial enterprises of China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(2), pages 4029-4054, February.
    41. Ludovic Cassely & Sami Ben Larbi & Christophe Revelli & Alain Lacroux, 2021. "Corporate social performance (CSP) in time of economic crisis," Sustainability Accounting, Management and Policy Journal, Emerald Group Publishing Limited, vol. 12(5), pages 913-942, June.
    42. Arthur Hughes & Michael A. Urban & Dariusz Wójcik, 2021. "Alternative ESG Ratings: How Technological Innovation Is Reshaping Sustainable Investment," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
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