Artificial Intelligence and Corporate Sustainability: Shaping the Future of ESG in the Age of Industry 5.0
Abstract
ABSTRACT The growing concern about the disruptive potential of new technologies compels us to reconsider the impact of AI on sustainability. This study examines the development of AI within Chinese listed companies from two key perspectives: technology‐driven innovation and institutional responses, and analyzes their effects on corporate sustainability. The findings reveal that (i) AI significantly enhances corporate sustainability, particularly within the tertiary industry; (ii) both productivity and information transparency serve as positive mediators in this relationship; (iii) employee education plays a crucial role, with a higher proportion of employees holding bachelor's and master's degrees benefiting firms more significantly; (iv) at the institutional level, the degree of factor market development exhibits a notable heterogeneous effect, with cities having lower levels of factor market development showing a stronger contribution of AI to sustainability—likely due to the diminishing marginal effect of technology; and (v) proactive AI policies are instrumental in improving economic sustainability, underscoring the positive role of well‐targeted government intervention. This study offers both technical and policy insights for governments seeking to foster AI‐driven sustainability while ensuring that AI itself contributes to broader sustainable development goals.
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AI improves the efficiency of sustainable business model decision-making when deployed as a decision-support system that complements, rather than substitutes, human managerial judgment.
“AI improves the efficiency of sustainable business model decision-making when deployed as a decision-support system that complements, rather than substitutes, human managerial judgment.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
Hybrid AI systems introduce high implementation costs, governance complexity, and integration risks.
“However, hybrid systems introduce high implementation costs, governance complexity, and integration risks.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
Hybrid AI systems represent the most comprehensive approach to ESG-oriented decision support.
“Hybrid AI systems, discussed extensively by Wang et al. [51], represent the most comprehensive approach to ESG-oriented decision support.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
AI enhances decision effectiveness in sustainable business models when AI systems are explicitly aligned with ESG objectives rather than purely economic performance metrics.
“AI enhances decision effectiveness in sustainable business models when AI systems are explicitly aligned with environmental, social, and governance (ESG) objectives rather than purely economic performance metrics.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
The legitimacy of AI-enabled decision-making in sustainable business models is positively associated with the transparency, explainability, and governance of AI systems.
“The legitimacy of AI-enabled decision-making in sustainable business models is positively associated with the transparency, explainability, and governance of AI systems.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
From an SBM perspective, hybrid AI systems enable firms to align strategic, operational, and reporting-level sustainability decisions.
“From an SBM perspective, hybrid AI systems enable firms to align strategic, operational, and reporting-level sustainability decisions.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
Hybrid systems support holistic ESG assessment by capturing both narrative disclosures and performance metrics, thereby overcoming the siloed limitations of single-model approaches.
“They support holistic ESG assessment by capturing both narrative disclosures and performance metrics, thereby overcoming the siloed limitations of single-model approaches.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
AI contributes to sustainable business model innovation when conceptualized as a dynamic capability that enables continuous adaptation to environmental and social complexity.
“AI contributes to sustainable business model innovation when conceptualized as a dynamic capability that enables continuous adaptation to environmental and social complexity.”
From Artificial Intelligence in Managerial Decision-Making for Sustainable Business Models: A Systematic Literature Review (2026) · cites this paper as [51]
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References 72 · Cited by 55
- Authors
- Wang, Q., Qi, Y., & Li, R.
- Affiliations
- China University of Petroleum, East China (CN)
- Corresponding author
- Wang, Qiang
- Li, Rongrong
- Venue
- Sustainable Development
- Publisher
- Wiley
- Published
- 2025-09-20
- Volume
- 34
- Issue
- 1
- Pages
- 1-26
- ISSN
- 0968-0802 (ISSN-L)
- 1099-1719
- OpenAlex
- W4414376611
- Cited by
- 55
- References
- 72
- Citations by year
- 2026: 38 · 2025: 17
- FWCI
- 42.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Sustainable Development (publishedVersion)
- Funders
- National Natural Science Foundation of China (72574236)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Strategy and Management › Digital Economy and Transformation
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Sustainability and Innovation in Business
- Keywords
- artificial intelligence, corporate sustainability, ESG, Industry 5.0, Chinese listed companies, technology-driven innovation, institutional responses, productivity, information transparency, employee education, AI policy, economic sustainability, service sector
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