Author
Listed:
- Zhen-Yuan Ralph Liu
(CUMT - China University of Mining and Technology)
- Yu-Ting Wang
(NFU - Nanjing Forestry University)
- Jia-Jia Yan
(School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350116, China and Engineering Research Center for Metal Rubber, Fuzhou University, Fuzhou 350116, China., Fuzhou University [Fuzhou])
- Shivam Gupta
(NEOMA - Neoma Business School)
- Mihalis Giannakis
(Audencia Business School)
Abstract
Despite the extensive discussions of human-centric AI (HCAI) in Industry 5.0, its effects on firms' idiosyncratic risks (IR) remains underexplored. This is an imperative issue for firms navigate financial risks during the current technological revolution, as IR reflects investor reactions to corporate heterogeneous AI strategies and implementations by isolating firm-level stock volatility from systematic factors. Integrating situated AI theory with social-technical systems theory, we conceptualise HCAI as a situated AI strategy that reduces AI-related ethical risks and fosters AI-Human synergies in firms' business operations, ultimately reducing IR by aligning with stakeholders' diverse expectations. Moreover, socio-technical factors, namely digitalisation, operational efficiency, executive shareholding, and CEOs with IT background, may moderate the HCAI-IR relationship. Using a multi-source panel dataset of Chinese listed firms from 2015 to 2023, we find that HCAI is associated with lower firm IR. Furthermore, digitalisation and executive shareholding strengthen this risk-reducing effect, whereas operational efficiency and CEOs with IT background surprisingly attenuate it. Our findings offer theoretical contributions and practical insights for both ethical AI governance and firm financial risk management in the AI era.
Suggested Citation
Zhen-Yuan Ralph Liu & Yu-Ting Wang & Jia-Jia Yan & Shivam Gupta & Mihalis Giannakis, 2026.
"Exploring the relationship between human-centric AI and firm idiosyncratic risks,"
Post-Print
hal-05665153, HAL.
Handle:
RePEc:hal:journl:hal-05665153
DOI: 10.1007/s10796-026-10759-7
Note: View the original document on HAL open archive server: https://hal.science/hal-05665153v1
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