Work

How does privacy protection affect the innovation performance of artificial intelligence corporations: empirical evidence from the personal information protection law

Year: 2026

Type: article

Abstract: As global data privacy protection regulations become increasingly stringent, privacy protection has emerged as a significant challenge for businesses. This study, based on AI companies listed on the Shanghai and Shenzhen A-share markets in China, empirically examines the impact of privacy protection on key technological innovation in AI firms and explores the underlying mechanisms through which this effect operates. The empirical results demonstrate that privacy protection significantly promotes innovation in key technological areas, especially in non-state-owned enterprises, non-loss-making firms, and firms with non-financial backgrounds, where the effect is particularly pronounced. Moreover, privacy protection indirectly drives core technological innovation by enhancing R&D investment, improving labor investment efficiency, and fostering a culture of collaboration. These findings underscore the importance of privacy protection not just as a compliance cost but as a strategic investment that can enhance long-term firm value. And it has important implications for investors, suggesting that privacy protection should be incorporated into investment evaluations and risk assessments, and can be a valuable signal of long-term sustainable growth.

Source: International Review of Economics & Finance

DOI: 10.1016/j.iref.2026.104991

Authors: Yanling Wang, Yingying Jiang, Kaili Li, Xiangjian Zhang

Institutions: Sun Yat-sen University, University of Macau, Beijing Institute of Technology, Shanghai University of Finance and Economics

Language: English

Topic: Firm Innovation and Growth

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,930