ORIGINAL RESEARCH article
Front. Public Health
Sec. Health Economics
This article is part of the Research TopicLow Carbon Economy and Public Health in the Age of Artificial IntelligenceView all articles
Artificial Intelligence, Green Innovation Efficiency, and Public Health Benefits: Evidence from China's Pilot Zones with a DID Approach
Provisionally accepted
- 1Weifang University of Science and Technology, Shouguang, China
- 2Nanjing Agricultural University, Nanjing, China
- 3Shanghai Institute of Technology, Shanghai, China
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Introduction: China has established Artificial Intelligence Innovation and Development Pilot Zones (AIDP) to promote industrial upgrading and digital transformation. This study evaluates whether these AI oriented policies enhance firm-level green innovation efficiency (GIE) and generate potential environmental and health benefits. Methods: Using panel data of Chinese firms from 2011 to 2022, we employed a difference-in-differences (DID) design exploiting the staggered implementation of AIDP as a quasi-experiment. The estimation identifies the causal effects of AIDP on green R&D efficiency and green innovation output efficiency, measured by DEA-based indicators and patent productivity. Results: The DID estimates show that AIDP increases firms' green R&D efficiency by approximately 1.7% and green innovation output efficiency by 1.4% relative to non-pilot firms, corresponding to the DID coefficients of 0.017 and 0.014. These effects are primarily driven by enhanced AI hardware investment, improved asset liquidity, and strengthened ESG performance, which together boost firms' digital capability, operational efficiency, and sustainability orientation. Mechanism analysis further indicates that these improvements reduce pollution intensity and support cleaner production processes, suggesting potential environmental and health benefits inferred from pollution reduction. Heterogeneity analysis reveals that the treatment effects are larger among non-state-owned enterprises, manufacturing firms, and labor-intensive sectors, underscoring the importance of tailoring interventions to sectoral and institutional contexts. Conclusion: AIDP generates economically and statistically significant improvements in green innovation efficiency, confirming the potential of AI oriented policies to promote sustainable industrial transformation. By fostering green technologies that cut emissions and reduce industrial pollution, these policies deliver dual dividends: advancing environmental sustainability and supporting public health. The findings highlight the importance of expanding pilot zones, integrating digital initiatives
Keywords: Artificial Intelligence1, green innovation2, Green R&D Efficiency3, GreenInnovation Output Efficiency4, Public Health Benefits 5
Received: 25 Sep 2025; Accepted: 31 Oct 2025.
Copyright: © 2025 Zhang, Zhang and XU. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: XING XU, xing.xu@sit.edu.cn
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