{"title":"Not all sparks ignite the same flame: Firm AI innovation and ESG performance","authors":"Zixun Zhou , Xinyu Zhou , Xuezhi Zhang , Qi He","doi":"10.1016/j.jbusres.2025.115738","DOIUrl":null,"url":null,"abstract":"<div><div>Technological innovation exhibits dual impacts—fueling progress while exacerbating disparities—especially regarding artificial intelligence (AI). While AI’s productivity benefits are well documented, its role in corporate sustainability remains contentious. Drawing on divergent perspectives from the resource-based view and stakeholder theory, this study examines the differential effects of firm-level AI innovation on Environmental, Social, and Governance (ESG) performance. Leveraging proprietary AI patent and hiring data from Chinese listed firms, we find that AI innovation significantly promotes ESG performance—particularly in governance and social dimensions—but not in environmental outcomes. Mechanism analyses reveal expanded AI talent recruitment, strengthened employee protection awareness, and improved corporate transparency as plausible channels. Moreover, AI innovation mitigates greenwashing behavior, corporate misconduct, and negative media coverage. By unpacking AI innovation-driven sustainability as a contested nexus, we advance the understanding of how technological capabilities and stakeholder accountability can reconcile ESG trade-offs.</div></div>","PeriodicalId":15123,"journal":{"name":"Journal of Business Research","volume":"201 ","pages":"Article 115738"},"PeriodicalIF":9.8000,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Research","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0148296325005612","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Technological innovation exhibits dual impacts—fueling progress while exacerbating disparities—especially regarding artificial intelligence (AI). While AI’s productivity benefits are well documented, its role in corporate sustainability remains contentious. Drawing on divergent perspectives from the resource-based view and stakeholder theory, this study examines the differential effects of firm-level AI innovation on Environmental, Social, and Governance (ESG) performance. Leveraging proprietary AI patent and hiring data from Chinese listed firms, we find that AI innovation significantly promotes ESG performance—particularly in governance and social dimensions—but not in environmental outcomes. Mechanism analyses reveal expanded AI talent recruitment, strengthened employee protection awareness, and improved corporate transparency as plausible channels. Moreover, AI innovation mitigates greenwashing behavior, corporate misconduct, and negative media coverage. By unpacking AI innovation-driven sustainability as a contested nexus, we advance the understanding of how technological capabilities and stakeholder accountability can reconcile ESG trade-offs.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.