The Effect of AIOps on Digital Transformation in Chinese High Tech Enterprises: The Moderating Role of Human-AI Interaction

The Effect of AIOps on Digital Transformation in Chinese High Tech Enterprises: The Moderating Role of Human-AI Interaction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Effect of AIOps on Digital Transformation in Chinese High Tech Enterprises: The Moderating Role of Human-AI Interaction Jun Cui This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6556577/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates the influence of Artificial Intelligence for IT Operations (AIOps) on the digital transformation of high-tech enterprises in China, with a specific focus on the moderating role of Human-AI interaction. Despite growing adoption of AIOps technologies, there remains a significant research gap regarding their effectiveness in facilitating digital transformation, particularly in the Chinese business context. This research employed a quantitative approach through a structured questionnaire distributed to 287 IT professionals and managers from Chinese high-tech enterprises. Data were analyzed using structural equation modeling via AMOS and regression analysis via SPSS. The findings reveal that AIOps implementation has a significant positive effect on digital transformation outcomes, including operational efficiency, service quality, and innovation capability. Furthermore, the Human-AI interaction quality significantly moderates this relationship, enhancing the positive effects when interaction is collaborative and intuitive. This study contributes to both theoretical understanding and practical implementation of AIOps in digital transformation initiatives, offering implications for technology adoption strategies in Chinese high tech enterprises and similar emerging market contexts. AIOps Digital Transformation Human-AI Interaction Chinese High-Tech Enterprises IT Operations Artificial Intelligence Technology Adoption Full Text Additional Declarations The authors declare no competing interests. Participant Consent Statement Participation in this study was entirely voluntary and anonymous. Completion of the online survey was considered as provision of informed consent, as stated in the introductory section of the questionnaire. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6556577","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449698713,"identity":"19de1628-508c-4fb8-8c66-439533d8cb2f","order_by":0,"name":"Jun Cui","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0002-9693-9145","institution":"solbridge international School of Business","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Cui","suffix":""}],"badges":[],"createdAt":"2025-04-29 12:47:07","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-6556577/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6556577/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81794921,"identity":"1611e39a-c4a5-41c8-ae24-fa10463c7548","added_by":"auto","created_at":"2025-05-02 03:14:04","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":262182,"visible":true,"origin":"","legend":"","description":"","filename":"CScholarAIOpsonDigitalTransformationJunCui.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6556577/v1_covered_0cbcc461-4d96-462e-932f-00af4894bc7d.pdf"}],"financialInterests":"\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eParticipant Consent Statement Participation in this study was entirely voluntary and anonymous. 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Despite growing adoption of AIOps technologies, there remains a \u0026nbsp;significant research gap regarding their effectiveness in facilitating digital transformation, \u0026nbsp;particularly in the Chinese business context. This research employed a quantitative approach \u0026nbsp;through a structured questionnaire distributed to 287 IT professionals and managers from Chinese \u0026nbsp;high-tech enterprises. Data were analyzed using structural equation modeling via AMOS and \u0026nbsp;regression analysis via SPSS. The findings reveal that AIOps implementation has a significant \u0026nbsp;positive effect on digital transformation outcomes, including operational efficiency, service quality, \u0026nbsp;and innovation capability. Furthermore, the Human-AI interaction quality significantly moderates \u0026nbsp;this relationship, enhancing the positive effects when interaction is collaborative and intuitive. 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