Norah Alharbi, Fareed Ud Din, David Paul, Edmund Sadgrove
{"title":"Driving AI chatbot adoption: A systematic review of factors, barriers, and future research directions","authors":"Norah Alharbi, Fareed Ud Din, David Paul, Edmund Sadgrove","doi":"10.1016/j.joitmc.2025.100590","DOIUrl":null,"url":null,"abstract":"<div><div>Adopting AI chatbots has gained significant momentum across various industries due to advancements in artificial intelligence. Despite their potential, AI chatbot adoption remains a complex process affected by numerous factors that are not fully understood. This systematic review seeks to identify and categorize the factors influencing AI chatbot adoption, including drivers and impediments. Following the PRISMA guidelines, a comprehensive review process was conducted. From 459 publications collected via Web of Science and Scopus, 84 research articles meeting eligibility criteria were analyzed to provide insights into the determinants of adoption. This review systematically examines the theoretical models employed, geographic distribution, primary domains of study, methodologies, and key factors shaping adoption. Furthermore, the study outlines future research directions to guide advancements in this area. The findings contribute to theoretical understanding by synthesizing determinants like anthropomorphism, trust, and hedonic motivation and advocating for integrating underexplored frameworks and hybrid methodologies. Practical implications are provided for developers, marketers, and policymakers, emphasizing user-centric design, privacy protection, and sector-specific strategies. This review advances knowledge in AI chatbot adoption and offers actionable insights for successful implementation across diverse industries.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 3","pages":"Article 100590"},"PeriodicalIF":0.0000,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Innovation: Technology, Market, and Complexity","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2199853125001258","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 0
Abstract
Adopting AI chatbots has gained significant momentum across various industries due to advancements in artificial intelligence. Despite their potential, AI chatbot adoption remains a complex process affected by numerous factors that are not fully understood. This systematic review seeks to identify and categorize the factors influencing AI chatbot adoption, including drivers and impediments. Following the PRISMA guidelines, a comprehensive review process was conducted. From 459 publications collected via Web of Science and Scopus, 84 research articles meeting eligibility criteria were analyzed to provide insights into the determinants of adoption. This review systematically examines the theoretical models employed, geographic distribution, primary domains of study, methodologies, and key factors shaping adoption. Furthermore, the study outlines future research directions to guide advancements in this area. The findings contribute to theoretical understanding by synthesizing determinants like anthropomorphism, trust, and hedonic motivation and advocating for integrating underexplored frameworks and hybrid methodologies. Practical implications are provided for developers, marketers, and policymakers, emphasizing user-centric design, privacy protection, and sector-specific strategies. This review advances knowledge in AI chatbot adoption and offers actionable insights for successful implementation across diverse industries.
由于人工智能的进步,采用人工智能聊天机器人在各个行业获得了巨大的动力。尽管有潜力,人工智能聊天机器人的采用仍然是一个复杂的过程,受到许多尚未完全了解的因素的影响。本系统综述旨在识别和分类影响人工智能聊天机器人采用的因素,包括驱动因素和障碍。根据PRISMA的指导方针,进行了全面的审查过程。从通过Web of Science和Scopus收集的459篇出版物中,分析了84篇符合资格标准的研究文章,以深入了解采用的决定因素。本综述系统地考察了所采用的理论模型、地理分布、主要研究领域、方法和影响采用的关键因素。此外,该研究还概述了未来的研究方向,以指导该领域的进展。研究结果通过综合拟人化、信任和享乐动机等决定因素,并倡导整合未充分探索的框架和混合方法,有助于理论理解。本文为开发人员、营销人员和决策者提供了实际意义,强调以用户为中心的设计、隐私保护和特定部门的策略。这篇综述推进了人工智能聊天机器人采用方面的知识,并为不同行业的成功实施提供了可行的见解。