Driving AI chatbot adoption: A systematic review of factors, barriers, and future research directions

Title
Driving AI chatbot adoption: A systematic review of factors, barriers, and future research directions
Publication Date
2025-09
Author(s)
Alharbi, Norah
Ud Din, Fareed
( author )
OrcID: https://orcid.org/0000-0001-6122-2043
Email: fuddin@une.edu.au
UNE Id une-id:fuddin
Paul, David
( author )
OrcID: https://orcid.org/0000-0002-2428-5667
Email: dpaul4@une.edu.au
UNE Id une-id:dpaul4
Sadgrove, Edmund
( author )
OrcID: https://orcid.org/0000-0002-8710-9900
Email: esadgro2@une.edu.au
UNE Id une-id:esadgro2
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
MDPI AG
Place of publication
Switzerland
DOI
10.1016/j.joitmc.2025.100590
UNE publication id
une:1959.11/71301
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.

Link
Citation
Journal of Open Innovation: Technology, Market, and Complexity, 11(3), p. 1-19
ISSN
2199-8531
Start page
1
End page
19
Rights
Attribution 4.0 International

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