This systematic literature review identifies and categorizes critical factors that affect consumer adoption of artificial intelligence (AI)-driven chatbots from 2017 to 2024, focusing on applications in e-commerce, healthcare, banking and education. A qualitative study was conducted using VOSviewer for bibliometric analysis of keyword co-occurrence and thematic analysis to identify four core themes: user experience, quality of interaction, technological background and behavioural characteristics. The key contribution of this study is the development of a new conceptual framework outlining the role of moderators such as anthropomorphism and gender in chatbot adoption. These findings provide critical improvements to the existing understanding of consumer adoption by highlighting interactions between user and technology-related factors. The results offer actionable advice for researchers and practitioners while contributing to a greater understanding of AI chatbot adoption by establishing a basis for future empirical studies. The findings have important implications for designing chatbots to optimize the user experience and quality of interaction, considering behavioural and technological nuances that will drive mainstream adoption in the e-commerce industry.
AdamM., WesselM., & BenlianA. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445. https://doi.org/10.1007/s12525-020-00ƒ414-7
Al-ShafeiM. (2023). Navigating human-chatbot interactions: An investigation into factors influencing user satisfaction and engagement. International Journal of Human–Computer Interaction, 1–18. https://doi.org/10.1080/10447318.2023.2301252
4.
ApergisE. (2019). Who is tech savvy? Exploring the adoption of smartphones and tablets: An empirical investigation. The Journal of High Technology Management Research, 30(2), 100351. https://doi.org/10.1016/j.hitech.2019.100351
5.
AshfaqM., YunJ., YuS., & LoureiroS. M. C. (2020). I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473. https://doi.org/10.1016/j.tele.2020.101473
6.
BhattacharyyaS. S. (2024). Study of adoption of artificial intelligence technology-driven natural large language model-based chatbots by firms for customer service interaction. Journal of Science and Technology Policy Management. https://doi.org/10.1108/JSTPM-11-2023-0201
7.
BilalM., ZhangY., CaiS., AkramU., & HalibasA. (2024). Artificial intelligence is the magic wand making customer-centric a reality! An investigation into the relationship between consumer purchase intention and consumer engagement through affective attachment. Journal of Retailing and Consumer Services, 77, 103674. https://doi.org/10.1016/j.jretconser.2023.103674
8.
BlümelJ., & JhaG. (2023). Designing a conversational AI agent: Framework combining customer experience management, personalization, and AI in service techniques [Paper presentation]. European Conference on Information Systems. https://aisel.aisnet.org/hicss-56/da/service_science/2/
9.
Botpress. (2024). Key chatbot statistics for 2025: Perceptions, market growth, trends. Retrieved, 3April2025, from https://botpress.com/blog/key-chatbot-statistics
10.
BouhiaM., RajaobelinaL., PromTepS., ArcandM., & RicardL. (2022). Drivers of privacy concerns when interacting with a chatbot in a customer service encounter. International Journal of Bank Marketing, 40(6), 1159–1181. https://doi.org/10.1108/IJBM-09-2021-0442
11.
BrünsJ. D., & MeißnerM. (2024). Do you create your content yourself? Using generative artificial intelligence for social media content creation diminishes perceived brand authenticity. Journal of Retailing and Consumer Services, 79, 103790. https://doi.org/10.1016/j.jretconser.2024.103790
12.
CardilloA. (2024). 40+ chatbot statistics. Retrieved, 3April2025, from https://explodingtopics.com/blog/chatbot-statistics?form=MG0AV3
13.
ChakrabortyD., Kumar KarA., PatreS., & GuptaS. (2024). Enhancing trust in online grocery shopping through generative AI chatbots. Journal of Business Research, 180, 114737. https://doi.org/10.1016/j.jbusres.2024.114737
14.
ChenQ., LuY., GongY., & XiongJ. (2023). Can AI chatbots help retain customers? Impact of AI service quality on customer loyalty. Internet Research, 33(6), 2205–2243. https://doi.org/10.1108/INTR-09-2021-0686
15.
ChenY., PrenticeC., WeavenS., & HisaoA. (2022). The influence of customer trust and artificial intelligence on customer engagement and loyalty: The case of the home-sharing industry. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.912339
16.
ChengY., & JiangH. (2020). How do AI-driven chatbots impact user experience? Examining gratifications, perceived privacy risk, satisfaction, loyalty, and continued use. Journal of Broadcasting & Electronic Media, 64(4), 592–614. https://doi.org/10.1080/08838151.2020.1834296
17.
ChengY., & JiangH. (2022). Customer–brand relationship in the era of artificial intelligence: Understanding the role of chatbot marketing efforts. Journal of Product & Brand Management, 31(2), 252–264. https://doi.org/10.1108/JPBM-05-2020-2907
18.
CherniakK. (2024). Chatbot statistics: What businesses need to know about digital assistants. Master of Code. Retrieved, 3April2025, from https://masterofcode.com/blog/chatbot-statistics
19.
ConnellA. (2025). 50 critical chatbot statistics you need to know in 2025. Retrieved, 3April2025, from https://adamconnell.me/chatbot-statistics/
20.
ElmashharaM. G., De CiccoR., SilvaS. C., HammerschmidtM., & SilvaM. L. (2024). How gamifying AI shapes customer motivation, engagement, and purchase behavior. Psychology & Marketing, 41(1), 134–150. https://doi.org/10.1002/mar.21912
21.
ErenB. A. (2021). Determinants of customer satisfaction in chatbot use: Evidence from a banking application in Turkey. International Journal of Bank Marketing, 39(2), 294–311. https://doi.org/10.1108/IJBM-02-2020-0056
22.
GaoY., & LiuH. (2023). Artificial intelligence-enabled personalization in interactive marketing: A customer journey perspective. Journal of Research in Interactive Marketing, 17(5), 663–680. https://doi.org/10.1108/JRIM-01-2022-0023
23.
GkinkoL., & ElbannaA. (2023). Designing trust: The formation of employees’ trust in conversational AI in the digital workplace. Journal of Business Research, 158, 113707. https://doi.org/10.1016/j.jbusres.2023.113707
24.
GoekenT., TsekourasD., HeimbachI., & GuttD. (2020). The rise of robo-reviews: The effects of chatbot-mediated review elicitation on review valence [Paper presentation]. European Conference on Information Systems. https://aisel.aisnet.org/ecis2020_rp/96/?utm_source=aisel.aisnet.org%2Fecis2020_rp%2F96&utm_medium=PDF&utm_campaign=PDFCoverPages
25.
HmoudH., ShishanF., QasemZ., & BaziS. (2023). The effect of Arabic language type on banking chatbots adoption. Heliyon, 9(10). https://doi.org/10.1016/j.heliyon.2023.e20686
26.
HultG. T. M., SharmaP. N., MorgesonF. V., & ZhangY. (2019). Antecedents and consequences of customer satisfaction: Do they differ across online and offline purchases?Journal of Retailing, 95(1), 10–23. https://doi.org/10.1016/j.jretai.2018.10.003
27.
IschenC., AraujoT., van NoortG., VoorveldH., & SmitE. (2020). ‘I Am Here to Assist You Today’: The role of entity, interactivity and experiential perceptions in chatbot persuasion. Journal of Broadcasting & Electronic Media, 64(4), 615–639. https://doi.org/10.1080/08838151.2020.1834297
28.
JanI. U., JiS., & KimC. (2023). What (de) motivates customers to use AI-powered conversational agents for shopping? The extended behavioral reasoning perspective. Journal of Retailing and Consumer Services, 75, 103440. https://doi.org/10.1016/j.jretconser.2023.103440
29.
JiangH., ChengY., YangJ., & GaoS. (2022). AI-powered chatbot communication with customers: Dialogic interactions, satisfaction, engagement, and customer behavior. Computers in Human Behavior, 134, 107329. https://doi.org/10.1016/j.chb.2022.107329
30.
JinY., CaiW., ChenL., HtunN. N., & VerbertK. (2019). MusicBot: Evaluating critiquing-based music recommenders with conversational interaction [Paper presentation]. Proceedings of the 28th ACM International Conference on Information and Knowledge Management. https://doi.org/10.1145/3357384.3357923
31.
JyothsnaM., VenkataS. P., & NataliaK. (2024). Exploring the chatbot usage intention: A mediating role of chatbot initial trust. Heliyon, 10(12), e33028. https://doi.org/10.1016/j.heliyon.2024.e33028
32.
KleinK., & MartinezL. F. (2023). The impact of anthropomorphism on customer satisfaction in chatbot commerce: An experimental study in the food sector. Electronic Commerce Research, 23(4), 2789–2825. https://doi.org/10.1007/s10660-022-09562-8
33.
KullA. J., RomeroM., & MonahanL. (2021). How may I help you? Driving brand engagement through the warmth of an initial chatbot message. Journal of Business Research, 135, 840–850. https://doi.org/10.1016/j.jbusres.2021.03.005
34.
LalicicL., & WeismayerC. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891–901. https://doi.org/10.1016/j.jbusres.2020.11.005
35.
LiC.-Y., & ZhangJ.-T. (2023). Chatbots or me? Consumers’ switching between human agents and conversational agents. Journal of Retailing and Consumer Services, 72, 103264. https://doi.org/10.1016/j.jretconser.2023.103264
36.
LinJ.-S., & WuL. (2023). Examining the psychological process of developing consumer-brand relationships through strategic use of social media brand chatbots. Computers in Human Behavior, 140, 107488. https://doi.org/10.1016/j.chb.2022.107488
37.
Martínez PuertasS., Illescas ManzanoM. D., Segovia LópezC., & Ribeiro CardosoP. (2024). Purchase intentions in a chatbot environment: An examination of the effects of customer experience. Oeconomia Copernicana, 15(1). https://doi.org/10.24136/oc.2914
38.
MoherD., LiberatiA., TetzlaffJ., & AltmanD. G.; Prisma Group. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLOS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097
39.
MurtarelliG., CollinaC., & RomentiS. (2023). ‘Hi! How can I help you today?’: Investigating the quality of chatbots–millennials relationship within the fashion industry. The TQM Journal, 35(3), 719–733. https://doi.org/10.1108/TQM-01-2022-0010
PereiraT., LimbergerD. P. F., & ArdigóD. C. M. (2021). The moderating effect of the need for interaction with a service employee on purchase intention in chatbots. Telematics and Informatics Reports, 1–4, 100003. https://doi.org/10.1016/j.teler.2022.100003
42.
PillaiR., GhanghorkarY., SivathanuB., AlgharabatR., & RanaN. P. (2024). Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots. Information Technology & People, 37(1), 449–478. https://doi.org/10.1108/ITP-04-2022-0287
43.
PillaiR., & SivathanuB. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199–3226. https://doi.org/10.1108/IJCHM-04-2020-0259
44.
PillaiR., SivathanuB., MetriB., & KaushikN. (2024). Students’ adoption of AI-based teacher-bots (T-bots) for learning in higher education. Information Technology & People, 37(1), 328–355. https://doi.org/10.1108/ITP-02-2021-0152
45.
PizziG., ScarpiD., & PantanoE. (2021). Artificial intelligence and the new forms of interaction: Who has the control when interacting with a chatbot?Journal of Business Research, 129, 878–890. https://doi.org/10.1016/j.jbusres.2020.11.006
46.
PrenticeC., & NguyenM. (2020). Engaging and retaining customers with AI and employee service. Journal of Retailing and Consumer Services, 56, 102186. https://doi.org/10.1016/j.jretconser.2020.102186
47.
PrenticeC., WeavenS., & WongI. A. (2020). Linking AI quality performance and customer engagement: The moderating effect of AI preference. International Journal of Hospitality Management, 90, 102629. https://doi.org/10.1016/j.ijhm.2020.102629
48.
PrzegalinskaA., CiechanowskiL., StrozA., GloorP., & MazurekG. (2019). In bot we trust: A new methodology of chatbot performance measures. Business Horizons, 62(6), 785–797. https://doi.org/10.1016/j.bushor.2019.08.005
49.
QinM., ZhuW., ZhaoS., & ZhaoY. (2022). Is artificial intelligence better than manpower? The effects of different types of online customer services on customer purchase intentions. Sustainability, 14(7). https://doi.org/10.3390/su14073974
50.
RasheedH. M. W., ChenY., KhizarH. M. U., & SafeerA. A. (2023). Understanding the factors affecting AI services adoption in hospitality: The role of behavioral reasons and emotional intelligence. Heliyon, 9(6). https://doi.org/10.1016/j.heliyon.2023.e16968
51.
Reuters. (2025). AI-influenced shopping boosts online holiday sales, Salesforce data shows. Retrieved, 3April2025, from https://www.reuters.com/business/retail-consumer/ai-influenced-shopping-boosts-online-holiday-sales-salesforce-data-shows-2025-01-06/
52.
Rosillo-DíazE., Blanco-EncomiendaF. J., & Crespo-AlmendrosE. (2020). A cross-cultural analysis of perceived product quality, perceived risk and purchase intention in e-commerce platforms. Journal of Enterprise Information Management, 33(1), 139–160. https://doi.org/10.1108/JEIM-06-2019-0150
53.
SaffanahL., HandayaniP. W., & SunarsoF. P. (2023). Actual purchases on Instagram Live Shopping: The influence of live shopping engagement and information technology affordance. Asia Pacific Management Review, 28(2), 204–214. https://doi.org/10.1016/j.apmrv.2022.09.002
54.
SalahO. H., & AyyashM. M. (2024). E-commerce adoption by SMEs and its effect on marketing performance: An extended of TOE framework with ai integration, innovation culture, and customer tech-savviness. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100183. https://doi.org/10.1016/j.joitmc.2023.100183
55.
SanjayaW., CalvinMuhammad, MeilianaR., & FajarM. (2023). Systematic literature review on implementation of chatbots for commerce use. Procedia Computer Science, 227, 432–438. https://doi.org/10.1016/j.procs.2023.10.543
56.
Scopus. (2024). Scopus. Retrieved, 3April2025, from https://www.elsevier.com/
57.
SheehanB., JinH. S., & GottliebU. (2020). Customer service chatbots: Anthropomorphism and adoption. Journal of Business Research, 115, 14–24. https://doi.org/10.1016/j.jbusres.2020.04.030
58.
SidlauskieneJ., JoyeY., & AuruskevicieneV. J. (2023). AI-based chatbots in conversational commerce and their effects on product and price perceptions. Electron Markets, 33(1), 24. https://doi.org/10.1007/s12525-023-00633-8
59.
SilvaS. C., De CiccoR., VlačićB., & ElmashharaM. G. (2023). Using chatbots in e-retailing – how to mitigate perceived risk and enhance the flow experience. International Journal of Retail & Distribution Management, 51(3), 285–305. https://doi.org/10.1108/IJRDM-05-2022-0163
60.
SinghC., DashM. K., SahuR., & KumarA. (2024). Investigating the acceptance intentions of online shopping assistants in e-commerce interactions: Mediating role of trust and effects of consumer demographics. Heliyon, 10(3), e25031. https://doi.org/10.1016/j.heliyon.2024.e25031
61.
SinghP., & SinghV. (2024). The power of AI: Enhancing customer loyalty through satisfaction and efficiency. Cogent Business & Management, 11(1), 2326107. https://doi.org/10.1080/23311975.2024.2326107
62.
SungE., BaeS., HanD.-I. D., & KwonO. (2021). Consumer engagement via interactive artificial intelligence and mixed reality. International Journal of Information Management, 60, 102382. https://doi.org/10.1016/j.ijinfomgt.2021.102382
63.
Van EckN. J., & WaltmanL. (2023). VOSviewer Manual. Retrieved, 3April2025, from https://www.vosviewer.com/documentation/Manual_VOSviewer_1.6.6.pdf
64.
Vention. (2024). AI adoption statistics by industries and countries: 2024 snapshot. Retrieved, 3April2025, from https://ventionteams.com/solutions/ai/adoption-statistics
65.
VimalkumarM., SharmaS. K., SinghJ. B., & DwivediY. K. (2021). ‘Okay google, what about my privacy?’: User’s privacy perceptions and acceptance of voice based digital assistants. Computers in Human Behavior, 120, 106763. https://doi.org/10.1016/j.chb.2021.106763
66.
WillemsJ., SchmidM. J., VanderelstD., VogelD., & EbingerF. (2023). AI-driven public services and the privacy paradox: Do citizens really care about their privacy?Public Management Review, 25(11), 2116–2134. https://doi.org/10.1080/14719037.2022.2063934
67.
YadavP., GuptaP., RaiP., NaikN., & KasipK. (2024). Exploring the factors influencing the adoption and continuous engagement in unlocking the potential of technology driven chatbots in banking and financial institutions. Engineered Science, 28, 1054. http://dx.doi.org/10.30919/es1054
68.
YounS., & JinS. V. (2021). ‘In A.I. we trust?’ The effects of parasocial interaction and technopian versus luddite ideological views on chatbot-based customer relationship management in the emerging ‘feeling economy’. Computers in Human Behavior, 119, 106721. https://doi.org/10.1016/j.chb.2021.106721
69.
YuJ., DickingerA., SoK. K. F., & EggerR. (2024). Artificial intelligence-generated virtual influencer: Examining the effects of emotional display on user engagement. Journal of Retailing and Consumer Services, 76, 103560. https://doi.org/10.1016/j.jretconser.2023.103560
70.
ZhuY., ZhangR., ZouY., & JinD. (2023). Investigating customers’ responses to artificial intelligence chatbots in online travel agencies: The moderating role of product familiarity. Journal of Hospitality and Tourism Technology, 14(2), 208–224. https://doi.org/10.1108/JHTT-02-2022-0041
71.
ZongwenX., & RandallS. (2024). Conceptualizing AI-chatbot application as an e-service agent to develop a customer-brand relationship. Operational Research in Engineering Sciences: Theory and Applications, 7(1). https://oresta.org/menu-script/index.php/oresta/article/view/712
