Effect of Artificial Intelligence on Consumer Awareness and Purchase Intention in Online Shopping
Authors
The Department of Computer Science, Al-Hikmah University Ilorin (Nigeria)
The Department of Computing, University of Greater Manchester (United Kingdom)
Carey Business School, John’s Hopkins University (United States of America)
The Department of Project Management, University of Lincoln (United Kingdom)
The Department of Artificial Intelligence, University of Greater Manchester (United Kingdom)
The Department of Pure and Applied Mathematics, African University of Science and Technology Abuja (Nigeria)
Article Information
DOI: 10.47772/IJRISS.2026.100700720
Subject Category: Computer Science
Volume/Issue: 10/7 | Page No: 10563-10571
Publication Timeline
Submitted: 2026-07-28
Accepted: 2026-08-03
Published: 2026-08-11
Abstract
The current study investigates the impact of artificial intelligence on consumer awareness and purchase intention in online shopping. With the advancement of artificial intelligence technologies like personalized recommendations, chatbots, predictive analytics, and targeted advertising, online shopping has changed dramatically in terms of how consumers identify products and make purchases. This study aimed to investigate how much AI increases consumer awareness, improves engagement, and purchase intention in online shopping. A qualitative methodology was used and the analysis of qualitative data was performed to investigate the influence of artificial intelligence on consumers’ behaviors in the digital market through the review of the relevant literature. The findings show that AI plays a significant role in enhancing consumer awareness through personalized marketing, real-time customer assistance, and recommendation of products. Furthermore, AI has been found to have a positive influence on the purchase intention of consumers in terms of increasing consumer trust in online platforms. Nevertheless, data privacy, algorithmic bias, and trust are some of the major challenges in adopting artificial intelligence. This study concludes that artificial intelligence is an important determinant of consumer awareness and purchasing behavior in online shopping.
Keywords
Artificial Intelligence, Consumer Awareness, Online Shopping, Purchase Intention
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References
1. Ajzen, I. (2020). The theory of planned behavior: Frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/10.1002/hbe2.195 [Google Scholar] [Crossref]
2. Baker, J. (2022). The technology–organization–environment framework. In Y. K. Dwivedi, M. R. Wade, & S. L. Schneberger (Eds.), Information systems theory: Explaining and predicting our digital society (2nd ed.). Springer. [Google Scholar] [Crossref]
3. Chen. (2023). Chatbot or human? The impact of online customer service on consumers' purchase intentions. Psychology & Marketing, 40(12), 2186–2200. https://doi.org/10.1002/mar.21862 [Google Scholar] [Crossref]
4. Davenport, T. H., Guha, A., Grewal, D., & Bressgott, T. (2020). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0 [Google Scholar] [Crossref]
5. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., ... Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 [Google Scholar] [Crossref]
6. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M., Al-Busaidi, K. A., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., ... Wright, R. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642 [Google Scholar] [Crossref]
7. Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024). Generative AI. Business & Information Systems Engineering, 66(1), 111–126. https://doi.org/10.1007/s12599-023-00834-7 [Google Scholar] [Crossref]
8. Huang, M.-H., & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49(1), 30–50. https://doi.org/10.1007/s11747-020-00749-9 [Google Scholar] [Crossref]
9. Le, X. C. (2023). Inducing AI-powered chatbot use for customer purchase: The role of information value and innovative technology. Journal of Systems and Information Technology, 25(2), 219–241. https://doi.org/10.1108/JSIT-09-2021-0206 [Google Scholar] [Crossref]
10. Mariani, M. M., Perez-Vega, R., & Wirtz, J. (2023). AI in marketing, consumer research and psychology: A systematic literature review and research agenda. Psychology & Marketing, 40(10), 1961–1988. [Google Scholar] [Crossref]
11. Nagy, S., & Hajdu, N. (2022). Consumer acceptance of the use of artificial intelligence in online shopping: Evidence from Hungary. Acta Oeconomica, 72(Supplement), 87–104. [Google Scholar] [Crossref]
12. OECD. (2021). OECD digital economy outlook 2020. OECD Publishing. https://doi.org/10.1787/bb167041-en [Google Scholar] [Crossref]
13. Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books. [Google Scholar] [Crossref]
14. Torres, A. I., & Delgado, C. J. M. (2023). Assessing customer interactions with chatbots in online shopping experiences: An empirical study. In Promoting Organizational Performance Through 5G and Agile Marketing. IGI Global. https://doi.org/10.4018/978-1-6684-5523-4.ch011 [Google Scholar] [Crossref]
15. UNESCO. (2021). Recommendation on the ethics of artificial intelligence. UNESCO Publishing. https://unesdoc.unesco.org/ [Google Scholar] [Crossref]
16. Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022 [Google Scholar] [Crossref]
17. Zhang, Y., et al. (2023). Would an AI chatbot persuade you? An empirical answer from the elaboration likelihood model. Information Technology & People. https://doi.org/10.1108/ITP-10-2021-0764 [Google Scholar] [Crossref]
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