Authors : Amen Lafi

Volume/Issue : Volume 10 - 2025, Issue 10 - October

Google Scholar : https://tinyurl.com/2wwfhewx

Scribd : https://tinyurl.com/bukf2387

DOI : https://doi.org/10.38124/ijisrt/25oct1525

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Abstract : The rapid advancement of artificial intelligence (AI) has fundamentally reshaped interactions between consumers and digital platforms. Among these technological innovations, ChatGPT and AI-powered chatbots have emerged as key tools influencing consumer attitudes, trust, and decision-making behaviors. This paper investigates both the theoretical and empirical aspects of AI chatbots’ impact on consumer behavior and purchase intentions. Drawing upon frameworks from consumer psychology, technology acceptance, and digital marketing, the study examines the advantages and challenges associated with chatbot-mediated communication. Employing a mixed-method approach that integrates literature review with consumer survey, the research highlights the roles of perceived convenience, personalization, and trust in shaping purchase decisions. The results indicate that AI chatbots, especially those with sophisticated conversational capabilities like ChatGPT, can significantly enhance consumer engagement and conversion rates when designed with transparency, empathy, and user-centric principles. The study concludes by discussing practical implications for marketers, ethical considerations, and avenues for future research within the AI-driven consumer environment.

Keywords : ChatGPT, AI Chatbots, Consumer Behavior, Purchase Decisions, Artificial Intelligence, Digital Marketing, Trust.

References :

1. Bhatnagar, R., & Singh, A. (2024). The impact of AI-driven personalization on consumer loyalty in digital retailing. Journal of Digital Marketing Research, 18(2), 55–72.
2. Chatterjee, S., Rana, N. P., & Sharma, A. (2023). Trust in artificial intelligence: A consumer perspective on chatbot adoption. International Journal of Information Management, 71, 102574.
3. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
4. Dwivedi, Y. K., Hughes, D. L., & Rana, N. P. (2023). Artificial intelligence for customer engagement: Challenges and opportunities. Journal of Business Research, 158, 113633.
5. Gursoy, D., Chi, O. H., & Lu, L. (2023). Artificial intelligence in service: A systematic review and research agenda. Tourism Management, 94, 104661.
6. Hoyer, W. D., Kroschke, M., Schmitt, B., & Shankar, V. (2023). Transforming the customer experience through artificial intelligence. Journal of the Academy of Marketing Science, 51(1), 1–21.
7. Huang, M.-H., & Rust, R. T. (2024). The next frontier in service: Emotionally intelligent AI. Journal of Service Research, 27(2), 145–160.
8. Kapoor, K. K., & Dwivedi, Y. K. (2024). ChatGPT and generative AI: Implications for marketing and consumer research. European Journal of Marketing, 58(4), 987–1008.
9. Li, C., & Kumar, P. (2024). AI-mediated decision-making and consumer autonomy in digital commerce. Computers in Human Behavior, 148, 107943.
10. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.
11. Nguyen, L., & Kim, Y. (2024). Privacy, trust, and AI chatbots: Exploring consumer acceptance in e-commerce. Journal of Retailing and Consumer Services, 75, 103538.
12. Nguyen, T., & Li, Q. (2024). Chatbots and consumer behavior: An empirical analysis of online shopping decisions. Electronic Commerce Research and Applications, 59, 101239.
13. OpenAI. (2023). GPT-4 technical report. Retrieved from https://openai.com/research
14. Park, S., & Kim, J. (2025). Anthropomorphism and discomfort in AI interactions: The role of emotional transparency. Computers in Human Behavior, 160, 108178.
15. Rahman, M. M., & Dwivedi, Y. K. (2024). Ethical AI in marketing: Balancing personalization and privacy. Journal of Business Ethics, 188(3), 845–864.
16. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
17. Wang, L., & Chen, S. (2024). Social influence and AI adoption: The role of perceived usefulness and trust. Computers in Human Behavior Reports, 10, 100257.