An Analytical Study of AI and ML-Based Chatbots in Integrated Technical and Business Applications
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This work examines how chatbots powered by Artificial Intelligence (AI) and Machine Learning (ML) improve efficiency, decision-making, and user interaction in integrated technical and business settings. The study aims to examine the two-sided effects of chatbots on operational performance and user satisfaction, and to identify the challenges that influence their successful implementation. The research design was descriptive-analytical, with 220 professionals and end-users selected and interviewed using structured questionnaires, and the data analysed using SPSS software (t-tests, ANOVA, correlation, and regression). These findings indicate that the chatbot integration has a significant positive effect on technical performance, as measured by response accuracy, system integration, and error handling, with all differences significant (p = 0.05). Measures of business processes, such as customer service, decision support, and operational efficiency, also show substantial improvements, with strong positive correlations between the technical metrics and user satisfaction. Nevertheless, the technical complexity, the cost of implementing it, employee adaptation, and data confidentiality issues were also found to impact the integration process's effectiveness negatively. This paper finds that AI- and ML-based chatbots revolutionised the field of automation by connecting technical effectiveness with manager efficiency. Their application strategy can result in high-quality customer relationships and responsive operations, provided that organisations overcome integration barriers through continuous training, ethical regulation, and systems optimisation. This study is also relevant to current research on intelligent automation, as it provides a practical contribution to organisations seeking to implement chatbots responsibly and efficiently through socio-technical systems.
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Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology, and applications. Machine Learning with Applications, 2, 100006. DOI: https://doi.org/10.1016/j.mlwa.2020.100006
Al-Amin, M., Ali, M. S., Salam, A., Khan, A., Ali, A., Ullah, A., ... & Chowdhury, S. K. (2024). History of generative Artificial Intelligence (AI) chatbots: past, present, and future development. arXiv preprint arXiv:2402.05122. DOI: https://doi.org/10.48550/arXiv.2402.05122
Alsaawi, A. (2025). Challenges and Opportunities Associated with AI Chatbots in Language Learning from the Perspective of Users in Saudi Arabia. International Journal of Learning, Teaching and Educational Research, 24(5), 400-415. DOI: https://doi.org/10.26803/ijlter.24.5.21
Chakraborty, C., Pal, S., Bhattacharya, M., Dash, S., & Lee, S. S. (2023). Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science. Frontiers in Artificial Intelligence, 6, 1237704. DOI: https://doi.org/10.3389/frai.2023.1237704
Eghaghe, I. E., & Ikushoni, E. O. (2025). The Influence of AI Chatbots On Customer Engagement and Service Delivery in B2B Environments. https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1973391&dswid=-9216
Gruenhagen, J. H., Sinclair, P. M., Carroll, J. A., Baker, P. R., Wilson, A., & Demant, D. (2024). The rapid rise of generative AI and its implications for academic integrity: Students’ perceptions and use of chatbots for assessment assistance—computers and Education: Artificial Intelligence, 7, 100273. DOI: https://doi.org/10.1016/j.caeai.2024.100273
Hasan, N. S., Doja, F., & Gupta, P. K. (2023). Chatbots: Past, Present & Future. IRSD2024, 309. ISBN: 978-81-967563-3-8
L. H. Kahn, O. Savas, A. Morrison, K. A. Shaffer and L. Zapata, "Modelling Hybrid Human-Artificial Intelligence Cooperation: A Call Centre Customer Service Case Study," 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 2020, pp. 3072-3075, DOI: https://doi.org/10.1109/BigData50022.2020.9377747
Krishnan, C., Gupta, A., Gupta, A., Singh, G. (2022). Impact of Artificial Intelligence-Based Chatbots on Customer Engagement and Business Growth. In: Hong, TP., Serrano-Estrada, L., Saxena, A., Biswas, A. (eds) Deep Learning for Social Media Data Analytics. Studies in Big Data, vol 113. Springer, Cham. DOI: https://doi.org/10.1007/978-3-031-10869-3_11
Lin, X., Wang, X., Shao, B., & Taylor, J. (2024). How Chatbots Augment Human Intelligence in Customer Services: A Mixed-Methods Study. Journal of Management Information Systems, 41(4), 1016–1041. DOI: https://doi.org/10.1080/07421222.2024.2415773
Liu, L., Duffy, V.G. Exploring the Future Development of Artificial Intelligence (AI) Applications in Chatbots: A Bibliometric Analysis. Int J of Soc Robotics 15, 703–716 (2023). DOI: https://doi.org/10.1007/s12369-022-00956-0
Rahevar, M., & Soni, S. K. (2024). The adoption of AI-driven chatbots into a personalised e-commerce environment: Impact analysis. International Journal of Mechanical Engineering and Computing, 9(2), 3132–3142. DOI: https://doi.org/10.62737/m1vpdq75
Sidlauskiene, J., Joye, Y. & Auruskeviciene, V. AI-based chatbots in conversational commerce and their effects on product and price perceptions. Electron Markets 33, 24 (2023). DOI: https://doi.org/10.1007/s12525-023-00633-8
Singh, J., Sillerud, B., & Singh, A. (2023). Artificial intelligence, chatbots and ChatGPT in healthcare—narrative review of historical evolution, current application, and change management approach to increase adoption. Journal of Medical Artificial Intelligence, 6.
DOI: https://doi.org/10.21037/jmai-23-92
Dr Suyash Kamal Soni, Dr Sumit Jain. (2025). AI Chatbots and Their Impact on the B2C Consumer Experience and Engagement. International Journal of Advanced Research and Multidisciplinary Trends (IJARMT), 2(1), 354–367. Retrieved from https://ijarmt.com/index.php/j/article/view/98
Tian, W., Ge, J., Zhao, Y., & Zheng, X. (2024). AI Chatbots in Chinese higher education: adoption, perception, and influence among graduate students—an integrated analysis utilising UTAUT and ECM models. Frontiers in Psychology, 15, 1268549.
DOI: https://doi.org/10.3389/fpsyg.2024.1268549
Virk, K. S. (2022). Artificial intelligence chatbots–history, applications, challenges, and future directions. Asian Journal of Multidimensional Research, 11(9), 155. DOI: https://doi.org/10.5958/2278-4853.2022.00385.8
Wiethof, C., & Bittner, E. A. (2022). Toward a hybrid intelligence system in customer service: collaborative learning of human and AI. https://aisel.aisnet.org/ecis2022_rp/66
Xiao, Y., Zhang, T., & He, J. (2024). RETRACTED: The promises and challenges of AI-based chatbots in language education through the lens of learner emotions. Heliyon, 10(18). https://www.cell.com/heliyon/fulltext/S2405-8440(24)13269-0