AI-Driven Autonomous Customer Support Systems
DOI:
https://doi.org/10.5281/29q4r372Keywords:
Autonomous AI agents; customer support; digital platforms; intelligent assistance; intelligent automation; natural language processing.Abstract
Digital-platform automation holds the potential to reduce operational costs while improving service quality and availability. Nevertheless, full or near-full automation of customer support remains elusive. Current automated solutions are limited in capabilities, often providing only basic and inflexible assistance. Autonomous AI agents capable of intelligent customer-support task execution would therefore represent a major milestone. Such technology could automatically carry out common support actions and ensure a satisfactory experience for all users that require assistance.
An architectural framework specifying the essential building blocks for the autonomous AI agent operation is proposed. Commonly employed data governance, privacy-preserving techniques, and deployment guidelines are also presented. Together, these concepts provide a theoretical foundation for the automated customer-support automation task in the digital platform domain and serve as guidance for future implementations.
References
1. Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31, 427–445.
2. Chao, L., Tussyadiah, I. P., Tuomi, A., Stienmetz, J., & Ioannou, A. (2021). Factors influencing users’ adoption and use of conversational agents: A systematic review. Psychology & Marketing, 38(7), 1031–1051.
3. Følstad, A., & Taylor, C. (2021). Investigating the user experience of customer service chatbot interaction: A framework for qualitative analysis of chatbot dialogues. Quality and User Experience, 6, Article 6.
4. Mozafari, N., Weiger, W. H., & Hammerschmidt, M. (2021). The chatbot disclosure dilemma: How revealing the identity of a chatbot affects customer responses. Journal of Service Management, 32(2), 239–263.
5. Rzepka, C., Berger, B., & Hess, T. (2022). Voice assistant vs. chatbot: Examining the fit between conversational agents’ interaction modalities and information search tasks. Information Systems Frontiers, 24(3), 839–856.
6. Kolla, S. H., & Loganathan, R. (2023). Cloud-Native Deep Learning Architectures For Secure Generative AI Deployment In Enterprise Workflow Platforms. Journal of International Crisis and Risk Communication Research, 603-618.
7. Misischia, C. V., Pöcze, F., & Strauss, C. (2022). Chatbots in customer service: Their relevance and impact on service quality. Procedia Computer Science, 201, 421–428.
8. Nicolescu, L., & Tudorache, M. T. (2022). Human-computer interaction in customer service: The experience with AI chatbots—A systematic literature review. Electronics, 11(10), 1579.
9. Yun, J., & Park, J. (2022). The effects of chatbot service recovery with emotion words on customer satisfaction, repurchase intention, and positive word-of-mouth. Frontiers in Psychology, 13, 922503.
10. Xu, Y., Zhang, J., & Deng, G. (2022). Enhancing customer satisfaction with chatbots: The influence of communication styles and consumer attachment anxiety. Frontiers in Psychology, 13, 902782.
11. Zhang, Z., Li, B., & Liu, L. (2022). The impact of AI-based conversational agent on the firms’ operational performance: Empirical evidence from a call center. Applied Artificial Intelligence, 36(1).
12. Mattaparthi, R. (2022). Engineering Predictive Industrial Systems Through IoT-Driven Asset Monitoring and Machine Learning Prognostics. International Journal of Future Innovative Science and Technology (IJFIST), 5(1), 7790.
13. Weiger, W. H., Moritz, A., & Hammerschmidt, M. (2022). Trust me, I’m a bot—Repercussions of chatbot disclosure in different service frontline settings. Journal of Service Management, 33(2), 256–278.
14. Becker, M., Mahr, D., & Odekerken-Schröder, G. (2023). Customer comfort during service robot interactions. Service Business, 17, 137–165.
15. Schepers, J., Belanche, D., Casaló, L. V., & Flavián, C. (2022). How smart should a service robot be? Journal of Service Research, 25(4), 615–632.
16. De Keyser, A., & Kunz, W. H. (2022). Living and working with service robots: A TCCM analysis and considerations for future research. Journal of Service Management, 33(2), 165–196.
17. Li, Y., & Wang, C. (2023). Customer acceptance of service robots under different service settings. Journal of Service Theory and Practice, 33(1), 46–71.
18. Li, M., Erickson, I. M., Cross, E. V., & Lee, J. D. (2023). Estimating trust in conversational agent with lexical and acoustic features. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 66(1).
19. Dubiel, M., Daronnat, S., & Leiva, L. A. (2022). Conversational agents trust calibration: A user-centred perspective to design. Proceedings of the 4th Conference on Conversational User Interfaces, 1–4.
20. Olujimi, P. A., & Ade-Ibijola, A. (2023). NLP techniques for automating responses to customer queries: A systematic review. Discover Artificial Intelligence, 3, Article 20.
21. Mariani, M. M., Hashemi, N., & Wirtz, J. (2023). Artificial intelligence empowered conversational agents: A systematic literature review and research agenda. Journal of Business Research, 161, 113838.
22. Reddy, V. A. R. (2022). Designing Fault-Tolerant Data Ingestion Pipelines for High-Volume Healthcare Transactions. Frontiers in Health Informatics, 11, 861-889.
23. Schöbel, S., Schmitt, A., Benner, D., Saqr, M., Janson, A., & Leimeister, J. M. (2023). Charting the evolution and future of conversational agents: A research agenda along five waves and new frontiers. Information Systems Frontiers.
24. Hsu, C.-L., & Lin, J. C.-C. (2023). Understanding the user satisfaction and loyalty of customer service chatbots. Journal of Retailing and Consumer Services, 71, 103211.
25. Xu, Y., Niu, N., & Zhao, Z. (2023). Dissecting the mixed effects of human-customer service chatbot interaction on customer satisfaction: An explanation from temporal and conversational cues. Journal of Retailing and Consumer Services, 74, 103417.
26. Zhang, Y., Sun, L., & Li, X. (2023). Understanding and improving consumer reactions to service bots. Journal of Consumer Research, 50(4), 848–863.
27. Poser, M., Küstermann, G. C., Tavanapour, N., & Bittner, E. A. C. (2022). Design and evaluation of a conversational agent for facilitating idea generation in organizational innovation processes. Information Systems Frontiers, 24, 771–796.
28. Aravind, R., & Surabhii, S. N. R. D. (2023). Harnessing Artificial Intelligence for Enhanced Vehicle Control and Diagnostics.
29. Misischia, C. V., Pöcze, F., & Strauss, C. (2022). Artificial intelligence in customer service: The role of conversational agents in service interactions. Procedia Computer Science, 201, 421–428.
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