Skip to main content

Opportunities and Challenges of AI-Driven Customer Service

  • Chapter
  • First Online:
Artificial Intelligence in Customer Service

Abstract

The present chapter introduces the concept of Artificial Intelligence-Driven Customer Service, including key AI (artificial intelligence) enablers that can dramatically transform how organizations serve customers. AI has immense potential and opportunities to acquire a competitive advantage but is open to challenges. Deployment of AI technologies for customer service embeds dichotomic dilemmas known as conundrums and paradoxes, such as the Personalization-Privacy Paradox, the Uncanny Valley Paradox, etc. On the bright side, factors such as personalization, convenience, and anthropomorphism unpack value co-creation. On the dark side, technology anxiety, privacy concern, lack of human interaction, and loss of control slip value co-destruction. A customer-centric service ecosystem requires the balanced use of AI-driven value co-creation while mitigating value-co-destruction concerns. The chapter concludes with a strategic framework to overcome challenges with balancing strategies to yield superior AI-enabled customer service.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abdulquadri, A., Kieu, T. A., & Nguyen, N. P. (2021). Digital transformation in financial services provision: Perspective to the adoption of chatbot. Journal of Enterprising Communities: People and Places in the Global Economy, 15(2), 258–281.

    Article  Google Scholar 

  • Aguirre, E., Roggeveen, A. L., Grewal, D., & Wetzels, M. (2016). The personalisation-privacy paradox: Implications for new media. Journal of Consumer Marketing., 33, 98.

    Article  Google Scholar 

  • Aldrich, S. E. (2011). Recommender systems in commercial use. AI Magazine, 32(3), 28–34.

    Article  Google Scholar 

  • Al-Emran, M., Malik, S. I., & Al-Kabi, M. N. (2020). A survey of internet of things (IoT) in education: Opportunities and challenges. Toward social internet of things (SIoT): Enabling technologies, architectures, and applications, pp. 197–209.

    Google Scholar 

  • Alzubi, J., Nayyar, A., & Kumar, A. (2018, November). Machine learning from theory to algorithms: An overview. In Journal of physics: Conference series (Vol. 1142, No. 1, pp. 012012). IOP Publishing.

    Google Scholar 

  • Ameen, N., Tarhini, A., Reppel, A., & Anand, A. (2021). Customer experiences in the age of artificial intelligence. Computers in Human Behavior, 114, 106548.

    Article  Google Scholar 

  • André, Q., Carmon, Z., Wertenbroch, K., Crum, A., Frank, D., Goldstein, W., & Yang, H. (2018). Consumer choice and autonomy in the age of artificial intelligence and big data. Customer Needs and Solutions, 5(1), 28–37.

    Article  Google Scholar 

  • Awad, N. F., & Krishnan, M. S. (2006). The personalisation privacy paradox: An empirical evaluation of information transparency and the willingness to be profiled online for personalisation. MIS Quarterly, 30, 13–28.

    Article  Google Scholar 

  • Babu, B. S., Srikanth, K., Ramanjaneyulu, T., & Narayana, I. L. (2016). IoT for healthcare. International Journal of Science and Research, 5(2), 322–326.

    Google Scholar 

  • Balakirsky, S., Kootbally, Z., Schlenoff, C., Kramer, T., & Gupta, S. (2012, October). An industrial robotic knowledge representation for kit building applications. In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1365–1370). IEEE.

    Chapter  Google Scholar 

  • Barsky, J. D., & Labagh, R. (1992). A strategy for customer satisfaction. Cornell Hotel and Restaurant Administration Quarterly, 33(5), 32–40.

    Article  Google Scholar 

  • Bawden, J. L. H. (2009). The process of customer engagement: A conceptual framework. Journal of Marketing Theory and Practice, 17(1), 63–74.

    Article  Google Scholar 

  • Bawden, D., Holtham, C., & Courtney, N. (1999). Perspectives on information overload. ASLIB Proceedings, 51(8), 249–255.

    Article  Google Scholar 

  • Bawden, D., & Robinson, L. (2009). The dark side of information: Overload, anxiety, and other paradoxes and pathologies. Journal of Information Science, 35(2), 180–191.

    Article  Google Scholar 

  • Beeson, M., Bonacina, M. P., Kinyon, M., & Sutcliffe, G. (2022). Larry Wos: Visions of automated reasoning. Journal of Automated Reasoning, 66, 1–23.

    Article  MathSciNet  MATH  Google Scholar 

  • Brenton, H., Gillies, M., Ballin, D., & Chatting, D. (2005, September). The uncanny valley: Does it exist. In Proceedings of human-computer interaction conference, workshop on human animated character interaction. Citeseer.

    Google Scholar 

  • Bughin, J., Seong, J., Manyika, J., Chui, M., & Joshi, R. (2018). Notes from the AI frontier: Modeling the impact of AI on the world economy. McKinsey Global Institute.

    Google Scholar 

  • Buhalis, D., Harwood, T., Bogicevic, V., Viglia, G., Beldona, S., & Hofacker, C. (2019). Technological disruptions in services: Lessons from tourism and hospitality. Journal of Service Management., 30, 484.

    Article  Google Scholar 

  • Burke, R. R. (2002). Technology and the customer interface: What consumers want in the physical and virtual store. Journal of the Academy of Marketing Science, 30(4), 411–432.

    Article  Google Scholar 

  • ÄŒaić, M., Odekerken-Schröder, G., & Mahr, D. (2018). Service robots: Value co-creation and co-destruction in elderly care networks. Journal of Service Management, 29, 178.

    Article  Google Scholar 

  • Cam, A., Chui, M., & Hall, B. (2019). Global AI survey: AI proves its worth, but few scale impacts. Mckinsey & Company.

    Google Scholar 

  • Carbonell, J. G. (2014). An overview of machine learning. Machine Learning: An Artificial Intelligence Approach (Volume I), 1, 3.

    Google Scholar 

  • Cassell, J. (2000). Embodied conversational interface agents. Communications of the ACM, 43(4), 70–78.

    Article  Google Scholar 

  • Castillo, D., Canhoto, A. I., & Said, E. (2021). The dark side of AI-powered service interactions: Exploring the process of co-destruction from the customer perspective. The Service Industries Journal, 41(13–14), 900–925.

    Article  Google Scholar 

  • Chaturvedi, R., Verma, S., Das, R., & Dwivedi, Y. K. (2023). Social companionship with artificial intelligence: Recent trends and future avenues. Technological Forecasting and Social Change, 193, 12–634.

    Google Scholar 

  • Chaturvedi, R., & Verma, S. (2022). Artificial intelligence-driven customer experience: Overcoming the challenges. California Management Review Insights.

    Google Scholar 

  • Chellappa, R. K., & Shivendu, S. (2007). An economic model of privacy: A property rights approach to regulatory choices for online personalisation. Journal of Management Information Systems, 24(3), 193–225.

    Article  Google Scholar 

  • Chellappa, R. K., & Sin, R. G. (2005). Personalisation versus privacy: An empirical examination of the online consumer’s dilemma. Information Technology and Management, 6(2), 181–202.

    Article  Google Scholar 

  • Cheng, Y., & Jiang, H. (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.

    Article  Google Scholar 

  • Chiang, A. H., & Trimi, S. (2020). Impacts of service robots on service quality. Service Business, 14(3), 439–459.

    Article  Google Scholar 

  • Choudhury, S., Shaleen, V. J., Sinha, A., Reddy, J. C., & Bhalla, S. (2021). A data-driven approach to improve customer engagement. The Boston Consulting Group (BCG). Accessed from https://www.bcg.com/en-in/data-driven-approach-to-improve-customer-engagement

    Google Scholar 

  • Chui, M., Hall, B., Singla, A., & Sukharevsky, A. The state of AI in 2021. McKinsey & Co. Accessed January 25, 2022, from https://www.McKinsey.com/business-functions/Mckinsey-analytics/our-in sights/global-survey-the-state-of-ai-in-2021.

  • Churchill, G. A., Jr., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing Research, 19(4), 491–504.

    Article  Google Scholar 

  • Cloarec, J. (2020). The personalisation–privacy paradox in the attention economy. Technological Forecasting and Social Change, 161, 120299.

    Article  Google Scholar 

  • Cotter, P., & Smyth, B. (2000, August). Personalisation technologies for the digital TV world. In ECAI (pp. 701–705).

    Google Scholar 

  • Di Nucci, E. (2020). The control paradox: From AI to populism. Rowman & Littlefield Publishers.

    Google Scholar 

  • Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961–974.

    Article  Google Scholar 

  • Dubé, L., & Le Bel, J. (2003). The content and structure of laypeople’s concept of pleasure. Cognition and Emotion, 17(2), 263–295.

    Article  Google Scholar 

  • Edmunds, A., & Morris, A. (2000). The problem of information overload in business organisations: A review of the literature. International Journal of Information Management, 20(1), 17–28.

    Article  Google Scholar 

  • Epley, N., Waytz, A., Akalis, S., & Cacioppo, J. T. (2008). When we need a human: Motivational determinants of anthropomorphism. Social Cognition, 26(2), 143–155.

    Article  Google Scholar 

  • Epley, N., Waytz, A., & Cacioppo, J. T. (2007). On seeing human: A three-factor theory of anthropomorphism. Psychological Review, 114(4), 864.

    Article  Google Scholar 

  • Fast-Berglund, Ã…., Gong, L., & Li, D. (2018). Testing and validating extended reality (XR) technologies in manufacturing. Procedia Manufacturing, 25, 31–38.

    Article  Google Scholar 

  • Feather, J. P. (1998). The information society: A study of continuity and change (2nd ed.). Library Association Publishing.

    Google Scholar 

  • Feki, M. A., Kawsar, F., Boussard, M., & Trappeniers, L. (2013). The internet of things: The next technological revolution. Computer, 46(2), 24–25.

    Article  Google Scholar 

  • Fiocco, A. J., Millett, G., D’Amico, D., Krieger, L., Sivashankar, Y., Lee, S. H., & Lachman, R. (2021). Virtual tourism for older adults living in residential care: A mixed-methods study. PLoS One, 16(5), e0250761.

    Article  Google Scholar 

  • Frankfurt, H. G. (1971). Freedom of the will and the concept of a person. The Journal of Philosophy, 68(1), 5–20.

    Article  MathSciNet  Google Scholar 

  • Gao, T. T., Rohm, A. J., Sultan, F., & Pagani, M. (2013). Consumers un-tethered: A three-market empirical study of consumers’ mobile marketing acceptance. Journal of Business Research, 66(12), 2536–2544.

    Article  Google Scholar 

  • Garcia-Sanchez, J. C. (2017). Augmenting reality in books: A tool for enhancing reading skills in Mexico. Publishing Research Quarterly, 33(1), 19–27.

    Article  Google Scholar 

  • Geller, T. (2008). Overcoming the uncanny valley. IEEE Computer Graphics and Applications, 28(4), 11–17.

    Article  Google Scholar 

  • Gerbert, P., Hecker, M., Steinhäuser, S., & Ruwolt, P. (2017). Putting artificial intelligence to work. BCG Henderson Institute. https://www.BCG.com/de-de/publications/2017/technology-digital-strategy-putting-artificial-intelligence-work.aspx. Zugegriffen am, 2, 2019.

  • Goldberg, D., Nichols, D., Oki, B. M., & Terry, D. (1992). Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35(12), 61–70.

    Article  Google Scholar 

  • Gordon, J. S., & Pasvenskiene, A. (2021). Human rights for robots? A literature review. AI and Ethics, 1(4), 579–591.

    Article  Google Scholar 

  • Han, X., Zhang, Z., Ding, N., Gu, Y., Liu, X., Huo, Y., et al. (2021). Pre-trained models: Past, present and future. AI Open, 2, 225–250.

    Article  Google Scholar 

  • Herbas Torrico, B., & Frank, B. (2019). Consumer desire for personalisation of products and services: Cultural antecedents and consequences for customer evaluations. Total Quality Management & Business Excellence, 30(3–4), 355–369.

    Article  Google Scholar 

  • Holland, J., Kingston, L., McCarthy, C., Armstrong, E., O’Dwyer, P., Merz, F., & McConnell, M. (2021). Service robots in the healthcare sector. Robotics, 10(1), 47.

    Article  Google Scholar 

  • Hoyer, W. D., Kroschke, M., Schmitt, B., Kraume, K., & Shankar, V. (2020). Transforming the customer experience through new technologies. Journal of Interactive Marketing, 51, 57–71.

    Article  Google Scholar 

  • Hsieh, C. L. A., Zhan, J., Zeng, D., & Wang, F. (2008, April). Preserving privacy in joining recommender systems. In In 2008 International Conference on Information Security and Assurance (ISA 2008) (pp. 561–566). IEEE.

    Chapter  Google Scholar 

  • Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172.

    Article  Google Scholar 

  • Jeffrey, R. C. (1974). Preference among preferences. The Journal of Philosophy, 71(13), 377–391.

    Article  Google Scholar 

  • Ji, S., Pan, S., Cambria, E., Marttinen, P., & Philip, S. Y. (2021). A survey on knowledge graphs: Representation, acquisition, and applications. IEEE Transactions on Neural Networks and Learning Systems, 33(2), 494–514.

    Article  MathSciNet  Google Scholar 

  • Karimov, F. P., & Brengman, M. (2011). Adoption of social media by online retailers: Assessment of current practices and future directions. International Journal of E-Entrepreneurship and Innovation (IJEEI), 2(1), 26–45.

    Article  Google Scholar 

  • Kattara, H. S., & El-Said, O. A. (2013). Customers’ preferences for new technology-based self-services versus human interaction services in hotels. Tourism and Hospitality Research, 13(2), 67–82.

    Article  Google Scholar 

  • Kerly, A., Ellis, R., & Bull, S. (2007). CALM system: A conversational agent for learner modelling. In International conference on innovative techniques and applications of artificial intelligence (pp. 89–102). Springer.

    Google Scholar 

  • Kerly, A., Hall, P., & Bull, S. (2006). Bringing chatbots into education: Towards natural language negotiation of open learner models. In International conference on innovative techniques and applications of artificial intelligence (pp. 179–192). Springer.

    Google Scholar 

  • Khalil, A., & Abdelli, M. E. A. (2022). Do digital technologies influence the relationship between the COVID-19 crisis and SMEs’ resilience in developing countries? Journal of Open Innovation: Technology, Market, and Complexity, 8(2), 100–109.

    Article  Google Scholar 

  • Kim, D., & Kim, S. (2017). Newspaper companies’ determinants in adopting robot journalism. Technological Forecasting and Social Change, 117, 184–195.

    Article  Google Scholar 

  • Kim, T. H., Ramos, C., & Mohammed, S. (2017). Smart city and IoT. Future Generation Computer Systems, 76, 159–162.

    Article  Google Scholar 

  • Lalicic, L., & Weismayer, C. (2021). Consumers’ reasons and perceived value co-creation of using artificial intelligence-enabled travel service agents. Journal of Business Research, 129, 891–901.

    Article  Google Scholar 

  • Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., & Coiera, E. (2018). Conversational agents in healthcare: A systematic review. Journal of the American Medical Informatics Association, 25(9), 1248–1258.

    Article  Google Scholar 

  • LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.

    Article  Google Scholar 

  • Lee, C. H., & Cranage, D. A. (2011). Personalisation–privacy paradox: The effects of personalisation and privacy assurance on customer responses to travel web sites. Tourism Management, 32(5), 987–994.

    Article  Google Scholar 

  • Leofante, F., Narodytska, N., Pulina, L., & Tacchella, A. (2018). Automated verification of neural networks: Advances, challenges and perspectives. oRR abs/1805.09938

    Google Scholar 

  • Letheren, K., & Dootson, P. (2017). Banking with a chatbot: A Battle between convenience and security. The Conversation.

    Google Scholar 

  • Liddy, E. D. (2001). Natural language processing.

    Google Scholar 

  • Lim, W. M., Kumar, S., Verma, S., & Chaturvedi, R. (2022). Alexa, what do we know about conversational commerce? Insights from a systematic literature review. Psychology & Marketing, 39, 1129.

    Article  Google Scholar 

  • Liu, B., & Sundar, S. S. (2018). Should machines express sympathy and empathy? Experiments with a health advice chatbot. Cyberpsychology, Behavior and Social Networking, 21(10), 625–626.

    Article  Google Scholar 

  • Lü, L., Medo, M., Yeung, C. H., Zhang, Y. C., Zhang, Z. K., & Zhou, T. (2012). Recommender systems. Physics Reports, 519(1), 1–49.

    Article  Google Scholar 

  • Lucente, M. (2000). Conversational interfaces for e-commerce applications. Communications of the ACM, 43(9), 59–61.

    Article  Google Scholar 

  • Luo, J. G., Wong, I. A., King, B., Liu, M. T., & Huang, G. (2019). Co-creation and co-destruction of service quality through customer-to-customer interactions: Why prior experience matters. International Journal of Contemporary Hospitality Management., 31, 1309.

    Article  Google Scholar 

  • Lv, X., Liu, Y., Luo, J., Liu, Y., & Li, C. (2021). Does a cute artificial intelligence assistant soften the blow? The impact of cuteness on customer tolerance of assistant service failure. Annals of Tourism Research, 87, 103114–103165.

    Article  Google Scholar 

  • Madakam, S., Ramaswamy, R., & Tripathi, S. (2015). Internet of Things (IoT): A literature. Journal of Computer and Communications, 3, 164–173.

    Article  Google Scholar 

  • Market Research Future. (2019). Smart Robot Market Research Report - Global Forecast Till 2023. December 2019. https://www.marketresearchfuture.com/reports/smart-robot-market-6622

  • McGoldrick, P. J., Keeling, K. A., & Beatty, S. F. (2008). A typology of roles for avatars in online retailing. Journal of Marketing Management, 24(3–4), 433–461.

    Article  Google Scholar 

  • Medvedev, A., Fedchenkov, P., Zaslavsky, A., Anagnostopoulos, T., & Khoruzhnikov, S. (2015). Waste management as an IoT-enabled service in smart cities. In In the internet of things, smart spaces, and next generation networks and systems (pp. 104–115). Springer.

    Chapter  Google Scholar 

  • Melville, P., & Sindhwani, V. (2010). Recommender systems. Encyclopedia of Machine Learning, 1, 829–838.

    Google Scholar 

  • Mercan, S., Cain, L., Akkaya, K., Cebe, M., Uluagac, S., Alonso, M., & Cobanoglu, C. (2020). Improving the service industry with hyper-connectivity: IoT in hospitality. International Journal of Contemporary Hospitality Management, 33(1), 243–262.

    Article  Google Scholar 

  • Merrill, K., Jr., Kim, J., & Collins, C. (2022). AI companions for lonely individuals and the role of social presence. Communication Research Reports, 39(1), 1–11.

    Google Scholar 

  • Meyer, C., & Schwager, A. (2007). Understanding customer experience. Harvard Business Review, 85(2), 116.

    Google Scholar 

  • Mick, D. G., & Fournier, S. (1998). Paradoxes of technology: Consumer cognisance, emotions, and coping strategies. Journal of Consumer Research, 25(2), 123–143.

    Article  Google Scholar 

  • Milgram, P., & Kishino, A. F. (1994). Taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems, 77, 1321–1329.

    Google Scholar 

  • Milne, G. R., & Culnan, M. J. (2004). Strategies for reducing online privacy risks: Why consumers read (or don’t read) online privacy notices. Journal of Interactive Marketing, 18(3), 15–29.

    Article  Google Scholar 

  • Miyazawa, A., Ribeiro, P., Li, W., Cavalcanti, A., Timmis, J., & Woodcock, J. (2019). RoboChart: Modelling and verification of the functional behaviour of robotic applications. Software & Systems Modeling, 18(5), 3097–3149.

    Article  Google Scholar 

  • Mogaji, E., & Nguyen, P. N. (2022). Managers’ understanding of artificial intelligence in relation to marketing financial services: Insights from a cross-country study. International Journal of Bank Marketing, 40(6), 1272–1298.

    Article  Google Scholar 

  • Mogaji, E., Soetan, T., & Kieu, T. (2020). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal., 29(3), 235–242.

    Article  Google Scholar 

  • Mori, M., MacDorman, K. F., & Kageki, N. (2012). The uncanny valley [from the field]. IEEE Robotics & Automation Magazine, 19(2), 98–100.

    Article  Google Scholar 

  • Mubin, O., Stevens, C. J., Shahid, S., Al Mahmud, A., & Dong, J. J. (2013). A review of the applicability of robots in education. Journal of Technology in Education and Learning, 1(209–0015), 13.

    Google Scholar 

  • Najafabadi, M. M., Villanustre, F., Khoshgoftaar, T. M., Seliya, N., Wald, R., & Muharemagic, E. (2015). Deep learning applications and challenges in big data analytics. Journal of Big Data, 2(1), 1–21.

    Article  Google Scholar 

  • Newell, A., Shaw, J. C., & Simon, H. A. (1959). Report on a general problem-solving program. In IFIP Congress (Vol. 256, p. 64).

    Google Scholar 

  • Ng, S. C., Sweeney, J. C., & Plewa, C. (2020). Customer engagement: A systematic review and future research priorities. Australasian Marketing Journal (AMJ), 28(4), 235–252.

    Article  Google Scholar 

  • Nitti, M., Pilloni, V., Giusto, D., & Popescu, V. (2017). IoT architecture for a sustainable tourism application in a smart city environment. Mobile Information Systems, 2017, 1.

    Article  Google Scholar 

  • Oliver, R. L. (1997). Satisfaction. A behavioral perspective on the consumer. Irwin-McGraw-Hill.

    Google Scholar 

  • Oussous, A., Benjelloun, F. Z., Lahcen, A. A., & Belfkih, S. (2018). Big data technologies: A survey. Journal of King Saud University-Computer and Information Sciences, 30(4), 431–448.

    Article  Google Scholar 

  • Papagiannis, H. (2020). How AR is redefining retail in the pandemic. Harvard Business Review, 7.

    Google Scholar 

  • Park, S. (2020). Multifaceted trust in tourism service robots. Annals of Tourism Research, 81, 102888.

    Article  Google Scholar 

  • Park, D. H., Kim, H. K., Choi, I. Y., & Kim, J. K. (2012). A literature review and classification of recommender systems research. Expert Systems with Applications, 39(11), 10059–10072.

    Article  Google Scholar 

  • Park, H. J., & Zhang, Y. (2022). Technology readiness and technology paradox of unmanned convenience store users. Journal of Retailing and Consumer Services, 65, 102523.

    Article  Google Scholar 

  • Paschen, J., Paschen, U., Pala, E., & Kietzmann, J. (2021). Artificial intelligence (AI) and value co-creation in B2B sales: Activities, actors, and resources. Australasian Marketing Journal, 29(3), 243–251.

    Article  Google Scholar 

  • Payne, E. H. M., Peltier, J., & Barger, V. A. (2021). Enhancing the value co-creation process: Artificial intelligence and mobile banking service platforms. Journal of Research in Interactive Marketing, 15(1), 68–85.

    Article  Google Scholar 

  • Perez-Vega, R., Kaartemo, V., Lages, C. R., Razavi, N. B., & Männistö, J. (2021). Reshaping the contexts of online customer engagement behaviour via artificial intelligence: A conceptual framework. Journal of Business Research, 129, 902–910.

    Article  Google Scholar 

  • Philp, D., Chan, N., & Sikos, L. F. (2020). Decision support for network path estimation via automated reasoning. Intelligent Decision Technologies, 2019, 335.

    Google Scholar 

  • Pieska, S., Luimula, M., Jauhiainen, J., & Spiz, V. (2013). Social service robots in wellness and restaurant applications. Journal of Communication and Computer, 10(1), 116–123.

    Google Scholar 

  • Plé, L., & Cáceres, R. C. (2010). Not always co-creation: Introducing interactional co-destruction of value in service-dominant logic. Journal of Service Marketing, 24, 430.

    Article  Google Scholar 

  • Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64–88.

    Google Scholar 

  • Prentice, C., Dominique Lopes, S., & Wang, X. (2020a). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing & Management, 29(7), 739–756.

    Article  Google Scholar 

  • Prentice, C., Weaven, S., & Wong, I. A. (2020b). Linking AI quality performance and customer engagement: The moderating effect of AI preference. International Journal of Hospitality Management, 90, 102629.

    Article  Google Scholar 

  • Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2021). Consumers and artificial intelligence: An experiential perspective. Journal of Marketing, 85(1), 131–151.

    Article  Google Scholar 

  • Rangaswamy, A., Moch, N., Felten, C., van Bruggen, G., Wieringa, J. E., & Wirtz, J. (2020). The role of marketing in digital business platforms. Journal of Interactive Marketing, 51, 72–90.

    Article  Google Scholar 

  • Ranjan, K. R., & Read, S. (2016). Value co-creation: Concept and measurement. Journal of the Academy of Marketing Science, 44(3), 290–315.

    Article  Google Scholar 

  • Rauschnabel, P. A., Babin, B. J., tom Dieck, M. C., Krey, N., & Jung, T. (2022a). What is augmented reality marketing? Its definition, complexity, and future. Journal of Business Research, 142, 1140–1150.

    Article  Google Scholar 

  • Rauschnabel, P. A., Felix, R., Hinsch, C., Shahab, H., & Alt, F. (2022b). What is XR? Towards a framework for augmented and virtual reality. Computers in Human Behavior, 133, 107289.

    Article  Google Scholar 

  • Renjith, R. (2017). The effect of information overload in digital media news content. Communication and Media Studies, 6(1), 73–85.

    Google Scholar 

  • Richens, R. H. (1956). Preprogramming for mechanical translation. Mechanical Translation Computer Linguistics, 3(1), 20–25.

    Google Scholar 

  • Roberts, M. L. (2003). Internet marketing: Integrating online and offline strategies. McGraw-Hill/Irwin.

    Google Scholar 

  • Rose, K., Eldridge, S., & Chapin, L. (2015). The internet of things: An overview. The Internet Society (ISOC), 80, 1–50.

    Google Scholar 

  • Samuel, A. L. (1967). Some studies in machine learning using the game of checkers. II—Recent progress. IBM Journal of Research and Development, 11(6), 601–617.

    Article  Google Scholar 

  • Schafer, J. B., Konstan, J., & Riedl, J. (1999, November). Recommender systems in e-commerce. In Proceedings of the 1st ACM Conference on Electronic Commerce (pp. 158–166). ACM.

    Chapter  Google Scholar 

  • Shahab, M. H., Ghazali, E., & Mohtar, M. (2021). The role of elaboration likelihood model in consumer behaviour research and its extension to new technologies: A review and future research agenda. International Journal of Consumer Studies, 45(4), 664–689.

    Article  Google Scholar 

  • Shortliffe, E. (Ed.). (2012). Computer-based medical consultations: MYCIN (Vol. 2). Elsevier.

    Google Scholar 

  • Siddike, M. A. K., & Kohda, Y. (2018). Co-creating value in People’s interactions with cognitive assistants: A service-system view. Journal of Creating Value, 4(2), 255–272.

    Article  Google Scholar 

  • Singh, J., Flaherty, K., Sohi, R. S., Deeter-Schmelz, D., Habel, J., Le Meunier-FitzHugh, K., et al. (2019). Sales profession and professionals in the age of digitisation and artificial intelligence technologies: Concepts, priorities, and questions. Journal of Personal Selling & Sales Management, 39(1), 2–22.

    Article  Google Scholar 

  • Skjuve, M., Følstad, A., Fostervold, K. I., & Brandtzaeg, P. B. (2021). My chatbot companion-a study of human-chatbot relationships. International Journal of Human-Computer Studies, 149, 102601.

    Article  Google Scholar 

  • Smith, K. T. (2020). Marketing via smart speakers: What should Alexa say? Journal of Strategic Marketing, 28(4), 350–365.

    Article  Google Scholar 

  • Sthapit, E., Del Chiappa, G., Coudounaris, D. N., & Bjork, P. (2019). Determinants of the continuance intention of Airbnb users: Consumption values, co-creation, information overload and satisfaction. Tourism Review, 75, 511.

    Article  Google Scholar 

  • Stibe, A., & De Cicco, R. (2022). Is the united intelligence response, the end of speciesism and the emergence of new avatar?

    Google Scholar 

  • Sutanto, J., Palme, E., Tan, C. H., & Phang, C. W. (2013). Addressing the personalisation-privacy paradox: An empirical assessment from a field experiment on smartphone users. MIS Quarterly, 37, 1141–1164.

    Article  Google Scholar 

  • Tom Dieck, M. C., & Jung, T. (2018). A theoretical model of mobile augmented reality acceptance in urban heritage tourism. Current Issues in Tourism, 21(2), 154–174.

    Article  Google Scholar 

  • Tondu, B. (2012). Anthropomorphism and service humanoid robots: An ambiguous relationship. Industrial Robot: An International Journal., 39, 609.

    Article  Google Scholar 

  • Tucker, C. E. (2014). Social networks, personalized advertising, and privacy controls. Journal of Marketing Research, 51(5), 546–562.

    Article  Google Scholar 

  • Tuomi, A., Tussyadiah, I. P., & Stienmetz, J. (2021). Applications and implications of service robots in hospitality. Cornell Hospitality Quarterly, 62(2), 232–247.

    Article  Google Scholar 

  • Uncles, M. D., Dowling, G. R., & Hammond, K. (2003). Customer loyalty and customer loyalty programs. Journal of Consumer Marketing., 20, 294.

    Article  Google Scholar 

  • Unni, R., & Harmon, R. (2007). Perceived effectiveness of push vs. pull mobile location-based advertising. Journal of Interactive Advertising, 7(2), 28–40.

    Article  Google Scholar 

  • Urban, G. L., Amyx, C., & Lorenzon, A. (2009). Online trust: State of the art, new frontiers, and research potential. Journal of Interactive Marketing, 23(2), 179–190.

    Article  Google Scholar 

  • Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68, 1–17.

    Article  Google Scholar 

  • Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002.

    Article  Google Scholar 

  • Waldman, D. A., Putnam, L. L., Miron-Spektor, E., & Siegel, D. (2019). The role of paradox theory in decision-making and management research. Organizational Behavior and Human Decision Processes, 155, 1–6.

    Article  Google Scholar 

  • Wang, W., De, S., Cassar, G., & Moessner, K. (2013). Knowledge representation in the internet of things: Semantic modelling and its applications. Automatika–Journal Control, Measurement, Electron Computer Communications, 54(4), 388–400.

    Google Scholar 

  • Wen, Q., Sherer, T., Tieto, V., Ferone, H., Frazier, K., & Coulter, D. (2022). What is mixed reality? Microsoft Docs. Accessed from https://docs.microsoft.com/en-us/windows/mixed-reality/discover/ What is mixed reality? - Mixed Reality | Microsoft Docs

  • Wirtz, J. (2020). Organisational ambidexterity: Cost-effective service excellence, service robots, and artificial intelligence. Organizational Dynamics, 49(3), 1–9.

    Article  Google Scholar 

  • Wirtz, J., Patterson, P. G., Kunz, W. H., Gruber, T., Lu, V. N., Paluch, S., & Martins, A. (2018). Brave new world: service robots in the frontline. Journal of Service Management, 29(5), 907–931.

    Google Scholar 

  • Wos, L., Overbeek, R., Lusk, E., & Boyle, J. (1984). Automated reasoning: Introduction and applications. Prentice-Hall.

    MATH  Google Scholar 

  • Wos, L., Pereira, F., Hong, R., Boyer, R. S., Moore, J. S., Bledsoe, W. W., et al. (1985). An overview of automated reasoning and related fields. Journal of Automated Reasoning, 1(1), 5–48.

    Article  MathSciNet  MATH  Google Scholar 

  • Xu, Y., Shieh, C. H., van Esch, P., & Ling, I. L. (2020). AI customer service: Task complexity, problem-solving ability, and usage intention. Australasian Marketing Journal (AMJ), 28(4), 189–199.

    Article  Google Scholar 

  • Yoon, V. Y., Hostler, R. E., Guo, Z., & Guimaraes, T. (2013). Assessing the moderating effect of consumer product knowledge and online shopping experience on using recommendation agents for customer loyalty. Decision Support Systems, 55, 883.

    Article  Google Scholar 

  • Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31–46.

    Article  Google Scholar 

  • Zeng, F., Ye, Q., Li, J., & Yang, Z. (2021). Does self-disclosure matter? A dynamic two-stage perspective for the personalization-privacy paradox. Journal of Business Research, 124, 667–675.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rijul Chaturvedi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Chaturvedi, R., Verma, S. (2023). Opportunities and Challenges of AI-Driven Customer Service. In: Sheth, J.N., Jain, V., Mogaji, E., Ambika, A. (eds) Artificial Intelligence in Customer Service. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-33898-4_3

Download citation

Publish with us

Policies and ethics