Optimizing customer relationship management through AI for service effectiveness: Systematic literature review

Aji HARTANTO

aji.hartanto@binus.ac.id
Bina Nusantara University (Indonesia)
https://orcid.org/0009-0003-4086-8373

VERONICA


Bina Nusantara University (Indonesia)
https://orcid.org/0000-0002-9506-5274

Danang PRIHANDOKO


Bina Nusantara University (Indonesia)
https://orcid.org/0000-0002-1664-7197

Abstract

 The current technological evolution has resulted in changes in the global business landscape. The technological changes have resulted in an organization's business processes changing due to increased customer expectations that have also changed service standards with customer management tools. The adoption of new technologies, namely artificial intelligence, has become an innovative approach strategy to Customer Relationship Management for organizational sustainability. This article aims to provide literature about integrating AI into CRM using a systematic literature review with bibliometric analysis to explore the latest trends in CRM development influenced by AI technology and the benefits and challenges faced by organizations from AI technology. This study is essential for any industry that adopts AI technology in CRM in organizations. This research was conducted by reading and analyzing 25 articles and papers related to AI and CRM. The 25 studies will be processed using the Vos Viewer tool to visualize the development of CRM trends influenced by AI technology. The study found the benefits of integrating AI-CRM into organizations by increasing operational efficiency and effectiveness, increasing customer interaction, and personalizing services. However, organizations face challenges that require aligning AICRM models with their specific needs, cultural transformation, and balancing the roles and responsibilities of humans and AI within CRM operations. In conclusion, the study found that a thorough understanding of the impact and purpose of the role of AI-CRM is needed, conditioned by the organizational situation, to maximize the benefits and minimize the risks of integrating AI with CRM in an organization.

Supporting Agencies

Bina Nusantara University, Indonesia

Keywords:

artificial intelligence (AI), customer relationship management (CRM), systematic literature review, bibliometric analysis, AI-CRM integration

Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012
  Google Scholar

Chatterjee, S., Ghosh, S. K., Chaudhuri, R., & Nguyen, B. (2019). Are CRM systems ready for AI integration?: A conceptual framework of organizational readiness for effective AI-CRM integration. Bottom Line, 32(2), 144–157. https://doi.org/10.1108/BL-02-2019-0069
  Google Scholar

Chatterjee, S., Rana, N. P., Khorana, S., Mikalef, P., & Sharma, A. (2023). Assessing organizational users’ intentions and behavior to AI integrated CRM systems: A meta-UTAUT approach. Information Systems Frontiers, 25, 1299–1313. https://doi.org/10.1007/s10796-021-10181-1
  Google Scholar

Chatterjee, S., Rana, N. P., Tamilmani, K., & Sharma, A. (2021). The effect of AI-based CRM on organization performance and competitive advantage: An empirical analysis in the B2B context. Industrial Marketing Management, 97, 205–219. https://doi.org/10.1016/j.indmarman.2021.07.013
  Google Scholar

Chaudhuri, R., Chatterjee, S., Kraus, S., & Vrontis, D. (2023). Assessing the AI-CRM technology capability for sustaining family businesses in times of crisis: the moderating role of strategic intent. Journal of Family Business Management, 13(1), 46–67. https://doi.org/10.1108/JFBM-12-2021-0153
  Google Scholar

Darban, K., Kabbaj, S., & Eljai, M. (2024). Assessing the adoption readiness of Moroccan consumers for AI-powered assistance and CRM systems. Procedia Computer Science, 236, 541–549. https://doi.org/10.1016/j.procs.2024.05.064
  Google Scholar

Dastjerdi, M., Keramati, A., & Keramati, N. (2023). A novel framework for investigating organizational adoption of AI-integrated CRM systems in the healthcare sector; using a hybrid fuzzy decision-making approach. Telematics and Informatics Reports, 11, 100078. https://doi.org/10.1016/j.teler.2023.100078
  Google Scholar

El Bakkouri, B., Raki, S., & Belgnaoui, T. (2022). The role of chatbots in enhancing customer experience: Literature review. Procedia Computer Science, 203, 432–437. https://doi.org/10.1016/j.procs.2022.07.057
  Google Scholar

Gaczek, P., Leszczyński, G., & Mouakher, A. (2023). Collaboration with machines in B2B marketing: Overcoming managers’ aversion to AI-CRM with explainability. Industrial Marketing Management, 115, 127–142. https://doi.org/10.1016/j.indmarman.2023.09.007
  Google Scholar

Jaruwanakul, T. (2024). The Influence of AI-CRM adoption and big data analytical capability on firm performance of large enterprises in Thailand. Global Business and Finance Review, 29(2), 112–126. https://doi.org/10.17549/gbfr.2024.29.2.112
  Google Scholar

Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
  Google Scholar

Khneyzer, C., Boustany, Z., & Dagher, J. (2024). AI-Driven chatbots in CRM: Economic and managerial implications across industries. Administrative Sciences, 14(8), 182. https://doi.org/10.3390/admsci14080182
  Google Scholar

Ledro, C., Nosella, A., & Dalla Pozza, I. (2023). Integration of AI in CRM: Challenges and guidelines. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 100151. https://doi.org/10.1016/j.joitmc.2023.100151
  Google Scholar

Ledro, C., Nosella, A., & Vinelli, A. (2022). Artificial intelligence in customer relationship management: literature review and future research directions. Journal of Business and Industrial Marketing, 37(13), 48–63. https://doi.org/10.1108/JBIM-07-2021-0332
  Google Scholar

Libai, B., Bart, Y., Gensler, S., Hofacker, C. F., Kaplan, A., Kötterheinrich, K., & Kroll, E. B. (2020). Brave new world? On AI and the management of customer relationships. Journal of Interactive Marketing, 51, 44–56. https://doi.org/10.1016/j.intmar.2020.04.002
  Google Scholar

Majumder, S., & Dey, N. (2022). Artificial intelligence and knowledge management. In S. Majumder & N. Dey, AI-empowered Knowledge Management (Vol. 107, pp. 85–100). Springer Singapore. https://doi.org/10.1007/978-981-19-0316-8_5
  Google Scholar

Miraz, M. H., Ya’u, A., Adeyinka-Ojo, S., Sarkar, J. B., Hasan, M. T., Hoque, K., & Jin, H. H. (2024). Intention to use determinants of AI chatbots to improve customer relationship management efficiency. Cogent Business and Management, 11(1), 2411445. https://doi.org/10.1080/23311975.2024.2411445
  Google Scholar

Mishra, N., & Mukherjee, S. (2019). Effect of artificial intelligence on customer relationship management of Amazon in Bangalore. International Journal of Management, 10(4), 168–172. https://doi.org/10.34218/IJM.10.4.2019.016
  Google Scholar

Monod, E., Lissillour, R., Köster, A., & Jiayin, Q. (2023). Does AI control or support? Power shifts after AI system implementation in customer relationship management. Journal of Decision Systems, 32(3), 542–565. https://doi.org/10.1080/12460125.2022.2066051
  Google Scholar

Pașcalău, S. V., Popescu, F. A., Bîrlădeanu, G. L., & Gigauri, I. (2024). The effects of a digital marketing orientation on business performance. Sustainability, 16(15), 6685. https://doi.org/10.3390/su16156685
  Google Scholar

Rahman, M. S., Bag, S., Gupta, S., & Sivarajah, U. (2023). Technology readiness of B2B firms and AI-based customer relationship management capability for enhancing social sustainability performance. Journal of Business Research, 156, 113525. https://doi.org/10.1016/j.jbusres.2022.113525
  Google Scholar

Sardjono, W., Cholidin, A., & Johan. (2023). Implementation of artificial intelligence-based customer relationship management for telecommunication companies. E3S Web of Conferences, 388, 8–13. https://doi.org/10.1051/e3sconf/202338803015
  Google Scholar

Saura, J. R., Ribeiro-Soriano, D., & Palacios-Marqués, D. (2021). Setting B2B digital marketing in artificial intelligence-based CRMs: A review and directions for future research. Industrial Marketing Management, 98, 161–178. https://doi.org/10.1016/j.indmarman.2021.08.006
  Google Scholar

Sewpersadh, N. S. (2023). Disruptive business value models in the digital era. Journal of Innovation and Entrepreneurship, 12, 2. https://doi.org/10.1186/s13731-022-00252-1
  Google Scholar

Sofiyah, F. R., Dilham, A., Lubis, A. S., Hayatunnufus, Marpaung, J. L., & Lubis, D. (2024). The impact of artificial intelligence chatbot implementation on customer satisfaction in padangsidimpuan: Study with structural equation modelling approach. Mathematical Modelling of Engineering Problems, 11(8), 2127–2135. https://doi.org/10.18280/mmep.110814
  Google Scholar

Yoo, J. W., Park, J., & Park, H. (2024). The impact of AI-enabled CRM systems on organizational competitive advantage: A mixed-method approach using BERTopic and PLS-SEM. Heliyon, 10(16), e36392. https://doi.org/10.1016/j.heliyon.2024.e36392
  Google Scholar

Download


Published
2025-03-31

Cited by

HARTANTO, A., VERONICA, & PRIHANDOKO, D. (2025). Optimizing customer relationship management through AI for service effectiveness: Systematic literature review. Applied Computer Science, 21(1), 153–163. https://doi.org/10.35784/acs_6871

Authors

Aji HARTANTO 
aji.hartanto@binus.ac.id
Bina Nusantara University Indonesia
https://orcid.org/0009-0003-4086-8373

Authors

VERONICA 

Bina Nusantara University Indonesia
https://orcid.org/0000-0002-9506-5274

Authors

Danang PRIHANDOKO 

Bina Nusantara University Indonesia
https://orcid.org/0000-0002-1664-7197

Statistics

Abstract views: 14
PDF downloads: 5


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.


Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.