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AI-Driven Chatbots in CRM: Economic and Managerial Implications across Industries

Author

Listed:
  • Chadi Khneyzer

    (Faculty of Business & Management, University of Balamand, Koura, Lebanon)

  • Zaher Boustany

    (Faculty of Business and Administration, Saint Joseph University, Beirut 1104 2020, Lebanon)

  • Jean Dagher

    (Faculty of Business & Management, University of Balamand, Koura, Lebanon)

Abstract

In the era of digitization and technical breakthroughs, artificial intelligence (AI) has progressively found its way into the field of customer relationship management (CRM), bringing benefits as well as difficulties to businesses. AI, particularly in the context of CRM, employs machine learning (ML) and deep learning (DL) techniques to extract knowledge from data, recognize trends, make decisions, and learn from mistakes with minimal human intervention. Successful firms have effectively integrated AI into CRM for predictive analytics, computer vision, sentiment analysis, personalized recommendations, chatbots and virtual assistants, and voice and speech recognition. AI-driven chatbots, one of the AI-powered CRM systems, arose as a disruptive approach to customer service, and as such, unfolded with economic and managerial ramifications in CRM. Given the literature’s focus on other AI-driven systems, there is an obvious need for an investigation of industry applications and the implications of AI-driven chatbots in CRM. The purpose of this study is to explore and elucidate the economic and managerial implications of AI-powered chatbots within CRM systems. This investigation aims to provide a comprehensive understanding of how these technologies can enhance customer interactions, streamline business processes, and impact organizational strategies. To reach this goal, this study conducts a comparative qualitative analysis based on many interviews with experts and contributors in the field. Interviews with CRM specialists yielded insights into the use of AI-driven chatbots in CRM and their impact on the industry. The primary advantages identified in this study were the impact of AI-powered chatbots on cost, efficiency, and human performance. In addition, AI chatbots have proven useful in a variety of industries, including retail and tourism. Nonetheless, there were limitations to its usage in the healthcare system, particularly in terms of ethical problems.

Suggested Citation

  • Chadi Khneyzer & Zaher Boustany & Jean Dagher, 2024. "AI-Driven Chatbots in CRM: Economic and Managerial Implications across Industries," Administrative Sciences, MDPI, vol. 14(8), pages 1-16, August.
    • Handle: RePEc:gam:jadmsc:v:14:y:2024:i:8:p:182-:d:1459192
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    References listed on IDEAS

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    1. V. Kumar & Werner Reinartz, 2018. "Customer Relationship Management," Springer Texts in Business and Economics, Springer, edition 3, number 978-3-662-55381-7, March.
    2. Sheth, Jagdish N. & Parvatiyar, Atul, 1995. "The evolution of relationship marketing," International Business Review, Elsevier, vol. 4(4), pages 397-418.
    3. Rahman, Muhammad Sabbir & Bag, Surajit & Gupta, Shivam & Sivarajah, Uthayasankar, 2023. "Technology readiness of B2B firms and AI-based customer relationship management capability for enhancing social sustainability performance," Journal of Business Research, Elsevier, vol. 156(C).
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    Cited by:

    1. Domingos Martinho & João Farinha & Vasco Ribeiro, 2025. "The Impact of Customer Relationship Management Systems on Business Performance of Portuguese SMEs," Sustainability, MDPI, vol. 17(12), pages 1-19, June.
    2. Nada Mallah Boustani, 2025. "ChatGPT—A Stormy Innovation for a Sustainable Business," Administrative Sciences, MDPI, vol. 15(5), pages 1-3, May.
    3. Adzman Shah Mohd Ariffin & Fitriyah Razali & Muhammad Najib Razali & Muhamad Amir Afiq Lokman, 2025. "Adoption of Artificial Intelligence and Technology in Customer Relationship Management for Property Management: A Systematic Literature Review," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(1), pages 3312-3320, January.

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