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<p>This study explores the transformative impact of conversational artificial intelligence (AI) on customer support systems across various industries. Through a systematic qualitative literature review of 15 empirical studies and the analysis of 10 contemporary abstracts, the research identifies key operational, experiential, and ethical dimensions associated with AI-driven service delivery. Findings reveal that conversational AI significantly enhances efficiency, scalability, and customer accessibility, especially during crisis periods like the COVID-19 pandemic. However, challenges such as limited emotional intelligence, ethical concerns over data privacy and bias, and lack of transparency persist. The review highlights that customer satisfaction and trust depend heavily on the system's communication quality, anthropomorphic design, and ability to escalate complex issues to human agents. Hybrid models, combining AI automation with human oversight, consistently produce the most favorable outcomes. Sector-specific variations underscore the importance of context-aware AI deployment strategies. The study emphasizes the urgent need for ethical frameworks, regulatory standards, and user-centered design in the development and implementation of conversational AI technologies. Future research should focus on longitudinal, real-world evaluations to address gaps in user experience, fairness, and technological accountability. This paper contributes to the understanding of how AI can be sustainably integrated into customer service, aligning innovation with human-centric values.</p>

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Conversational AI in customer support: Revolution or risk?

  • 期刊论文

  • 发表日期：

    2025年12月15日

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  • Bilawal Sarwar,
  • Joudat Irshad Hashmi

摘要

This study explores the transformative impact of conversational artificial intelligence (AI) on customer support systems across various industries. Through a systematic qualitative literature review of 15 empirical studies and the analysis of 10 contemporary abstracts, the research identifies key operational, experiential, and ethical dimensions associated with AI-driven service delivery. Findings reveal that conversational AI significantly enhances efficiency, scalability, and customer accessibility, especially during crisis periods like the COVID-19 pandemic. However, challenges such as limited emotional intelligence, ethical concerns over data privacy and bias, and lack of transparency persist. The review highlights that customer satisfaction and trust depend heavily on the system's communication quality, anthropomorphic design, and ability to escalate complex issues to human agents. Hybrid models, combining AI automation with human oversight, consistently produce the most favorable outcomes. Sector-specific variations underscore the importance of context-aware AI deployment strategies. The study emphasizes the urgent need for ethical frameworks, regulatory standards, and user-centered design in the development and implementation of conversational AI technologies. Future research should focus on longitudinal, real-world evaluations to address gaps in user experience, fairness, and technological accountability. This paper contributes to the understanding of how AI can be sustainably integrated into customer service, aligning innovation with human-centric values.