A qualitative analysis of AI-driven chatbots on customer service employees’ productivity and satisfaction
Apostolakis, Anastasios (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025051411732
https://urn.fi/URN:NBN:fi:amk-2025051411732
Tiivistelmä
Artificial-intelligence-driven chatbots are reshaping customer service by automating routine tasks, yet
their impact on employees’ productivity and satisfaction requires deeper exploration. This thesis examines how chatbot implementation influences customer service employees’ daily work experiences, focusing on productivity, motivation, and job satisfaction. The study was conducted within a customer service department of a company integrating chatbots, addressing the transformative effects on traditional roles. The research aimed to identify gaps in understanding chatbot-related impacts on employees and provide recommendations to enhance their workplace experience. The theoretical framework integrates Herzberg’s Two-Factor Theory, employee productivity theories, and studies on AI applications in customer service, emphasizing how chatbots redefine workflows and responsibilities. A qualitative case study approach was employed, utilizing structured interviews with six customer service employees experienced in pre- and post chatbot environments. Data were analysed through thematic analysis, guided by Braun and Clarke’s (2006) methodology, to uncover patterns in employees’ perceptions. Findings reveal that chatbots enhance productivity by reducing repetitive
workloads, boost job satisfaction through skill development, and increase motivation by enabling focus on complex tasks. However, technical barriers and job security concerns highlight the need for targeted
training and communication. Based on the findings and theoretical framework, recommendations include implementing comprehensive training programmes and transparent communication to address technical and ethical challenges. While limited to a small sample, specific customer service team, the results offer insights applicable to other organizations adopting AI-driven chatbots. These findings contribute to discussions on balancing automation with human-centric workplace strategies, fostering positive employee outcomes in service oriented industries.
their impact on employees’ productivity and satisfaction requires deeper exploration. This thesis examines how chatbot implementation influences customer service employees’ daily work experiences, focusing on productivity, motivation, and job satisfaction. The study was conducted within a customer service department of a company integrating chatbots, addressing the transformative effects on traditional roles. The research aimed to identify gaps in understanding chatbot-related impacts on employees and provide recommendations to enhance their workplace experience. The theoretical framework integrates Herzberg’s Two-Factor Theory, employee productivity theories, and studies on AI applications in customer service, emphasizing how chatbots redefine workflows and responsibilities. A qualitative case study approach was employed, utilizing structured interviews with six customer service employees experienced in pre- and post chatbot environments. Data were analysed through thematic analysis, guided by Braun and Clarke’s (2006) methodology, to uncover patterns in employees’ perceptions. Findings reveal that chatbots enhance productivity by reducing repetitive
workloads, boost job satisfaction through skill development, and increase motivation by enabling focus on complex tasks. However, technical barriers and job security concerns highlight the need for targeted
training and communication. Based on the findings and theoretical framework, recommendations include implementing comprehensive training programmes and transparent communication to address technical and ethical challenges. While limited to a small sample, specific customer service team, the results offer insights applicable to other organizations adopting AI-driven chatbots. These findings contribute to discussions on balancing automation with human-centric workplace strategies, fostering positive employee outcomes in service oriented industries.