AI Chatbots vs. Human Customer Service: Impact on Consumer Satisfaction and Purchase Decisions

Abstract

This paper presents an in-depth comparative assessment of AI-powered chatbots and human customer service agents, focusing on their roles in shaping consumer satisfaction and influencing purchasing behavior. Drawing on insights from over thirty scholarly sources—including empirical studies and theoretical models such as the Technology Acceptance Model (TAM), Expectation-Confirmation Theory (ECT), and the SERVQUAL framework—the study examines how different modes of service delivery affect trust, emotional resonance, perceived usefulness, and consumer decision-making. The findings reveal that while AI chatbots offer significant operational advantages—such as round-the-clock availability, rapid response times, and cost-efficiency—they often fall short in scenarios requiring emotional nuance or contextual sensitivity, areas where human agents continue to excel. Through case studies of successful implementations by companies like Amazon, H&M, and Sephora, as well as less effective examples such as Facebook M, the analysis underscores the potential of hybrid models that combine the scalability of AI with the empathetic capabilities of human agents. The paper also addresses pressing ethical concerns, including data privacy, algorithmic bias, and the displacement of human labor. Ultimately, it argues that the future of customer service lies not in choosing between humans and machines, but in developing integrated systems that leverage the unique strengths of both to meet the evolving expectations of contemporary consumers.