Blending Automation with Empathy: Customer Preferences for Human vs. AI Interaction in Service
Tanuj Mathur, Sanjeev Kadam, Reshma Rakesh Nair, Jaymin Arvind Shah · 2025
The increasing integration of artificial intelligence in customer service has transformed customers service delivery. However, in the customer service delivery process AI-driven agents often struggle to replicate human empathy, influencing customer preferences for choosing AI-driven agent versus human agent across different service situations. This study examines customer preferences for AI-driven versus human agent interactions using a scenario-based survey approach, where respondents evaluated four distinct service scenarios to assess the relative importance of efficiency and empathy. The study employed a purposive sampling technique and a structured online questionnaire to collect data from 130 respondents who had prior interacted with AI-driven and human agent for service consumption. The findings reveal that AI-driven agents are preferred for transactional and decision-support tasks, such as retrieving store information and providing product recommendations. Conversely, in sensitive situations like billing disputes and complaint resolution, human agents are strongly preferred due to their ability to provide empathetic value. The study provides valuable insights for technology developers and service firms on the specific scenarios that may assist them in building empathetic AI models for the AI-enabled service delivery systems.