Research conducted by the Goa Institute of Management (GIM) has revealed that a balanced approach to humanizing Artificial Intelligence (AI) in chatbots can significantly enhance customer trust and comfort. The study, conducted in collaboration with researchers from Cochin University of Science and Technology (CUSAT) in Kerala, indicates that while some level of human resemblance can be beneficial, excessive anthropomorphism tends to cause discomfort among users.
The findings, published in the International Journal of Consumer Studies, focus on consumer behavior towards AI-enabled service agents, including chatbots, digital assistants, and service robots. As AI technology continues to reshape Frontline Service Encounters (FLSE), the research aims to deepen the understanding of how consumers perceive and interact with AI in everyday service scenarios.
To conduct this study, the research team reviewed 157 peer-reviewed articles and examined 44 top-tier journals across multiple sectors, including hospitality, retail, banking, and healthcare. This comprehensive analysis sought to identify key drivers, theories, and outcomes that influence consumer interactions with AI.
“Our findings show that when AI agents are designed with the right balance of humanization, competence, and empathy, they can foster stronger consumer trust and engagement,” said Manu C, Assistant Professor at GIM. He emphasized that the study found that a carefully calibrated level of humanized AI design not only enhances customer comfort but also significantly builds trust. Conversely, he noted that designs with excessive human likeness can lead to negative feelings among users.
The research posits that AI interaction design—including aspects such as appearance, empathy, and communication style—strongly influences customer trust, engagement, and satisfaction. This insight led to the development of an integrated framework that consolidates previously scattered findings into a cohesive model. This model seeks to explain how the design of AI agents, along with consumer traits and service contexts, collectively affect customer outcomes.
In outlining the implications of their research, the team provided a roadmap for future studies in AI and consumer behavior. The proposed framework identifies crucial mediators and moderators that shape consumer responses to AI service agents. “This model advances understanding of how AI design features, such as human-likeness, empathy, reliability, and consumer traits jointly influence trust, acceptance, and satisfaction,” added Manu C.
The study also highlights significant research gaps, such as the variations in AI perception across different cultures, the impact of social identity on trust in AI, and the ethical considerations surrounding AI humanization. These insights hold direct relevance for service managers, designers, and marketers aiming to deploy AI responsibly in customer-facing roles.
As AI continues to permeate various industries, including hospitality, banking, and retail, the findings from this research offer strategic guidance for decision-makers. The insights derived from this study may help organizations navigate the complexities of AI integration, ensuring that customer engagement remains at the forefront of technological advancements. The careful design of AI interfaces could ultimately play a pivotal role in fostering positive consumer relationships as AI becomes an increasingly integral part of service delivery.
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