Start Date
10-12-2017 12:00 AM
Description
As more organizations establish artificial intelligence-based service agents to offer an automated customer dialogue it is crucial to understand how users perceive this new form of technology-mediated communication. AI-based service agents interact in a similar way as humans in human-to-human chat conversations, but instead of a live person on the other end, a chat bot steers the communication based on artificial intelligence and Natural Language Interaction. By combining qualitative and quantitative methods, we examine this context and explore the role of perceived authenticity and its impact on users’ attitudinal and behavioral outcomes. Our results from the qualitative studies show that users infer the authenticity of the AI-based service agents based on two different categories of cues: (1) agent-related cues and (2) communication-related cues. We employ additional experimental studies to empirically test antecedents and consequences of authenticity perceptions in AI-based service encounters.
Recommended Citation
Wuenderlich, Nancy Viola and Paluch, Stefanie, "A Nice and Friendly Chat with a Bot: User Perceptions of AI-Based Service Agents" (2017). ICIS 2017 Proceedings. 11.
https://aisel.aisnet.org/icis2017/ServiceScience/Presentations/11
A Nice and Friendly Chat with a Bot: User Perceptions of AI-Based Service Agents
As more organizations establish artificial intelligence-based service agents to offer an automated customer dialogue it is crucial to understand how users perceive this new form of technology-mediated communication. AI-based service agents interact in a similar way as humans in human-to-human chat conversations, but instead of a live person on the other end, a chat bot steers the communication based on artificial intelligence and Natural Language Interaction. By combining qualitative and quantitative methods, we examine this context and explore the role of perceived authenticity and its impact on users’ attitudinal and behavioral outcomes. Our results from the qualitative studies show that users infer the authenticity of the AI-based service agents based on two different categories of cues: (1) agent-related cues and (2) communication-related cues. We employ additional experimental studies to empirically test antecedents and consequences of authenticity perceptions in AI-based service encounters.