Abstract
This study explores use cases for conversational agents using an interview-based study with 50 individuals. We report an analysis that illustrates which conversational agents designs are perceived as useful or enjoyable by individuals and are therefore a predictor for adoption and diffusion of conversational agents in both private and professional contexts. The results of the interviews are classified into seven use case categories: Use of conversational agents for information retrieval, smart home control, goods and services, car and navigation, music and entertainment, work and office and other. However, the results also indicate that in order to improve perceived usefulness, conversational agents must improve and become “more intelligent”. Though, concerns such as privacy issues and transparency should be addressed by companies in order to ensure a sustainable development and diffusion. Hence, we conclude an agenda for research and designers of conversational agents to focus on use cases and conversational agents designs that provide the breeding ground for adoption and diffusion.
Recommended Citation
Laumer, Sven; Gubler, Fabian Tobias; Racheva, Ana; and Maier, Christian, "Use Cases for Conversational Agents: An Interview-based Study" (2019). AMCIS 2019 Proceedings. 16.
https://aisel.aisnet.org/amcis2019/adoption_diffusion_IT/adoption_diffusion_IT/16
Use Cases for Conversational Agents: An Interview-based Study
This study explores use cases for conversational agents using an interview-based study with 50 individuals. We report an analysis that illustrates which conversational agents designs are perceived as useful or enjoyable by individuals and are therefore a predictor for adoption and diffusion of conversational agents in both private and professional contexts. The results of the interviews are classified into seven use case categories: Use of conversational agents for information retrieval, smart home control, goods and services, car and navigation, music and entertainment, work and office and other. However, the results also indicate that in order to improve perceived usefulness, conversational agents must improve and become “more intelligent”. Though, concerns such as privacy issues and transparency should be addressed by companies in order to ensure a sustainable development and diffusion. Hence, we conclude an agenda for research and designers of conversational agents to focus on use cases and conversational agents designs that provide the breeding ground for adoption and diffusion.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.