  The rise of AI conversational agents has broadened opportunities to enhance
human capabilities across various domains. As these agents become more
prevalent, it is crucial to investigate the impact of different affective
abilities on their performance and user experience. In this study, we surveyed
745 respondents to understand the expectations and preferences regarding
affective skills in various applications. Specifically, we assessed preferences
concerning AI agents that can perceive, respond to, and simulate emotions
across 32 distinct scenarios. Our results indicate a preference for scenarios
that involve human interaction, emotional support, and creative tasks, with
influences from factors such as emotional reappraisal and personality traits.
Overall, the desired affective skills in AI agents depend largely on the
application's context and nature, emphasizing the need for adaptability and
context-awareness in the design of affective AI conversational agents.
