As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and successful adoption. Our study employs a multi-method approach—combining participatory design workshops, paper-and-pencil testing, expert review, meta-analysis, and in-depth interviews—to identify and validate a design framework of eight core UX principles for human-AI agent interaction in the workplace.
These principles, along with their underlying criteria, provide actionable guardrails for designers and software engineers, laying a foundation for developing effective and human-centered AI agent interactions. This study contributes to a structured foundation for future empirical studies on agentic AI in enterprise settings.
Blogger's Review: This research provides a systematic framework of user experience principles for AI agents, emphasizing trust and effectiveness in human-AI interaction. It offers significant guidelines for designing more human-centric AI systems, making it worthy of attention and application.