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This study establishes a comprehensive framework of eight core user experience (UX) principles tailored for human-AI agent interactions in workplace settings, derived from a multi-method approach that includes participatory design workshops and expert reviews. By validating these principles through in-depth interviews and meta-analysis, the research highlights the critical role of user trust in the successful adoption of AI agents. The resulting framework not only offers actionable guidelines for designers and engineers but also lays the groundwork for future empirical investigations into agentic AI in enterprise environments.
Eight UX principles for human-AI interactions could redefine how businesses integrate AI agents into their workflows.
As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and successful adoption. To address this, our study uses a multi-method approach - combining participatory design workshop, paper-and-pencil, 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. Together with their underlying criteria, these principles provide actionable guardrails for designers and software engineers, creating 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.
