We present a comprehensive, user-centric approach to understand preferences in AI-based productivity agents and develop personalized solutions tailored to users' needs. Utilizing a two-phase method, we first conducted a survey with 363 participants, exploring various aspects of productivity, communication style, agent approach, personality traits, personalization, and privacy. Drawing on the survey insights, we developed a GPT-4 powered personalized productivity agent that utilizes telemetry data gathered via Viva Insights from information workers to provide tailored assistance. We compared its performance with alternative productivity-assistive tools, such as dashboard and narrative, in a study involving 40 participants. Our findings highlight the importance of user-centric design, adaptability, and the balance between personalization and privacy in AI-assisted productivity tools. By building on the insights distilled from our study, we believe that our work can enable and guide future research to further enhance productivity solutions, ultimately leading to optimized efficiency and user experiences for information workers.

翻译：我们提出了一种以用户为中心的全面方法，旨在理解基于AI的生产力代理的偏好，并开发满足用户需求的个性化解决方案。采用两阶段方法，我们首先对363名参与者进行了一项调查，探讨了生产力的各个方面，包括沟通风格、代理方法、人格特质、个性化及隐私。基于调查洞察，我们开发了一个由GPT-4驱动的个性化生产力代理，该代理利用通过Viva Insights从信息工作者处收集的遥测数据提供定制化帮助。在涉及40名参与者的研究中，我们将其性能与仪表盘和叙事等替代生产力辅助工具进行了比较。我们的研究结果强调了以用户为中心的设计、适应性以及AI辅助生产力工具中个性化与隐私平衡的重要性。通过基于研究提炼的洞察，我们认为本研究能够为未来进一步优化生产力解决方案提供指导和推动，最终实现信息工作者效率与用户体验的最优化。