From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Information workers increasingly struggle with productivity challenges in modern workplaces, facing difficulties in managing time and effectively utilizing workplace analytics data for behavioral improvement. Despite the availability of productivity metrics through enterprise tools, workers often fail to translate this data into actionable insights. We present a comprehensive, user-centric approach to address these challenges through AI-based productivity agents 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 these insights, our work provides important guidance for developing more effective productivity solutions, ultimately leading to optimized efficiency and user experiences for information workers.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 8 of its 83 references that are in the map. First posted on arXiv 17 Jan 2024.
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8 of 83 references.
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Other references · 7
- 2017Calendar.help: Designing a Workflow-Based Scheduling Agent with Humans in the Loopcited by 26
- 2018Understanding Chatbot-mediated Task Managementcited by 12
- 2023Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic Procrastinationcited by 12
- 2020Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamworkcited by 9
- 2022A Survey of Passive Sensing for Workplace Wellbeing and Productivitycited by 4
- 2018Towards effective AI-powered agile project managementcited by 3
- 2022Imagining Future Digital Assistants at Work: A Study of Task Management Needscited by 3
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Citing papers per year: 2026: 1.
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