From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions

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.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757408
Citations
1
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
1.94
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From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions

Shamsi T. Iqbal, Mary Czerwinski, Javier Hernandez, Judith Amores Fernandez et al.
1 citations
Proceedings of the ACM on Human-Computer Interaction
Innovative Human-Technology Interaction
1.94
article

From User Surveys to Telemetry-Driven AI Agents: Exploring the Potential of Personalized Productivity Solutions

Shamsi T. Iqbal, Mary Czerwinski, Javier Hernandez, Judith Amores Fernandez, Brian Houck, Talie Massachi, Kael Rowan, Jina Suh, Subigya Nepal, Gonzalo Ramos
article en
1 citations

Abstract

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.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
Microsoft (United States) (US), University of Virginia (US), University of Pennsylvania (US)
Openalex Percentile: Top 12%
Innovative Human-Technology Interaction
1.94
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