Shifting Work Patterns with Generative AI

2025-04-15

AI Summary

This study investigates the independent causal effect of generative AI on knowledge workers’ task behaviors—specifically, whether it autonomously alters individual behavior or requires organizational coordination. Method: We conduct a six-month, cross-industry randomized field experiment involving 6,000 employees, isolating generative AI’s impact on autonomy-intensive tasks (e.g., email processing) versus coordination-dependent tasks (e.g., meeting participation). AI tools were embedded in email, document, and meeting software for the treatment group. Contribution/Results: Generative AI significantly reduced weekly email processing time by 3 hours (25%) and improved document completion efficiency; however, meeting duration showed no statistically significant change. These findings demonstrate that generative AI’s initial behavioral impact is confined to individually controllable, low-coordination tasks—revealing critical boundary conditions and selection mechanisms for AI-driven behavioral intervention in organizational settings.

Technology Category

• Humans and AI: Human-Aware Planning and Behavior Prediction
• Intelligent Robots: Embodied AI
• Natural Language Processing: Generation

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

We present evidence on how generative AI changes the work patterns of knowledge workers using data from a 6-month-long, cross-industry, randomized field experiment. Half of the 6,000 workers in the study received access to a generative AI tool integrated into the applications they already used for emails, document creation, and meetings. We find that access to the AI tool during the first year of its release primarily impacted behaviors that could be changed independently and not behaviors that required coordination to change: workers who used the tool spent 3 fewer hours, or 25% less time on email each week (intent to treat estimate is 1.4 hours) and seemed to complete documents moderately faster, but did not significantly change time spent in meetings.

Problem

• How generative AI alters knowledge workers' independent work behaviors
• Impact of AI tools on email and document tasks efficiency
• Limited effect of AI on coordination-dependent activities like meetings

Innovation

• Generative AI tool integrated into existing applications
• Reduced email time by 25% weekly
• No significant change in meeting time