Adoption of Generative AI in the Workplace: Increasing and Shifting the Balance of Productivity and Communication Activity

2026-08-16

AI Summary

This study addresses the paucity of empirical evidence regarding how generative AI reshapes work practices by leveraging Microsoft M365 digital trace data and a difference-in-differences model to quantify the dynamic impact of AI adoption on productivity and communication balance. The research reveals a novel structural shift effect: high-frequency users exhibit a 21.2% increase in productivity and a 7.1% rise in communication activities, alongside a marked reorientation toward individual documentation. These findings bridge the empirical gap concerning AI’s influence on the quantity and nature of information work, elucidating the intrinsic mechanisms driving the technology-induced rebalancing of productivity and communication within modern workplaces.

Abstract

Generative AI is transforming the workplace by augmenting and automating cognitive tasks, reshaping how organizations work and innovate while raising questions about workplace inequality and the future of work. Despite rapid adoption, empirical evidence on how these tools alter work practices and generate productivity gains remains limited. We examine how AI use affects the quantity and nature of information work using digital trace data from the Microsoft M365 application suite across multiple large international companies. Specifically, we study how generative AI adoption shifts the balance between communication and productivity-oriented activities, such as content creation in Word. Difference-in-Differences analyses show that AI adoption is associated with significant increases in both productivity (21.2%) and communication (7.1%) application actions among users who used the AI system more than 100 times over a 20-week post-adoption period. Among users with 100-500 AI use instances, higher AI usage is also associated with continued increases in both types of activity. The smaller increase in communication represents an overall shift toward individual, documentation-focused work and reflects mixed changes in communication, including decreases in reading and organizing email, compared with more uniform increases in productivity actions. These findings suggest potential efficiency gains and reductions in information overload, while highlighting the need to ensure that AI adoption does not weaken interpersonal communication and the diffusion of diverse information that supports innovation.

Problem

• Generative AI
• Workplace Productivity
• Communication Activity
• Information Work
• Digital Trace Data

Innovation

• Generative AI
• Digital Trace Data
• Difference-in-Differences
• Workplace Productivity
• Information Overload