The ActivTrak Productivity Lab today released new research revealing patterns in how artificial intelligence changes work. The analysis found that AI users have workdays up to 90 minutes longer than non-users, while heavy users switch between applications more frequently and have shorter periods of uninterrupted focus.

Unlike employee surveys or self-reported AI adoption, the analysis draws on actual digital work patterns from 9,140 knowledge workers across 467 enterprises collected between April 1 and September 25, 2026.

Using ActivTrak’s proprietary behavioral work data , researchers examined how AI usage relates to workday length, application switching, focus and workflow efficiency — revealing differences between adopting AI tools and integrating them effectively into daily work.

The analysis also identified significant differences in application switching based on how employees access AI tools and their job roles:

These findings suggest that integrating AI directly into existing applications may help reduce context switching while standalone tools may introduce additional steps into workflows.

“AI may help employees complete tasks faster, but our research shows it contributes to longer workdays, more application switching and shorter focus sessions,” said Gabriela Mauch , Chief Customer Officer and Head of the ActivTrak Productivity Lab. “For leaders, the goal can’t simply be AI usage; they need to treat AI usage as a means to measurable gains in productivity, efficiency and business performance.”

The ActivTrak Productivity Lab is the research and advisory division of ActivTrak, helping organizations understand how work evolves in the AI era. Powered by one of the world’s largest behavioral datasets on workplace activity, the Lab analyzes aggregated workforce intelligence data from thousands of organizations to uncover how productivity, AI adoption and collaboration patterns change. The Lab advances a deeper understanding of how work impacts organizational performance and workforce wellbeing through privacy-first analytics and responsible data practices.