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AI Adoption Is Up. So Why Is Work Getting Harder?
AI adoption is climbing across the enterprise—but is it actually making work better?
In this episode of AI Leadership Studio, host Dan Verton speaks with Gabriella Mauck, Chief Customer Officer and head of the ActivTrak Productivity Lab, about one of the most revealing workforce studies of 2026: a three-year behavioral analysis of 163,000 employees across more than 1,100 companies.
The findings challenge one of the most common assumptions in enterprise AI: that adoption automatically leads to efficiency.
Instead, the data shows that after AI adoption:
- Time spent in email increased 104%
- Time in chat and messaging rose 145%
- Every major work category measured increased
- Average focused work sessions fell to just 13 minutes
- Only a small percentage of users reached the level of AI usage associated with measurable productivity gains
This episode explores the growing AI measurement gap—the disconnect between tracking logins and understanding business impact—and what leaders must do next to govern AI effectively, protect focus, and redesign work for better outcomes.
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By ISMG Content Intelligence & AI InnovationAI adoption is climbing across the enterprise—but is it actually making work better?
In this episode of AI Leadership Studio, host Dan Verton speaks with Gabriella Mauck, Chief Customer Officer and head of the ActivTrak Productivity Lab, about one of the most revealing workforce studies of 2026: a three-year behavioral analysis of 163,000 employees across more than 1,100 companies.
The findings challenge one of the most common assumptions in enterprise AI: that adoption automatically leads to efficiency.
Instead, the data shows that after AI adoption:
- Time spent in email increased 104%
- Time in chat and messaging rose 145%
- Every major work category measured increased
- Average focused work sessions fell to just 13 minutes
- Only a small percentage of users reached the level of AI usage associated with measurable productivity gains
This episode explores the growing AI measurement gap—the disconnect between tracking logins and understanding business impact—and what leaders must do next to govern AI effectively, protect focus, and redesign work for better outcomes.