AI and productivity
AI saves minutes. Why are workdays still getting longer?
A new workplace study raises a practical question: when AI speeds up a task, what happens to the time saved?

AI can draft a reply in seconds. But if the saved time fills up with more requests, extra review and another round of copying information between tools, the workday may feel just as crowded. A recent study offers a reason to examine the whole workflow, not just the speed of a single task. ActivTrak Productivity Lab
What the research found
ActivTrak's October 2026 analysis examined digital work patterns for 9,140 knowledge workers at 467 enterprises between April 1 and September 25, 2026. In its sample, AI users' workday spans averaged 8.4 to 9.1 hours, compared with 7.6 hours for non-users: a difference of up to about 90 minutes. The company also reported more application switching among heavy AI users than non-users, and shorter uninterrupted focus sessions than light users. ActivTrak Productivity Lab
These are observed associations, not proof that AI caused longer days. Roles, responsibilities and other differences between groups could also matter. A workday span is not the same thing as uninterrupted work, and the sample does not represent every worker or workplace. The finding is a prompt to ask better questions, not a prediction about your team.
Where can the saved minutes go?
A draft may be faster while the surrounding work remains: finding the right thread, checking an AI suggestion, agreeing on a time, updating a record and following up. The extra capacity may also be absorbed by more requests. None of those outcomes is inevitable; each is something a team can examine.
Gallup's research points to a related consideration: reported productivity gains are stronger when AI fits existing systems and managers support its use. Fit and follow-through deserve attention alongside adoption. Gallup
Run a five-day workflow audit
- 1
Choose one recurring request
Pick a real, repeatable task such as booking a client consultation. Record the first message and the completed outcome; avoid collecting unnecessary customer details.
- 2
Count handoffs and waiting
Note the tools used, information copied, follow-up messages and time spent waiting for a decision. Separate elapsed time from active work.
- 3
Remove one unnecessary step
Try a booking link or turn a date in an email into a meeting. Keep the same quality checks and confirm who owns the next action.
- 4
Compare a small sample
Track a few similar requests before and after the change. Record completion, corrections and time spent. A small sample can guide a decision, but it is not a company-wide productivity study.
- 5
Protect the result
Agree whether time saved supports customer work, fewer interruptions or a lighter workload. Revisit the process if the time immediately disappears into additional tasks.
Example: from inquiry to appointment
A client emails to arrange a consultation. One approach is to copy the request into a separate calendar, exchange several availability messages and retype the details. Another is to use a booking link or create a meeting from the date in the message, then check the details before confirming. Venmail supports booking from email and turning dates into meeting actions. The time saved will depend on the request and how the team works.
Measure the outcome, not the number of AI prompts
Ask whether customers got a useful response, whether the next action was completed and whether employees had enough uninterrupted time to do the work well. If demand still exceeds capacity, redesigning a process may help, but staffing and priorities need attention too. AI is most useful when the time it saves becomes something people can actually use.
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