For most people, yes. Jabra's WorkLife 2026 study of 6,000+ knowledge workers, released October 13, 2026, found 85% doing more of at least one kind of work, with heavy AI users reporting the biggest jumps. Dorie Clark's The Long Game explains why: saved time gets refilled unless you protect it as white space. Decide in advance where freed hours go, and train managers first.

People who adopted AI early and hard keep describing the same thing: the tools work, and the week got fuller anyway. A new survey puts numbers on that feeling, and the numbers say more about the people running the company than about the software.

Jabra released WorkLife 2026: The New Shape of Work on October 13, 2026. Toluna ran the survey in May 2026 for the Jabra Research Institute among more than 6,000 knowledge workers in France, Germany, India, Poland, the UK and the US. In every category of work measured, people said they did more than a year earlier: 51% spend more time on strategic planning and analysis, 50% on creative work and 49% on administrative tasks, and 85% report more work in at least one area. Digital Reviews Network's breakdown of the data shows the jump is steepest among heavy users. Of people using AI several times a day, 57% report more administrative and coordination work, against 38% of non-users and light users, and 56% report more strategic planning, against 35%.

Read that carefully before you build a theory on it. The survey asked how time spent on each kind of work changed. It did not measure output, and it does not show that AI caused the extra work; heavy users may simply hold bigger jobs. Jabra also sells headsets, so its finding that people who speak to AI are 24% less likely to associate work with stress deserves the same scepticism. Even so, the pattern matches what Aruna Ranganathan and Xingqi Maggie Ye argued in Harvard Business Review in February 2026 under a blunt title: AI doesn't reduce work, it intensifies it. We covered a similar signal from Korn Ferry's September report. Two sources from different angles, one direction.

The part founders should sit with is the gap between levels. In Jabra's data, 30% of senior leaders are heavy AI users against 8% of employees without management responsibilities, and 47% of senior leaders say their work changed significantly or fundamentally in the past year against 18% of non-managers. Sixty-four percent of non-managers got no AI training or only a brief introduction, against 26% of senior leaders. Digital Reviews Network adds that 44% of C-suite respondents believe their organisation has put at least three AI support measures in place, while only 14% of individual contributors say the same. And employees whose manager is capable with AI are 2.4 times more likely to use it daily, 65% against 27%, with career optimism of 8.3 out of 10 against 5.5.

If you are reading this page, you are probably in Jabra's roughly 15% of "AI Superusers." Your team is probably not. The risk is that your expectations rise at your adoption speed, and you set output targets for people who were never shown how.

The book that explains the first problem is Dorie Clark's The Long Game. Her argument starts with white space: "You can't pour more liquid into a glass that's already full." She treats busyness as a status signal and an anaesthetic, a way to avoid the uncomfortable question of what the work is for. AI time savings are not white space. They are spare capacity, and spare capacity left undecided fills with whatever is loudest, which in Jabra's data is coordination and admin. White space has to be claimed before the week starts, or it never exists.

So here is a protocol, built from Clark's white-space rule and Jabra's numbers, that a founder can run on themselves and then on one team.

The freed-hour ledger

  1. Count before you celebrate. For two weeks, write down every task AI shortened and a rough estimate of the minutes it saved. You are done when you have one weekly number, even an approximate one.
  2. Assign the hours in advance. Before Monday, put half of that number on the calendar as named white space for one long-game question, such as pricing, a hire or what to stop doing. The other half can go to output. You are done when the block exists and has a name.
  3. Check for refill on Friday. Compare the saved minutes with the growth in reviewing, meetings and messages. If coordination grew by more than you saved, AI is producing review work, so cut one report or one recurring meeting. You are done when one thing has been removed.
  4. Train down before you raise the bar. Do not raise output expectations for a team until its manager can demonstrate the workflow themselves. That is the 2.4x finding turned into a rule. You are done when the manager has shown it, not described it.

The ledger has limits. The estimates are rough, and some weeks, such as a launch, the right call is to spend every freed hour on output. The failure mode is not working more. It is letting the extra capacity be decided by default, at the top, by the person who is furthest ahead.

Sources: Jabra WorkLife Report Unveils a Productivity Paradox: AI is Giving Workers Time Back, But They're Not Working Any Less, Jabra via GlobeNewswire, October 13, 2026; AI was supposed to make work easier. So why are employees doing more?, Digital Reviews Network, October 19, 2026; AI Doesn't Reduce Work—It Intensifies It, Harvard Business Review, February 9, 2026; Dorie Clark, The Long Game: How to Be a Long-Term Thinker in a Short-Term World (Harvard Business Review Press, 2021).

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