Three Ways "More" Plays Out
So, how is this More Trap working out in practice? According to the research, it's threefold:
1. People absorb work that isn't theirs.
AI made unfamiliar tasks feel suddenly doable.
- Product managers started writing code.
- Researchers took on engineering work.
Nobody was told to do more; it just felt possible.
The result: individuals quietly absorbed work that would previously have gone to someone else or would have justified a new headcount.
As one engineer in the study put it: "You had thought that maybe you could work less. But then really, you don't work less. You just work the same amount or even more."
2. Work bleeds into every gap.
Because AI makes starting a task so frictionless, with no blank page, no unknown starting point, people began slipping prompts into lunch breaks, meetings, and even the moments before leaving their desk.
It didn't feel like extra work, because typing a prompt feels closer to chatting than to starting a formal task.
But over time, the workday lost its natural pauses.
Downtime stopped feeling like recovery. Work became ambient, something that could always be advanced a little further.
3. Multitasking explodes.
AI created a new rhythm: writing code while AI generates alternatives, running multiple agents in parallel, and reviving long-deferred tasks because AI could "handle them" in the background.
Workers felt like they had a partner.
The reality was constant attention-switching, frequent output-checking, and a growing pile of open threads.
More momentum, but also more cognitive load, and a quiet pressure to keep up with the pace AI made possible. As Simon Willison aptly noted, "the productivity boost these things can provide is exhausting."
Why This Matters
The danger is that all of this looks like a win from the outside. More output. More initiative. More speed.
But the study is clear: what looks like productivity can mask silent workload creep and growing cognitive strain.
Because the extra effort is voluntary and feels like experimentation, leaders easily miss how much additional load their people are carrying.
Over time, that leads to impaired judgment, higher error rates, and burnout. It's another silent killer, along with 'checkers, not leaders,' we reported on recently.
Your Move This Week
Every time something speeds up, pick something that stops.
When your team moves a process to AI, ask: What can we now drop?
If the answer is "nothing," you haven't gained productivity; you've only increased workload density.
Sustainable productivity only happens when leaders are as intentional about what to stop as they are about what to start.
I'll start: we implemented a bi-weekly 'clean-up' session where we go around the table to discuss what we can offload or kill.
That's future-proofing the team.
