An eight-month study at a US tech company finds AI tools didn't reduce work but intensified it, as employees worked faster and took on a broader range of tasks
Right now, many companies are worried about how to get more employees to use AI. After all, the promise of AI reducing the burden of some work …
Harvard Business Review
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Discussion
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@sh_reya
Shreya Shankar
on x
I texted this to the group chat and Hamel aptly commented “I feel like this is the same dynamic of ‘I need to keep all my GPUs busy’ for ML engineers”
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@simonw
Simon Willison
on x
Interesting research in HBR today about how the productivity boost you can get from AI tools can lead to burnout or general metal exhaustion, something I've noticed in my own work https://simonwillison.net/...
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@emollick
Ethan Mollick
on x
A corporate position that workers should “just use AI to do stuff” has never been enough. AI use in companies is a leadership problem that involves answering fundamental questions about what people should do with their time, how work is organized, and how to center people in work
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@burkeholland
Burke Holland
on x
If you're a dev, you already know this is true. We are working WAY more and nobody is asking us to do it. https://hbr.org/...
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@anildash.com
Anil Dash
on bluesky
There's a meta-point here, which is key: Commercial AI tools are built for bosses. It's very obvious, and very simple. This manifests in every part of their design and implementation and use, and it's no wonder they cause burnout. [embedded post]
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r/ArtificialInteligence
r
on reddit
AI at work leads to 10x productivity, but also burnout (HBR study)
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@grimalkina
Cat Hicks
on bluesky
I think this is super interesting, matches all the qualitative interviews I've had with developers on this, and continues to show that we cannot evaluate the impact of tools on people with a metric of “production” alone. Psychological factors are always central! — hbr.org/2026…
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@ericmbudd.com
Eric Budd
on bluesky
very good piece on how workers use LLMs and how it changes their work patterns. I've noticed some of these patterns myself working in software engineering
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@prietschka
Paul Rietschka
on bluesky
“PMs and designers began writing code; researchers took on engineering tasks; and individuals across the organization attempted work they would have outsourced, deferred, or avoided entirely in the past.” — You mean they delved into areas they were incompetent in and had no bus…
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@ethanmarcotte.com
Ethan Marcotte
on bluesky
Whatever the productivity gains promised by LLMs, they result in heavier workloads—and that leads to workers experiencing “cognitive fatigue, burnout, and weakened decision-making.” — All this from the notoriously pro-worker rag [checks notes] Harvard Business Review: hbr.org/2…