Less focused work with AI

Aruna Ranganathan and Xingqi Maggie Ye are studying how work loads are shifting as companies try to integrate AI into the flow. So far it seems that AI is mostly creating a different kind of work and more of it. On Harvard Business Review:

AI introduced a new rhythm in which workers managed several active threads at once: manually writing code while AI generated an alternative version, running multiple agents in parallel, or reviving long-deferred tasks because AI could “handle them” in the background. They did this, in part, because they felt they had a “partner” that could help them move through their workload.

While this sense of having a “partner” enabled a feeling of momentum, the reality was a continual switching of attention, frequent checking of AI outputs, and a growing number of open tasks. This created cognitive load and a sense of always juggling, even as the work felt productive.

Over time, this rhythm raised expectations for speed—not necessarily through explicit demands, but through what became visible and normalized in everyday work. Many workers noted that they were doing more at once—and feeling more pressure—than before they used AI, even though the time savings from automation had ostensibly been meant to reduce such pressure.

I don’t think I like this direction. I was really hoping we’d go the other way where all current work is done with AI tools but companies still pay employees the same amount.