Botsitting: The Work Draining AI Gains

**Nathaniel Whittemore** (0:00)
Today on The AI Daily Brief, we're talking about bot sitting and the hidden labor that comes with the AI transformation of work. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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Today, we're talking about a new report from Glean and the Work AI Institute. That's part of their Work AI Index for 2026, and it's all about something called bot-sitting or the hidden human labor of AI at work. Now, one of the things that you may or may not have noticed this year, is that I've done a little bit less coverage of studies from, for example, consulting firms or enterprise-focused research houses, and there is an actual specific reason for that. There's actually a couple of reasons, but they all come back to my feeling that the paradigm has shifted so much between non-agentic and agentic work that anything that's interacting with non-agentic work is largely irrelevant. Now, of course, if you are an enterprise AI leader, that's not the case. There are still lots of use cases that are non-agentic that are going to be valuable and productivity enhancing. But you guys know that I have a very strong bias towards being interested in opportunity AI, not just efficiency AI and the big changes that I see happening in terms of how we work, not just doing the same stuff we've always done a little bit faster. This report, however, starts to get into and name some new types of work that surround AI and agents that I think is really valuable to call out and start to explore. So that's what we're going to get into. Now, let's start with the statistics that they use to set everything up. Their big banner tweet-worthy statistics are that 87% of digital workers now use AI at work, with 75% saying it makes them more productive, saving them 11 hours per week through automation. Yet only 13% say their organization is performing significantly better as a result. And these numbers are almost a perfect encapsulation of what I was just talking about. 11 hours per employee is nothing to sneeze at. AI reaching nearly full penetration, with the vast majority of people saying it makes them more productive, are also interesting things. And of course, the contrast between that individual performance and organizational performance reinforces a story that will be very familiar and that we hear over and over again, which is that translating individual AI gains into larger organizational gains is very difficult and not at all implied just by using AI well individually. Now, interestingly, I disagree with the report's key argument about why only 13% of those workers say their organization is performing better.
I believe that on a fundamental level, individual productivity gains wherever they come from do not inherently translate to organizational gains unless there is a mechanism to actually facilitate that transformation. The question is what specifically are people using those 11 hours per week for, and how much does it have to do with actually advancing key company missions? The report's argument is that the gains are, in their words, being swallowed by a new largely invisible form of labor.
They continue, We call it bot-sitting, the work required to make AI usable, including feeding it missing context, checking its outputs, debugging its mistakes, rerunning prompts, and cleaning up the confident but wrong answers AI leaves behind. Workers now burn an average of 6.4 hours a week bot-sitting. So basically the argument is the reasons that organizations aren't getting gains is that those 11 hours per week that people are saving are being eaten in large part by the 6.4 hours a week they now have to bot-sit.
My position is that even if they weren't spending those 6.4 hours a week bot-sitting, you still wouldn't see a direct translation from individual productivity to organizational performance. But, and this is important, I think that this new largely invisible form of labor that they're calling out is extremely important to understand as we figure out how to integrate AI.