Is AI making employees too productive?

AI could be pushing employees past the point of healthy efficiency and productivity.

That’s one concept Liane Davey, co-founder of Toronto-based consulting firm 3COze, explored in her book, Thoughtload: Manage the Madness and Free Your Team to Do Great Work, published earlier this year.

“AI is making productivity frictionless…and this is why we’ve all had some colleagues send us a 70-page thing of AI slop,” Davey told HR Brew. “Yeah, it’s easy to produce. That doesn’t mean that it is the output that’s going to make us effective.”

Davey shared more about her book, and the effect AI is having on employees, with HR Brew.

This interview has been edited for length and clarity.

What will HR pros learn from your book?

We have not cracked the problem of overwhelm that our folks are facing, and the biggest problem is because we’re paying attention to workload, which is only a small part of the challenge, and not paying attention to thoughtload, which is a much more comprehensive look at the weight that our employees are carrying…We need to stop paying attention to workload as much and start paying attention to thoughtload.

What’s the difference between thoughtload and workload?

Thoughtload, you can think of it as an equation, with the weight on the top, and then the strength to carry the weight on the bottom. So, on the top, we have two factors: the cognitive demands, so all that we have to pay attention to, all of the complexity, all of the decision fatigue…and the second piece on the top of the equation is the emotional burdens, so we’re living in a very emotionally dysregulated society.

You can think of those two things as the combined weight, and then the denominator of the equation is the energy reserves, so the cognitive, physical, emotional kinds of energy you have…That’s the thoughtload equation: the rising cognitive demands and increasing emotional burdens. All that we’re trying to carry with declining energy reserves.

How does AI impact thoughtload?

We constantly talk about the cognitive demands of AI and don’t talk about the emotional burdens…[With recent research about AI brain fry,] it is not just a cognitive response to AI overload. It is equally an emotional and affective response.

The reason why understanding thoughtload is important in the context of AI is because the idea of cognitive load is insufficient to understand the costs of AI on our people…We need to think about what are going to be the impacts on our employees’ thought load, not just their workload. What is a reasonable amount of work to be doing where we don’t just send an agent and it does all the work?

The problem is we underplay how much thoughtload there is even in using agentic AI. There’s still a lot that is weighing on you…[The AI brain fry research] showed that people tend to work longer because there’s this illusion of frictionlessness. It just feels so easy…“Look at how much I’m churning out.”

What else will HR learn from your book?

The book really starts on this concept that there are three things you can pay attention to, and HR folks really need to understand this. You can pay attention to activity: Do I see people at their desks? When you think about the token wars, like the places where they were rewarding people for any tokens they were using. All of these kinds of things are about rewarding activity.

The other thing you can reward is output: Did I push code? Did I create the proposal? Did I invent a new product? Did I produce something? And, the third thing you can pay attention to is an outcome, which is not something you can control, but is ultimately: Did our profit go up? Did we change the mix of what our customers buy?

If you pay attention to activity, what you will get is busy people. It’s not really what we’re looking for. If you pay attention to output, you get productive people, and most people think that’s great. Most HR people think that’s, “Oh, I get my gold star now. I made our workforce more productive.” The problem is that a huge amount of our productivity in 2026 is not contributing to the outcomes we’re looking for.