---
title: How we steer AI’s impact on our team dynamics
description: Explore how AI impacts team dynamics, leading to relationslipping and decreased trust. Learn how to steer against it.
image: https://www.jbgai.com/hubfs/work%20group%20scene.png
---

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ai culture

# How we steer AI’s impact on our team dynamics

![JB](https://www.jbgai.com/hs-fs/hubfs/JB.png?width=48&height=48&name=JB.png)

 JB

October 30, 2026

What happens to a team when its members ask a chat bot instead of their colleagues?   
Kate Niederhoffer and her co-authors from BetterUp Labs and Stanford University surveyed more than 1,000 U.S. desk workers and coined a word for it: "relationslipping". It is the latest chapter of a story HBR has been telling for a year.

It started in September 2025 with "workslop": AI-generated work that looks polished but leaves the real work to the person receiving it. We have all seen it. Research suggests that the costs circle around almost two hours per case! The authors' advice back then: "Frame AI as a collaborative tool, not a shortcut."

In April 2026, Jan-Emmanuel De Neve, Jeffrey T. Hancock and Kate Niederhoffer showed that it matters whether employees believe AI is there to augment them or to automate them away. Those who feel forced into AI produce 65% more “workslop”. Those who see augmentation are 32% less likely to leave.

And now “relationslipping”. In workplaces, where asking the AI instead of a teammate has become the norm, coordination is 22% lower and so is trust. For a company with 10,000 employees, the authors estimate around 243 additional resignations and more than $25 million in costs a year. For an SME with about 500 employees, that is still about a dozen people. Taking the shortage of skilled workers into account, the cost of human capital loss can turn into a serious business problem.

If we’re honest with ourselves, though, this isn’t that surprising. The chatbot is always available and it even flatters. AI models affirm their users about 49% more often than humans do. The trend is age and industry agnostic. AI enthusiasts and people in teams with low psychological safety slip the most. I wrote about that in [February](https://www.jbgai.com/en/bring-your-data-to-life/harnessing-ai-embrace-the-change-or-get-left-behind?hsLang=en). AI is a tool, like a sharp kitchen knife. A better knife makes the chef faster, but no chef stops talking to the sous-chef because the knife got sharper.

So, it comes down to leadership, effectively.

Also in September 2025, researchers from ghSMART reported in HBR that the few companies succeeding with AI (just about 5%) don't win with their technical experts (they call them "architects") alone, but with leaders who act as "shapers" and connect AI with strategy, trust and adoption.

In April, I quoted a [Deloitte study](https://www.jbgai.com/en/bring-your-data-to-life/ai-from-operatios-to-strategy?hsLang=en) with the same message: AI belongs with the people accountable for strategy, and real returns take two to three years. The HBR authors from April describe the same J-curve. Augmentation means a deeper dip first and much higher gains later. Only about half of workers have received insights into their company’s AI plans. Hence, it doesn’t really come as a surprise that 40% of individual contributors suspect AI will take their jobs at some point, while 81% of senior leaders believe AI empowers their people.

What does this mean for us?   
The articles I refer to have a list of potential actions. I’d summarize them into three pillars:

1. First, clarity. We should provide clear guidance on what AI shall be used for in our organization, and we should say openly whether and when we augment or automate. Silence gets interpreted, and that is rarely in the organization’s favor.
2. Second, ownership. We should create a positive, forward-thinking and collaborative environment for everyone, where asking a colleague is as natural as asking the chatbot. Every individual should understand the value of a supportive work culture.
3. Third, direction. Our targets should be aligned on team outcomes instead of usage or input. KPIs steer the managers’ and the team’s attention, they always have been.

AI is a toolkit that we learn to use effectively as we continue using it. We’ll make mistakes and we will break stuff.   
Next time, while sitting aside a colleague, I’ll ask them first before turning to the chatbot.

And a brain teaser for all team leaders, maybe have an eye on colleagues, who haven't been asked anyone for support for a while.

 

 

Sources: Even though they are long, I recommend reading the HBR articles for more depth:

- [AI-Generated "Workslop" Is Destroying Productivity](https://hbr.org/2025/09/ai-generated-workslop-is-destroying-productivity) (September 2025),
- [What Companies with Successful AI Pilots Do Differently](https://hbr.org/2025/09/what-companies-with-successful-ai-pilots-do-differently) (September 2025),
- [Why Companies That Choose AI Augmentation Over Automation May Win in the Long Run](https://hbr.org/2026/04/why-companies-that-choose-ai-augmentation-over-automation-may-win-in-the-long-run) (April 2026), and
- [Team Dynamics Weaken When Employees Turn to AI Instead of Colleagues](https://hbr.org/2026/10/team-dynamics-weaken-when-employees-turn-to-ai-instead-of-colleagues) (October 2026).

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