AI Collaboration: Relationslipping and Team Guidelines
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Relationslipping is the weakening of work relationships as interactions with colleagues are replaced by AI. Related survey figures can be understood in the context of the environment for asking questions, asynchronous communication, and standards for sharing how AI is used.

- Relationslipping is a phenomenon in which work relationships within a team weaken as people repeatedly turn to AI instead of colleagues.
- In a survey featured by HBR, work coordination was 22.3% lower in teams where replacing colleagues with AI was common.
- 49% of respondents said they experienced colleagues turning to AI instead of them at least sometimes.
- Psychological safety and consistent team communication help create an environment where people can ask colleagues questions.
- When evaluating the results of AI use, contributions to knowledge sharing need to be considered alongside individual speed.

Even if AI helps you finish work faster, your ability to collaborate with colleagues can weaken. Relationslipping is the weakening of work relationships as people turn to AI instead of colleagues. Team management should address both the environment for asking questions and the ways knowledge is shared.
The survey figures in this article are based on an HBR research overview published on October 15, 2026.

What is Relationslipping?
Relationslipping is the weakening of work relationships as AI replaces interactions with colleagues. The English term used by the researchers is Relationslipping. The key is not how much AI people use, but how their conversations with colleagues change.
When you ask a colleague a question, you learn about their experience as well as getting an answer. As you listen to their explanation, you learn the criteria they use to assess a problem. These experiences help you decide whom to ask for help next time.
HBR's research overview explains how relationships weaken. Skipping conversations reduces opportunities to discover a colleague's expertise. When AI takes over the work process, it also becomes harder to understand a colleague's judgment. This explanation is available in the summary of HBR's research overview.

What the survey figures show
The survey shows an association between replacing colleagues with AI and team relationships. It covered about 1,000 full-time office workers on project teams in the United States. The findings were presented in HBR in October 2026.

Survey measure
Reported figure
What to distinguish when reading

Work coordination in teams where replacing colleagues with AI is common
22.3% lower
A finding about work coordination, not a rate of decline in output

Team trust under the same conditions
21.9% lower
A finding about trust among colleagues

Respondents who had experienced colleagues turning to AI instead of them at least sometimes
49%
Not the percentage of people who were laid off or whose roles disappeared

Likelihood of replacing colleagues with AI among members with low psychological safety
At least twice as likely
An association with the behavior of turning to AI instead of colleagues

Work coordination among AI users who stay in regular contact with their team
28% higher
No guarantee that contact alone will produce the same effect

Team trust among AI users who stay in regular contact with their team
19% higher
An observed association between communication and trust

These figures also appear in BetterUp's post introducing the research. The public summary alone does not make it easy to verify all the comparison groups and formulas. The survey dates must also be distinguished from the publication date.
Differences found in a survey do not, by themselves, establish causation. The possibility that teams with weaker relationships turned to AI more often must also be considered. Do not use these figures as effect sizes that apply to every organization.

Comparing individual productivity and team collaboration
Individual productivity focuses on the ability to finish one's own work. Team collaboration includes the process of connecting people's knowledge. It is therefore difficult to judge team performance solely by the speed of individual work.

Category
What to check in individual work
What to also check in team work

Getting answers
Whether the person quickly obtained the answer they needed
Whether they know colleagues with relevant experience

Producing work
Whether the person completed a draft or analysis
Whether colleagues can understand the reasoning behind it

Solving problems
Whether the person resolved what was blocking them
Whether someone else will have to solve the same problem again

Experience using AI
Whether the person found an approach that works for them
Whether other members can also use that approach

This table applies the concerns raised by the research to team reviews. It is not a validated assessment scale or diagnostic tool. Choose items that fit your team's work and use them as a basis for discussion.

Psychological safety and barriers to asking questions
Psychological safety is the sense that you can ask questions or reveal mistakes without worrying about negative consequences. It is hard to approach colleagues if you worry that asking questions could hurt your evaluation. AI can provide someone to ask without this interpersonal burden.
If you are a leader, start by examining how you react when someone asks a question. A sigh or a dismissive attitude can make people hesitate to ask the next question. If you cannot answer right away, one option is to let them know when you can respond.

Identify where the person is stuck before judging the quality of the question.
When you do not know the answer, point them toward someone or something you can check together.
When you disagree, explain the reasoning behind your judgment.
Do not assume that asking for help is a sign of incompetence.

What to include in asynchronous communication
Asynchronous communication is a conversation that can continue without everyone being online at the same time. Reading and replying later to messages left in Slack or email are examples. The researchers suggest staying in touch with colleagues through these channels.
Posting only whether work is complete may not reveal where judgment is needed. Encourage people to share questions they are still working through. It helps to specify where a colleague's experience is needed.

Where you are currently stuck and what you have already checked
Parts of AI responses you have not yet been able to assess
New facts learned during the work and the evidence behind them
Questions that need a colleague's experience or review

Do not turn a requirement for daily contact into an obligation to be constantly available. Asynchronous channels are a way to communicate without having to respond immediately. Message counts alone also make it difficult to assess the level of collaboration.

Guidelines for sharing the process of using AI
When sharing AI output, include a record of the judgments made by people. A completed analysis alone makes it difficult to know which questions were effective. Document the process so colleagues can refer to it when doing the same work.
Using AI for customer analysis is one example. The items below are suggestions for preserving the results as team knowledge. They are not examples of actual business performance or verified time savings.

Item to share
What to record
What colleagues can learn

The problem you were trying to solve
The purpose of the analysis and the questions that needed answers
The work context in which to apply the method

Requests made to AI
Questions and conditions that influenced the result
Ways of making requests that they can use

Changes made by people
Responses that were accepted or excluded
The process of reviewing AI responses

Reasons for decisions
Facts or work criteria used to make changes
Why the result was accepted

Remaining questions
What has not yet been verified
What needs further review

Saving only prompts may leave out why the results were accepted. Recording the reasons for changes also gives colleagues clues to understand the judgment behind them. Check whether other people have used these records as well.

Criteria for evaluating the results of AI use
Evaluations can include both individual work results and contributions left for the team. Checking only whether someone uses AI skillfully makes it difficult to assess knowledge sharing. Also look at whether they have documented their experience in a form colleagues can use.
The following are examples of applying the researchers' knowledge-sharing suggestions to evaluations. They are not criteria with specific scores or weights. Choose what to observe based on how your team works.

Whether the person documented work methods that other members can use
Whether they explained to colleagues why they changed AI responses
Whether they contributed to colleagues' questions or review requests
Whether the shared methods were used again in actual work

Common mistakes and misreadings of the figures
The most common misunderstanding is to read survey figures about relationships as measures of work performance. The same number means something different when the survey measure changes. Keeping the following distinctions in mind can help avoid overstating the findings.

Misunderstanding
Accurate distinction

If collaboration is 22.3% lower, output falls by the same amount
Work coordination and output are different measures

49% lost their jobs because of AI
The percentage who experienced colleagues turning to AI instead of them

Sending messages every day increases trust by 19%
An association between communication and trust, not a guaranteed improvement

People who use AI a lot cause relationships to weaken
The issue concerns how AI use replaces interactions with colleagues

Posting only the output also shares the know-how behind its use
How questions were asked and why changes were made must be documented separately

Where to start with a team review
Start by identifying conversations that have decreased in recent, actual work. It is easier to discuss a single task than a vague impression of the whole team. The sequence below is an operational suggestion based on the concerns raised by the research.

Choose one recent task that involved AI. Identify the problem you were trying to solve.
Check whether any conversations with colleagues were skipped in the process. Review whether you missed experience you needed.
Record the human judgment applied to the AI output. Leave it in a channel colleagues can refer to.
Check whether the record was used in the next similar task. Adjust how you share any parts that were not helpful.

FAQ
Q. What does "relationslipping" mean?
A. It is a phenomenon in which working relationships within a team weaken as interactions with colleagues are replaced by AI. It includes the problem of having fewer opportunities to learn what colleagues know well.
Q. Does using AI necessarily reduce trust within a team?
A. That conclusion cannot be drawn. The research focuses on the behavior of replacing interactions with colleagues with AI. The association observed in the survey cannot be treated as a causal relationship that applies to every team.
Q. Does the figure showing 22.3% lower work coordination represent a decline in productivity?
A. It cannot be used as a rate of productivity decline. It is a figure related to work coordination from a survey presented by HBR. It does not mean that revenue or the amount of work completed fell by the same percentage.
Q. Does this mean that 49% of respondents lost their jobs to AI?
A. It does not mean layoffs or the elimination of jobs. It is the percentage of respondents who said they had experienced colleagues turning to AI instead of them at least sometimes.
Q. How is psychological safety related to AI collaboration?
A. It is hard to turn to colleagues if you worry that asking questions will lead to negative judgments. In the study, team members with lower psychological safety were more likely to turn to AI instead of colleagues.
Q. Does asynchronous communication mean holding meetings every day?
A. It does not mean meetings where everyone gathers at the same time. It means leaving messages in Slack or email for others to read and respond to when they can. You can share progress updates along with questions that need review.
Q. What should I document when sharing my experience using AI?
A. Document the problem you were trying to solve and the request you made to AI. You can also record the parts a person revised and the reasoning behind those decisions. Note any unresolved questions so colleagues can understand where the method can be applied.
Q. What else should be considered when evaluating AI skills?
A. You can consider contributions to knowledge sharing alongside individual work performance. This means checking whether other team members have used the method. Do not judge contributions solely by the number of documents shared.
Q. Can the survey findings be applied to all organizations in Korea?
A. Figures from a survey of workers in the United States cannot be directly applied as effect sizes for Korean organizations. They can serve as reference evidence when reviewing the environment for asking questions and how knowledge is shared.

Sources
- Harvard Business Review, Team Dynamics Weaken When Employees Turn to AI Instead of Colleagues, October 15, 2026: https://hbr.org/2026/10/team-dynamics-weaken-when-employees-turn-to-ai-instead-of-colleagues
- Harvard Business Review Store, publication details and public summary of the article introducing the study: https://store.hbr.org/product/team-dynamics-weaken-when-employees-turn-to-ai-instead-of-colleagues/H09BZ1?sku=H09BZ1-PDF-ENG
- BetterUp’s official LinkedIn, overview of the Relationslipping study’s participants and key figures: https://uk.linkedin.com/company/betterup/

Images
- A man extends a hand toward a colleague who is focused on a chat screen on her tablet.: https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6MzkxOTMsInB1ciI6ImJsb2JfaWQifX0=--77da2917efa51c2c524b79700f9ca08f5cd2adf6/ai-e6148b85.webp
- A woman in a blue cardigan points to annotated documents on a wall while discussing them with colleagues.: https://injoys.com/rails/active_storage/blobs/proxy/eyJfcmFpbHMiOnsiZGF0YSI6MzkxOTQsInB1ciI6ImJsb2JfaWQifX0=--3f45650b909f19f7ae3c01eacf9c186578d4fa6e/ai-d455ad4f.webp

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Category: Knowledge Base
Source: https://injoys.com/en/articles/ai-collaboration-relationslipping-team-trust
License: cc_by
Translation-Status: reviewed