Did you catch this research published a few months back? It explored how employee–AI collaboration can sometimes create unintended side effects at work. While the potential of AI is exciting, and organizations everywhere are rushing to adopt it, this study shows we need to proactively address the human concerns that come along with it.

The researchers found that when employees work more closely with AI, they often interact less with other people. That lack of social contact leads to loneliness, which in turn drives emotional fatigue and, eventually, counterproductive work behaviors (CWBs) like withdrawal, lower effort, or disengagement. The good news: leadership support and intentional connection points can help buffer against these risks.

And if your team is remote or hybrid? The stakes are even higher. Without casual hallway chats or shared lunches, employees are already at risk of fewer human touchpoints. Layer in AI-heavy workflows, and disengagement can accelerate quickly.

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Before We Dive Into the 3 Ways: What This Looks Like on Real Teams

Story #1: The Direction Dispute That Never Surfaced

You read the AI-generated meeting notes and saw that the team agreed to shift focus toward a new product feature. On paper, everything looked aligned. The summary, however, missed how frustrated Alex really was. He strongly disagreed with the decision and chose not to speak up. Normally, you’d catch the tension in a hallway chat or a quick debrief. Without that moment of connection, you missed the chance to address his concerns. A month later, Alex disengages quietly, contributing less in meetings because he feels unheard.

Story #2: The Churn Signal That Got Lost

Sofia, your customer success lead, noticed a major client showing red flags of churn. Instead of raising it with you right away, she typed her concern into ChatGPT: “How do I prevent a customer from leaving without offering discounts?” She gets a list of tactics, tries a few, but doesn’t share the situation. The client still leaves. By the time you find out, it’s too late. What you truly missed was a learning opportunity for the whole team to see where your product experience was falling short.

Story #3: The Silent Overload

Jordan has been logging long hours, juggling tasks across multiple projects. Instead of reaching out for help, he leans on AI to reprioritize his to-do list and draft updates that make everything look “under control.” From the outside, the work appears to be humming along. But behind the scenes, Jordan is burning out. The signal you would have caught in a casual, “How are you holding up?” never happens. By the time he raises his hand, it’s not a conversation about workload, it’s a resignation notice. In a world where AI can simulate answers, generate documents, and “coach” individuals privately, leaders lose the very conversations that surface tension, opportunity, and learning.

What Changed? (It’s Not Just the Tech)

• Always-on answers dilute social reinforcement. When AI gives fast, private answers, the subtle reward for tapping a colleague (“Thanks, that helps!”) disappears, and with it the social fabric.
• Perceived “cost to bother.” Employees don’t want to interrupt a busy manager, especially across time zones. AI feels cheaper than asking a human.
• Confidence theater. AI-polished prose can make tentative ideas look finished, discouraging open debate and iteration.

How Disengagement Shows Up (Before You See It in Metrics)

• Signal loss: Fewer upward signals reach leadership because questions that used to spark discussion are now resolved solo with AI.
• Shadow knowledge bases: Individuals accumulate AI-generated snippets that never make it into shared playbooks.
• Decision dispersion: Teams make reasonable decisions in isolation that don’t harmonize across functions.
• Lower discretionary energy: People complete tasks but invest less in cross-team collaboration, mentoring, and innovation.
• “Polite silence” in meetings: Updates are crisp; learning is thin. No one wants to slow the room down to unpack assumptions.

What Leaders Actually Control

Leaders can’t, and shouldn’t, roll back AI. But you can re-humanize AI-enabled work by designing for connection. Think of AI as the first pass and human conversation as the last mile. Your job is to engineer the last mile back into everyday work.

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3 Ways Leaders Can Stay Ahead of the Problem

Cultivate Leader Emotional Support

Train managers to do more than just track tasks. Regular emotional check-ins, active listening, and encouragement go a long way toward reducing loneliness and boosting team energy.

Add depth: Make “emotional support” operational, not aspirational. Equip managers with a 5-minute rhythm for 1:1s: (1) How are you, really? (2) What’s felt harder than it should this week? (3) Where did you feel momentum? (4) Who helped you? (5) What’s one thing I can unblock? Implement a Leader Listening Loop:

1. Collect – weekly lightweight prompts (one question, one click, one sentence).
2. Synthesize – managers share two patterns and one surprise in their team channel.
3. Act – commit to a 14-day fix (process tweak, doc, or escalation).
4. Close the loop – publicize what changed and who surfaced it.

You’ll reduce loneliness by increasing felt responsiveness, the sense that speaking up leads to change.

Monitor Well-being, Not Just Output

Don’t wait until disengagement shows up in performance metrics. Use pulse surveys, team check-ins, or even informal 1:1s to watch for early signs of emotional fatigue and address them proactively.

Add depth: Track leading indicators:

• Participation rate in retros/standups (not just attendance).
• Response latency within working hours (spikes often signal overload).
• Review feedback depth (are reviews becoming rubber stamps?).
• Meeting talk-time distribution (a few voices dominating?).

Hybrid Work Policies with Intentional Social Time

If your team is part in-office, part remote, be deliberate about how you use those in-person days. Create space for unstructured bonding and connection, not just meetings and project sprints.

Add depth: Treat onsite days like relationship sprints, not status marathons. Protect unstructured blocks (90–120 minutes) for working together in the same room on thorny problems. Add peer-teaches: 15-minute demos of an internal trick, tool, or customer story. Cap each onsite with a “decision review”, list the week’s decisions, state owners, expected outcomes, and known risks. The goal is to transform proximity into shared context, not more slides.

From Ideas to Action

Now, all of this might sound overwhelming, where do you even start? The good news is that you don’t need to change everything at once. What follows is a sample plan, designed to show how these ideas can be put into practice over time. Think of it as a framework: a way to integrate new habits gradually, without adding unnecessary layers of complexity.

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A Practical Playbook: Re-Humanizing AI-Enabled Workflows

1) Build “Human Checkpoints” Into AI-Heavy Work

• Draft with AI → Discuss assumptions live → Publish.
• Analyze with AI → Pair-review with a cross-functional partner → Ship.
• Summarize with AI → Human-led prioritization → Roadmap update

2) Codify “When to Ask a Human”

Create a “talk if…” list:

• The decision impacts another team’s roadmap or customers.
• There’s a material trade-off (speed vs. quality, revenue vs. risk).
• You’re unsure who owns the decision.
• You’ve gone back-and-forth in a doc or thread more than twice.

3) Design for Visibility Without Performance Theater

• Replace “update meetings” with asynchronous videos or memos plus live Q&A focused on the why and the risk.
• Use rotating facilitators to broaden voices.
• Encourage messy drafts explicitly, label early docs “seeking critique” to normalize dialogue.

4) Rituals That Create Connection at Scale

• Monday “two truths and a tension”: one win, one appreciation, one tension per person (two minutes each).
• Friday “failure files”: micro-postmortems on small bets that didn’t pan out.
• Buddy system for new hires with a 30-day question log reviewed by the manager.

A 30-60-90 Day Leader Plan

Days 1–30: See the System

• Map your top five workflows where AI is heavily used (planning, reporting, QA, contract review, etc.).
• Interview five ICs: Where did you use AI last week? What question would you have asked a human before AI?
• Establish two lightweight prompts to measure felt visibility and heard-ness.

Days 31–60: Insert Human Last Miles

• Add one explicit human checkpoint to each AI-heavy workflow.
• Pilot a pair-review practice across two teams.
• Start a weekly 20-minute Leader Listening Loop across managers.

Days 61–90: Normalize and Scale

Publish your “talk if…” list.

• Replace one recurring status meeting with async + live Q&A.
• Define three OPRs (Observable Practice Results):

  • 80% of decisions above $X or severity Y have a human checkpoint.

  • 90% of new hires log five “why” questions their first month.

  • 10% improvement in “I feel seen by leadership” prompt over baseline

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Objections You’ll Hear (and How to Respond)

• “AI is faster, talking slows us down.”

Reframe: Human checkpoints prevent expensive rework and cross-team thrash. The minute saved now can cost a sprint later.

• “My team prefers to stay heads-down.”*

Reframe: Many do, until they hit ambiguity. Short, structured interactions reduce decision anxiety and keep momentum high.

• “We don’t have time for more meetings.”

Reframe: Replace meetings, don’t add them. Use async for updates; reserve live time for sense-making and alignment.

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Questions Leaders Can Start Asking This Week

• What felt harder than it should this week?
• What decision did you or your team make where another group should have been in the room?
• What’s one assumption we’re treating as fact because an AI answer looked confident?
• Where did a quick human conversation save you time?
• What win didn’t get enough recognition, and who made it happen?

Use these prompts in 1:1s, team channels, or end-of-week reflections. Small questions, asked consistently, build the culture you want.

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Disengaged employees are one of the costliest risks companies face, and in remote or hybrid settings, the danger is amplified. Quisdom uses AI to bring people together, not replace them, ensuring teams stay connected, informed, and engaged.

Email us at contact@quisdom.ai if you are interested in joining our next alpha cohort.