The AI Conversation You’re Avoiding with Your Team

Your team knows AI is coming. Half are terrified they'll lose their jobs. The other half can't wait to try it. And you're stuck in the middle, uncertain what to say.

I walked into the conference room on August 24th knowing this could go either way.

My daughter Megan—CEO of Full Focus—had asked me to lead a two-hour AI training for our entire team. As I scanned the room, I saw two distinct groups. The first leaned forward, laptops open, ready to dive in. They couldn’t wait to learn what AI could do for them.

The others? Arms crossed. Skeptical expressions. A few staring at their phones.

I’d seen this before. And I knew exactly what was running through their minds:

Is AI going to replace me?

I’m already drowning in work. How can I possibly make time to learn one more thing?

Am I even smart enough for this? I’ve never been great with technology.

Valid concerns. Every single one.

But here’s what happened: thirty minutes in, the arms uncrossed. The phones went down. Everyone—and I mean everyone—was leaning forward.

Not because I’m some captivating speaker. But because they started seeing something they hadn’t expected. AI wasn’t the threat they feared. It was the leverage they needed.

The transformation was immediate. And it taught me something critical about leading AI adoption.

The biggest barrier isn’t the technology. It’s the conversation you’re not having.

If you’re a business owner, you’re probably stuck in the same tension I faced before that meeting. On one hand, you know your team is nervous. Maybe scared. You don’t want to lie to them or give false assurances that could compromise your integrity.

On the other hand, you want them to see AI’s potential. You know the employees who embrace it will be the ones who thrive. The ones who don’t? They’re the most vulnerable.

So you’re paralyzed. Unsure how to move forward without either crushing morale or dodging the hard truths.

Let me show you the way through.

The reason most business owners stay stuck isn’t lack of knowledge about AI—it’s uncertainty about how to lead through it. Let me show you four PRINCIPLES that will transform how you approach this conversation with your team.

Principle #1: Anchor Before You Accelerate

The first mistake most leaders make? They lead with the change.

They walk into the room and immediately start talking about what’s going to be different. New tools. New processes. New expectations. And their teams immediately go into defensive mode.

Here’s what research tells us: people function best in environments they feel are safe and predictable.[^1] When you introduce massive change without first establishing what won’t change, you create psychological instability that kills adoption before it even starts.

This isn’t theoretical. A 2024 study analyzing change management across multiple organizations found that successful transformations consistently emphasized continuity alongside innovation. Organizations that balanced stability with change saw dramatically higher success rates than those that focused solely on transformation.[^2]

So before you talk about AI, talk about what’s staying the same.

Your mission isn’t changing. Your values aren’t changing. Your commitment to your team isn’t changing. The core work that makes your business unique—the relationships you build, the problems you solve, the customers you serve—none of that is going away.

AI isn’t replacing your foundation. It’s building on it.

When I started our Full Focus training, I didn’t begin with ChatGPT. I began with why we exist as a company. I reminded the team that our purpose—helping people achieve their most important goals—wasn’t changing. AI was simply giving us a more powerful way to fulfill that purpose.

That’s what changed the energy in the room.

Give your team solid ground to stand on. Then—and only then—show them the new horizon.

Principle #2: Surface the Fear Before It Festers

The second principle sounds counterintuitive: name the thing everyone’s afraid to say.

Most leaders avoid acknowledging fear because they think it will make things worse. They believe if they don’t mention the concerns, maybe people won’t worry about them.

That’s backwards.

Research from Harvard Business School shows that psychological safety—the belief that you can speak up without negative consequences—is the foundation of high-performing teams.[^3] And psychological safety doesn’t come from pretending concerns don’t exist. It comes from leaders creating space where those concerns can be voiced.

A 2024 study found that 89% of employees believe psychological safety encourages greater innovation and stronger community. But here’s the critical finding: 65% of workers believe that a lack of psychological safety contributes to actual safety risks in their workplace.[^4]

In other words, when people can’t voice their fears, those fears don’t disappear. They go underground. They create resistance. They sabotage implementation.

So get ahead of it.

In our training session, I said it out loud: “Some of you are wondering if AI is going to replace you. That’s a legitimate concern. Let me tell you the truth about that.”

The shift in the room was immediate. Because I wasn’t pretending the elephant wasn’t there. I was acknowledging it, addressing it, and giving them permission to think about it openly.

Here’s what I told them—and what you should tell your team: AI won’t replace people who learn to use it effectively. But people who use AI will absolutely outperform people who don’t. The choice isn’t whether AI happens. The choice is whether you’re equipped to leverage it.

That’s honest. It’s direct. And it respects their intelligence.

Don’t sugarcoat the disruption. Don’t minimize the uncertainty. But don’t let fear be the loudest voice in the room either.

Principle #3: Prove Value Through Experience, Not Explanation

Here’s where most AI training fails: leaders spend two hours explaining what AI can do, then send people back to their desks with a pat on the back and a prayer.

You can’t talk people into believing in AI. They have to experience it.

Educational research consistently demonstrates that experiential learning—hands-on, active engagement with material—produces dramatically better outcomes than passive instruction. A 2024 study examining network technology education found that students exposed to practical, hands-on learning demonstrated significantly greater conceptual mastery than those receiving traditional lecture-based instruction.[^5]

Another comprehensive analysis found that early career professionals who engaged in experiential learning reported higher career satisfaction, better workplace performance, and earned an average of $15,000 more in salary than those who didn’t.[^6]

Why? Because doing creates conviction in a way that hearing never can.

In our training, we didn’t just talk about AI for two hours. Within the first thirty minutes, every person in that room had prompted ChatGPT to solve an actual problem they were facing at work. They watched it draft an email, summarize a document, create a project plan—something real, something immediately useful.

That’s when the arms uncrossed.

Because they weren’t listening to me tell them AI was powerful. They were experiencing AI being powerful for them, in their specific role, solving their specific problem.

Don’t make this a presentation. Make it a workshop.

Give every person in the room a login. Give them a prompt. Give them three minutes to try something related to their actual work. Then have them share what they discovered.

The skeptics won’t be won over by your words. They’ll be won over by their own experience.

Principle #4: Position AI as Leverage, Not Replacement

The fourth principle determines whether your team moves toward AI or away from it.

The narrative you establish matters.

If your team believes AI is coming to take their jobs, they’ll resist it. If they believe AI is coming to make them better at their jobs, they’ll embrace it.

And here’s what the research shows: AI is fundamentally a tool for augmentation, not replacement.

A February 2025 study from the Federal Reserve Bank of St. Louis found that workers using generative AI saved an average of 5.4% of their work hours—roughly 2.2 hours per week for a full-time employee.[^7] But here’s the critical insight: productivity gains were highest when workers used AI to enhance their existing capabilities, not replace them.

Multiple studies confirm this pattern. Boston Consulting Group research found that AI not only increases productivity but actually expands workers’ capabilities, enabling them to complete tasks that were previously beyond their skill level.[^8] Employees using AI reported productivity increases ranging from 14% to 40%, with the greatest gains coming from AI augmentation rather than AI automation.[^9]

Think about that: AI doesn’t make people obsolete. It makes people more capable.

That’s the story you need to tell.

AI won’t replace the relationship builder on your team—it’ll give them more time to build relationships by handling the administrative work that bogs them down. It won’t replace your strategic thinker—it’ll give them better data and faster analysis to inform their strategy. It won’t replace your creative—it’ll eliminate the tedious execution work so they can spend more time on actual creative thinking.

Position AI as the thing that frees your team to do their best work—not the thing that threatens their work.

Because that’s not spin. That’s what the data actually shows.

The Path Forward

Leading your team through AI adoption doesn’t require you to have all the answers. It requires you to have the conversation.

Anchor them in what’s not changing. Surface the fears before they fester. Let them experience AI’s value firsthand. And position it as leverage, not replacement.

Do that, and you won’t just get compliance. You’ll get excitement. You’ll get experimentation. You’ll get the kind of adoption that actually transforms how your team works.

Imagine what becomes possible when your entire team—not just the early adopters—starts using AI to do their best work. Imagine the time you get back. The problems you can solve. The margin you can create.

That’s not a distant future. That’s available right now.

What conversation have you been avoiding with your team that needs to happen this week?

Comments

Got a question or story about AI, Reader? Hit reply and let me know.

I read every email. Seriously. Your experiences help me write better content, and sometimes the best insights come from readers like you.

Transforming AI from noise to know-how,

Michael Hyatt
​Founder & CEO​
AI Business Lab

P.S. Consider the AI Business Lab Mastermind: Running a $3-10M business? You’re past the startup chaos but not quite at autopilot. That’s exactly where AI changes everything. The AI Business Lab Mastermind isn’t another networking group—it’s a brain trust of leaders who are already implementing, not just ideating. We’re talking real numbers, real strategies, real results. If you’re tired of being the smartest person in the room, this is your new room. 👉🏼 Learn more and apply here.

REFERENCE

1. Dahl Consulting, “Navigating Organizational Change: Strategies for Stability and Long-Term Success,” July 23, 2024, https://www.dahlconsulting.com/2024/07/23/navigating-organizational-change-strategies-for-stability-long-term-success/.
   
2. Peter Cronemyr, Anders Fundin, and Lars Wemme, “Change-Driven Process Management: Exploring a New Process Paradigm Adaptable to Societal Changes,” Business Process Management Journal 31, no. 8 (2025): 1–23, https://doi.org/10.1108/BPMJ-06-2024-0456.
   
3. Amy Edmondson, “What Is Psychological Safety?,” McKinsey & Company, July 17, 2023, https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-psychological-safety.
   
4. British Safety Council, “Psychological Safety: A Genuine Risk to Physical Safety,” 2025, https://www.britsafe.org/safety-management/2025/psychological-safety-a-genuine-risk-to-physical-safety.
   
5. Zhandos Zulpykhar et al., “Practical approaches to network technology education: a study within secondary institutions in Kazakhstan,” Frontiers in Education 10 (2025), https://doi.org/10.3389/feduc.2025.1557946.
   
6. Sasha Patil, “Impacts of Experiential Learning on the Gen Z Early Career Experience,” National Association of Colleges and Employers (NACE), April 18, 2025, https://naceweb.org/talent-acquisition/trends-and-predictions/impacts-of-experiential-learning-on-the-gen-z-early-career-experience.
   
7. Alexander Bick, Adam Blandin, and David Deming, “The Impact of Generative AI on Work Productivity,” Federal Reserve Bank of St. Louis, February 27, 2025, https://www.stlouisfed.org/on-the-economy/2025/feb/impact-generative-ai-work-productivity.
   
8. Boston Consulting Group, “GenAI Doesn't Just Increase Productivity. It Expands Capabilities,” February 4, 2025, https://www.bcg.com/publications/2024/gen-ai-increases-productivity-and-expands-capabilities.
   
9. Apollo Technical, “27 AI Productivity Statistics You Want to Know (2025),” August 29, 2025, https://www.apollotechnical.com/27-ai-productivity-statistics-you-want-to-know/.
   
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