The first time we rolled out an AI-powered tool to a team, I was so excited. My own experiments showed promise. The case studies and research suggested it could be a game changer for LaFleur. We were going to streamline processes, eliminate bottlenecks, and make everyone’s lives easier.
Then I got in the room. Some people seemed curious, but I mostly got back polite silence. Some people nodded. One voiced concerns about implementation and hallucinations. Another asked if this was optional (it wasn’t).
It took time, but we’ve gotten to the point where everyone on the team is using AI. But it wasn’t instantaneous or easy.
This journey taught me about how to navigate change: the success of any new tool—AI, automation, or otherwise—isn’t just about whether it works. It’s about whether your people are ready to trust it. Or more accurately, whether they’re ready to trust you.
The myth that people hate change is one of the most persistent leadership misconceptions out there. Most of us don’t hate change—we hate what it represents: uncertainty, loss of control, and the possibility of failure. If a change feels like an exciting opportunity, people will sprint toward it. If it feels like a threat? They’ll dig in their heels.
Understanding why people resist isn’t just good management—it’s a requirement for any leader guiding their team through AI integration, digital transformation, or major organizational shifts.
Let’s break it down.
In the late 1970s, psychologists Daniel Kahneman and Amos Tversky developed Prospect Theory, which fundamentally changed how we think about decision-making. One of the theory’s most powerful insights is this: losses loom larger than gains.
In practice, this means that when you offer someone a shiny new solution, what they’re often thinking about is what they might lose: autonomy, confidence, routine, or even job security. Here’s a simple example: imagine you’re introducing a generative AI content tool that can produce blog posts or landing pages in minutes. Sounds great, right?
To the writer on your team, that change might not sound like a gift. It might sound like a red flag. They may wonder:
Even if the new tool improves efficiency and frees up time for more strategic work, the immediate emotional reaction is often rooted in loss aversion. People are far more motivated to avoid losing what they have than to gain something new—especially if the “gain” is abstract or future-based.
This is why so many change efforts fall flat. We lead with gains (“This will make your life easier!”), but our teams are still mentally calculating what they’re about to lose.
There’s another deeply human fear lurking beneath resistance: the fear of looking stupid.
You may have heard of the Dunning-Kruger effect, which describes how people with low ability in a domain often overestimate their competence. But the inverse is just as important—people who are highly competent often underestimate themselves or worry they’re not “good enough.”
When you introduce something new—especially something technical or AI-driven—it triggers this fear in unexpected ways. Your high-performing employees might not say it out loud, but they’re wondering:
And here’s the kicker: fear of incompetence often shows up as disengagement, not panic. People might avoid meetings, skip training sessions, or nod along while secretly feeling lost. They don’t want to be seen as the slow one in the room—so they opt out, quietly.
If you don’t create an environment where people feel safe saying “I don’t get this yet,” they’ll never get the chance to grow into it.
Finally, there’s the powerful pull of what behavioral economists call status quo bias, a preference for the current state of affairs, even when better options are available.
In a classic 1988 paper, researchers William Samuelson and Richard Zeckhauser found that people overwhelmingly tend to stick with the default, even when presented with superior alternatives. We’re biologically and culturally conditioned to avoid the unfamiliar, especially in high-stakes environments like the workplace.
This bias becomes even more pronounced when a change comes from the top down. If your team wasn’t part of the decision-making process—or worse, didn’t even know it was coming—they’re more likely to reject the change on principle, even if it’s technically “better.”
From their perspective, the status quo may be inefficient, clunky, or imperfect—but it’s known. They’ve built habits, workarounds, and comfort into it. Even if it’s not optimal, it feels safe.
And when people perceive a change as being imposed on them, rather than developed with them, it often becomes a proxy battle for deeper concerns: trust in leadership, organizational transparency, and agency in their roles.
You start by acknowledging that resistance isn’t irrational; it’s deeply human. If your team is hesitant, it doesn’t mean they’re wrong or unmotivated. It means you have to lead with empathy, not just logic.
That means:
When you make space for fear, you make room for real transformation. Because the truth is, your team doesn’t hate change. They hate feeling powerless, unprepared, or unseen. If you can fix that, you can lead through anything.
Even the most adaptable teams have limits. Over the last decade, businesses have undergone an unprecedented number of transformations: digital migrations, pandemic pivots, hybrid work models, AI integration, and more.
It’s not just that people are afraid of change. It’s that they’re tired of it.
According to Gartner, 73% of employees say they’re overwhelmed by the pace of change at work. The more transformations they’ve been through, the more skeptical they become about the next one.
And that skepticism is justified. Many digital transformations fall flat—not because the tech fails, but because the human part of the equation is neglected. Leaders often focus on implementation plans and ignore buy-in. They throw training sessions at people instead of building trust.
In other words, we often try to manage change when we should be leading it.
Let’s say your company rolls out an AI-based marketing dashboard or automation system. It works. It’s live. But three months later, hardly anyone is using it the way it was designed.
Executives might look at the login data and declare success. But if usage is shallow, skeptical, or performative, you haven’t changed behavior—you’ve just added another box to check.
Adoption isn’t the same as engagement. And that gap—the space between “we implemented it” and “people actually believe in it”—is where most change efforts fail. You can’t strong-arm someone into trusting new technology. You earn their engagement by showing them that the change is for them, not to them.
If your team doesn’t feel safe to ask questions, admit they don’t know something, or challenge assumptions, they’ll never embrace new tools. They’ll comply, but they won’t commit.
Harvard Business School professor Amy Edmondson coined the term “team psychological safety” to describe this dynamic. In psychologically safe environments, people feel comfortable taking risks, offering ideas, and being vulnerable without fear of judgment or retribution. There’s a “felt permission for candor.”
When you’re introducing something disruptive, like AI, this matters more than ever.
So how do you build it?
The goal isn’t to make everyone love change—it’s to make them feel safe enough to explore it.
Most rollouts happen like this: leadership picks a new system or tool, makes the case in a meeting, and then expects people to fall in line. But people rarely embrace what they had no hand in shaping.
At LaFleur, we use human-centered design principles to avoid this trap. That means involving the people most affected by the change from the beginning. Not just in training—but in ideation, testing, and iteration.
Here’s what that looks like in practice:
These small shifts help teams see the change as a joint effort, not a top-down mandate.
One of the fastest ways to build momentum around a new tool or system is to make the benefit immediate and visible. Not for the business. Not for the strategy. For the person using it.
If a new AI content engine helps someone write faster, help them see that. If an analytics dashboard saves five hours of manual reporting, highlight that in their workflow. Don’t just communicate features. Show people how their lives get easier, their work gets smarter, and their impact gets clearer. When it comes to adoption, rushing doesn’t make it happen faster. Clarity does.
So build clarity through:
People trust people, not systems.
I’ve been in enough boardrooms, conference calls, and implementation scrums to know that no change effort, no matter how well-designed, works without trust.
If you want people to adapt, you have to treat them like adults who are capable of learning, questioning, and contributing. You can’t outsource the emotional labor of change. You have to lead it.
That means being transparent about what’s changing and why.
It means owning what you don’t know and listening when your team points out what they do.
It means slowing down, not to delay progress—but to lay the foundation for something stronger than compliance.
It means trading control for clarity and trading certainty for trust.
When I think back to that quiet room from years ago—the one where my AI pitch landed with a thud—I don’t blame the team for their response. I blame myself for treating a rollout like a checklist instead of a conversation.
If I could go back, I wouldn’t start with the tool. I’d start with the people. I’d ask what they were worried about, what made them excited, and what they wished their tools did better. I’d invite them to build with me instead of just asking them to buy in.
That’s the real work of leading through change. Not pushing people forward, but walking with them through the uncertainty—until the new thing doesn’t feel scary anymore.
Because the thing we’re most afraid of isn’t change itself. It’s being left behind by it.
Change isn’t a project. It’s not a rollout or a press release or a checkbox in your quarterly goals. Real change, the kind that sticks, requires leadership that sees the humans in the system, not just the outcomes. Yes, AI is powerful. Yes, automation can streamline workflows. But none of it matters if your team doesn’t feel secure, supported, and seen in the process. You can’t fast-track trust. You have to build it.
When you take the time to understand where fear lives—in loss aversion, in uncertainty, in the very human fear of being left behind—you unlock something bigger than compliance. You unlock alignment. Confidence. Momentum. You get a team that’s not just willing to adopt change, but ready to lead it alongside you.
And that’s what moves companies forward. Not tech. Not trends. Trust.?
At LaFleur, we help businesses navigate change with strategy, empathy, and the right tools, not just for today’s goals, but for tomorrow’s growth. Whether you’re rolling out AI-powered tools, rebuilding your marketing system, or just trying to make your data more human and usable, we’re here to walk with you—not ahead of you.
Let’s talk about where you’re headed, and how to bring your team with you.
Change management communication. (n.d.) Gartner. Retrieved from https://www.gartner.com/en/corporate-communications/insights/change-communication.
Gallo, A. (2023, February 15). What is psychological safety? Harvard Business Review. Retrieved from https://hbr.org/2023/02/what-is-psychological-safety
Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263–291. https://doi.org/10.2307/1914185.
Samuelson, W., Zeckhauser, R. Status quo bias in decision making. J Risk Uncertainty 1, 7–59 (1988). https://doi.org/10.1007/BF00055564.