I was at a conference recently when a speaker wrapped up a compelling talk on AI transformation with this: “Lean into this disruption. Don’t be afraid to experiment, and forget about stability.”
I clapped. And then I sat with that last part for the rest of the day.
I want to be fair to the speaker, because I think the intention was good. When people are scared, nervous, and feeling like they’re already behind, telling them to loosen their grip and experiment is reasonable encouragement. I get it. But telling people to forget about stability is risky, and the research has been telling us that for decades. It costs you the trust and buy-in of the people you most need to execute and get this right.
I’d go further: it flies in the face of what we actually know about basic human needs.
What the research says about stability
Maslow’s hierarchy of needs places safety and security at the second tier, right above physiological survival and beneath everything else: belonging, esteem, and self-actualization. That means when someone’s sense of stability is threatened, their brain cannot access the higher-order thinking you need from them. You can’t ask people to experiment, collaborate, and co-create when their nervous system is in threat mode. Neuroscience calls it fight, flight, or freeze. Leaders experience it as resistance, silence, and disengagement.
Gallup’s 2026 State of the Global Workplace report puts a number on what that looks like at scale: only 20% of employees worldwide are engaged at work, the lowest level since 2020. And 40% of employees report experiencing daily stress. Four out of five workers are checked out to some degree, and that’s not a motivation gap. It’s what happens when stability disappears.
Gallup has been studying what employees need from their leaders for decades, and one of the four core needs they’ve identified is stability, alongside trust, compassion, and hope. It’s a fundamental human need, not a personality preference, which means when a leader stands on a stage and tells an organization to forget about stability during AI transformation or any major organizational change, they’re not inspiring courage. They’re activating a threat response in the majority of the room.
Brené Brown’s research in Dare to Lead adds another layer: the number one shame trigger at work is the fear of being irrelevant. Think about what that means at this moment. The new hire who feels pressure to prove their value immediately starts moving fast without enough context. The 20-year veteran sits quietly, wondering if their expertise still matters in an AI era. Both of them are carrying that fear right now, and most leaders are walking past it entirely.
Not everyone in your organization runs toward disruption
When you tell your team to forget about stability, you’re speaking directly to the roughly 20 to 30 percent who are energized by change and newness. Those people hear it and feel permission. The other 60 to 70 percent hear something different. Some hear that their caution isn’t welcome. Some hear that they don’t fit. And some go quiet, dig in, and stop contributing, which is exactly the opposite of what you need during a change leadership moment.
Those are also the people who’ll flag the pothole three steps out instead of hitting it, if you give them room to say so. Treating that instinct as pushback instead of the asset it is tends to be where things actually go wrong, not the disruption itself. That’s a partner, not resistance. The leaders who build both groups into the process, the early adopters and the methodical thinkers, tend to have AI adoption efforts and organizational transformations that actually land.
Dan Shipper, CEO of Every, a publication covering AI and the future of work, published a piece in May 2026 arguing that AI progress is actually creating more work for humans, not less, and that the more organizations automate, the more expert human judgment is required. Gallup’s 2026 data backs this up: the strongest predictor of AI adoption success is not technical integration. It is whether employees have a manager who actively supports their engagement with new ways of working. Gallup found that employees whose managers actively support the use of AI are 8.7 times more likely to say AI has transformed their work.
If that’s true, and I think it is, your 20-year veterans and your careful methodical thinkers are not obstacles to your AI transformation. They’re assets. The institutional knowledge, the pattern recognition, the sense of what the organization has tried and why it didn’t work, that context is going to be mission-critical for any AI change management effort to succeed. It will be as sturdy as your existing expertise.
So what do you actually do about creating stability?
You don’t slow down your AI strategy or your change leadership efforts. You add three things most leaders are currently skipping.
1. Be specific about what’s NOT changing.
Leaders pour enormous energy into communicating what is changing, and forget that their people are walking around wondering what the ground still feels like under their feet. Deliberately communicate what remains core and foundational to your business. Your values aren’t changing. The way your frontline managers are empowered to get to yes for a client isn’t changing. For people who have been there for 10, 15, or 20 years, their institutional knowledge matters. Name that explicitly, and name it often, because people will not hear it the first time, and they will not believe it until they’ve heard it repeatedly.
This is also where you address the fear of irrelevance directly. Don’t dance around it. The people who have been there the longest are quietly asking whether they still belong in the future you’re building. Answer that question before they have to ask it out loud.
Ask yourself: In your last all-hands or team meeting, what percentage of your time went to what is changing versus what is staying the same? If you spent 90% of the time on what’s changing and nothing on what’s not, that’s the gap your people are filling with their own assumptions.
2. Regulate your own mood.
Two moods destabilize people during organizational change, and they sit on opposite ends of the spectrum. The first is visible frustration when things move more slowly than you want, when mistakes happen, when some people seem to have their heels dug in. The second is what I call “cheer culture,” that hypercharged executive optimism in which a leader bounds onto a stage, radiating excitement about everything AI is going to do for the business. At the same time, everyone in the room can feel the anxiety humming beneath the surface. Both moods signal to your people that the ground isn’t safe.
Ask yourself: If the people on your team were describing your energy in the last few change-related conversations, what words would they use? If you’re not sure, that’s worth finding out.
3. Own it when it’s not going well.
The numbers on AI transformation are sobering. Gallup’s CEO, Jon Clifton, cited in his foreword to this year’s report, an MIT study finding that despite roughly $40 billion in enterprise AI investment, 95% of organizations have seen no measurable impact on profits. Separately, the NBER surveyed nearly 6,000 global executives, with 89% reporting no effect on labour productivity. Everyone in your organization is reading versions of those headlines. When you pretend otherwise, you don’t protect people from worry; instead, you lose their trust.
I watched a leader do this well. At a Fortune 500 company, in front of a department of 100 people, they walked through the entire change initiative: the project plan, the timeline, the desired outcome, the phases, and who would be impacted at each stage. Then, after all of it, they said this: “Don’t assume we’ve thought of everything.”
That one sentence did more than the rest of the presentation combined. It told every person in that room that their perspective mattered, that this wasn’t being handed down from 12 executives in a conference room, and that the people closest to the work had something real to contribute. It also told them the truth: we are figuring this out together, and we know it.
Ask yourself: Is there something your team is clearly feeling right now that you haven’t named out loud yet? If you can feel it in the room and you’re not saying it, they’re noticing that gap.
Getting stability right is the difference-maker
Change management, and especially in the era of AI, succeeds or fails on one thing more than any other: whether people trust the ground is still under them while everything else moves. Leaders tend to treat stability as something to protect once the real work of change management is done. However, it’s the other way around; it’s what makes the rest of the work possible.
Does prioritizing stability slow down innovation?
The opposite tends to happen. Teams move faster through disruption when they trust the person leading them enough to flag problems early, admit what isn’t working, and try things without fear of blame. That kind of trust doesn’t show up on its own; it’s built by the stability a leader provides along the way, not despite it.
What’s the biggest mistake leaders make during AI implementation and transformation?
The biggest mistake is assuming that communicating the vision is enough. It isn’t. People need to know where the ground still is. They need to know that their experience, their relationships, and their contributions still matter. Without that, even the best-designed AI initiative runs into the human wall of disengagement and quiet resistance.
If your company is in the middle of enacting change right now
None of that happens by accident, and most managers were never trained to do it under pressure. That’s the gap Activate by Leadology️ was built to close. It’s Leadology’s signature program, designed explicitly to give executives, department heads, and managers the toolkit to lead through exactly this kind of disruption, not just react to it.
If your team is in the middle of a transformation and you’re not sure the ground feels steady under them, let’s talk. That conversation is usually where the actual plan starts.
