There is no shortage of content and conversation about AI right now. Reports, frameworks, predictions, warnings, the volume of information is staggering, and it shows no signs of slowing down.
As a keynote speaker, adviser, podcast host and the founder of The Edge of Work, I spend a lot of time advising and talking with leaders who are navigating AI transformation in the workplace. Over the past several years, I’ve spoken with and advised hundreds of leaders navigating the intersection of AI, leadership, and the future of work. And while every organization is different, a handful of themes keep surfacing. Honest, recurring tensions that transcend industry, function, and seniority level.
I want to share five of them. Not because they come with easy answers (spoiler alert: they don’t) but because I’ve found that naming and sharing these key themes often helps others process and think through the challenges that they are facing themselves, along with offering some ideas for how to move forward.
1. Most leaders feel caught between a past that’s fading and a future that isn’t clear yet.
The word I hear more than any other right now is change. Not as a concept. Leaders have always dealt with change. But as a felt experience. Something about this moment feels different. More disorienting. Harder to get traction in.
What I’ve come to believe is that we are in what psychologists call a liminal space. The in-between. Think of a hallway connecting two rooms. On one side is the past: familiar, legible, but losing relevance by the day. On the other side is the future: visible in glimpses, but not yet formed enough to anchor to.
What makes this moment hard isn’t the presence of change. Leaders have always had to navigate change. What makes it hard is the nature of this particular transition, especially as it relates to AI and how it’s transforming the workplace. The ground is shifting in ways that make the old playbooks feel less trustworthy, without yet offering clear replacements. And in that gap, it can be genuinely hard to know where to put your energy. On one hand, you don’t want to anchor too much to the past, but you know some of those playbooks and tools work. On the other, you can’t see the future clearly, so it’s hard to commit to a blurry vision, but you can see some of what the potential is, and it may even feel transformative. This makes it hard, to know what to do, or where to anchor your priorities and direction.
In my experience, I have found that the leaders navigating this best aren’t the ones with the most certainty. They’re the ones who have found ways to move forward without waiting for certainty to arrive.
2. AI adoption is about far more than learning new tools.
In almost every organization I work with, there is a version of the same conversation happening. Leadership wants teams to adopt AI. Teams are being trained on tools. Everyone is hoping that something meaningful will change as a result.
But meaningful change is not what’s happening in most places, and it certainly requires more than just hope. What’s happening instead is what I’ve started calling copy-paste AI. Teams taking the work they’ve always done and doing it in AI. Same workflows, same outputs, same assumptions about what work is worth doing. Just a little faster, a little easier.
To be clear, that is a reasonable starting point – it’s what we know and we’re most comfortable with, and there’s benefits to be had from it. But doing what you currently do just with a new tool (ex: copy paste) isn’t going to fundamentally change and improve the way that you work, and if isn’t going to do it for you, it’s certainly not going to translate into significant outcomes for your organization.
The leaders who are getting the most value from AI are the ones asking harder questions before reaching for the tool. Why are we doing this work at all? Does it still make sense? What could we do differently to achieve our goals? Those questions, not the tools themselves, create more possibilities and potential for impact and value.
I wouldn’t be the first to say this, but what I’m seeing so far is that AI is not just a technology adoption challenge. It’s a thinking and behavioral change challenge. And until leaders and organizations start thinking about it in that way, most of the potential will remain on the table.
3. The leaders who are building the most trust aren’t the ones with all the answers.
There’s a certain pressure on leaders right now to project confidence about AI. To have a point of view, a strategy, a plan, even when the landscape is shifting faster than any strategy can keep up with. And that pressure can lead to a performance of certainty (or even worse: “AI theater”) that actually makes things worse for the people around them.
That said, the leaders who are building the most trust with their teams right now are not the ones who have everything figured out. They’re the ones who are honest about what they don’t know, curious enough to keep exploring, and clear enough about direction to take the next step forward, even without a complete picture. They ones who seem to be most at peace with the uncertainty are even going as far to collaborate with their teams, to share their learnings, questions and concerns, so that the collective intelligence can be far greater than the individual intelligence.
Employees are not looking for omniscience and for leaders to have everything all figured out. They’re looking for leaders who are willing to navigate the uncertainty alongside them. Leaders who model what it looks like to stay grounded and keep moving when the path isn’t fully visible.
4. Creating the conditions for experimentation is what drives change, but is hard to do
Tool adoption is relatively straightforward. Behavioral change is not. And most leaders I speak with have discovered, often the hard way, that these are not the same thing.
You can tell a team to use AI. You cannot tell them to fundamentally rethink how they work. That kind of change requires something that doesn’t show up in a tool rollout plan: psychological safety, protected time to experiment, visible modeling from leadership, and consistent signals over time that trying something new and failing at it is acceptable and okay.
The leaders making the most progress on this are not the ones with the most sophisticated AI strategies. They’re the ones trying to create conditions that enable their people to experiment, test and learn. Building containers for experimentation. Making it safe to be curious. Staying consistent between what they say, what they do, and what they reward.
One of the most common gaps I see is the space between intention and signal. A leader says exploration matters, and then only recognizes and rewards execution. Teams are smart. They read the actual signals, not the stated ones.
5. Most leaders haven’t clearly defined what their highest value contribution actually is right now.
This is the question underneath all the others. And the one I find most leaders have not taken the time to answer.
As AI absorbs more of the work that used to fill our days, the summarizing, the drafting, the coordinating, the routine decisions, a real and important question emerges. What is the work that only I can do? What is the uniquely human contribution I bring as a leader that cannot be replicated or automated away?
In the medical profession, there is a concept called operating at the top of your license. The idea is that every practitioner should focus on the highest-value work they are specifically trained to do, so that collectively the team achieves what none of them could alone. I think this is one of the most important questions leaders can be asking themselves right now. Not as an abstract exercise. As a practical reckoning with where time and attention is actually going, and whether it’s pointed at the things that matter most.
A Final Thought
One of my observations and key takeaways when trying to come up with these five themes is that none of them are fundamentally about technology. They’re about leadership. The same timeless challenges of navigating uncertainty, creating conditions for people to do their best work, staying clear about what matters most, and being at the forefront of what’s coming next are showing up in a new and more urgent form.
While AI may change the conditions of work, and work itself, it is not changing the need for good leadership and good leaders – if anything, it demands more of it.
During this time, it’s my belief that the leaders who will stand out and thrive won’t be the ones who wait around for what comes next, but rather, they will be the ones who will operate without complete certainty, sensing what’s happening, identifying the next move, and bringing their people with them through the uncertainty.
Reflection Questions
If any of these five themes resonated with you, I’d offer a set of additional reflection questions to help you think through what you can do to navigate these times.
- How are you finding navigating the liminal space?
- How are you using AI today? To what degree has it allowed you to do new things or tackle new capabilities?
- Where is your team at with their own usage around AI? Are they “Copy-Paste” or are they getting creative about how they think and work differently?
- Do you know what your highest value contributions are? What are they, and how does AI change that?
- What are some ways you have allowed your team to experiment with AI? What have they learned from this?
