Organizations are investing heavily in AI, but giving employees access to a tool is not the same thing as changing how work gets done.
I’ve been through enough technology rollouts to know the pattern: select the platform, communicate the launch, train people, measure usage, and then look at the numbers to determine whether adoption was successful.
I don’t think that approach works with AI.
The question I keep coming back to is not, “Are people using it?” It’s, “Is it actually making the work better?”
That means looking at where people are spending their time, where work gets stuck, what takes hours that shouldn’t, and where we are doing something a certain way simply because that’s how we’ve always done it.
Start with the work
One of the biggest mistakes we can make is starting with, “How do we get more people using AI?”
I’d rather ask, “Where are we spending time today that could be spent better?”
That might include preparing recurring reports, drafting routine communications, searching through information, or trying to identify themes across hundreds of employee comments.
I’ve used AI for exactly that last example.
When I’m reviewing a large amount of employee feedback, AI can help me organize the information and identify recurring themes much faster than I could manually.
However, I’m not taking what it gives me and dropping it into a leadership presentation.
I still have to understand the context and question what I’m seeing. Is this really a theme? Is something important missing? Does it align with what we know is happening in the business? Most importantly, what should we actually do with the information?
AI can accelerate the work. It doesn’t eliminate the thinking.
That’s where I think organizations sometimes get AI adoption wrong. The goal becomes getting people to use the tool instead of figuring out where the tool can make a meaningful difference.
There’s another question leaders need to consider. If something that used to take three hours now takes 30 minutes, what are we doing with the time we just gave back to that employee?
If the answer is simply giving them more work, we may be missing a much bigger opportunity.
People need clarity
I also think we underestimate how much uncertainty employees have around AI.
What can I put into it? Which tools am I allowed to use? Do I need to disclose that I used AI? What happens if the information it gives me is wrong? When do I need to stop and get someone else involved?
If we haven’t answered those questions, telling employees to “go experiment with AI” isn’t enough.
Some people will avoid it because they don’t want to make a mistake. Others will jump in without fully understanding the risks.
Leaders don’t need to become AI experts, but they do need to know enough to have these conversations with their teams. People need to understand where AI can help, where it shouldn’t be used, and where they are still accountable for the final result.
That last piece matters.
AI can create something in seconds that looks finished, but that doesn’t mean it is.
A first draft that used to take 45 minutes might now take five. That is valuable, but if we stop questioning it because it sounds polished, we haven’t necessarily improved anything.
The more we use AI, the more important human judgment becomes.
The talent question may be even bigger
A lot of the conversation around AI focuses on jobs. Which roles will disappear? What will be automated? Which skills won’t be needed anymore?
I understand why we’re asking those questions.
As someone who has spent much of my career in talent and leadership development, I’m equally interested in another question:
What do we need people to become better at because AI exists?
If AI takes on more routine work, then critical thinking, judgment, communication, problem-solving, creativity, and relationship-building become even more important.
That should change how we think about talent.
What are we hiring for? What are we developing? What do we expect from our leaders? Are we teaching people how to think critically about what AI gives them, or are we just teaching them how to use the tool?
For me, AI strategy and talent strategy have to connect.
If the work changes, the skills people need will change too. We shouldn’t wait until jobs look completely different to start preparing people for that change.
Leaders also have to be willing to learn alongside their teams.
Employees notice when leaders talk about AI but never use it themselves. They also notice when they are encouraged to experiment and then criticized when an early attempt isn’t perfect.
There has to be room to learn.
I don’t think leaders need to pretend they have AI figured out. I certainly don’t.
There’s value in saying, “Here’s something I tried. Here’s what worked. Here’s what didn’t. Here’s what I still had to do myself.”
That makes AI much more practical and a lot less intimidating.
This is bigger than the technology
AI is going to keep moving faster than most organizations can write policies, build training programs, or create the perfect rollout plan.
We’re not going to have everything figured out before the next tool arrives, but we can get better at asking the right questions.
Where does AI actually improve the work? Where do people need clearer boundaries? What skills will matter more because of it? What do leaders need to do differently?
The organizations that answer those questions well may not be the ones using the most AI. They may simply be the ones using it with the most purpose.
At the end of the day, AI adoption isn’t really about convincing people to use another piece of technology.
It’s about helping people figure out a new and better way to work.
