Recently, I found myself in one of those conversations that leaves you both energized and concerned at the same time.
I spoke with a young professional with several years of experience who was thoughtfully weighing the pros and cons of using AI in his work. Refreshingly, he neither approached AI with blind excitement nor fear, but carefully considered how new tools might enhance his work.
He brought up the inevitable learning curve with AI: it’s steep, and much of the learning comes from experimentation and, yes, through making mistakes. This can be uncomfortable, especially for high performers used to getting things right. After discussing common traps like avoiding AI, he shared one of his biggest career disappointments.
He had taken the initiative to use AI to automate a process involving Excel spreadsheets and some fairly complex formulas—work that he had been performing almost weekly.
This wasn’t a casual experiment.
He had conducted thorough due diligence to ensure the results generated through AI were accurate and consistent with the spreadsheets he had been using. He had tested it carefully, verified the outputs, and ensured the process was reliable before using it in real-world work.
Then his face lit up as he told me what happened next.
“A process that normally takes me between a day and a half and two days to complete,” he said with a big smile, “I can now complete in about an hour… maybe two hours at the most.”
Think about that for a moment.
A young professional had just discovered a way to reduce a recurring task by more than 90 percent. Naturally, he was excited.
He recently submitted his work to his manager for review, just as he normally would, and was looking forward to showing him the new process and the benefits it had created. Unfortunately, that conversation didn’t go where he expected. His manager didn’t start by asking how the process worked. He didn’t ask what efficiencies had been created.
Instead, his first question was simple.
“What are these new worksheets, and why did you use them?”
Then came the line that stopped the conversation cold.
“I do not want you using AI in this process; do this just like we always have.”
In other words, STOP. That was the summary of the review. The young professional sat there stunned.
I’m afraid that scenario will repeat itself in organizations again and again over the next few years. Not because leaders are malicious, but because many are uncertain.
AI is moving quickly, and uncertainty often triggers the most common leadership response of all. CONTROL. Instead of building thoughtful structures and guardrails that allow professionals to experiment, learn, and improve processes, some leaders will default to shutting things down entirely. From fear to procrastination and the discomfort of feeling behind or not fully understanding the technology, the wheel of innovation comes to a screeching halt. If we are honest, frequently it’s the quiet fear of looking incompetent in front of younger team members who are learning faster.
But here’s the problem with that response. In a world of exponential change, learning cannot be centralized. Organizations cannot rely on a handful of technology specialists while the rest of the workforce waits for instructions.
Learning has to happen everywhere. It has to happen through experimentation. It has to happen through initiative. And it absolutely has to happen through younger professionals who are curious enough to explore new tools and brave enough to test new ideas.
Leadership in the AI era requires a different posture. Instead of saying, “Don’t use that,” wise leaders ask different questions.
How does it work?
What guardrails should we put around it?
How do we validate the outputs?
Where could this help others on the team?
Those questions don’t eliminate risk, but they turn curiosity into capability which leads to progress and a competitive advantage.
The truth is, the organizations that thrive in the coming decade will not be the ones that perfectly control technology. They will be the ones who build cultures where people feel safe to learn, experiment, and improve how work gets done.
Because the real risk isn’t that someone experiments with AI. The real risk is that curiosity gets shut down. When curiosity disappears, learning slows. When learning slows, organizations fall behind.
Learn Fast, Learn Forward, Learn Together.
And always remember to #beBetter.
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