One subplot of last week's election was that at least 38 jurisdictions passed moratoriums on data centers. The mood music was that Democratic control in states and Congress would slow the industry down. The news even led to stock market drops.
I had that mood music in my head on Thursday when I had the first of two magical moments with AI. I received a Word file with the agenda for an upcoming conference. My first instinct was to read it over, decide which sessions to attend, and add them to my calendar manually. Luckily, I realized that was probably the old way of doing it. I asked Claude, “Can you take the attached agenda and create Outlook calendar events?” In about two minutes, it was done.
I wrote to my friend that this was “one of those obvious use cases that reminds you that, despite what people might feel about AI, it's totally going to happen.”
Even if I were skeptical about AI’s impact on society or the environment, I would probably use it this way for every conference from now on. The time and effort saved are just too great.
On Friday morning, I had another magical moment. One of my eyes was irritated, which made it hard to stare at a computer screen or sit in a bright room. I was working at home, so I went to my bedroom, lay down, and started using Claude. The ailment wasn't a barrier because I could just keep voicing instructions and having the results read back to me. It felt like a cheat code—work without working. The only limitation was my phone battery.
My limited vision was temporary, but it gave me a personal window into the accessibility power of AI. The experience reminded me of a story an educator told at a conference. Her dyslexia hindered her ability to communicate effectively, but ChatGPT’s writing and editing skills meant her disability was no longer a barrier. For her, using AI wasn’t complicated. It was essential.
Her story and my irritated eye led to the same reflection: Even if society slows down on AI, and it doesn’t improve, it’s here to stay. It’s already good enough to have a meaningful place at work.
Coincidentally, I spent that eyes-closed morning working on the HR implications of our organization’s AI strategy. When should we add AI skills to the list of technology tools that people should know how to use? When would they become part of performance reviews? Which roles will require basic skills, and which will use advanced skills as the benchmark?
But all of those questions come back to the crux of the issue: When would we tell people, “I hear your reluctance and fear about AI, but we’re doing this regardless”?
Fortunately, we had an AI learning session scheduled for that afternoon, and a friend was our guest speaker. I asked how his company drew the line between encouraging people to use AI and mandating it, and what advice he’d have for us. He offered a helpful reframe: AI is new, but the human challenges of change management are the same ones we’ve always faced.
As someone who teaches a change management course, I slapped my forehead. Of course.
I’d been looking at our AI strategy so closely that I missed how it fit into the larger picture. Treating AI as fundamentally different was a distraction. Like every organization, we’ve always required employees to use certain technology tools—we’re just adding one more to the list. And every change brings early adopters and laggards, and managing both has always been part of the job.
The technology is different, but the questions it raises for leaders are the same. What do we really care about? And where will we hold the line?
It’s the point in my change management class where I tell students the answer is inside them—their values and what they’re willing to do as leaders.