AI has quickly become a regular part of how I work. It’s not just a tool I use, but something closer to a partner, a collaborator. While I wouldn’t say I’ve mastered it (who has, really?), I’ve definitely moved past the experimentation phase into something more meaningful. These days, I see AI as a thought partner who helps me think through problems, refine ideas, and surface possibilities that I might not have seen on my own.
That’s the phrase I keep coming back to, “thought partner.” In the beginning, like most people, I used AI to organize my thoughts or clean up rough drafts. It was fun to just throw in a messy idea and get back something polished. But over time, I realized it could offer more than just formatting or phrasing help. It could actually add to my thinking. That shift, from treating AI as a tool to seeing it as a kind of partner, changed how I approached my work.
Now, when I’m working through something, whether it’s a report, a presentation, or just trying to make sense of data, I’ll use AI to look at it from different angles. Sometimes it gives me suggestions I hadn’t considered. Other times, it just helps me prioritize, remember something I forgot, or fill in a gap. It’s not doing the work for me, but it’s definitely helping me do it better.
There was a point when I realized that I’d moved past just using AI for surface-level tasks. For example, in the beginning I might have said, “Here’s some data, make a table.” And it would create a simple table. Pretty cool. But now, I’ll say, “Here’s some data. What can we learn from it? Where are the inconsistencies? What’s missing?” The results I get back help me build a stronger, more complete output. The final report is better thought through because I used AI to get there.
That’s a big shift. It’s not about giving AI a task and expecting a perfect result. It’s about using it to think through the task together. The biggest lightbulb moment for me has been the mindset shift: seeing AI as a collaborator rather than just a tool.
Of course, there are boundaries. AI is only as good as the data it’s trained on. In our work at The Canton Group, especially in Organizational Change Management, we’re usually dealing with frameworks and structured processes. That reduces the risk of bias or misinformation. But still, I never take an output at face value. I always give it a human review. It might help shape my thinking, but I’m the one who decides where we go with it.
That’s the balance I try to strike; using AI to speed up the process, surface new ideas, and create consistency across our team, all while keeping human judgment at the center. That’s something I think every team should be thinking about. Not just “Should we use AI?” but “How do we use it well, and use it together?”
If I had one piece of advice for teams just starting to explore AI, it would be: don’t ignore it. Don’t wait until it’s forced on you. Start experimenting now. Train your team. Set some basic guidelines. Figure out how it can enhance your workflows, not replace them. Aim for consistency. When everyone uses AI in a thoughtful, aligned way, your work looks sharper and more professional across the board.
AI isn’t here to do our jobs for us, but it can absolutely help us do them better if we treat it like the thought partner it has the potential to be.
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