I’ll be honest — for most of my academic career, I was not worried about AI. I figured it was useful for generating ideas or summarizing lengthy readings, but not capable of the kind of nuanced, critical thinking that actually matters in business. That perspective started to crack a few weeks ago, and honestly, I’m not so sure anymore.

The shift happened a few weeks ago during a guest session in my Technology and Management course. A speaker made a point that stuck with me: the free models we interact with every day are barely scratching the surface of what AI can do. The tools most people know, like free-tier assistants and consumer chatbots, are the tip of the iceberg. Beneath the surface, enterprise-grade models are being trained on industry-specific data, integrated into business workflows, and used to make real decisions. That’s when it clicked for me.

If I’m not building AI fluency now, someone else is. And that someone will have a leg up on me.

The Comfort of the Status Quo

It’s easy to feel comfortable with the skills you have. You study hard, build your resume, and tell yourself that your work ethic and soft skills will carry you. And they will, to a point. But this course challenged me to think about what happens when those things become table stakes. When everyone is hardworking and personable, something else has to differentiate you.

Earlier in the course, I learned that attitude and effort matter even more than soft skills alone. Now I’m adding a third layer to that: leverage. The people who learn to use AI tools effectively will produce higher-quality work in less time. They’ll be more productive, more creative, and more valuable to employers. That’s not a guess — that’s already happening.

That doesn’t mean AI should do your job for you. It means AI should make you better at doing it.

The Risk-Taking Parallel

Another big lesson so far has come from a market simulation we ran a few weeks into the course. The takeaway was straightforward: take risks early. In fast-moving markets, waiting for perfect information is a losing strategy. You test, you learn, you adapt. Customers often don’t know exactly what they want, so getting firsthand feedback from the market is almost always more valuable than sitting on the sidelines doing research.

AI is no different. A lot of professionals are in “wait and see” mode right now, watching how the technology develops before committing to learning it. I understand that instinct; it’s a rapidly changing space and nobody wants to invest time into a tool that might look completely different next year. But the underlying skill of knowing how to work with AI, how to prompt it effectively, how to integrate it into your workflow. That’s not going anywhere. Just like knowing how to code outlasted dozens of specific programming languages, AI fluency will outlast any single platform or model.

The students experimenting with AI now, even imperfectly, are building that fluency. The ones waiting for the dust to settle are falling further behind every day.

Reputation Is Currency

There’s another idea that keeps coming up in this course: your net worth is your network. More specifically, social credit matters as much, if not more, than professional credit. Being knowledgeable about AI isn’t just a productivity advantage. It’s a credibility signal. In a room full of professionals, being the person who can speak to AI capabilities, who understands where it adds value and where it falls short, and who can translate that into real business decisions is enormously valuable.

Conversely, being dismissive of AI or unable to engage with it substantively is a liability. It signals stagnation. And in an industry that rewards people who adapt early and adapt well, stagnation is a risk few can afford.

One of our speakers put it plainly: good ideas don’t always come to fruition, and the people who make it aren’t necessarily the smartest ones in the room. They’re the ones who stayed curious, built the right relationships, and kept moving. That’s the mindset I’m trying to carry forward.

What I’m Taking With Me

This course hasn’t just taught me about technology; it’s teaching me how to think about it. Not every trend is worth chasing. But some shifts are structural, and AI is one of them. It’s not a novelty. It’s becoming infrastructure. Just like the internet moved from being a curiosity to the backbone of the modern economy, AI is being embedded into how businesses operate at every level.

My goal isn’t to become an AI researcher or an engineer. My goal is to be the person in the room who knows enough to ask the right questions, who can spot where AI creates value and where it doesn’t, and who adapts as the tools evolve. That’s a realistic goal. And based on what I’ve learned so far, it’s also a necessary one.

The most important thing I’ve taken away so far? Don’t wait to adapt. By the time something feels obviously necessary, it’s already too late to be early. And in technology and business, being early is often the whole game.