I recently completed the Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” with the goal of better understanding how to use AI and how AI tools actually fit into the way we work—not just in theory, but in practice. As part of that process, I’ve been translating those learnings into real-world application for our team and our clients, while also pressure-testing them against day-to-day realities. This blog series is a reflection of those takeaways—shaped by the Masterclass teachings, hands-on use, practical experience, and, fittingly, collaboration with AI tools like ChatGPT to help organize and refine the thinking.

AI has quickly become part of the conversation in almost every industry, often framed in best case or worst case extremes—either as a transformative breakthrough or a looming replacement for existing roles. But most of those conversations focus heavily on what AI can produce, rather than on how those outputs are actually created or evaluated.

At this point, there is some general agreement on what AI is capable of. It can analyze data, generate ideas, summarize information, and produce structured outputs at speed. However, focusing only on those capabilities misses the more important shift underneath. Unlike traditional tools, AI does not operate within a fixed set of functions. It combines what it has been trained on with the context it is given, producing outputs that are shaped by that interaction.

As AI takes on more execution, the value of the work shifts. Less value sits in producing outputs, and more value sits in defining problems, providing context, asking better questions, and making educated final decisions. AI can support thinking, but it does not replace the need for it.

This shift is about redefining what good work looks like. Speed alone is no longer the differentiator. Thoughtfulness and relevance drive value.

What we are seeing is not a gap in access—it is a gap in approach. Some treat AI as a shortcut; others treat it as a collaborator. The difference in outcomes is significant. AI is powerful, but not strategic on its own. It requires direction, context, and judgment. As adoption grows, the advantage will come from how intentionally these tools are used. This perspective will be explored across the rest of this series.

If you are working through what that balance looks like, you are not alone!

BY KRISTEN ORTON Based on learnings from the AI Masterclass Certification, “AI Fundamentals: Think, Create, and Work Smarter,” and real-world application, with support from AI tools like ChatGPT.

This is part of a 5-part series on using AI. Read the other articles by clicking below:

Article 1: AI is Changing the Work It Is Not Replacing It
Article 2: AI Is Confident Even When It’s Incorrect. Here’s What That Means For You
Article 3: Using AI Is Easy, Using It Well Is Not
Article 4: What AI Can’t Replace and Why That Matters
Article 5: Why Many AI Results Feel Generic and What Better Teams Do Differently