What AI is (and what it isn’t)
When I first started digging into artificial intelligence, it wasn’t because I thought it was some magic tool that would change everything overnight. My interest actually grew out of something a little less flashy: data.
I’ve seen firsthand how a strong data-driven culture can be the greatest competitive advantage an organization has. Decisions backed by solid data consistently outpace those based on instinct alone. So naturally, when AI started taking center stage in nearly every business conversation, I wanted to understand: how does this really fit into the world of data, and where does the real business value come from?
I’ll be honest, part of my curiosity also came from being a lifelong science fiction nerd. Movies and books make AI look like this futuristic, beyond human intelligence. But as I’m learning, the reality is a lot less like The Matrix and a lot more practical.
Over the past year, I’ve been learning in every way I can, reading articles on LinkedIn, following the news, experimenting with AI tools like ChatGPT, and diving into books. (If you’re looking for a great starting point, I recommend AI Literacy Fundamentals by Ben Jones and AI & Data Literacy: Empowering Citizens of Data Science by Bill Schmarzo.)
And along the way, I had my first big “aha moment”: AI is only as good as the data it’s trained on. If the data is messy, biased, or incomplete, the AI’s output will be too. That simple truth helped me see past the hype and start focusing on what really matters.
So, what is AI really?
While inspired by the human brain, AI is not that same, and it doesn’t “think” the way humans do. Instead, it’s more like a powerful tool that learns patterns from large sets of data and uses those patterns to make predictions, classifications, or suggestions.
Think of AI as a calculator on steroids. Just as a calculator doesn’t “understand” math but can process numbers at lightning speed, AI doesn’t “understand” in the human sense—it just processes data at massive scale, far beyond the speed at which the human brain can process it.
This is an important distinction as many people talk about AI as if it were human-like intelligence or has the ability to understand the concepts beyond the data. That’s where some of the biggest misconceptions begin.
ANI vs. AGI: Where We Are Today
A quick call out. Here’s a term I wish was more talked about early in the AI conversation: the difference between Artificial Narrow Intelligence (ANI) and Artificial General Intelligence (AGI).
ANI is what we have today. It’s “narrow” because it’s built to do one specific thing very well—like recommending your next movie on Netflix, detecting fraud in a credit card transaction, or helping identify patterns in imagery.
AGI is what science fiction imagines; a system with the flexibility, reasoning, and adaptability of a human brain. That doesn’t exist today, and experts debate how close (or far) we are from it.
So when you see headlines about AI, remember: the tools we’re using in business today are narrow AI tools. They can be powerful, but they’re not a substitute for human judgment or strategy.
Setting the Stage
This post kicks off a series I’m calling AI for the Rest of Us. The goal isn’t to overwhelm you with technical jargon or show you how to design you own AI agent. It’s to share what I’m learning in plain language, so we can all cut through the hype together.
Over the next several posts, I’ll tackle some of the biggest myths and misconceptions I’ve come across, such as:
Why AI isn’t a magic solution you can just plug in
Why data maturity matters more than AI hype
Where AI can actually help (and where it can’t)
How AI compares to the human brain
Why strategy must come before shiny tools
If you’re a business leader, operations manager, or just curious about AI, this series is for you. If you’re an AI wizard, your understanding, experience, and feedback would be greatly appreciated and will help get the rest of us up to speed.
So dear reader, my hope is that by the end of this short series, you’ll feel confident separating fact from fiction, and maybe even spot some practical ways AI can support your work.
Final Thought
AI isn’t magic, and it isn’t a crystal ball. It’s a powerful tool, but still just a tool. The real music happens when people, strategy, and good data come together to put that tool to use.
So let’s dig in, learn together, and keep asking questions. Because the more we understand AI, the less intimidating and more useful it becomes.
