Where Do I Even Start with AI?

"I want to learn more about AI, but I don't know what I should know — and I don't know what to do next."

In my conversations with private school administrators, this is the single thing I hear most often.

What I see in these conversations is a pattern. Many school administrators are trying to learn AI the same way they learned software tools in the past. That model no longer works.

There is no shortage of information about AI. What is missing is orientation. For most leaders, the real challenge is figuring out where to begin.

When you do not have a starting point, even good information becomes paralyzing. That is where learning about AI often goes off the rails. A few common responses I see when administrators are trying to start:

• Waiting for the technology to "settle down" before engaging

• Assuming you need technical knowledge before you can do anything useful

• Sampling tools without clarity about where they actually fit

• Treating AI as something separate from everyday school work

• Feeling pressure to understand the whole landscape before taking a first step

None of these responses comes from apathy. They come from uncertainty.

I ran into this myself when I first set out to learn more about AI. I consumed large amounts of information, hoping clarity would emerge on its own.

What finally shifted things for me was recognizing a chicken-and-egg problem underneath all of this.

You need to understand AI before you can decide where to begin. But trying to understand everything before deciding what matters keeps you stuck.

Here is the insight that unlocked things for me:

You don't learn AI broadly to decide how to use it.

You learn just enough to decide where depth actually matters.

That shift changes everything.

Once you stop trying to start everywhere, learning gains structure. You begin by understanding the landscape at a high level, then move toward depth only where AI can make a real difference in your specific work.