Why is it so much harder?

Yeah.

By the way, the data backs that up.

It particular- So let me put a caveat out there, which is what I know very well is the small and mid-sized business world, okay? Which is, which has nothing to do with the large business world.

Two different worlds, and certainly nothing to do with the world of government employment, right? So i- and you know, it would be normal for somebody to say, "Wait a second.

There's gotta be plenty of people out there." I'm reading, like, I'm a Wall Street Journal reader for practically my entire life, and if you, when you read the Journal, every week there's, you're hearing about some layoffs going on, right? You gotta remember, these layoffs are w- large company layoffs, right? If small and mid-sized business companies are doing some sort of layoffs, you're not gonna read about in the paper, and you're just not seeing those, right? These are large companies that are public that really need to button down, et cetera.

Those people don't always make for great employees in a small or mid-sized business, right? They have different skill sets, and, you know, like, I'll leave it at that.

What, assessments like Myers-Briggs or DiSCs or more skill-based kinds of assessments?

What's new now in the agentic context?

A few areas.

Um, the first in strategy is, you know, end-to-end workflows.

We, we'd always sort of had this concept that thinking about the broader change versus individual use cases had value.

That's just become incredibly clear with agentic AI and this ability to actually automate the majority of a tasks, of tasks in an end-to-end workflow.

Um, reimagining that end to end versus just sort of deciding on an MVP use case in a workflow is clearly the path to success.

You know, w- w- in the last book, we talked a lot about the, the challenge of getting density of scarce technology talent and sort of keeping them happy and at top of their craft.

Rob, what are the gaps most businesses miss in their AI maturity journey?