After two days with nearly 100 SaaS CEOs, one thing became crystal clear: the AI-native wave isn’t coming—it’s already here. And the companies that recognize this are moving fast. Really fast.

Not because they have more money. Not because they have more people. But because they have less baggage.

This isn’t about checking the “we use AI” box. AI-native companies don’t bolt artificial intelligence onto what they’re already doing. They rebuild from the ground up with AI woven into the very fabric of how they work—how they make decisions, how they build products, how they grow.

And speed? Speed is their moat.

Legacy Slows You Down

At this CEO summit, I kept hearing variations of the same pain point from traditional software companies: growth is harder, product development is slower, and customer expectations are higher than ever. 

Why? Because they’re still dragging around old systems, legacy code, and outdated business models built for a world that no longer exists.

They’re trying to compete in an AI-powered world with tools built in 2005.

Meanwhile, AI-native teams are shipping new features weekly. They’re lean. They’re agile. They’re hitting $500M in revenue with fewer than 100 employees. That’s what happens when you ditch legacy systems and let AI lead.

Scaling Without Headcount

AI-native organizations scale differently. They don't grow by hiring people. They grow by amplifying what small teams can do.

In traditional SaaS, growth meant more people. More engineers. More support reps. More layers.

But in an AI-native world, growth means more training data, more feedback loops, and more automation. Which in turn drives more innovation.

You can’t retrofit your way into this mindset. Slapping a chatbot on your website doesn’t make you AI-native. The difference lies in how you think, build, and organize. AI-native companies give you action.

What This Means for Higher Ed (and Everyone Else)

If you’re in higher education (or any legacy industry)the urgency to adapt isn’t theoretical. Your students, faculty, and staff are using AI tools in their daily lives. If your institution isn't adapting, they’ll start to feel the gap.

We often say students want an Amazon-like experience. But what they really want is an AI-native experience: personalized, immediate, and efficient. The bar is being raised, not by your peer institutions, but by the tools people use every day.

And it’s not just about the product. It’s about mindset and culture.

Start Where You Are. But Start Now

The worst thing an organization can do right now is put AI in a silo. One innovation team can’t carry the weight of transforming your operations. AI literacy and experimentation need to be part of every function, from admissions to advancement.

Yes, it's hard. It means letting go of the way things have always been done. It means unlearning old habits. But the risk of standing still is greater than the risk of starting wrong.

This isn't about replacing humans. It's about removing friction that slows us down and creating space for our teams to do more meaningful, impactful work.

We don’t need to become AI-native overnight. But we do need to take steps every single day—rethinking, reimagining, rebuilding.

Because in this new era, the winners won’t be the biggest or the oldest. They’ll be the ones that move fastest.

And speed is the new moat.

Listen to the full episode of Generation AI today.