The Retention Problem Wasn’t What They Thought

I recently worked with a small private institution focused on continuing education and professional certifications.

Like a lot of schools right now, they were trying to improve student retention without hiring more staff. The student support team was already stretched thin — large caseloads, constant outreach, lots of manual coordination.

Everyone was working hard.

And yet retention goals still felt frustratingly out of reach.

At first, the assumption was simple: the organization needed more capacity.

But after spending time with the organization, it became clear the bigger issue wasn’t effort. It was where people were spending time, how decisions were being made, and how hard it was to see where support would actually make a difference.

The work was landing with the wrong people

Over time, a surprising amount of operational work had drifted toward IT simply because it touched systems or data.

On paper, that made sense. In practice, it slowed things down.

IT understood the systems, but they didn’t always have the context to make quick decisions around student support. It was also an expensive way to handle work that wasn't deeply technical.

So instead of adding more technical resources, the institution trained a tech-savvy operations team member into a more operational systems role — someone who understood both the tools and the student experience.

That shift created a lot more flexibility almost immediately.

Better visibility changed the conversation

The institution already had several technology projects underway. But when we stepped back and looked closely, not many were directly helping the retention problem.

So instead of starting with technology, the conversation shifted to a much simpler question:

How could the team better identify which students needed support — and when?

Once the team could see that more clearly, outreach became much more targeted.

They stopped treating every student the same way. Communication became more adaptable. And the team had a much better sense of where their time would actually matter.

For a lean organization, that’s a big deal.

AI worked best with human direction

The institution also piloted an AI communication tool to help scale outreach beyond what the team could realistically manage on their own.

Overall, it worked well. The team was able to communicate more consistently, personalize outreach more easily, and stay engaged with far more students than they could manually.

What stood out most, though, was that the AI worked best when it was treated as part of the workflow — not a replacement for it.

The team still needed to refine messaging, make judgment calls, and decide where human intervention mattered most.

I think that’s where a lot of organizations are still calibrating expectations. AI can absolutely help teams move faster and extend their reach, but the best results usually come when the technology is paired with thoughtful direction and people who understand the day-to-day realities of the work.

What actually changed

Retention improved, but more importantly, the team operated differently.

They became more focused. More adaptable. More confident about where to spend their time and energy.

And I think that lesson applies well beyond higher education.

A lot of organizations assume the answer is more people, more technology, or more process. Often the bigger challenge is understanding where time, attention, and resources are actually going.

Adding more people sometimes helps. So does investing in new technology.

But the biggest gains often come from something less obvious: making sure the right work is being done by the right people, supported by the right tools.

When those pieces start working together, teams become more focused, more adaptable, and far more effective.

That's usually where the biggest opportunities are hiding.