How AI Will Reshape Summer Camps

Not long from now—five years, maybe less—the way summer camps interact with data will change entirely. If you want a glimpse into that future, don’t look at your current camp database, with its clunky search bar tucked in the upper right corner. Look instead at a chat box. Simple. Open-ended. Conversational. The kind you might see on ChatGPT or remember from early Google searching (before the annoying ads plagued our results).

You’ll type in a question—“What do I need to know about Bus 7?” or “Why is the Bock family upset?”—and the system will respond as though you were talking to a colleague. A really, really competent one.

Say, for example, a camp administrator gets word that Bus 7 is running late and the Bock family is frustrated. She types that into the chat box. Instantly, the system replies: “The Bock family is the fifth stop on Bus 7, normally picked up at 8:38 a.m. Their camper, John, is in Group Boys 1A. His first scheduled activity is swim. You may want to alert the swim director for that age group, Hayden, that John will be arriving late.”

What just happened?

The system pulled data from transportation logs, camper enrollment, activity schedules, and staff directories. It synthesized all of it into a single, useful answer—not unlike what the best office manager would do after twenty minutes on the phone and in the files. But this happened in seconds.

This is where every modern database is heading. But for camps—a world that still traffics in clipboards and spreadsheets—it will feel revolutionary.

And yet, there’s a trap here: confusing AI with the goal itself. AI is not the product. It’s the infrastructure that enables the product. And that product, broadly speaking, is a smarter CRM—a customer relationship management system tuned specifically for camps.

It will do what today’s camp software already tries to do: manage camper data, track communications, log tasks. But it will do all of this in a way that is anticipatory rather than reactive.

Take the conversation about Bus 7. After the chat box gives the answer, the system logs the conversation with Mrs. Bock. It tags it: “transportation concern,” “swim delay,” “parent frustration.” Now fast-forward to August. A camp director asks the system: “Who are the top 10 families least likely to re-enroll?” John’s name comes up. The system explains: repeated late pickups, swim-related issues, a flagged note about Mrs. Bock’s dissatisfaction. The director now has a strategy—not a mystery.

If that sounds powerful, it is. But to understand its impact, you have to understand how innovation actually spreads.

When Andrew Carnegie helped usher in the era of steel, he didn’t advertise the alloy itself. He didn’t run ads explaining its tensile strength or its metallurgical makeup. Instead, steel became synonymous with something bigger: the Brooklyn Bridge—suspended by steel cables, bridging two boroughs that once felt worlds apart. Then, skyscrapers—once impossible with traditional iron—suddenly seemed to defy gravity. Carnegie didn’t need to explain steel. He just needed to point to the skyline.

It wasn’t about the technical information about the material. It was about what the material made possible.

Elon Musk faced the same dilemma with PayPal. The backend technology was complicated. Encryption protocols, digital wallets, secure servers. But the message that caught on was much simpler: send money safely by email. That’s what people needed to hear.

So it is with camps and AI.

We don’t need to say, “AI will be integrated into your database.” We need to say:

• “You’ll recognize camper concerns so you can make a pro-active phone call.”
• “You’ll identify solutions to staff challenges for those team members get burnt out.”
• “You’ll re-engage alumni before they donate elsewhere.”

The phrase “artificial intelligence” doesn’t matter. What matters is what it does. It allows you to see patterns you would otherwise miss. It connects various banks of data that, currently, are not connected. It creates space for intuition, by doing the grunt work of data retrieval and analysis.

Whoever figures out how to translate that promise—the language of algorithms into the language of outcomes—will shape the future of camping. And they may never need to say the word “AI” at all.