Amanda Loveland shares the five bricks necessary to build an effective foundation for AI in community recreation.
Most community rec centers I talk to have already “started” using AI. Someone opened ChatGPT during their lunch break, drafted a class description and quietly declared the organization in the game. Six months later, the tool is gathering digital dust, the team is still drowning and leadership wants to know whatever happened to the productivity revolution.
The honest answer is almost always the same — the foundation got skipped.
We would never build a new wellness wing without a blueprint, a budget and a real conversation with the people who would use it every day. AI deserves the same respect, because it’s not something you sprinkle on top of existing operations. It’s a meaningful shift in how your team works and shifts like that need something solid underneath them. After three years of helping rec centers get this right, I can tell you the organizations that succeed always lay the same five bricks first.
Brick one is a real policy.
Before your team uses AI in any serious way, they need to know what’s allowed, what’s expected and what’s off-limits. A good policy is a permission slip and a guardrail wrapped into one. Without it, half your staff quietly experiments in ways that put member data at risk, and the other half avoids the technology entirely because no one ever signaled it was safe to try.
Brick two is the people side.
The tech is rarely the hard part. Your team is exhausted. They have lived through technology rollouts that promised the moon and are protecting whatever bandwidth they have left for actual member care. Change management is how you bring them along instead of leaving them behind. It doesn’t require a six-figure consultant. It requires starting with the why, making space for fear before pushing adoption and celebrating early wins loud enough so the quietly skeptical start paying attention.
Brick three is training that goes beyond the surface.
Most staff who say they use AI are using it for the occasional polished sentence, which represents maybe 10% of the value sitting on the table. Real training teaches workflows, context-loading, and using the tool for analysis and planning — not just copywriting. The “they’ll pick it up on their own” approach almost never produces real outcomes.
Brick four is use cases tied to actual pain.
Stop asking what AI can do and start asking what’s making your team miserable. Survey responses no one reads. Grant cycles that consume entire weeks. Program launches that require six redundant forms. Those are where AI earns its place, because the time it saves goes straight back to the lobby, the gym floor and the conversation with a member who needed to be seen today.
Brick five is a human-first North Star.
Without a human anchor, AI drifts toward the easiest answer every time, and the easiest answer is rarely the one that strengthens community. My personal rule has not changed in three years. If I wouldn’t say it out loud to a member, I will not send it no matter how polished AI makes it sound.
You don’t need a bigger budget or a chief AI officer to do this well. You need a foundation. Lay the bricks in the right order, and everything you build on top of them stands up.
