Does AI Fit Your Business?

If you run any business built around real experiences and real spaces (think a warehouse, a construction crew, a historic site, a visitor attraction, a retail floor), you've probably asked some version of this question: does AI even fit my business?

My answer is yes.

And if you think it doesn't, you're not thinking big enough. Eventually the gap between knowing about this technology and being able to practically apply it gets so wide you'll know exactly what you missed.

A lot of the businesses we work with are the ones that don't think, right out of the gate, that AI could be for them. This one is for them.

What I hear first

Does AI fit in a warehouse? A manufacturer? Historical sites? A ski hill, a museum, a store?

When I talk to leaders and employees at places like this, the first reaction is usually confusion.

"We don't have robots, if that's what you mean."

"We like to do it old school."

"I just use it to make funny pictures."

(real quotes I've heard, by the way)

Fair enough. For a lot of people, AI still means robots on a factory floor or an app that makes funny pictures. Neither one looks anything like their average Tuesday.

Sometimes the reaction is outright resistance.

"People like us because we're real."

"We aren't interested in AI."

"AI doesn't fit in here."

I take those seriously. Being real is the whole point of a business built around a place, a craft, or an experience people show up for in person. Nobody wants to lose that... and nobody should have to.

Why some industries are slower to adopt technology

The teams I'm talking about often have a long-standing trend of being a little further behind on technology adoption. There are usually good reasons behind it, and they tend to fall into three buckets.

1. History. Some of these businesses have done things the same way for a long time, and done them well. When something has worked for years, there's no obvious reason to change it.

2. Culture. The people in these industries often take pride in the hands-on part of the work. That pride is earned. It can also make anything that sounds like "technology" feel like it belongs to somebody else's business.

3. Regulation and security. This concern is real and important. Everything we build for and with our clients lives in a secure environment that doesn't train AI models or expose client data to the world.

Beyond that, most of data governance is about having a plan. Understanding where, when, and how you want to use AI. Most organizations and teams just haven't had a deliberate enough discussion yet to make those decisions and decide what they want it to look like.

Here's the thing: you already run on technology

In the background of any operation, whether you're selling tickets, propane, or powder coating, your people are already running on technology. Even if it's "basic."

Calendar. Email. CRM. Spreadsheets. Marketing platforms. POS. The list goes on.

Technology has already earned its place in your business.

AI isn't a step past that.

It's a bridge, connecting your team's best skills to the work that actually needs them: better products, better service, a better experience for the people on the other end.

What the bridge looks like in real work

Let me give you two examples.

A program coordinator at a ski resort. They came in feeling lost about how AI could help with their job. Then we started talking through how new programs actually come together each year, and it clicked.

So much of the next year's programming depended on what they had done before. The data on how previous programs performed was sitting right there. And that data could be used to create new programs and improve the ones already running.

What they needed was a way to put what the business already knew to work without it feeling like an entirely new job.

An account manager at an energy company. They had never used AI. They figured it was mostly for generative, creative work: writing, images, that kind of thing.

That can be true. But every week, they were reconciling prices and balance sheets, and it took a lot of time and energy. That's a job AI could easily help with, handling 80 to 90 percent of it on a regularly scheduled cadence.

Look at what these two have in common. Neither of them works in "tech." Both of them already had the knowledge and the data. What was missing was the bridge between that and the work eating their week.

What it looks like when you wait or avoid

So what does this actually mean for a business that decides AI doesn't fit?

It shows up in three places.

Slower response. The questions, requests, and follow-ups that take your team hours will keep taking hours.

Staff held back. Your people could be accomplishing more and have more open time to do what they do best. When a team stays away from AI simply out of fear, that time never comes back to them.

Competitors getting there first. Somebody in your market is going to get around to using this technology. And when they do, they'll just do better.

None of that happens in a week. It builds slowly, and then one day it's wide enough that you can see exactly what you missed.

Where to start if you're behind on technology

If you're reading this from a job site, a front desk, or a back office and thinking "okay, but where do we even begin," here's where I'd have you start.

1. Have the conversation. Sit your team down and decide where, when, and how you want to use AI. That discussion is most of your data governance, and it takes the fear out of the room.

2. Find the weekly grind. Look for the task that comes back every week and takes a lot of time and energy. Reconciling, reporting, pulling the same numbers together, preparing for meetings or proposals. That's usually the first place AI earns its keep.

3. Look at what you already know. Every business has history sitting in spreadsheets, calendars, and systems it already runs on. Ask where that history could be shaping next month or next season.

Your business already made room for technology. Give AI the same fair shot.