Your First 30 Days with AI: A Field-Proof Pilot Plan

Pat: So far we’ve talked about what AI is and isn’t, the different types of AI, and in our last episode, making sure you have the data and processes to effectively leverage AI at your business. Now we’re going to show you how to get started. Today we’re going to get into where the rubber meets the road. How do you actually start using AI in fire protection without slowing down your ops or confusing your techs? Inspect Point started as a family business, and I’m happy to have my wife and co-founder with me.

Jenn: Hi, I’m Jenn Doyle, co-founder and Chief Customer Officer at Inspect Point. In my 12 years here, I’ve spent a lot of time getting to know fire protection businesses and their day-to-day operations. Today we’re going to briefly walk through a 30-day blueprint for a low-risk, high-impact pilot. One that helps you learn fast, measure clearly, and keep your team in control.

Jenn: There’s a lot going on, and pardon the pun, but a lot of fires to put out. How do you make time for testing a new technology? It really all comes down to small incremental tests. Some tips: Identify a workflow or process that is repeatable, consistent, and most likely a pain point. Map out that process, and ideally it’s something that AI can actually help with.

Pat: Then select a tool, map out the process, and compare the results to the old way of doing business.

Pat: A lot of this comes down to being flexible, testing, and learning. It’s probably going to be a little rocky at first, but the companies that become proficient at leveraging these technologies are going to gain an advantage quickly. Let’s get into some specifics as an example. Scope small. Measure results. Adapt and grow.

Pat: Day 0: Pick one workflow and define what success looks like. It could be upcoming appointment reminders to lower dispatcher burden and higher confirmation rate. It could be monthly reporting with AI-sourced data crunching and insights. Or it could be Inspection Report QA and Submission for higher quality from the field and faster submission time. We’re obviously partial here, but we launched the first embedded AI tool, and we’re proud of it, so we’ll be using Inspection Assistant as the example.

Jenn: Week 1: Start by mapping the current process. How does it actually work today? For example: My techs spend X minutes on average conducting a monthly sprinkler inspection. We give them their visits for the day. They conduct the inspection using the pre-printed form and drop it off at the office at the end of the day. The next day, the Inspection Manager calls them to review any notes and has them make edits as needed. Then we scan and upload to an AHJ. You’re looking for time, consistency, rework, anything you’d want AI to help with.

Pat: Week 2: Run it both ways. Same workflow, two versions. Traditional vs. AI-assisted. Track the difference. Map out how AI can help you. You could look up manufacturer specs on hardware with ChatGPT, use an AI dialer to confirm appointments, or use software plus an embedded AI tool like Inspection Assistant. Be flexible. Test, learn, and adjust. That’s the muscle you’re building here.

Jenn: Week 3: Run side-by-side, where AI suggests and humans approve. You could buy a ChatGPT license for your tech and have them look up a code there for quality and timeliness. Quick note: When using tools like ChatGPT, especially for manufacturer specs or code, always double-check sources. These tools are helpful but not infallible. That’s why human oversight matters. You could test Inspection Assistant-powered inspections against traditional Inspect Point inspections. Or if some techs are still using pen and paper, even better. Even if it’s just a small test to start, like one inspection a week. Building the muscle and getting used to the idea will start to unlock other opportunities.

Pat: Week 4: Time to review results. Compare results: How much time did the tools save you? Were there processes or human tollgates that needed to be ironed out? Are there other tools that may be better suited to the pain point you’re trying to solve? Pro tip: You can use AI to help answer all of these questions.

Jenn: See where you’re winning, where it could improve, and adapt. The key with all of these tests is to remain patient and keep testing and learning.

Pat: There’s your quick 30-day blueprint to getting started with one AI-powered workflow. Real simple. Pick one workflow or pain point. Map the current process. Run it both ways. Measure. Adapt. Repeat. Let us know what tests you’re running, where you’re seeing success, and where you’re hitting roadblocks. We love hearing the stories and learning together.

Jenn: We’re also happy to help with any questions or ideas you might be working through. We’d love to hear what you’re testing. What’s working, what’s not.

Pat: Next week, we’ll turn these early wins into a business case: how to get to an ROI, manage change, and beat out the competition. See you in Episode 6: The Business Case, ROI, Compliance, and Customer Experience.