Businesses are buying AI but not teaching employees how to use it. That’s dangerous!

If a fire brigade buys software like FireMapper the promise is obvious straight away. You get shared maps, better situational awareness, real-time collaboration, critical incident information in one place and the ability to keep working even when internet coverage is poor. On paper that sounds like a smart operational move and in the right hands it is. FireMapper is built around helping emergency services capture, manage and distribute critical information at incidents so crews and officers can work from the same picture instead of a patchwork of assumptions. 

But here’s the part that matters. Just buying the software does not make the brigade safer. It does not improve decision making on its own and it definitely does not magically create a more capable crew. If the officers don’t use it, if they don’t champion it, if they don’t train firefighters on it and if they don’t make it part of how incidents are actually managed in the field, then all they’ve really done is buy an expensive tool that sits off to the side while people keep working the old way drawing on the side of a truck with a whiteboard marker.

That’s exactly what most businesses are doing with AI right now. They’re buying the tools and mistaking the purchase for the transformation. They’re signing off on subscriptions, rolling out licences and telling themselves they’re now an AI-enabled business while the staff who are supposed to use the thing are left to poke around and figure it out on their own. In a recent article in The AI Journal, the problem is pretty clear. Companies are spending heavily on AI, executives say AI skills are strategically important and yet only a small minority have embedded AI into core business processes in a repeatable measurable way. Training budgets are weak, formal training is rare and most organisations are relying on ad hoc learning instead of building real capability.

That should sound ridiculous to anyone who has spent time around emergency services. Imagine a station officer saying, “We’ve rolled out a new mapping platform across the brigade so we’re sorted now,” while half the officers still brief off paper maps, some firefighters have never opened the app, nobody has run scenarios on it and crews are expected to work it out in the middle of a fast-moving fire. No sensible person would call that an operational improvement. They’d call it a risk. Yet in business this same nonsense gets “sold” as innovation every day of the week.

The truth is that new capability only becomes real when the people responsible for outcomes are trained to use it properly under normal conditions before pressure hits. That’s how firefighting works. If you want crews using a new tool safely on the fireground, you don’t start with a glossy vendor demo and a login email. You start with officers learning it first so they can lead from the front. Then you run drills on quiet nights. You use it in training scenarios. You let people make mistakes while the stakes are low. You build confidence through repetition. Then when the pressure is on and the job gets messy, people don’t have to stop and think about whether they trust the tool or where to find the right layer or how to share the information. They already know. That familiarity is what turns a new system into an operational advantage.

You need to think about AI exactly the same way. If your team is going to use AI well, safely and consistently, everyone has to be involved. Not just the leadership team at the top and not just the keen early adopters in the corner. The AI Journal points out that middle managers are one of the biggest weak spots in organisational AI adoption with many having little responsibility for developing AI capability in their teams. That’s a serious problem because in every organisation it’s all of the frontline leaders who determine whether a new way of working becomes normal practice or just another abandoned initiative.

This is why I mentioned FireMapper. A brigade doesn’t become safer just by having access to a shared map. It becomes safer when officers and firefighters actually use the same map in the same way, with the same expectations and the same understanding of what they’re looking at. Shared situational awareness is what improves safety. Shared understanding is what improves decisions. If one crew is working off the live incident picture and another is relying on memory from twenty minutes ago, you don’t have coordination. You have drift. On a fireground that can get dangerous quickly. In a business, it creates a different kind of danger where one person is using AI intelligently, another is feeding sensitive information into tools they don’t understand and everyone else is pretending the whole thing is under control.

That governance gap is another issue that businesses should be taking seriously. It isn’t just that people aren’t being trained to get more value from AI. They also aren’t being trained well enough to manage the risks around privacy, security, bias and responsible use. Executives say these things matter but very few organisations have comprehensive enforced systems in place. That means workers are being handed powerful tools without enough practical guidance on how not to create problems with them. In firefighting terms that’s like handing out new gear without proper safety training and hoping common sense will cover the gaps. It won’t.

So how would a firefighter approach AI? It would start with officers using the tool first and using it visibly. It would mean 

• leaders explaining why the new system matters, where it fits and what good use looks like in the field. 

• structured training instead of self-directed wandering.

• running practical scenarios instead of relying on theory. 

• encouraging use during real operations so the habit actually forms. 

• After-Action Reviews after use so crews can ask what worked, what didn’t and what needs tightening before next time. 

• making sure everyone is working from the same map. 

That’s what we would do and that’s what will make AI adoption in business less chaotic and more useful to you.

The mistake businesses are making is treating AI like a procurement decision when it’s really a training and leadership issue. Yes, the tools matter. Yes, the software keeps improving. But the value does not come from owning access to the tool. The value comes from building a workforce that knows how to use it well, where to trust it, where to check it and how to apply it consistently in real work. 

If you want a simple way to think about it, here it is. Buying AI without training your people is like issuing every truck in the brigade a digital map that no one of the crews knows how to open. You might still get through some jobs on experience and improvisation but when conditions turn bad and speed matters, the brigade that has trained together to build their map skills will be safer and more effective than the one that just bought the software and hoped for the best.

That’s where most businesses are right now. You’ve bought the map. You haven’t trained the brigade. If you want help doing this the right way inside your business, that’s exactly the sort of work I do in the AI-Powered Authority Multiplier Mastermind. We don’t just talk about the cool gear. We train the crew to use it properly before the AI fire gets into your business.