FROM THE INDUSTRY
puzzle approach lets you build credibility with early wins while maintaining a coherent vision for where the whole thing is headed. It also gives your teams time to adapt. Nobody wakes up one Monday morning to discover their entire workflow has been replaced by a robot. They get a new tool, they learn it, they start to trust it, and then they ask you for more. That is how real adoption works. The gap I see across the industry is not a technology gap. It is a translation gap. The demos are great. The proof- of-concept videos look incredible. But somewhere between the conference stage and the actual operations floor, the signal gets lost. Operators walk away inspired but paralysed, because nobody showed them the version of AI that works with a lean team, an existing tech stack, and a leadership team that wants to see results in quarters, not years. That version exists. It is not as photogenic as the keynote version, but it is the one that actually moves the needle. It starts with the data you have. It solves problems your people already feel. It makes your existing team better instead of smaller. And it builds outward, piece by piece, until one day you look up and realise you have built something that the big carriers spent ten times as much to achieve - because you were never trying to be them. You were trying to be a better version of you. The operators who will define the next decade of this industry are not the ones with the biggest AI budgets. They are the ones who figured out that the puzzle pieces were already on the table. They just needed to dump them out and start building.
assisted diagnostics so they can resolve issues on the first visit instead of the third. We give the CSR a tool that surfaces a customer’s full history and likely intent before they even say hello. We give your dispatch team an optimisation layer that handles the combinatorial math no human brain can do at scale, so they can focus on the judgment calls that require a human brain. You are not shrinking your team. You are multiplying what your team can do. I like to describe deploying AI at an enterprise level like putting a puzzle together. You do not pull one piece out of the box at a time, squint at it, and try to figure out where it goes in isolation. You dump all the pieces out on the table. You see what you are working with. Then you start with the edges, the structure, and build inward, section by section, each cluster connecting to the next. Some pieces will not make sense until you have more of the picture assembled. That is fine. The point is that you can see the full scope of what you are building from the start, even if you are only snapping together one corner at a time. For us, the edge pieces were the data sources we already had and the operational pain points that were costing us the most. Customer Health & Dispatch was the first corner. Technician guidance was the next section. Each one taught us something about our data, our processes, and our people that made the next section easier to assemble. And critically, each one delivered value on its own. You do not have to finish the whole puzzle before you can point to it and say, “look, this is working.” I feel that it matters enormously at smaller organisations where every dollar spent on technology has to justify itself quickly. The
The operators who will define the next decade of this industry are not the ones with the biggest AI budgets.
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MARCH 2026 Volume 48 No.1
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