Since ChatGPT showed up a few years back, it feels like AI is the topic on everyone’s mind. Including mine. 

As a recovering AI skeptic, I thought I would share where I’ve landed, not as an expert, but as a heavy daily user of the technology, and as the leader of a company that has invested in AI on a lot of different fronts. 

Our corner of the world, facility and infrastructure asset management, tends to be a bit of a laggard when it comes to technology adoption. We were late to CMMS. We were late to mobile. We were late to the cloud. I would rather we weren’t late to this one. 

The idea for this series really took off after the APPA National Conference in D.C. this past July. I was asked to join a panel of university senior leaders to talk about AI from a business partner perspective. I enjoyed the conversation, but what stuck with me was what happened afterwards. Attendee after attendee came up to share thoughts and ideas, and almost every one of them landed on the same question, “Where should I get started?” 

I recognize there are organizations much farther along than we are. But I can tell you what we’ve tried, and what we’ve learned the hard way. 

Here’s one we learned the hard way. At least, it looked that way at the time.  As part of our early AI trials, we were looking for a way to prospect online. We tried some initial prompts to help us identify potential clients and pull their contact information so we could add them to our CRM. At the time, ChatGPT simply couldn’t do it. So we licensed a fairly expensive piece of software that specialized in that one thing, and we’re still paying for it. 

That was a sales problem rather than a facilities one, but the pattern holds everywhere. Because here’s what happened next: AI got better. What it couldn’t do then, it can do now, straight out of the box. More on how that works later in this series. 

The real lesson: a no today often means not yet. If you hit a roadblock, park the idea and come back to it as things evolve. 

AI is not a panacea. But it shouldn’t be ignored either. The longer you wait, the more catching up you’ll have to do, not just against your peers, but against the expectations your board and your funders are already forming. 

Next week I’ll start with why I was an AI skeptic in the early days, and what changed my mind. If I’m being honest, I don’t know exactly where this series is going to take me. I have a general idea about the tools, the data underneath them, and the people problem nobody wants to talk about, but I expect new ideas will pop up as I write and change course. 

Let’s see where these next few weeks take us, shall we!