Industry experts Brian Haines and Edward Wagoner discuss why facility managers should view AI as a powerful new "staff member" rather than a threat. They explore practical ways to use AI tools to automate complex tasks and "fast-forward" to critical data-driven answers.
In this episode, host Edward Wagoner sits down with global influencer Brian Haines to demystify artificial intelligence for the facility management community. Together they discuss:
This episode is sponsored by TMA Systems! Discover more at https://www.tmasystems.com/ifmapodcast
Timestamps:
Brian Haines: [00:00:00] AI is something that I think is probably one of the most life-changing capabilities that's ever come to fm, right? I believe it's not gonna replace, take our jobs away. It's gonna make us better.
Host: Welcome to Connected fm, a podcast connecting you to the latest insights, tools, and resources to help you succeed in facility management. This podcast is brought to you by ifma, the leading professional association for facility managers. If you are ready to grow your network and advance in your career, go to ifma.org to get started.
In today's episode, host Edward Wagner sits down with IFMA Global influencer. Brian Haynes, the Vice President of Strategy for Asset Centric at kahua to demystify artificial intelligence for facility managers. Together, they discussed practical steps for FMS to get started. How AI agents can monitor building [00:01:00] control systems and solve problems.
Why it's critical to verify AI generated work and what to expect as AI evolves. Now, let's get into it.
Prevent operational inefficiencies, the loss of the critical institutional knowledge and more. Now let's get into it.
Edward Wagoner: Hi everybody and welcome to Connected fm. My name is Edward Wagoner, and we're coming to you live from World Workplace in Minneapolis. I'm here with my good friend and fellow global influencer, Brian Haines, welcome Brian.
Brian Haines: Thanks, Eddie.
And thanks for stepping in here and helping me with this today. It's
Edward Wagoner: gonna be absolutely always fun as, as
Brian Haines: usual,
Edward Wagoner: always happy to, to talk, for people to know. Brian and I go back many, many, many years probably when technology was first being introduced into real estate and facility management.
Yes. And I can think about some of those early conversations around work order [00:02:00] systems Yeah. And how people needed to approach that. And if I think back over my career and your career also for facility management, it's been a constant. Here's what other people are doing. Here's new technologies. Almost like a, oh my goodness, I've got all this going on and now it is telling me there's something you I need to do.
You're telling me there's a new technology and now everybody's saying you need to learn ai, but it's also going to take your job.
Brian Haines: Right?
Edward Wagoner: So let's set some of that fear aside a little bit. Just for facility managers. No, no tech talk. What is ai? Why AI and why should facility managers embrace it now?
Brian Haines: That's, that's a great question, Eddie.
And, you know, recently I love this topic and I love talking about it quite a bit. I had kind of an aha moment not so long ago. AI's everywhere we hear people talk about it, I started using products like chat GTP to sort of help in my daily workflow tasks. [00:03:00] And it's been kind of revolutionary. You know, I'm not the youngest guy in the room anymore, you know, I'm bas basically.
Probably the most senior person in most of the conversations that I'm in. That's what happens when you get to be the age that I am. So the interesting thing is, is that I've never been someone who's been afraid to just try new stuff, right? Try new technology. And over the course of my 30 year career in FM, I've seen significant revolutions and evolutions in technology.
You know, going from drawings to CAD to bim. To mobile devices, all kinds of things, connected devices. AI is something that I think is probably one of the most life-changing capabilities that's ever come to fm, right? I believe it's not gonna replace, take our jobs away. It's gonna make us better.
I think of AI as like, suddenly I get to hire some new people on my staff. They just happen to be ai. And I'll, I'll tell you the, the, the aha moment. This might sound kind of mundane. Early in my career [00:04:00] I was directing product management for a lease accounting system. And if you've ever been involved in the development of a lease accounting system, the math is, complex.
We had a PhD on staff. We used one of the largest global SER service providers, their lease experts. It took us. Months and, and about a year and a half to write a lease accounting system because the, the calculations are so complex and I'll never forget that because I remember that as being a very difficult assignment, but being really excited about the outcome.
I took the most complicated scenario for a lease I threw out at all kinds of things. I'm like moving into a space. I've got free month. I'm moving in on the 17th. I wanna prorate the first month. I get all this complicated stuff and I just spoke that into Chachi tp and I asked it to produce a spreadsheet of my rent payments over the next five years for a five year lease.
It did it in one minute [00:05:00] with an amazing high degree of accuracy. I checked all the math, everything was perfect. It took into account all of my options, my bumps, everything. And that had taken a team of people just 20 years ago, a year and a half to do. And I did it literally by just asking. And so that made me think, what are the questions that FMS can start asking to get help so that we can expedite increase?
Not not only just get better at our jobs, but also elevate how we're viewed in our profession. So that's the sort of why, to me, it's really, really amazing. I don't think it's something that people should be afraid of. I think it's something that people should embrace, especially our FM community.
Edward Wagoner: I'll actually admit I was a little fearful of , embracing ai, specifically around writing some of the posts.
Said refine it. Like there's no way that's ever gonna mimic my voice. But it came back with some suggestions where I had to admit, wow, that's actually [00:06:00] really good. Yeah.
It didn't replace me. It actually made me better.
Brian Haines: Yes.
Edward Wagoner: So from an experience I can remember the resisting.
Brian Haines: Mm-hmm.
Edward Wagoner: And then trying it, then realizing, yeah, I can't add this as a part of my toolkit, it's not replacing me. Right. The, the, the user of the tools. It's just one more tool. So, so as I think about that.
With everything that FMS have coming at them right now. You know, I want a safe workplace. I want, you know, flexibility in my workplace. Our, our organizations are still saying Do more faster. Right. And cheaper. With all of that, that's coming at fms, why should fms take AI seriously right now at this moment in time?
Brian Haines: Yeah, because we all need backup. Most of the organizations that I, I talk to right now. They're not in heavy hiring mode. I don't see it. I don't see a lot of people bringing a lot of FMS on staff. We we're, we're challenged to do more with more complex real estate [00:07:00] portfolios than we've ever had.
We've got, I, I could go on about technology and I won't, but connected devices, connected systems, connected buildings, smarter buildings, more complex usage patterns with things like return to work and hybrid working, like people don't use buildings. The way they used to. It used to be everybody just showed up.
You worked all day, you went home. Now it's highly chaotic, very difficult to measure. And when you're challenged with how your workplace is performing as, as an fm you, you don't, you don't have the afforded time to go and write a report. I remember earlier in my career, I was a space analyst. My boss would say, Hey, I need a building renewal report in.
In other words, I need a calculation on. All of our buildings on campus, how much does it cost to operate those? And so I could go to the Board of Regents and ask for budget so I can address all of our deferred maintenance. It would take me, and she would understand that it would take me six months to come back with that report.
[00:08:00] That's not accepted anymore. Here's the assignment. I need the answer on Wednesday. So we're all asked to produce more with backup, and I'm talking like numbers. All quite accurate. Everything organized and prioritized by, let's say Wednesday. That same kind of request. It's a little bit like the way we all watch things.
I like to say attention deficit because you used to be able to sit down and watch a training video for hours and get through it. Now we all just wanna fast forward, fast forward, fast forward. Everybody wants to fast forward to the answer. AI in my opinion, helps you to fast forward to the answer.
Edward Wagoner: So I love that analogy to fast forward to the answer, but
as you were talking, I thought about my, my daddy, so he's 85.
Brian Haines: Mm-hmm.
Edward Wagoner: Never finished college. I was a CIO for almost 30 years. And I would come home with something new about technology and the man would actually be conversant,
Brian Haines: right.
Edward Wagoner: And I asked him, how do you keep up with all this? And he [00:09:00] showed me that he actually read the four dummy books.
Brian Haines: Oh.
Edward Wagoner: He wouldn't tell people, but he, he had pride. He didn't want people to know. He didn't know, but he went and found the the four dummies, if you will. Right. And I was always shocked. And he's like, well, but it enabled me to talk to you about it. So what's the four dummies for fms? If they do wanna fast forward it,
Brian Haines: right.
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Edward Wagoner: How can they get some information to understand it better without, yep. You know, none of us wanna expose that. I don't know. Something about one of the biggest topics of the day. So what would you advise for FMS to do to get up to speed on. What AI can do for them. Sure. And maybe even play with some of Yeah, that's great.
Without of causing themselves problems.
Brian Haines: That's a great question because there's, there's two sort of AI paths, if you will. There's one that's personal development, helping you also achieve your personal goals. That's sort of one part there. There's also the AI that's embedded in building control systems, things that are, it's called agentic ai, essentially things that are agents that are acting on our behalf.
And so. I sort of divide those two out. [00:11:00] So my first point or your your four dummies points, I'm gonna say absolutely know what you're trying to achieve before you try it. So if you're gonna, let's say you've never tried Chad t tp, you've never tried copilot or the hundreds of other AI tools out there. Get a log in, think about what you want to ask it and ask it.
It's not Google. It's a lot more than that. It's not just about Googling and getting popular responses about. It learns your questions over time. I had a colleague who used it for about six months doing all kinds of work to optimize some digital work that he was doing, and he asked it to summarize the last six months of his conversations in his own voice, and it did it.
So it's learning and it learns. So that's a big difference between Googling. So one is try it. And pick a few goals and, and to, and to do it. Understand two, number two is that it's learning, it's gonna get better over time. Number three is in lockstep with [00:12:00] number two, and that is you always have to be the adult in the room.
Anytime you're using AI type technologies, even if it's for your own personal use or through your business. You should understand that it's our responsibility as humans to check the work. You know, it's like your teacher always telling you to check the work right in school, do it because it's learning.
AI is really still in its infancy in terms of its learning. And sometimes the, the answer comes out and it's not quite right or it interpreted what you asked in a way that you may not have thought. So that's, that's an important point. As well. So that's three. Number four is , don't be afraid of this because there's nothing you're going to do to stop it.
It's coming. It's here. It's in everything. I guarantee every single one of these vendors out here, it doesn't matter what they're in or what they're doing, they have a strategy and they're implementing it some way. I've been involved in a software development project [00:13:00] recently. Where we had an AI tool write software in two weeks that it took us a year and a half to write.
We have to check that work. We have to always make sure that we don't just assume that what we're getting is right for now and hopefully into the very, very distant future. Having humans in the room to check the work and also to make sure that it's ethically bound right and, and has a fence around it so that the answers you're getting are sound.
Edward Wagoner: So I would say to fms listening to us, there are the AI four Dummies book. I know it because I actually got it in Reddit and you'll hear a lot of us IT people throw out terms like agentic and large language models. That's a really good way just to get some base understanding of what we're talking about so that you can be more articulate.
The second thing that I think that every FM should do, and if you're at World Workplace. Go to every one of the technology vendors that have an exhibition booth here in the exhibit hall and ask them about their ai, [00:14:00] what's their strategy, what's in their product? You don't have to know anything about it.
Let them explain to you how they're thinking, and you'll get some learnings out of that. And then the third thing that I think everybody could do is go ask your organizational CIO. And I say that because in addition to running with fms, I run with CIOs. They're all thinking about this in their organizations.
They know where a lot of your data is, that you may not, and I can promise you, your CIOs would love to have that question from you. So those are some steps you can take right now. But Brian, let's talk about, and this is where we're gonna get out over our skis. Mm-hmm. What's next? Yeah. A year from now, if we were to come back and if the audiences here with us were to come back and join us.
What would you predict they're going to see a year from now that they should be thinking about, and we've done this before, we're never 100% perfect, but I'm shocked as I've gone back and looked at some of our episodes over the years and [00:15:00] conversations how close a lot of your predictions have come. To the reality.
So put you on the spot one more time. Yeah. Predict what we're gonna see the next year or two.
Brian Haines: Yeah. So the life of an AI presentation when you, when you do these a lot is actually fairly short because it's developing so quickly. A year ago, I probably would've been talking quite a bit about natural language interfaces to data and being able to just speak the way humans speak and get answers back in a way that humans understand.
I think it's sort of like when you look at a really beautiful dashboard for any of the products out here. And you look at it and you go, what? What's it actually really telling me? And it's kind of hard to say. There's lots of, lots of lines and diagrams and bubble charts and all sorts of things, but what it's, what's it really trying to tell me?
So that type of AI will tell you what you're looking at. And I, that was a, that was a year ago. Then we started to look at something called Gen ai. And Gen AI started to produce sort of like output, like images. If, if you've ever tried a product like Jet GTP, [00:16:00] you're, you could be like, you could, you could go in there and say, here's a picture of my dog.
Make my dog look like a cartoon. And it's gonna do that. Right? So that's a gen, that's a, that's the gen ai. Then there's something called agentic ai, and it's new, well, it's fairly new.
People who have been at this know this for quite a while. But agentic AI is essentially agents, in other words, ai, little AI capabilities that learn and are autonomous and they start understanding and solving problems and recommending solutions to those problems without human inter input. So you'll see ag agentic ai, for instance, in building control systems.
They're looking at how the building control system is, is operating based upon millions of data points and making. Physical re or, you know, recommendations to you based upon what it thinks it's going to happen. And it learns over time. So these agents, when combined start acting a bit more autonomously.
And I think [00:17:00] it's an interesting thing. I think we're gonna see a lot more of that that don't require a human interaction. But I will say even with Agentic ai, you still need to have an adult in the room. You still need to check the work of the agents. Many of you see this when you're, when you're talking to a chat bot.
Now chatbot seems to be just sort of responding to questions based upon a list of recorded questions. Now, it can in, it can understand what you're saying. It can infer it can do a lot of things. And, and it can also suggest further May now that you asked this one question, don't you have this other question you wanna have answered as well, tho those are agents that we're seeing that take off.
Really quickly, you're gonna see us talk about that a lot over the next year.
Edward Wagoner: If you're listening to us on the Connected FM podcast we'll be in Anaheim. Join us in person. We'll put Brian on the spot, and we'll ask him how those predictions came true.
A lot of them will, but I guarantee you we're gonna have some new things to talk about, some new [00:18:00] AI opportunities. So stay connected through the podcast. And we'll look forward to seeing many of you in Anaheim at World Workplace 26. Thank you, Brian.
Brian Haines: Thank you, Eddie.
As always,
Host: thanks for tuning into the Connected FM podcast. If you enjoyed today's episode, please take a moment to rate and review the show because it really helps us reach more listeners just like you. And don't forget to hit the subscribe button so you never miss an episode. See you next time.