Episode 25 AI Agents and the Future of Physical Security with Don Morron

Welcome to Executive Checkpoint, the live podcast for security professionals. Each week, we explore industry trends, challenges, and insights with leading experts. This is your insider access to the minds driving change in our industry.

All right, here we go. Welcome to Executive Checkpoint, where security professionals gather insight to navigate the ever-evolving world of physical and cybersecurity. I'm your host, Tino Urbina, and today I have the great honor to have, uh, Don Moran, CEO of Highland Tech, a host and host of the AI Psych Today podcast. And Don comes with 15 years of security technology industry experience, and he's gonna share not only his journey, but how AI and emerging techs are transforming our industry. So Don, today has been an interesting day to catch up to do this. Flights got canceled. In my case, I'm doing this in the airport, and so glad that you had the flexibility to jump in and get this done on the day. So appreciate you. Welcome to the show.

Yeah, Tino, glad to be here. Hey, you gotta rip the pod whenever you get a chance, man. So it's hard to align calendars. So that's all good. We're here and we're gonna rock it.

Especially with a busy schedule like, seem like you have. I, I was just looking at all the awards that you got this year. Emerging Leader Under 40, Top 4, uh, Thought Leaders, um, Top 40 Thought Leaders, uh, SBN Security Innovation, and Marquis Who's Who. How do you find time, Don?

Uh, yeah, yeah, I don't. I just do, right? I think a lot of it is, um, especially with the proliferation of AI we've seen for several years now, although it's been around since the '50s, really since GenAI hit the streets and ChatGPT got super popular about 2 and a half years ago, maybe 2 years ago. Um, it's, you know, you just kind of just do some days, right? And I think what happens Is it starts to form into something that's more clear and that's all that happens, right? I've been fortunate enough to have a great community in the security industry that's recognized that some of the things I've been doing and really talking about bleeding edge stuff that in other— and really what is within an otherwise very risk-averse industry.

Yeah.

So it doesn't do me any favors by doing that because it's not like these things are flying off the shelves in the security industry. Um, but, uh, they're doing well in other industries. But I think what it does do is just highlights the fact that, um, AI agents are, uh, by far like the biggest transformational tech that we're seeing, uh, that have the biggest impact across really any industry. But, you know, obviously especially ours where we protect people, property, and profits. And there's just not a lot of people talking about it a lot, right? A lot of times it gets, you know, um, thrown into the shadows and it's like, well, you know, We don't really talk about AI, we talk about solving problems. Like, obviously, you know, that's like anything else. That's how you apply tech to solve problems. But, you know, from my perspective, uh, there needs to be some voice to talk about this so that way as an industry we're not just slow to adopt because we are risk-averse, um, or we're playing it safe.

Mm-hmm.

I don't know that this is the right time to do that, right? If we're at industrial revolution, it's— we need some people to push the envelope and I didn't necessarily assume that position. It just kind of happened with the podcast. Uh, and I don't know that I even have that position, but I guess it's formulated to be that way. And I'm just grateful to be here and, and grateful to have, uh, amazing talented peers that have recognized that.

That's fantastic. And you know what, to your point, I think because every— the industry tends to be cautious and likes to assure outcomes is, is kind of slow, it's too slow on implementing some of this new tech that invariably is taking over other industries and it's gonna impact ours no matter what we do. So why not, you know, be part of it? But let me ask you, earlier in your career, how were you always wanting to be in security? Was this like so many people I talked to, was it an accident that you ended up in security or what's your story there?

Yeah, I think that everybody I talk to is the same way. They don't know this industry exists a lot of times. Yeah. And so, you know, I— one of my undergrad degrees was criminal justice, and I remember they had a sheet that they gave us that says, here's 101 jobs you can get. And I don't remember any of them talking about this industry, right? And so I think that, uh, you know, it's funny, but it's also like, hey, the industry should do a lot better, um, uh, by, uh, by marketing themselves to universities and letting them know that. And they— I think they definitely have since SIA has done such a great job with that with Accelerize and programs like FAST for technicians. So, you know, they're doing a good job. And it's hard to get to all the universities, but punchline is I fell into it because it was recommended to me. I went to a trade show, met ADT, and they recommended me to Tyco, which is their commercial security division, which I went and worked for and moved from North Carolina to New York. Where I worked for them, uh, and then transferred to West Palm Beach, also with Tyco at the time that later got acquired by Johnson Controls. Um, and then went and found a great job and career at Brevo. I was there for in the range of about 7 years. Um, and then my last stint before I became an entrepreneur was, uh, at Honeywell. And so, yeah, man, it's, um, it— that's how it started. I think like most people, they just kind of fall into it and they don't realize it's there, but it's a great Great community. It's done very well for me. Um, I know it's done very well for my— for friends and close colleagues. So it's a great space to be.

Yeah, I tell you what, I think, um, we definitely need more people. We need young people. We need tradesmen installation groups. That experience is kind of moving away. So no, 100% I agree. You know, it sounds to me that your experience kind of touches a couple portions of the industry from manufacturing to integration, and now you're in the consultancy side. Is that kind of the basis of your company today?

No. So we're an engineering firm. So what we do is we build AI agents to automate business workflows, or more, or a little bit more specifically, we solve for repetitive and mundane tasks, mostly in the operational efficiency side. Like anything around the operations side, we tend to tackle. And so I don't consult today. I'll likely turn up the heat on that after, you know, maybe, who knows. I think about it almost every day. I just don't personally like to trade my time for money to say like, oh, I'm gonna consult and get paid something an hour. I'm more of like, let's go solve big problems. And that's where what we're doing on the AI agent side is very tough. It's very tough. It's not easy. I think anyone that builds them, they would know that. You know, one of the things we've seen is we can get down to the demo side where it's like flawless, like we can get that product working and it's like what we wanted and what the customer wanted. But what we realized too is that in production, when you turn it live, that there's a lot of challenges that are not, that have nothing to do with us, you know, but that's not what, you know, the customers want to hear, of course, you know, but what we, when we've seen them turn into live, there's all kinds of things, but that's very. Normal for the AI agent space. And, but the way we've modeled our process has allowed us to, you know, foresee a lot of things that we could run into to set proper expectations to customers. And, yeah, it's go— every month, every project we do, we learn something from it. We improve our process. So we're, we're really growing like a fine wine here.

Nice.

And I think by the end of the year, we're gonna be super sharp, and that would allow me to I think go to the companies and charge. If I was going to consult, charge at a rate that I think would be worth my time. But today it's you know it's kind of security sales leader turned AI founder entrepreneur kind of guy. So but really the practicality is so much more important even than the education side. Like I have a no code certificate from MIT machine learning and AI, and that was cool. And then just being really How can I say, intentional about learning about this space for a couple years now. You know, I believe, and this is a great example for anyone listening, if you ever want to change your career, that I believe that the effort that you put in within that, within whatever amount of time, does not equal the same effort as someone else, right? So I think about, you know, me going toe-to-toe with anyone that's been AI community for a decade. And I could think like, how could I ever compete with that? Well, my 2 years isn't your 10 years, right? I don't know what they did for the last 10 years, but this is stuff where I've had sleepless nights, you know, thinking about, reading about, you know, this is my life. And so, you know, I think about it to say, show me a lot. There's a couple people, but show me people that are in the security industry that have turned into the AI community and have brought that back into the security industry. Usually you're gonna find people in the AI community that will come, seldomly come to the security industry. You know, they're usually going to the manufacturer side, but to be able to bring it down to really small, medium businesses, um, and, and forms and contexts that they can understand, you know, it just, not to my knowledge, just doesn't exist. So, which what we do as an AI automation agency, um, what we focus on.

Yep. Yeah. And it's only changing. It's gonna be, you know, it's gonna change even more just because agentic AI is coming in. And then of course, the, the speed of computing is evolving with, you know, quantum computers. In fact, I was, uh, watching this, uh, uh, conversation that describes how now diamonds, specifically blue diamonds, are the key for faster computing and cheaper than the quantum, you know, that we're building in low, low temperatures. And that's getting a little too nerdy, right, for some people listening. But if and when that takes place, everything, you know, everything that we know as an industry is just gonna, you know, times 10 go up and whatnot. Let me ask you a question. I feel that our industry and many implementing AI needs to reimagine the processes, not just slap AI in the sequence of operation, right? So how do you, how do you explain that to a client? And, you know, focusing maybe a little bit, like you said, midsize security companies to adopt something that requires them to rethink their processes and potentially, you know, not potentially implement something that is relatively new and really drive it, right? Test it and drive it and improve it.

Yeah. It's funny, I just had a conversation yesterday. I'm on the advisory board for University of North Georgia where they have an AI program. And, you know, and I've heard this before, but one of the discussions that we were having was when you look at this AI adoption, it's like 2 flavors. One is how do we become more efficient? And the other one is how do we do something new that we couldn't have done before, right? So 2 trains of thoughts. I think the easiest approach is find your efficiencies first because it helps people learn the application of and the experience of before they jump into something brand new. Doesn't mean that they can't, they can do whatever they want. I just think over here there's low-hanging fruit to get money back on return on investment because we know there's inefficiencies, right?

Right.

So I can calculate that. I could say, if I could remove that mundane task from my team's load, how much time do I get back? Okay, spend the money, get the money. All right, next, you know. And so I think through that experience, it affords people the opportunity to get confidence so that way they can be creative And they can start to think about new ways to apply it. And really, it's in those new ways to apply it that is probably the highest value things, right? I mean, creativity is what we're really good at as people. And so while AI isn't necessarily creating quite yet, I think the goal would be is to get over to this creative spot as soon as possible. And I think it needs to start with just the basics. The basics is Identifying what are repetitive mundane tasks. Like I did an AI 101 Small Business Success Series. I'd presented in front of like 80 or so people. And in that I provided frameworks for helping people on how to identify repetitive tasks. But one of the ones that I've seen in practice is they can take 2 approaches. And I try to, if you ever hear me talk, I try to get down to 2 approaches to make people easy decisions, right?

Right.

Sometimes it's one, but then we don't live in an absolute world either. And so one approach is you're generalized where you're like, hey, just tell me the use cases. What are the use cases? And I don't like that approach because people aren't working to solve their own problems. Like meaning, okay, let's say one approach is automating invoices or bill collections. Okay.

Right.

Well, maybe that's a problem, but maybe that's not their most pressing problems right now. Like meaning we can solve it But like the problem that we're solving isn't that vast. And what it does is it starts to shut down, like I would call the creative juices, you know what I mean? Where it keeps them from actually thinking deeply. And so the other route is they go specific where they sit amongst their peers to really figure out maybe over the course of 1 to 2 weeks what those repetitive mundane tasks are, list them, work to prioritize them, draw out the workflow diagram so they understand what those processes are. And then they build towards that because that is something they could say, wow, we've been having this problem daily. It's an issue. It really hits home for the company rather than them fitting into a general box. And so that's where people need to, I think, need to focus on the most right now. And it's all practical. Like none of this is, uh, there is some aspects of the technology that can be black boxy, but the way it is today, AI agents is it's mostly just business process automation.

Mm-hmm.

This is what's being applied in business today, like the one that people trust. It's basically business process automation. So if this happens, then this happens, then this happens. And then when we need to give the agent some decision-making, otherwise called agency, then we inject like the large language model on that with a set of instructions, knowledge base tools, stuff like this, right? Um, and so yeah, so that— so we're at a really good place today to automate tons of things. But what we have today that we didn't have a couple years ago, let's say, or really even 6 or 7 months ago because of the reasoning models and more intelligent AI models, is the ability to automate the gray, which you can't do with BPA.

Yeah, right. You know what, it's interesting to me that people like the idea, but when you put it in context with the quick return of investment, let's call it that, or operational efficiencies, Right?

Mm-hmm.

It, it hits home. It's like, I, I don't know if it makes sense to me just yet, but if it can do that, let's, let's move ahead. Now, in the security segment, of course, it's, it's a little different because sounds to me there's a balance between trust, compliance, ethical considerations, and, you know, the AI security cyber. So it, it becomes a little more convoluted. But to your point, introducing this from the operational side first, So it can evolve within an organization, seems to be the— what would be your recommendation for someone that is looking to bring AI to their organization, small or large?

I would— what I think about a lot is mindset. You know, you think about the security adoption curve. If the audience hasn't heard this, basically it's something that's kind of this tried and true, um, uh, thought, or I don't know how to call it, a thinking framework, if you will, where it shows how people accept technology as it comes out, right? And we've gone through many industrial revolutions. You've got the naysayers and you got the people on the other side are like, I'll just, you know, take my money, right? And that spectrum, um, is very defining, like meaning that I think people need to self-reflect some to realize where they're at and then realize that AI is this, whereas a is absolutely one of the largest technological advances in human— that we know in human history, right? So, and we've learned what saying no to the calculator was, or the internet, or, you know, the cellular, or we learned what it was like to say no to farming equipment, right? Or industrial manufacturing, right?

Yeah.

Or this, or this, or the steam era, right? So we, we don't— humans do not overcome technology advances. Technology drives innovation, and innovation rules the world. And I think that people fight against that. I think it's foolish. I think it's a waste of energy. I think that their best bet is— I mean, look at it. You've got people, you got trillions of dollars, you got a new internet being created. There's more wealth generation in one company, probably. Yeah, one company, AI company, than the entire security industry. But yet we want to stand on the shoulders of giants. We can't, right? So I think we need to be a little bit more humble to the reality that we can't drive the bus. We not really, right? We can try to, but ultimately they're going to, because what's going to happen that most applications consume the AI API most of the time when they want to use generative AI, they'll get down to small language models and they'll have use cases where, you know, cameras will identify more than people and objects on the edge to have edge use cases. And that's all great, but really like big intelligence will likely continue to operate from a cloud perspective and being consumed by an API where their, what they call their topmost best models called foundation models will live. And so what that means is to make those, you have such a long tail of investment and technology advancement that's been made by companies that nobody in the security industry can afford to build. That's it. And so what happens is we end up consuming it.

Right.

So it means that basically our post-training, 'cause these are pre-trained models, are really up to us. And that is not necessarily, that's not an even playing field. So there is an aspect where we can, each company can really take advantage of this. But at its foundation, we're not driving the bus. And so I think like when people push back in the security industry, where I found a lot of mentality is, is, uh, very few are the innovators, few are early adopters. There's a good chunk in the early majority, and the early majority of the technology adoption curve are people that usually need proof, uh, about it, which is fine and reasonable. But I think if anyone that's on the late majority or the Laggard side, they should— they really should self-reflect and look to adjust, or you'll just be behind, you know. And I know that people hear that a lot. Sometimes it seems a little abrasive, but I just don't think it's— we've learned from history, doesn't repeat, but it does rhyme. And we know how this rhyme is going to go. Uh, and if you don't think it's going to go, uh, how you think, how people are saying it, then you must be the smartest person in the world and we should come work for you. But I just, yeah, I mean, and who are security people to say this, right? Most people in security are ex-cops, military. What do they know? No offense, but what do they know about data science, right? And what's happened in the AI community? And so I think the biggest thing is just to embrace it, embrace it with caution. Yes, you know, get your validations, do proof of concepts or minimally viable product runs, You know, start off building for efficiencies so you can get familiar with how these projects go. There's a lot of off-the-shelf stuff people can buy, and you could run those through your IT security team like you would any other product, you know, and then allow the creativity juices to flow so that you can solve big, even bigger stuff. So that'd be my response there.

And to your point, Bring an expert, right?

Mm-hmm.

I understand that if your background does not meet the need of implementation for something like this, if you understand the benefit in the short-term and long-term, right, of implementing this technology from operations and forward, it's gonna be key. Well, let me ask you, You're at the point of your career, then you're launching this business. And can you think back when you started your career, would you ever guess that you were going to be doing this? It was not even a—

I mean, I've always had some interest in doing entrepreneurship, whether it was fractional sales leadership or something around sales. But, you know, Yeah, I mean, one day I used ChatGPT and I was like, oh my gosh, this is amazing. Like, what is this? And I went on a pursuit to figure out what was going on. And, um, you know, and so no, I would never thought I would have gotten into this. Um, I mean, I knew about AI like existing but never really paid attention because it was, it was out of reach for majority of people, right? You want to buy, um, AI automation services for your company, you better have a lot of money. You know, but now that's been democratized, and that's amazing, right? Honestly, there's also a lot of concerns, but that's more some stuff I think is is maybe for a different day. But or we could talk about it today. But hey, listen, I never I never thought I would extend this another hour.

Absolutely. Yeah. Well, Dan, let me ask you a question. What will be your advice to yourself? Let me change the question when you started your career.

My career in the security industry?

Sure.

Um, your network—

You know, that younger self.

Yeah, my— your network is your net worth. That's what I would have told myself. I don't think when I was younger I took early stage— most of it I did not take advantage of that. I didn't start to build personal brand until probably like 18 months ago. Yeah.

And so I think I can—

that was a huge thing.

Yeah. Well, Don, I mean, it's been a pleasure and, um, unfortunately I have to catch a plane, so—

Sounds good.

But we, we need to extend this and, uh, I'm sure it's a little weird to be in somebody else's podcast. I still— we're still gonna catch up and, and do some more collaboration, but I appreciate your time. I appreciate your flexibility. Um, want to thank everybody, uh, listening to the conversation. Don, uh, absolutely pleasure talking to you. And for the audience, thank you for your time. Stay secure, stay engaged, and we'll see you on the next Check Point.