Brian Walters is the Director of IT at Building Plastics Inc, known as BPI, an employee owned flooring and tile distributor based in Memphis, Tennessee with 13 locations, mostly in the Mid South, and more than 60 years in business. Brian spent years in consulting across government, nonprofit, and commercial clients, and he says that experience taught him that understanding the business makes an IT leader better. He was brought in about a year ago, after a turnover in the C-suite, to transform technology at a company that sees itself as not just a flooring distributor but also an IT company, and he holds all the responsibility of a CIO without the title. He joins the show to talk about wading into AI through governance and education, putting data and security fundamentals first, and why he believes human expertise remains essential as AI use grows. 

Here’s a glimpse of what you’ll learn: 

• Why BPI sees itself as an IT company as well as a flooring distributor
• Why Brian believes understanding the business makes IT leaders better at driving transformation
• How Brian is wading into AI through governance, employee education, and a business reason for every use
• Why a modern ERP rollout became a chance to clean up data, and what garbage in, garbage out means for AI
• Why Brian focused on foundational security, including multi factor authentication, before rolling out AI tools
• Why Brian wants tools that show what employees are doing with AI, as guardrails and not Big Brother
• How an AI written ERP script showed Brian why oversight and expert review still matter
• Why Brian says smart people know you can’t just let AI do everything, from deepfakes to children’s education
  
  

In this episode…

Sponsor for this episode...

This episode is brought to you by CyberLynx.

CyberLynx is a Bethesda managed IT and cybersecurity company. Local techs you know, not a call center. Month-to-month. 24/7 intrusion detection.

We help growing companies with managed IT, help desk, backup and recovery, and a fractional CIO.

Talk to us at https://cyberlynx.com/contact, info@cyberlynx.com, or 301-798-9170.

Check out previous episodes:

Why Fear of AI Hands the Bad Guys an Edge with Jason Stockinger - Ep 248

Who Gets the Benefit of AI? Enhancing the Core Experience with Neil Goodrich - Ep 247 

Start Small, Scale Smart, Govern Carefully: A CISO’s AI Mantra with Adam Palmer - Ep 246

Transcript: 

Cyber Business Podcast

Guest: Brian Walters

Director of IT

Building Plastics Inc

Matthew Connor: Matthew Connor here, host of the Cyber Business Podcast. Today we're joined by Brian Walters, Director of IT at Building Plastics Inc. Brian, welcome to the show.

Brian Walters: Hey, thanks for having me, Matt. It's a pleasure to be here.

Matthew Connor: Thanks for coming on. Before we get too far in, a quick word from our sponsors.

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Matthew Connor: And now, back to our show. Brian, for those who aren't familiar, can you tell us about Building Plastics, Inc. and your role there as Director of IT?

Brian Walters: Sure. I'm at Building Plastics, Inc., and we like to refer to ourselves as BPI. We've been an employee-owned company for sixty-plus years. We're based in Memphis, Tennessee, and we have thirteen locations right now and growing, mostly in the Mid-South. We started off as a vinyl flooring company, and then we moved into wood floors, and from there into tile and countertops and everything else. We're primarily a distributor. We get products from all over the world, and I believe we're always in the top five of flooring distributors in the country, and we're usually a little bit higher in tile distribution. I'm the Director of IT. I don't have the big title of CIO, but I have all the responsibility. So that's me in a nutshell. A little history on me: I grew up in Washington, DC, and worked in the consulting industry for many years, on both the government side and the commercial side. I worked with large companies, nonprofits, and smaller mid-sized companies, so across the gamut. I like to think I have a ton of wealth of experience, but that's me.

Matthew Connor: That's great. I'm sure, being in the DC area, we miss you, but you probably don't miss the traffic. You probably have a little better traffic down there in Memphis than we have up here, huh?

Brian Walters: Just a little bit. But I do miss the food and the culture and everything else, and just the diversity of the DMV, for sure.

Matthew Connor: Yeah, the food and the culture, that's hard to beat. I think New York may have us beat there, but that's about it. New York's quite the food town, they do that right, it's no slouch. But you know, whatever. Although you've got us beat with BBQ, there's no way we're even coming close.

Brian Walters: This is true. This is true. And if you come, my tip for you is shredded pork. Some rib places are good, but brisket, no, no, no, no, you've got to go to Texas, we just don't do brisket well here. So my tip to anybody who's listening, come here, get the shredded pork, you can't go wrong, and reach out to me. I'm on LinkedIn. I'll give you tons of BBQ recommendations if you need them.

Matthew Connor: I love it. Well, let's dive into the IT side of the flooring business, because sixty years as an employee-owned company is quite a feat. Statistically, it's so unlikely, most companies fail in the first couple of years, and to go sixty years and make it to this level is phenomenal. And in today's day and age, it doesn't really matter what the business is, technology is such an important part of keeping it running and profitable and making sure operations run smoothly. So how do you do that with thirteen locations, the advent of AI, everything changing? You certainly do not have a dull, boring, easy job.

Brian Walters: That's a good question. I started here about a year ago, and when they brought me in, we had a slight turnover in our C-suite. We had a new COO and a new CFO, and with sales being kind of level for a couple of years, they know, hey, we need to figure out how to grow our revenue. So they brought me in to help transform IT. We had a lot of technical debt, and we still do, I'm working toward fixing that. We were on a very old mainframe system that we had customized so much that we couldn't update it with regular updates any longer, among so many other things. So they brought me in saying, hey, we believe technology is the future for our company and we want to keep up with our competitors. We view ourselves as not just a flooring distribution company, but also an IT company, so they brought me in to transform things. I came in with a lot of history, like I said, of technical debt, but also, I think, a lack of trust in IT. It was the mindset of IT being just there to keep the lights on. The new leadership doesn't see it that way, and I'm not saying the old leadership didn't think that way too, at all. But that's why I'm here. And I would say the biggest thing coming in, with AI moving so fast these days, where every day something's different coming in and changing, was security initially, and some governance processes and things like that. Those were some of the quick, easy wins I implemented when I got in here.

Matthew Connor: So I think it's really interesting, for a guy with a history of transformation, how is that different now with AI than the historical transformation process in a business?

Brian Walters: First, I'll say that in any IT role, my experience shows that if you have a good understanding of the business, you're just going to be a better leader in IT, because you know the pain points, you know the gaps, you know everything else. I feel like that's the way most IT leaders are going. I honestly think a lot of the IT leaders who are changing the culture today are the ones with that digital transformation experience, where we can come in and, from the get-go, help the business make educated decisions and set the strategic goals. So first, I just wanted to say that. Now I need you to remind me of your initial question, because I'm getting old and I forgot what it was.

Matthew Connor: I think it was really, how is transformation different today with AI than historically?

Brian Walters: Yeah. I think another thing, as we all know, is that as the AI market's been set on, you want to get into it to improve your business, to leverage your return on investment, to meet your strategic goals. But at the same time, because it's changing fast and so much is unknown, I think it's just wise to wade yourself into it, and educate too. A lot of people are coming out and hearing all the stories of executives saying, we need AI now, just get it done. And the failure rate, as we all know, is like seventy or eighty percent, or sixty percent, depending on which statistics you look at. So for me, coming in, it was, let's slow down over here. One of the things we're doing, which I mentioned before, is that I set up some governance policies and some education for employees to say, hey, these are things you can do. We know you're going to use AI, there's no way around it. Obviously, with some of the tools in cybersecurity and networks these days, we could totally lock it down, but I don't think that's really reasonable. Plus, if we teach and educate them to use the tools that can help them in their day-to-day, so that's the governance piece, but also making sure there are strategic and business reasons for implementing AI, not just doing it because you're going to do it. So, hey, why do we need to do this? The third thing I'm learning here is that when I came in a year ago, we had selected a new ERP, moving to a modern SaaS-based application. One of my first questions was, oh, this is a chance to make sure the data is good, because we know good data is essential and key to making sure your AI models work. I used to be a developer, and I always remember the term "garbage in, garbage out," and today it's more of a reality than anything else. Imagine if we had kept good data standards and monitored data all those years, we'd be rolling in AI right now, maybe not rolling, but a lot of companies would be better off than they were in the past. So we're taking that process of modernizing our ERP as a chance to clean up the data, and we're setting up the governance structures, setting up boards where we can monitor AI, and things of that nature. My company is really in the beginnings, but I don't feel there's a need to rush right now. Not that we're not using it in other ways, like meeting minutes, and using Power Automate or whatever for some generic workflows to increase efficiency and things like that. But my challenge right now has been more on securing foundational principles. We came in and we didn't have MFA. I'm like, how can a company not have MFA? So foundational principles like implementing MFA are what I'm more focused on right now, because I think that's more of a concern than me getting AI tools out there. I need to secure the data, I need to get the data in a good place, and I need to set some guidelines here, because I know it's going to come. It's like everybody when the cloud started: oh yeah, this is the greatest thing, let's get on it first. It balanced out, and now it's flipping, like, oh wait, it might be better to start housing data in-house because of these AI things. So it's interesting to see how the market's changing, and like I said, people are still figuring things out with this AI.

Matthew Connor: Yeah, and it's advancing so rapidly, and it is still early days. Right now, in September 2026, it's been just under four years since ChatGPT came out, and the progression of the LLM from that day to today has been phenomenal. It's really interesting to see the effect it had. When it first came out, I think everybody expected it to be more like it is today, and when they found out it was a glorified autocomplete, and not really a great assistant, a lot of times it was easier to just do the work myself. It's good at maybe drafting an email very generically, but it doesn't really know the organization, it doesn't know my writing. I think a lot of people got disgruntled and got the wrong impression of AI early on. And for most people, I don't think they go into technology thinking, let me try it now, and then I'm going to come back in a few months and try it again and see how it goes. They tried it and said, yeah, that's garbage, next, moving on. For a lot of people it left a bad taste in their mouth, so they've got this bad impression, even though where we are with AI today is so much better than where we were six months ago. Today it's in a place where it does some really great stuff, and it's very handy. But I think because of that, we're going to see a slower rollout of AI in a lot of companies, because there's a mass feeling of despair, of letdown, that it wasn't what they thought it was. People will reference things like Meta firing thousands of people trying to replace them with AI, only to bring them back, and a lot of discussion about the ROI not being there, because it wasn't there. I think that had we launched with where we are today, the world would be entirely different. But the frontier models today are really impressive compared to where they were six months ago, let alone four years ago. So that puts us in a really interesting spot, and I don't think you're alone. Despite all of the pressure to roll out AI, roll out AI, I think for a lot of people it's really difficult to do what you're doing, which is to say, yes, we're okay, we need to get the fundamentals right, we sprinkle in AI where it makes sense, and we focus on whether there's a problem we're solving with this and whether it produces a great result, not just, here's a cool new toy, play with it and use it all the time.

Brian Walters: Yeah, I totally agree. You start with the low-hanging fruit. Wade into the waters is kind of the approach I'm taking. Of course, I'm not a big Fortune 500 company, so I don't have a ton of money either, and that may be one reason that's slowing me down a little bit too, if I'm honest. I've got to be cost-conscious, because building models can be super expensive. Another thing I'm really concerned about in this AI area, and there have been a lot of discussions right now, is the ethical use of it, the governance around it, and the fact that there isn't really anything out there saying, hey, you can't or shouldn't do this, or you should do that. I don't even think there's anything saying, hey, if you're talking to AI, you've got to let them know you're talking to AI. So I want to wade in, because I know we need those things set up. I want to say China is a little ahead of us in setting up some guidance and rules. The European Union's always in front of us in terms of policy, it seems, and we're kind of always lagging there, when it comes to compliance and things of that nature. But that's one of my concerns too, to see how that plays out. Even some of the AI experts are saying, hey, we might need to slow our roll here. You start to see those conversations right now. You've got to winnow through all the talk and find the truths out there that are good.

Matthew Connor: It's interesting, because both Europe and China approach things from a completely different perspective than the US. They are more, the government is here to protect us and give us these guidelines, and we are much more, the government is here to allow us to innovate and build and grow. And what's currently happening is the narrative that the large frontier model companies are espousing right now, that we need more regulation. I think it's a smokescreen, and they're going to hate me for this, but think about this. If your dog attacks somebody or causes damage, you're liable for that damage. If something that's under your control commits a felony, then you have committed that felony, because you did not stop your thing from doing that. So I think the call for regulation is a smokescreen for, please don't punish us for committing felonies. Because when your LLM that you are testing goes and hacks something, you took a tool and used the tool and it committed a felony, that was you committing that felony, and you're liable. And I think that's what they're doing with wanting a call for regulation. If we start prosecuting for the crimes that are being committed, guess what's going to happen? Those crimes will stop immediately. There will be no call for regulation, because they don't need to, because we're making sure our agents cannot get out of the sandbox, and we're watching to make sure they are not going and committing crimes, because we're liable. So when Hugging Face is like, whoa, we're being hacked, guess what, whoever's hacking is in trouble, and that would stop it right then and there. I think that's what's happening. And now, if I show up dead tomorrow, we all know why, Big AI killed me.

Brian Walters: You, being in the intelligence community, I think you know what's really going to happen to you tomorrow. But your background there, yeah, that's a good perspective. I hadn't heard that one before, the legality and everything around that. In a way we'll give them that smokescreen, we'll help them, going forward. Yeah, I like that perspective.

Matthew Connor: Well, it's really interesting. As we wade into AI, and I like that expression you used, wading into AI, I think it's really smart, because so many companies, especially smaller organizations, are in a similar position to what you found BPI to be in, where it's like, look, we've got to dial in the fundamentals. We don't need to be working on our trick shots when we don't even have the basic shots down yet. We've got to get our fundamental game down and be really solid in that if we're going to be good, because it doesn't matter what you do beyond that if you're not doing the basics right and somebody can just walk right in the front door. Dude, we should at least put a lock on that thing. Even if we don't have a fancy security alarm, can we at least all agree to lock the front door so the bad guys can't walk right in? Great. But as you get the fundamentals down, I like this idea of wading in to AI, especially on the security side. There have been some really cool products around for about fifteen years that have been using machine learning to do what people are now expecting an LLM to do. Look at things like Darktrace, where it watches your network for abnormal behavior, oh, that's weird, and machine learning can sift through and immediately see when something's different, which is really hard to do using traditional stuff. So I like that idea, that's a great place for people to start. We're not throwing LLMs at everything, we're not just going to bolt an LLM onto everything and expect it to solve the problem. Instead, what if we use the right technology for the right thing? I think that's the crawl, walk, run analogy, you get in on stuff like that and move forward. I think that makes a lot of sense. Wade into AI, I like that.

Brian Walters: Yeah. And we talked a little bit about governance, but another thing, and one of the reasons we're wading in, is that one of the things I do want to do is put in modern security that tracks AI and what people are entering. I know CrowdStrike, Fortinet, and some of the other cybersecurity vendors out there are working on those monitoring tools now, as you know better than I do, being a cyber expert. But I'm looking this year, it's on my roadmap, to start implementing that so we can at least start putting some guardrails in place. Not just the governance helping the guardrails, but having tools so we can see what actual people are doing. And it's not to be Big Brother, or to keep people from doing stuff. It's more like, hey, let's make sure we're not putting proprietary, I can never say that word right, proprietary, thank you, information out there. And also see what our people are actually using, because that may help us find the tools or the LLMs or whatever that can really help them do their jobs better. So that's our next step in that wading process. I'm looking at [unclear] right now to do that.

Matthew Connor: I think that's such a great idea, because so many users and employees are using AI in various ways, and it becomes shadow IT in a lot of cases, where they say, look, we don't have it at work, I'm just going to use my personal account and drop this in here. Getting visibility on that is key, and you're right that CrowdStrike is coming out with its solution, and Darktrace has its Secure AI, and there are a few others coming out with the same level of, hey, let's see how our users are using AI, monitor it with AI, and say, here are the guidelines. And when it happens, be able to see it and stop the misuse, so that information isn't getting out there and you don't have this leakage. I don't think any employee is acting maliciously, it's just that this is new stuff that's hard to get your hands around, and we need the tools to really get control of it. And until very, very recently, like literally the last couple of months, it didn't exist.

Brian Walters: That's right. So it's fairly new technology, right?

Matthew Connor: Yeah, yeah, yeah. So it's exciting times. Look at the progression of self-driving cars over the last five or six years. It's gone from a drunk toddler to now being statistically eight times safer than a human driver, and that makes perfect sense now. I was just watching a video yesterday of a Tesla on full self-driving, and one of these guys hid a dummy behind some big block on the side of the road and threw the dummy into the road, and it took four frames at thirty frames per second. So it was like point-one-two seconds from the time the first little bit of the person's leg showed behind the box to the time the Tesla identified it and started reacting. It's so fast, humans just don't react like that, we need a second to see and figure it out. So to see it moving and making decisions so rapidly, that's a great use of technology, to see how far we've come, how fast. It is really fascinating. And I think we're a little bit further ahead in the self-driving aspect than we are on the business use front, so it gives us a glimpse at where we're going. It's much more mature, it's right on the cusp of, oh yeah, humans are never going to touch the wheel again. You can see that day is not too far ahead. But on the business side, we're still a little bit drunk. Maybe we're not a drunk toddler anymore, but we're still a kid, and even though it's a really smart kid, like a little genius, they still need supervision, because they're a kid.

Brian Walters: Yeah, here's another example. Somebody sent me, just a typical employee, not in IT, and I don't want to give details away, but they sent me a script in a document and said, hey, we want you to implement this in the ERP. And I'm like, okay, I have questions. So basically my response was, hey, we'll look into this, but it's a non-IT person. If they're not really educated in AI, or they don't know the system they're building the script for, the AI is still not intelligent enough to say, hey, have you thought about this in the system? Have you thought about this program? How is this going to affect this? They're just writing a script to get what they need, which is great, that AI can help people do that. But my point is you still need oversight right now, and I think that's what you just mentioned. You still need people to review it, and they still need to be experts. I think that's where our roles are changing, where we're going to have more people doing that oversight, the pulse check, all the things when you get your AI model running, like monitoring the logs, making sure new data is coming in, making sure you're still getting your ROI, your technical ROI as well as your business ROI. So I think it's fascinating, just like with self-driving cars. I'm totally on the same page with you, brother, that the business is still lagging behind, and I still think there's a lot of oversight needed and attention to these tools we're using.

Matthew Connor: Yeah. And don't get me wrong, I think where we are today with the frontier models, for very little money, and let's just say on the IT side, for very little money every month, you've got expert-level assistance. You look at something like Claude Fable 5.1, it's so much more powerful and capable. And it does take a look at the safeguards, and now they're rolling it out with these guardrails in place to say, hey, wait, don't give me that API key, you pasted it in here, don't give me the password, would you stop it? Whereas before it was like, yeah, we can totally post this, let's post that API key on Google, on your website, no problem, I've got it, there it is. It had no concern and no way of having that. But now it's coming baked in. So we're seeing it mature in a way that the IT professional gets to have this expertise. A shop that maybe only has one or two IT people can now say, hey, can you help me go through our firewall and see if we've got everything set right? Because I'm not the firewall guy, but we've got a firewall and it needs to be set right. And then it takes a look at your Microsoft 365 and says, did you know you don't have MFA set, oh yeah, fortunately they had you. But being able to have that expertise that you had to outsource in the past, partnering with an MSP or an MSSP, somebody whose expertise that was. Now I think we're on the cusp of small businesses, with just one IT person, being able to do great things very cost-effectively. For that hundred-dollars-a-month subscription, that one IT person becomes a heck of an IT person who's now got the subject matter expert right there for everything, which we didn't have even a few months ago. So it's a fascinating time.

Brian Walters: Yeah, it's interesting. I was talking to an employee at one of my former companies, and I was saying, man, you need to get on board here and start leveraging it where you can. He's like, nah. I'm like, dude, with that kind of mentality, you're going to lose your job eventually, because somebody who's just as smart as you is going to leverage these tools that are maturing, like you said, and they're going to be able to do twice as much work as you. They're going to be more efficient. And I get it, people are concerned about losing jobs. But I think, like any market, the jobs are just going to switch. As you said, the models are getting smarter, but who's making the models smarter? The people behind them, who are adjusting them and making them better. It's fascinating how some people are going to adapt. There are always your early adopters, the people who are getting on it. I don't consider myself one of the smartest people in the world, but I like to surround myself with smart people. I'm always reading and learning, and there are certain news sources out there that are great tools to keep me educated. You see the ads like, hey, I spent five minutes a day and now my CEO thinks I'm the AI expert and they put me over these projects. I don't know, that's a little exaggeration.

Matthew Connor: I don't think it's that much of an exaggeration. It is a little bit of an exaggeration, but I think we are now entering the phase, if we're not there already, where the standard of work is going to be this AI-assisted work, because now the output is so much more professional. Take any slide deck, any report, any meeting minutes, you name it, whatever it is, it's generated so much more professionally and so much faster, and then you tweak it. I think that is becoming the standard, and if people don't start keeping up with that standard, well, I'm sorry, there's not a human being in the world who can compete with that. It's not about AI taking my job. It's the person performing at this level with AI assistance who is going to take your job. The new standard is AI-assisted work, so now your output is spectacular, and that's the baseline, and what you do on top of that is what matters. And I don't think AI is taking your job, because for every dollar spent on software, six dollars are spent on service. That's going to continue, because AI is part of that software equation. We're always going to want people there. Nobody wants to just walk up and talk to a machine and have your burger or whatever delivered to you all cold. We've tried this, right? McDonald's has experimented with it, and we found that we reject it as humans, we don't want it. It's not appealing, there's something off-putting about going in and getting this automated food. McDonald's is even moving back because it doesn't work for the human, even though it's fast food. And you'd think it would be just for restaurants, like a sit-down restaurant, you don't want some robot coming up and taking your order, taking it back to the robot kitchen that produces it and brings it back. That's just a weird thing. It might be cool to see once, and then that's it, because, oh, we can do that. Nobody's going to want to go there every day. Well, I would like AI in restaurants like McDonald's and stuff if they could figure out, hey, I said no ketchup on my burger, and I drive away, and the AI actually does it better than the humans, and there's actually no ketchup on my burger. This is a great example of AI-assisted. When the order comes in, McDonald's should be watching that order be prepared, and it's like, oh, they said no ketchup and you put ketchup on that. And you take that analogy and apply it to every other business, that is the new standard. McDonald's will get there for sure. McDonald's is a front-runner in a lot of things because they're so big and they stay on the cusp of technology and everything. But I think this is one of those times where the little nimble guy is able to move a lot faster than the big guys. We're going to see that the small business is going to be able to outperform the bigger businesses that aren't able to implement it at scale like the little guys can.

Brian Walters: Yeah. And where I see another human-side element, I'll give you another example. The other day I presented, I forget exactly what, to the rest of the C-suite, and one of the pieces of feedback was, you just did that in AI. I stopped and said, no, I didn't just do that in AI. I used my thirty years of experience to write prompts and put in my own input. I actually started off writing everything myself, I put it in there, I had it spit something out, and based upon my expertise and my learning what to ask it, I know to ask, hey, where did you source this data from? The questions you ask are what make an educated, good output. So some people still go, oh, you just did that in AI, and I'm like, no, smart people know you can't just let AI do everything. One of my concerns too, and some of the challenges we're seeing, is in the school system, the education system. You've seen that Facebook ad or something saying, hey, I did my AI report in ten minutes, and you tell them, oh yeah, we read the book and wrote a ten-page report all in one night when we were your age. Something spoofing life like that. But I'm worried about how this is going to affect our children's education, and education in colleges, there are so many aspects of this AI that the world's trying to figure out. It's just fascinating to me in general. You see some universities, I forget which law school, saying their first-year students are banned from using AI, and you see phones being taken away, but all these kids work on tablets and computers these days. So you're going to need good tools to start locking down that AI, like we mentioned earlier, so our kids can actually learn, because the frontal lobe isn't fully developed until you're twenty-six or twenty-seven. You need to teach them these habits of creative and constructive thinking so they can be well prepared for the future. I hope we don't end up like, what is it, WALL-E, the movie, where they're all just sitting there handing everything over to AI, and everybody's gone fat and just trusts AI for whatever it's going to do. Obviously it's going to grow and get better, but those are some of the things that run through my mind, a gamut even outside the business world, with AI.

Matthew Connor: I think you raised a really great point. The challenge we have with our education system as a whole, and have had for decades, is that what we've been focused on is testing: did you learn something? So we're training for the test, not teaching for creative problem solving and creative thinking. The whole point of learning more and more math is not to be able to use it, because the computer will always be better than you. It's to learn the thinking that goes along with it. We need to transform our education system into one that creates good thinkers and speakers and writers. Not, hey, did you learn this information? Who cares? You could look that up in three seconds. It doesn't matter. What matters is that you can find it and then think creatively about it. Now, you do need a certain amount of knowledge to be able to think constructively on a topic, and that will come naturally if we engage them in those ways of thinking and creating and doing, versus, hurry up and learn it and spit it out. Oh, don't worry, you're going to forget it in two weeks and you won't remember any of it. What was the point?

Brian Walters: Yeah, how many times did your math teacher say, I want to see you work out the problem, write it on the paper? That's because that's the creative part, that's what they want to see. They don't care that you get the answer right. I mean, yeah, that's important, but they want to see that logic. My kids are like, no, you've got to write it out. So to your point, that's a great example of why those teachers always ask you to do that.

Matthew Connor: I think that's our key to the future. And you see Elon Musk, I think that guy lives in the future, and I think he's actually AI. He might be right. He might be an alien. And I think the interesting part is that what he does with his kids is exactly that. He's created a school for his kids to learn, and it's more of that Montessori method. That's hard to do at scale, but I think there's going to be a reckoning, and AI is pushing that to where we have to adjust. Right now it's all, oh, federal funding comes based off your test scores on these standardized tests. Stop it. Get that out of here and just stop. Let's focus on raising children who can really think and problem-solve and who are excited to go to school to learn stuff, not sit in some factory-like classroom and try to learn in a very particular way to memorize and regurgitate. That is so archaic. It was great for the factory worker it was designed for, so they could go in and read the sign and not get their hand chopped off. That's why we have the bell between classes, it was for factories. We're so far from raising factory workers. Come on, we have to revamp our educational system.

Brian Walters: For sure. Speaking of Mr. Musk, being here in Memphis, xAI is pretty big here. That's where he's building all his big data centers. But there's another challenge of AI. From what I hear in the construction industry, they can't build data warehouses and data centers fast enough to keep up with the development of AI. That's why I think Musk is looking to space, which I think is kind of [unclear]. Somebody's like, dude, it's brilliant. He's one of the smartest people I've ever heard. I was with a friend who helped bring him in. He works for the city of Memphis, and he and another lady brought xAI in here to Memphis years ago. And I asked, tell me a little bit about Elon, is he as smart as he seems? And the guy's like, he's wicked smart. If anybody outsmarts him in a meeting, the next meeting he comes back knowing more about that person and that topic. I really think he's AI. But more so, we're seeing the chip industry prices go crazy, so we also have that factor in how fast AI can grow. And then everybody's concerned with how it affects the environment, how it warms areas. You see those stories of, hey, let me buy your land, I think it was in Pennsylvania, for twenty-eight million dollars, and the ladies are like, no, I'm not selling it. It's just fascinating, all the aspects centered around AI. That's why it's in the news every day, and why it's the center of focus in IT and everybody's paying so much attention to it.

Matthew Connor: Yeah, well, we live in fascinating times. I think it's the most exciting time to be alive, and I wish there was less fear-mongering in the media, scaring people about the future, because realistically that's not how this plays out. And even if it is, what are you going to do? So you might as well enjoy the time we have left. And almost certainly it's not going to go poorly. Because I think the technology is finally at a place where, instead of us using technology to work harder and longer and be more productive, it's getting to the point where it can help make every job better, easier, more enjoyable. Take the tedious stuff out of it, let you work on the more enjoyable aspects of the job. You hear it even with coders, some coders really love using AI and some are so mad. I think the good coders are really mad at AI, because if they work in a place where it's kind of mandated that everything is written with AI, they're like, but I love coding, and now I don't get to code. I now have to supervise my agents, I'm basically a prompt engineer, and they have to focus more on the structure and the strategy and the implementation versus the actual coding they enjoy. But I think even in that we'll get to a balance, where the coders who love coding still get to code and those who don't get to have AI code. I'm very much an optimistic person, but I think that's the way it will play out, where we've got this great assistance that we're going to learn to leverage in the right way to help us as humans be more human.

Brian Walters: Yeah. It's kind of like you made me think of another topic, besides coders: what about music and artists and graphic designers? Some of these models are getting so advanced that I feel like they're going to feel the same way as some of those really good coders. It's going to be interesting to see how that all plays out in terms of the future. I've heard some great AI songs, and I'm just like, man.

Matthew Connor: Yep. Well, I've got a hot take there. If you take a look at some of the AI-generated content on social media, initially it's super interesting and you're like, oh wow, look at what we can do now. And that novelty quickly wears off and it becomes, is it just AI crap? It's not genuine, it's not real. When you extrapolate that into the future and think about things like, say, Tom Cruise, I want to see the eighty-, ninety-year-old Tom Cruise hanging from the side of the plane, not AI Tom Cruise hanging from the side of the plane. There's something really impressive in the fact that he did it at fifty, at sixty, and it becomes less enjoyable when it's just AI-generated, like, who cares? And when you apply that to music, to art, whether it's music, drawing, sculpting, anything, I think it takes the soul out of it. It'll be cool to see, oh, it can do it, great. It'll be cool that you could record a Marvel-like movie with your iPhone, where it's like, holy crap, because all of the CGI that goes in will be better than the most recent Marvel movie, because the CGI will be so much more realistic, and you shot it on an iPhone. It'll be amazing. But if the people acting in it are all CGI, I think that's where it breaks. When it's computer-generated, people are like, there's no soul in that, I don't like it, it's off-putting, just like the robot serving you your food. It'll be cool to see once, but off-putting to see more than once. I think it's going to create this resurgence, kind of a renaissance of people getting to spend more of their life in the arts and humanities, and I think we're going to value it so much more. So the kid who wants to grow up and be a YouTuber, I think there's going to be a lot more of that human-generated content that has real value. And I think we'll see the AI-generated content go away. I could be wrong, but I think that's how people will take it.

Brian Walters: Yeah, that's, so like deepfakes. That's going to get better and better in terms of the cybersecurity world. So I hear you on your point, but I'm wondering, what if we adapt? The movies get so good, even with the fake characters, and they get more personality. I feel like at some point it's just like deepfakes. It might be too hard to tell them apart.

Matthew Connor: I think you will. And I think there's a solution. Where we end up going, and I don't have it fully worked out yet, is that we have to have a sort of digital rights management on things. Maybe it ties into the blockchain, but the originator of that content, when it's shot on your iPhone and edited, can say, look, this is my thing, and if even one pixel changes, whether it's cropping or anything, suddenly that breaks it, and it no longer has the digital rights management. So if you do that, and it's kind of certified as the original, then any platform should not be allowed to publish anything that isn't tied to that, because that means, oh, now this is a deepfake. This might be some sort of abusive content, some sort of anything else. And that gives us a way of filtering that out immediately as, this isn't right or good. If it's not tied to that person, if it's not the original thing, fantastic. I think there's a solution there. I'm not the smartest guy in the world, and I'm pretty sure there are smarter people working on that, because we're already seeing it in things like your Sony cameras, which can incorporate that already. The challenge will be the platforms, getting them to say, and maybe it's a policy thing, where we say, hey, look, if it isn't DRM, then it can't be posted anywhere. We could do this across all platforms and be like, yeah, this is safe. Anything that's not, you've got to wonder, why is it not right? There may be a legitimate reason, I don't know, but all the nefarious reasons certainly will not be tied to someone and will not be original content. All the deepfakes, nope. So I think that's the only way we can do it. And the same has to go for voice. There's got to be a way that, with our phone as we're speaking, or on Zoom or Teams or whatever, the system can say, yep, that's my phone and I've already identified that that's me, so that's indeed Matt. When you get a call from Matt, if it's not certified as, oh, that's Matt, then, oh, that's a deepfake, and it can just stop. So I think we'll get to that point in the future where that sort of DRM is in place for video and for audio. I'm sure there's some other creative way of doing it, but I think it's going to be something in that vein.

Brian Walters: Yeah. And that authentication mindset goes back to some guidelines and rules, maybe in the government or around the world. We've got to identify these things. Another way we see AI used a lot today, or at least I've heard, is in submitting resumes, and HR departments receiving resumes. Now they have functions built in where they can say, oh, this was completely AI-generated. I don't know what the factor is and how many people actually get jobs through applying that way. I think the percentage of interviews you get through AI would probably lift if you're using it correctly to get more interviews. But my whole point is that AI is getting smarter, where it can start identifying AI itself.

Matthew Connor: Yeah, and no, it really is. It's fascinating how it can identify it just by the word choices and how it's put together. It's like, yeah, that was AI, because humans don't have this pattern. And yet to us it's indistinguishable, we can't say that was. But yeah, it's getting there. It's a fascinating time. Well, Brian, I cannot thank you enough for coming on today. This has been a really fantastic and fascinating conversation. But before we go, can you tell everybody where they can find out more about you and more about BPI?

Brian Walters: Yeah, bpiteams.com is our domain name, and we're on LinkedIn, and you can find me on LinkedIn easily. It's Brian Walters, B-R-I-A-N W-A-L-T-E-R-S. So yeah, look me up, I'd love to connect with you. I love networking and meeting new people like you. And maybe if I did well enough, you can invite me back and we can have some more discussions around these topics.

Matthew Connor: Oh, you're always welcome back, and I look forward to having you back on the show, Brian. All right, until next time.

Brian Walters: Okay. Thanks, Matt.