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Beyond the AI Buzz: Practical Lessons for Northwest Arkansas Business Growth

June 15, 2026

In this episode of The Same Day Podcast, Yoni Schmidt is joined by Ken McLoud, Founder of Laconic Technology, to discuss about leveraging AI to improve profitability and operational performance. The discussion explores why so many AI initiatives fail and what separates successful implementations from costly distractions.

Turning AI Hype Into Profit With Ken McLoud

Ken McLoud

Ken McLoud is the Founder of Laconic Technology, where he helps organizations leverage artificial intelligence and custom software solutions to improve workflows, increase productivity, and support long-term growth. Combining technical expertise with strategic consulting, he works with businesses to implement solutions that produce measurable outcomes rather than unnecessary complexity. Through Laconic Technology, Ken helps organizations integrate artificial intelligence and custom software into existing systems. His approach focuses on practical applications that improve performance while supporting broader business objectives.

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

  • [02:57] Ken McLoud explains why most corporate AI projects fail to deliver ROI
  • [05:15] Ways to identify if your business is supply or demand constrained
  • [07:18] How top agencies use AI to supercharge teams
  • [08:51] The three pillars of successful AI implementation
  • [16:45] Exploring AI leverage in property management by assessing operational needs 
  • [22:45] How AI-powered lead magnets attract and convert clients
  • [30:33] The hidden risks when AI replaces customer interactions
  • [36:34] Ken shares essential AI advice for property managers to succeed over the next three years

In this episode…

The excitement surrounding AI often causes business owners to focus on technology before strategy. Ken believes this is backwards. Instead of asking which AI tools are popular, leaders should identify where growth is being restricted and concentrate on solving those issues first.

When AI is applied to a clearly defined challenge, it can dramatically improve efficiency and decision-making. For Northwest Arkansas business owners, the conversation offers a valuable reminder that technology works best when it supports a well-defined business goal.

As Northwest Arkansas continues experiencing rapid business expansion, companies are exploring new ways to scale efficiently. Ken explains that AI can create significant value, but only when it addresses genuine operational needs. Businesses that rush to adopt new tools without understanding their bottlenecks often struggle to see meaningful returns.

Resources mentioned in this episode:

Quotable Moments

  • “We got to make sure that we avoid the whole solution in search of a problem trope.” 
  • “The right thing to do is to kind of take off the AI hat and put on more like a business consultant hat.” 
  • “It’s a lot better to think of these tools as super-powering the humans than out and out replacing them.” 
  • “You absolutely do want to use it, but you want to use it to superpower your operations, not to come in between you and those high-value customers.” 
  • “You absolutely do not want to be a solution in search of a problem.” 

Action Steps

  1. Identify your primary business constraint first: Clarifying whether you are demand or supply constrained ensures AI investments directly target growth bottlenecks.
  2. Calculate customer lifetime value before investing: Understanding what a client is truly worth helps determine whether an AI system will generate positive ROI.
  3. Use AI to enhance, not replace, human relationships: Keeping high-value interactions human protects trust, reputation, and long-term revenue.
  4. Build AI systems around workflows, not chat tools: Integrating AI into repeatable processes creates scalable efficiency instead of isolated productivity gains.
  5. Commit to ongoing optimization after implementation: Continuously refining prompts, data inputs, and models ensures sustained performance and profitability.

Sponsor for this episode…

This episode is brought to you by Keyrenter Property Management.

Keyrenter Property Management is a full-service property management company that helps clients buy, renovate, and operate real estate assets.

The team helps clients build wealth while taking the headache out of property management.

That’s why, no matter what rental you have — single-family homes, condos, townhomes, or apartments — they can give you the management solutions you need. 

To learn more about their services, go to https://keyrenterpmc.com/ or send them an email at [email protected].

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Episode Transcript

Intro 00:04

Welcome to The Same Day Podcast, where we discuss driving incremental business growth and other topics related to real estate, property management and entrepreneurship. Now to the show at hand.

Yonatan Schmidt 00:20

Hi there, Yoni Schmidt here hosting today’s episode of The Same Day Podcast where we connect with top business and real estate leaders. Past guests include Ben Nemecek, Chris Lyle, Ben Aussenberg and many others. And today’s episode is brought to you by Keyrenter Property Management. Keyrenter Property Management is a full service property management company helping our clients buy, renovate and operate real estate assets. We help our clients build wealth while taking the headache out of real estate and ownership and property management.

That’s why no matter what assets or rentals you have single family homes, boutique multifamily condos, townhouses or apartments. We have the management solutions for you go to keyrenterpmc.com or email us at [email protected] for more details. Today I’m excited to welcome Ken McLoud. Ken is the Founder of Laconic Tech and the secret weapon behind custom AI software growing businesses. 

 After more than 15 years as an engineer working with brands like Toyota, Lockheed Martin, Bose and many more, can now helps entrepreneurs implement AI the right way, combining strategy, implementation and follow through to deliver measurable results, including systems that have added over $28,000 in pure profit per month. Ken doesn’t just build what clients ask for, he builds what actually solves problems. And today, we’re here to dive into how the real estate industry and property management companies can think strategically about AI, where it can drive real return on the investment and where we can, where it can quietly become a tar pit or an expensive tar pit can. Welcome to the show and thank you so much for being here. I should put my phone on Do not Disturb.

Ken McLoud 02:08

Thanks for having me. I’ll do the same.

Yonatan Schmidt 02:11

Yeah, I’m getting all these notifications and I realized I did not do that. Sorry. I guess let’s dive right in. Right. Framing AI for, you know, real estate companies and property management companies.

There’s just so much hype around this. It’s been the hype for what, the last 18, 24 months now. You know, people are using it. People don’t understand it. People are, you know, half in, half out. 

 There’s a lot of, like I said, AI hype right now. If you’re if you were sitting in, you know, the owner’s seat of a real estate firm or a property management companies, you know, you know, I guess like leadership seat. What’s the first question that you would ask before implementing anything AI related?

Ken McLoud 02:57

Yeah, that’s a great question. So the the first thing that we got to do is we got to make sure that we avoid the whole solution in search of a problem trope. Right. So like it’s it’s very corporate America to say something like, well, we’ve got to be doing more with AI right now. But this leads to like a couple months ago, the MIT Business Review had an article that over 90% of the AI projects funded by corporate America were still not showing a positive ROI.

And it’s exactly because of that kind of thinking. Unfortunately, I’ve been involved with a couple of them. So the key is to not even phrase it as what are we going to do with AI? Instead, the right thing to do is to kind of take off the AI hat and put on more like a business consultant hat and think, what are the constraints of the business that are preventing us from getting to our goals. Right? 

 So maybe the goal right now is revenue growth. Maybe it’s driving down costs to improve, to improve profitability. Maybe it’s both of those things. But what are the constraints that are keeping us from getting where we want to go, irrespective of AI or technology at all? And then once we identify what the real constraints of the business are, then we want to go, okay, now we’ve got access to these amazing new technologies that we didn’t have a year ago. 

 So is there something new that we can do? Can we attack these constraints with these new technologies that probably weren’t available to us the last time we were considering this problem?

Yonatan Schmidt 04:36

And if we’re framing this, you know, just for example, for a second, for real estate, you know, agents and the real estate world, right. Today there’s a constraint. Maybe you don’t call it a constraint, right. It’s you know, we’re shifting into more of a buyer’s market. There’s more inventory on the market and rates are higher.

Things are more expensive. Things are, you know, selling for a little less than listing price. And it’s not like the frenzy that we experienced, you know, during the pandemic. What would you say? What would you suggest for agents who are struggling to help their clients sell their homes because they’re competing with, you know, thousands of other listings?

Ken McLoud 05:15

Yep. So the first thing we got to do is determine whether we’re demand constrained or supply constrained, right. So take a little bit more clear example like with property management here. It would be if if you’re frequently kind of backing off of trying to acquire new properties because you’re not sure that you’ll be able to take care of them. You know, maybe constrained on team size, this would mean your supply constrained, right?

In that case, it’s a supply of labor. However, if you’re like, pedal to the metal. We’re trying to get new traffic in the door at all times. Go go go. We could fill twice the amount of traffic we have right now. 

 Then you’re more demand constrained. So the first question you got to ask when you’re up top is are you supply constrained or demand constrained? Like for a real estate agent that would be am I trying to get every listing I possibly can? Because I know as soon as I get a listing, I can flip that thing that would have been in the Covid days, right? Or is it the other side? 

 Like, geez, I’m kind of worried about taking more because I can’t move the ones that I’ve already got on the books. Yeah. So then you’re more supply constrained on that side. So then once you determine which one of those two you’re in, which one of those boats you’re in now, that kind of sets you down the path of where you’re going to attack.

Yonatan Schmidt 06:42

We hear a lot of property managers. I guess I hear a lot in the industry property managers saying, you know, leads are down. Owner leads of of property owner, you know, of properties you know are not calling us and the phone isn’t, you know, ringing off the hook like it may be used to. And leads are down. Do you see AI replacing.

You know what traditional marketing firms have been doing? You know, for years now, decades now, and coming into just like revolutionize the marketing, the marketing industry as well?

Ken McLoud 07:18

Yeah, it certainly is. And I actually work with a handful of marketing agencies. It’s another good point, though, across the board. I think it’s a lot better to think of these tools as super powering the humans than out and out replacing them. So like all of the successful marketing agencies right now, to take that example, they aren’t worried about being replaced by AI.

They’re using AI tools. some of them that we’ve built in order to super power their existing team so they can get much better results for their clients than they used to able to be. Or maybe they can handle many more clients per employee than they used to be able to. Yeah, it’d be the same sort of thing.

Yonatan Schmidt 08:02

I and that was my sentiment, I guess. Up until very recently is I wasn’t worried about AI, you know, coming in to replace my job or, you know, taking my job. I was just worried about, you know, the company down the street leveraging AI and doing a better job than us. Right. With these systems and tools to where our clients will, you know, ultimately go there.

Right. Now with new agent, the agent AI products that are out there, you know, I have some different thoughts, but, you know, we can get into that later if we have some more time. You talk a lot about AI being a three legged stool, right? Strategy Implementation and follow through. Can you, I guess, expand on that? 

 And where do most companies fall down?

Ken McLoud 08:51

Yeah. So unfortunately there’s a lot of falling down across all three. But so that three legged stool strategy implementation follow through to kind of burn through those quick strategy is that process we were talking about at the top of the show here, where we don’t want to be a solution in search of a problem. Instead, we want to identify the constraint of the business. And then we want to say, is there some way we can use this awesome new technology to attack that constraint, to relieve the constraint in a way that wasn’t possible 12 months ago?

Let’s say the second layer is implementation. This is the stuff that’s exciting for me, but probably boring for most other people. This is the like hands on keyboard, typing out the code, actually building the application bit of it. And then the third bit is the follow through, right? So for most of these systems, thinking of it as kind of a one off quick hit and hit and run sort of situation is not going to lead to success. 

 So we almost always have to go through a process where we get the system set up. You get it running in the real world, you get water flowing through the well, and then once you get enough water, you’ll see like, oh, when this thing happens, we thought it was going to do that, but it’s actually doing this, and then we’ve got to adjust. Maybe we’re just adjusting prompts, maybe we’ve got to change what data is available to the AI. There might be some more kind of architectural tweaks that we have to do in order to get it to behave, and then that problem will be solved. And then you kind of sit and wait and another one will come up, and then you’ve got to attack that. 

 And kind of the pattern here is like the first week is systems deployed. You’re going to have a whole bunch of these, you know, and then the next week a lot less, and the next week a lot less, until eventually it’s just kind of a a low simmer as new, unusual situations come up. And then you also have that all of the major labs that everyone’s heard about, like OpenAI, grok, Claude, they’re all constantly improving these models. Right. So you also have you want to continuously be upgrading to the latest and greatest models as they come out. 

 But these models have kind of a unique personality each time, even if it’s just the new version of a model from the same provider. So we’ll often find that, you know, let’s say you’re going from GPT five to GPT 5.2. You might have to redo some of those prompts or kind of retweak the prompts, because 5.0 saw it in one way and interpreted it one way. 5.2 has got a slightly different personality and now it’s interpreting it a different way. Yeah. 

 So that’s that kind of continuous follow through is super important to actually get your ROI out of the system.

Yonatan Schmidt 11:50

Yeah. And I’m noticing like a lot of these updates and iterations and improvements are also happening at a much faster pace now. Right. It’s not you know, whereas you went from, you know, ChatGPT one point whatever to to 1.9 to 2, right? Then that may have taken a little longer than going from 5 to 5.2, right.

So I guess let’s talk a little bit about ChatGPT and the difference between using that and actually implementing AI in the business, right. That’s something that people confuse often. Right. That you ask them, are you using AI in your business. They say, yes. 

 How are you using it? I use ChatGPT every day, not necessarily implementing AI and integrating it into the business Talk to us a little bit about that difference.

Ken McLoud 12:39

Yeah. So like I think what most people think of when they think of AI is essentially a chatbot, right? It’s like it’s that classic ChatGPT interface. And you can get this. This isn’t just a ChatGPT, right?

You can get this from Claude and Grock and Gemini, and that’s super useful. Like I use it multiple times a day, every single day. A lot of times I’ll use it as sort of a research assistant. I’ll send it off to the internet to go get some piece of information for me. A lot of times I’ll use it to kind of help me write stuff, kind of organize my thoughts, and collect my thoughts a little better. 

 So there you’ve got to you’ve got to watch, because it definitely has a tendency to sound like an AI. And they’re very they’re very eager to like over promise and use a bunch of flowery adjectives, you know. So that’s that’s the kind of stuff that I think most people are doing when they say, yeah, I’m using ChatGPT or using AI and it’s not at all that that’s bad. I do that stuff all the time. The kind of stuff that I’m building out, however, is, is much more of a workflow. 

 So to give you an example, I’ve got a system that I built for a trucking company out of Memphis. So they’re a trucking brokerage. Essentially, they’re a matchmaker between companies that have urgent freight that needs to be moved. Right? So maybe it’s a load of two by fours that’s got to go from Tallahassee to Dallas. 

 They’ll take that job, and then they got to go find a truck to move the job for. Cheaper than what? They got paid for it. Right. And then essentially they make the money.

Yonatan Schmidt 14:26

It’s an arbitrage.

Ken McLoud 14:27

Yeah, a match making, service arbitrage kind of business. Yep.

Yonatan Schmidt 14:30

Yeah.

Ken McLoud 14:31

So there we have an AI tool set up that watches the customer sites for these jobs to become available when a job becomes available. It goes out to the internet and calls some APIs in order to get things like current diesel price, what trucks are available along that route, current weather conditions even come up obviously with that like big storm we had a few weeks ago. Then it will take that information and pass it to an AI. That one’s using grok. Pass it to an AI, along with a pretty complex set of instructions on what jobs tend to be profitable and how we want to bid on those jobs.

Right. So then the AI will then decide, are we going to bid on that, yes or no? And how much are we going to bid? So if it decides yes, the system then automatically goes to the customer’s website and bids on the job for the amount determined by the AI. So everything I just said used to be something that there were a handful of office workers and kind of one of their jobs was constantly watching these customer sites for these jobs to come up. 

 And then basically doing the process I just described. And now that just entirely happens behind the scenes without a human touching it. And the humans are all focused on much higher value tasks, like managing those customer relationships and tracking down solutions for emergencies. Like, you know, we had an urgent truck going somewhere and it just broke down on the side of the road. So now we got to get someone there to pick it up.

Yonatan Schmidt 16:03

Yeah, that’s fascinating. And it’s probably doing it at a much faster speed too.

Ken McLoud 16:09

Absolutely. Yeah. So they’re like there is no chat interface. Like it’s a it’s a fully AI powered system that’s making a bunch of money. But there’s no there’s nothing that looks like ChatGPT there.

Yonatan Schmidt 16:21

Right. That’s interesting. Let’s talk a little bit about mid-size property management companies. Maybe one like ours. You know, where would you first look for AI leverage opportunities within, even if it’s not property management, maybe real estate, right?

Lead generation, leasing, sales, maintenance, back office. If you if you were coming in, what would be the first thing that you would check?

Ken McLoud 16:45

Yeah. No, I think this will be a super fun example. So like let’s jump right into it. Yeah. So take the example from earlier.

Are you guys currently pedal to the metal on finding as many new properties as you can? Or are you kind of holding off easing off the throttle on? Hey, maybe we’d run out of manpower if we took on more properties.

Yonatan Schmidt 17:08

I mean, I would say we like the consistent growth with, you know, selective owners and selective properties and, you know, nicer product and nicer neighborhoods and nicer areas, things that are, you know, potentially a little us more. Call it. They’re easier to manage, right. Instead of, like, very difficult, classy products that that often, you know, attract the wrong people. And, you know, owners are constantly only focused on cash flow when in reality, maybe, you know, in a, in a economic and interest rate environment like the one that we’re in right now.

And, you know, let’s date this at, you know, February 19th of 2026. You know, you should be focused maybe more on cash flow. And maybe, you know, you have you have several things that are working for you with your investment in real estate and a few things that are not performing as well. Right. Such as cash flow in this interest rate environment. 

 So I don’t know that we’re pedal to the metal, but I also don’t know that we’re slowing down completely. We’re probably somewhere in the middle there.

Ken McLoud 18:21

I guess. Here’s the like, let’s say five new properties dropped in your lap tomorrow. Would that be like. Hell yeah. We are going to have an awesome year.

Or is that like, oh, I don’t know if I can take care of.

Yonatan Schmidt 18:32

Definitely. We would definitely. I mean, we would say that was a good week. I don’t think that it would reflect entirely on the year. Yeah.

Or it could, it could be, you know, if it’s the first week or second week of the month, maybe, you know, that’s a good start to the month. So we would but we would definitely, you know, if it fits our rubric cube of qualifying owners and properties, then yes, we would take it on and we would not have a capacity issue.

Ken McLoud 19:01

Cool. Yeah. No I think we’re we’re demand constraint. Then like the business would be better off to get more high quality leads in the door 100% thing that’s constraining growth. So can you tell me about your your best channels specifically for getting those good leads in the door?

Yeah, I’m sure you have lots of leads that you guys wind up kind of pushing to the side. But what’s your best channels for getting the good leads?

Yonatan Schmidt 19:29

I mean, it’s referrals and networking. People who have been doing business with us, they know us. They know our systems and our processes. They value, you know, the partnership and the relationships and the the the value to our contractors and our vendor network, those. That is definitely the highest conversion rate, I guess.

Avenue, highest converted rate avenue that we have.

Ken McLoud 19:55

Gotcha. What are we doing to encourage those referrals?

Yonatan Schmidt 19:58

A ton. I mean, outbound, you know, outbound activities such as networking. I was just at an event in northwest Arkansas in Bentonville, a Bigger Pockets event on Tuesday. I’m going to an event tonight. You know, for some, I guess for some reason, I made top 500 agents in Oklahoma.

So they invited us to like a toast to the top or something like that. So I’m headed out to that. And, you know, you shake hands and meet people, rub shoulders, and then one on ones with vendors in our network, with mortgage brokers, with insurance brokers, with, you know, any trade, right, that’s out there, you know, whether it’s flooring or,you know, roofing or foundation or maintenance or electrical, plumbing, HVAC, all the trades out there that, you know, we rely so heavily on and we would be nothing without those vendors. We’re networking with them and we’re having deep, meaningful conversations, not just to learn more about their business and what are good referrals for them, but also educating them on our business and explaining what are the good referrals for us.

Ken McLoud 21:03

That’s awesome. So what are you doing? So you meet somebody at one of these networking events, let’s say let’s say rather than a referral partner, they’re a good potential property owner for you. What are we doing to get them engaged with Keyrenter?

Yonatan Schmidt 21:18

Yeah. I mean, it takes, you know, consistent follow up and follow through. You know, potentially, you know, let’s use an example from this past Tuesday. There’s a guy who’s a software engineer who was at this event. He just texted me last night.

And, you know, he was asking me if I could connect him with our agent in the Northwest Arkansas market because he wants to buy a duplex in house hack. Right. So I put him in touch with, you know, the great and mighty Daniel Gerardo from our office in northwest Arkansas who’s an executive broker. And she is really just a go getter and a wonderful person to I don’t know how she does it with raising five children as well. So she’s definitely busy. 

 And, you know, she could help him find a duplex. And then when he when he wants to house hack, he can essentially use our services for the other side of the duplex. Right. And we could find a tenant, we could lease the property, we could manage it, collect the rent, distribute the rent, handle communication, handle maintenance, provide him with, you know, financial statements and financial overview of his investment and so on and so forth.

Ken McLoud 22:28

You know, so I think I’ve got a good idea here for specifically for engaging people like that that you encounter at these networking events. And we want to kind of pull them into the Keyrenter ecosystem. So you’ve probably heard of the term lead magnet.

Yonatan Schmidt 22:44

Right?

Ken McLoud 22:45

So I’ve got a number of successful projects for clients across a few industries that are essentially AI powered lead magnets. So how this would work in this case is we’d come up with what some key bit of information that Keyrenter understands really well that that potential house hacker doesn’t understand. Right. Like maybe the first one that comes to mind to me would be something like what’s my cash flow likely to be in this situation? Right.

Am I just covering expenses or am I going to be cash flow positive here? You guys probably know the other stuff that are like the top questions on their head.

Yonatan Schmidt 23:31

I mean.

Ken McLoud 23:31

Like potential. Like what?

Yonatan Schmidt 23:33

What would something even rent for would be the first question. Right. And then yeah, definitely other financial KPIs and metrics like cash on cash return, your cap rate, your internal rate of return, so on and so forth. You know, for for house hacking that you’re say it’s called your debt service coverage ratio, which is your ability to cover the debt, essentially is what a lender would look at. And in today’s environment, if it’s not more than 1.1, 1.2, a lender may just say this isn’t a great investment investment.

Although if it’s a duplex and it’s also, you know, call it subbing as your primary, it may be something that an investor, a lender, would say yes to, right?

Ken McLoud 24:15

Yep. So so great example. How this sort of tool would work would be we’d stand up a landing page that you could then point people to at these events. Right. So like maybe you print a card with a QR code on it.

People do all sorts of like fun stuff sometimes. I’ve seen stickers that they’ll put on dollar bills. Right. And then you hand out the dollar bill like, hey, we’d like to make you some more money. Here’s, here’s some money. 

 And it’s got a sticker with a QR code on it, fun stuff like that. And then this landing page that they drive to. Importantly, we capture their email address. And then we also ask them kind of the bare minimum questions we’d need to ask them in order to answer some of these questions. Right. 

 It’s like in this case, maybe it’s the address of the property we’re looking at, or there can even be free form like free text questions about like, what’s your goal for this? Yeah. You know, the specifics would depend on which questions we’re trying to answer, but you get the idea. So then what we do is we would take the information that they put into that form, and we’d send it off to an AI, along with a pretty detailed set of instructions from you guys on how you would attack this client’s problem. So it would be exactly the sort of stuff you were just telling me, hey, in this lending environment, we’ve got to see this debt service ratio. 

 You know, this this particular market that you’re looking at is is really weak right now. So we probably want to throw like a 10% knockdown on the number we’d normally use to estimate rent here, all sorts of stuff like this. And that can just be a text file, like as though you had a human intern who was going to write these reports for people on their house hacking ideas. Right. And so it’s not code. 

 It doesn’t have to live in some special system. It can be a text file on a Google Drive that when you guys want to change this advice about debt ratios or about the strength or weakness of certain markets, you just open up the text file and change it like you were changing the SOP for a human. Yeah. So then we’d send that off to the AI and have the AI generate a custom report that are answering the questions that that this person’s going to want to know. So like in this case, it’s it’s those financials. 

 Maybe it’s got some information in there about what working with Keyrenter is like, what are the sort of problems that they’re not going to have to deal with once they hire you guys to take care of them? It can be branded. Maybe we’ve got a branded beautiful PDF here, but it’s not just a generic how do you house hack? It’s specifically about one, two, three Mulberry Street and how that market’s doing, how you guys would attack that problem. And then we email it to them, which was our excuse to ask them for their email, because these things will tend to take a minute or two to generate, especially if we got to go look up. 

 Maybe we call the Zillow API and look up the specifics on the property, let’s say. So now we’ve done a few really important things. We’ve captured their email. So you guys have an easy way to reach back out to them. We know specifically which property they’re looking at, which probably helps you vet whether or not they’re actually a good lead and worthy of your time to follow up with. 

 And perhaps most importantly, we’ve established Keyrenter as the authority in the space right there. The person who you come to to get the questions answered. They know what’s what and how to do this. Yeah, these systems have been super effective for turning kind of like tire kickers, people sniffing around the periphery, who you run into at these sort of events into engaged leads who are ready to get on sales calls and talk business.

Yonatan Schmidt 27:56

Yeah. Fascinating. I guess let’s talk a little bit about, you know, calculating whether a, an AI implementation is even worth it, right? What are the metrics that you know, anyone, whether they’re in the property management world or not, should be watching, right? Is it is it, you know, is this helping my labor efficiency ratio is it not?

What are you look at to say.

Ken McLoud 28:21

It would.

Yonatan Schmidt 28:22

It’s worth it or not.

Ken McLoud 28:23

It would super depend on the project in particular that we’re looking at. Right. So like to take that specific example. We were just doing their you can probably look at your overall book of business and determine that an average customer has this value to you over the customer lifetime. Right.

And that’s something we need to disclose here. But you could take you know, on average we make X dollars in gross profit from a client each month. And on average a client stays with us for 36 months or I have no idea what your number is. Maybe longer. Yeah. 

 There you go. Awesome. So then you can multiply those two numbers and know that, okay, a new customer is worth X dollars to us. So then we can say, okay, we only want to spend some very small fraction of that in order to go acquire them. Right. 

 So 10% or less probably the value of that client in order to go acquire them. So then we can look at how many new clients with this system have to give us in order to be positive ROI. Got it. Right. So like in this case, this is a perfect example. 

 There’s a very good chance in your situation that a single new client would pay off that system. And then everything beyond that single new client is just money in the bank. So in that case, you’ve got to go, like, do I believe this AI lead magnet system that we just talked about could get me one new client.

Yonatan Schmidt 30:03

Yeah.

Ken McLoud 30:03

If the answer is yes, then like, you should probably go ahead and pull the trigger on that. Because if it gets for everyone more than one that it gets, you know, you’re just money in the bank.

Yonatan Schmidt 30:15

Interesting. Let’s change course a little bit. Talk about, you know, risk reality long term thinking here. What what are some of the biggest risks or downsides of AI implementation that you’re thinking of and seeing that business owners aren’t necessarily thinking of right now?

Ken McLoud 30:33

Yeah, I know, I’ve got a couple great examples in this space actually. So I’m talking to a gentleman out of South Dakota who does. So he’s both the property owner and he does his own management, like what you guys do. He’s got a number of multifamily units, and he originally came to me looking for a call system, an automated call system. Right.

So like, somebody interested in renting an apartment, instead of having somebody sitting in the office taking those calls, he wanted an automated system to take the call. But a little bit like that conversation we just had started out going, okay, what’s a new renter worth to you? Right? Like how much? Take your average stay for a tenant and then take your average, say, monthly gross profit for a tenant and multiply those two out. 

 What’s it worth? And I won’t give his number away. But it was, you know, many thousands of dollars. Yeah. Okay. 

 And what percentage? By the time somebody is picking up the phone to call the office and ask about a lease, what percentage of those people wind up turning into tenants for you? He’s like, oh, it’s it’s pretty high. It’s probably 25 or 30%, you know, because nobody wants to pick up the phone. So by the time they’re picking up the phone, they’re pretty dead set on. 

 I’m renting an apartment. It’s just a matter of. From who? Right.

Yonatan Schmidt 32:01

Right.

Ken McLoud 32:03

So. Okay. So 25 or 30% of many thousands of dollars, let’s say, to keep it vague is still a heck of a lot of money. So each time that phone rings, it represents like a couple grand, potentially on that phone.

Yonatan Schmidt 32:18

Yeah.

Ken McLoud 32:18

Okay. So if the AI phone system isn’t there all the way, if it isn’t as good as a human, as a human at interacting with that person and getting them to the point, like, so what it there, we probably want them to come in and fill out an application.

Yonatan Schmidt 32:36

Right.

Ken McLoud 32:36

There, even a little bit. Not as good as that. How much money does that stand to lose us? And it’s like it’s significant, right? For all of these businesses, especially big multi family operations like that.

So like and then what are you paying that person to sit in the office and answer the phone. Like much less than many thousands of dollars per call. Right. Like, whatever their hourly rate is, they take I don’t know how many calls a day. It still is. 

 Is it? Turns out it is much, much cheaper to actually have that human answer the phone than to risk losing those customers to an AI system that isn’t quite there.

Yonatan Schmidt 33:17

Yeah, because that’s standard. The level has to be human. Even with AI, right? I mean, you call American Airlines, you call Southwest, you call, you know, Hotels.com, you get these AI bots, and the first thing you do is say, put a human on the line. Yeah.

Ken McLoud 33:33

Yep. And the like I know I do the AI stuff, right. And so they’ve gotten I so I’m always really interested whenever I’ve got to call something for personal or business. And I run into one of these bots. So I pay close attention.

They’ve gotten super good at synthesizing voices, you know, so it doesn’t at all sound like a robot anymore, right? It sounds like a human talking. They do the tacky, like you can hear the keys.

Yonatan Schmidt 34:01

Right.

Ken McLoud 34:02

In the microphone.

Yonatan Schmidt 34:03

Tacky? Yeah. Yeah.

Ken McLoud 34:05

It’s like. Come on.

Yonatan Schmidt 34:06

It’s like. It’s like a call center. You hear it in the background, and other people are talking in the background and like, people are typing.

Ken McLoud 34:12

Yeah, there’s always, like, a little bit too much lag, like a question that a human would just answer immediately. It’s got to go through the whole pipeline and bounce off a dozen servers. So it takes a little too long, which is the first thing. And then, man, if you ever interrupt it, it just becomes instantly clear that you’re not talking to a human. Like, they cannot handle interruptions the way a human can.

At all. Now, I want to hedge all this. Like you said, we’re having this discussion in February 2026. By a year from now, this might be changed. Right. 

 The level might have.

Yonatan Schmidt 34:46

Fixed.

Ken McLoud 34:47

Many or all of those problems, and then it would change the math on this, because if it didn’t do that, it’s probably better at following instructions than a human is, for instance. But right now it’s got all of these problems that and and even I as an AI expert, I feel this way when you call one of these lines and you get one of these bots that’s pretending to be a human, it kind of pisses you off.

Yonatan Schmidt 35:14

Right?

Ken McLoud 35:14

Like, it’s it’s something like it thought it could trick me. These people thought this was going to trick me. Like they don’t think very highly of me. They thought they were going to fool me into thinking this was a human. And it instantly turns me off.

And I’m sure if it turns me off, it turns non-ai people off even more.

Yonatan Schmidt 35:35

Yeah, although I did, I did come across one situation I’m not going to name the company, but it was. It was basically I received a full refund for something that, you know, I probably would have gotten a refund anyways, but it was for a non-refundable reservation and I went through the AI bot thing and it ended up like returning everything. So I got a full refund on it. I was like, I don’t know, $640 that I saw come back on my card. For a non-refundable hotel reservation, which I, you know, had every intention of using.

But, you know, the storm that came through in late January kind of messed things up. So, you know, that’s interesting. It can also make mistakes, I guess if you could give one, if you could give property managers one piece of advice about AI for, you know, over the next three years, what would it be?

Ken McLoud 36:34

So give me two. And they’re both stuff that we’ve talked to already, but I think they’re already super important. The first one is that one we were just talking about. That is especially when you have high value Do customers like, like tenants who are going to be with you for a long time and spend a lot of money, or in the property management scenario. Property owners who are going to be with you for for years and earn you a lot of money.

You want to think of this as you’re putting the AI behind you, so you’re talking to the customer and then the AI is behind you, super powering your operations. You don’t want to put the AI between you and that super valuable customer. Yeah, because it’s not there yet in early 2026. Like that’s going to wind up costing you money and hurting your reputation amongst those customers. So you absolutely do want to use it, but you want to use it to superpower your operations, not to come in between you and those high value customers.

Yonatan Schmidt 37:37

Yeah.

Ken McLoud 37:37

And then and then the second one is the one that we’ve already hit this drum at least twice. But you absolutely do not want to be a solution in search of a problem. So you don’t want to go? Man, ChatGPT is awesome. Where can we use ChatGPT in this business?

And we’re trying to come up with where to use ChatGPT. Yeah. Instead, you want to attack the business problem. And if there’s a good way to employ AI there, all the better.

Yonatan Schmidt 38:05

Yeah. Such as? You know, when ChatGPT first came out, I created a little bot with a Zapier, and I had it answer all my emails. Right. But instead of actually hit send, it just put them into my draft folder.

So that way when I wake up in the morning, I can just go through it and read everything, edit stuff, and then hit send. So I mean, it’s doing quite a bit, but love that. Tell us, I guess, what are you what podcast are you listening to? Books. Are you reading? 

 You know what’s inspiring you at the moment?

Ken McLoud 38:41

So let me think of some good examples here. The first one that came to mind is one that might be a little technical. For everyone else, it’s a little more on the the kind of math and science behind the AI stuff side, but is a YouTube channel called AI explained. Okay, they’ve got a Patreon to where they do more in-depth stuff behind the scenes, but if you’re interested, if you’re not necessarily techie like computer programming, but if you’re into like, the math and science side of this stuff, and also want to keep up on all the latest developments, that’s an awesome YouTube channel. And then from from the business side, I like Can’t get enough.

Alex Hormozi. So yeah, I’m just drinking up every bit of content that he puts out. Yeah. So that’s not he’ll mention AI plenty that’s not AI specific, but is a lot like we’re talking about here on attacking the constraints of the business. That’s like that’s the ammunition you need there. 

 Yeah.

Yonatan Schmidt 39:41

Alex Hormozi and I explained on YouTube. Ken McLoud any other final thoughts on the topic?

Ken McLoud 39:54

No, I think we hit it all.

Yonatan Schmidt 39:55

Yeah. Awesome. Thanks for watching. Ken McLoud from Laconic Tech. If you have any questions, people should reach you by going to laconictech.com.

Ken McLoud 40:07

Yep. I’ll spell it out. laconictech.com or my email is [email protected].

Yonatan Schmidt 40:18

Awesome. We’ll put those in the comments below so that you have easy access to them. Ken, thank you so much for educating me and our listeners.

Ken McLoud 40:27

Thanks for having me.

Outro 40:32

Thanks for listening to The Same Day Podcast. Tune in to a new show each week and be sure to subscribe to get future episodes.

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