SPEAKER_02 0:00

I think people are going to get excited about not supporting the Ubers of the world and instead supporting the local company that provides way better experience than Uber. I think that the opportunity from a customer service perspective and the relationship building perspective with some of the companies you're describing is enormous. And I think the consumer of that service is going to prefer that.

SPEAKER_03 0:52

Well, good afternoon, Ground Transportation Podcast audience. My name is Ken Lucci from Driving Transactions, and I'm here on a great episode. Unfortunately, it's without my partner in crime, James Blaine from PAX Training. I saw on Facebook he's traveling to yet another industry conference. Hope you're having fun out there, keeping the world safe. But I'm joined today by John Bruton, who I was introduced to by my CPA. And then I checked you out on Substack and looked at your bio and you teach operators and companies how to become AI fluent. So welcome to the podcast, John Bruton.

SPEAKER_02 1:35

Well, Ken, thank you so much. It's a pleasure to be here.

SPEAKER_03 1:37

I appreciate it. Give us your background, give us your career background, and what's the career been like the whole way? And then let's talk about what got you into AI.

SPEAKER_02 1:46

Uh, sure, absolutely. I'm uh I'm 45 years old. The long and short of my career background, it goes like this. I did my undergraduate uh work. I thought I was gonna be an academic when I was in my 20s. I I did my undergraduate work in economics at Harvard, and then from there proceeded to go and do PhD work uh at the University of Chicago, uh, also in economics. And so I was out there thinking I was going to teach, maybe go the finance route at some point. And I had a professor of mine come to me and says, says, John, said you're always talking about your family's business. I grew up in an entrepreneurial household, Kent. So my my father and grandfather had started an industrial distribution company uh called RG Bruton. My grandfather was Robert Bruton. He passed away in the mid-1980s, and so my folks then took the business over. So I grew up watching them build this business from under a million dollars in revenues to about, I would say, maybe 10 to 12 million dollars in revenue by the time I graduated high school. But needless to say, my entire youth was spent around the dinner table talking about business.

SPEAKER_03 2:53

And all as was mine.

SPEAKER_02 2:55

Yes. And so all family vacations were inundated with work calls and I know it well and all of those things. And so it was very much in my blood. And I loved those conversations. I enjoyed them. I think I felt probably closer to my folks getting to be a part of those and just really enjoyed understanding the business and the economic side of whatever interested me at any point in time. And so, anyhow, as I progressed into my life as an adult and was thinking about teaching economics and investing in these kinds of things, uh, professor of mine came to me and said, you know what? Those parents of yours, if they're ever gonna retire, they're gonna need to sell their company. And you're always talking about their business in class. I was always using that as an example and a way of understanding things economically. And so he said, you know, you should go to work for your family's business for a year, should help them sell their business. Uh, you're never gonna have more influence inside a business than you would inside of your family's business. And that would be great learning. It spent all this, all these years studying and reading and writing, and and and that was a fantastic set of experiences and uh early work for me. But he said, you should go do that, then come back, you'll have an interesting perspective because not many folks in academia have also been inside of the actual operator.

SPEAKER_03 4:13

Damn straight. They teach business management or operations, but they've never been in knee deep in a in a business day to day, seven days a week. So yes, good advice. He gave you good advice.

SPEAKER_02 4:26

He did, he did, and so I said, Okay, and I went to do that. I actually brought uh a really talented undergraduate uh with me at the time who was looking for a job and went to do that work. And my thinking was look, this is 12 to 24 months of work, and then I'll go back. But Ken, that 12 to 24 months turned into 12 years of work, and we scaled the business from about 25 or so million in revenues up to 75. We grew it across the Midwestern United States and the Northeastern United States, uh, a bit down in the south as well. We grew it into Mexico, into Costa Rica. We were doing inventory management systems. In our space, it was called integrated supply. I think Ranger, Fast and all. You walk into any manufacturing plant today, you see lots of vending machines in there that are holding all the indirect material. So these were cutting tools, grinding wheels, safety supplies, welding supplies, cool-ins, lubricants, anything that a plant needed to make what they make, we were going to supply those parts. And then our systems were really there to optimize the purchasing process and the inventory control process of this, so that they were running uh optimally profitable production lines out of their plants.

SPEAKER_03 5:39

With minimal leakage.

SPEAKER_02 5:40

Yes. Because you organize their inventory in vending machines, in vending machines and also inside of RFID controlled tool cribs.

SPEAKER_03 5:49

Correct. So nobody could steal anything, which is a huge issue in manufacturing.

SPEAKER_02 5:54

When we would go in and we would pitch new contracts, the guaranteed savings commitments that we would make uh at the start of any contract were largely based on our understanding of what the current leakage looked like and and knowing that if we were just reducing what was being, in some cases, absolutely being stolen and gone and sold on eBay and whatnot. Just mismanaged also. But then also the other thing you would see is this you would go into a plant, you would go to the different workstations, we would start opening drawers in the different workstations, and you would see cutting tools are small, you would just see thousands and thousands of dollars of tooling uh that was sitting there. Sadly, in many instances, it was often custom tooling that had been for a line that they were running two years prior, and they just never used those tools. They probably ended up buying more of those custom items, which of course are also the most expensive. And so we would come in, we would collect all the tools from all the workstations, kind of had a don't ask, don't tell policy. And they had a day where everyone could bring everything into the center of plant. We collect all of that, organize all of it. We had a an incredible uh person who managed our implementations and had a think it was like a 437-step uh smart sheet that was all gant charted for how to go from yes, we're gonna do this with you, to let's order all the parts, show up, do the implementation, and then train it and start managing.

SPEAKER_03 7:19

There people think cost containment, cost management is so unsexy, but it's the key to maximum profitability. Regardless of the industry, regardless of the margins, if you can affect that inventory by five points, that goes right to the bottom line.

SPEAKER_02 7:37

It does. It does.

SPEAKER_03 7:39

So you sold your parents' business, got them out of the business.

SPEAKER_02 7:42

And one of the things I would say on that front, too, I think is so important, is like the example I always use is this, Kim, is I couldn't agree with you more. Is that there's a reason Steve Jobs picked his operations guy to become the CEO after his departure from that role and tell these passing? But if you look at any business, in my experience, most any business, the profitability of that business, the value of the stock of that business is largely predicated on the efficiency of their operations. And the integrated supply, that the distribution, that's a thin margin business. You're the middleman. So in order to grow, in order to grow EBITDA, in order to get to a goal of a multiple that we wanted to get to someday. The only way to do that, I literally remember I was in Pittsburgh one morning. I was based out of Chicago for a lot of this, but I was in Pittsburgh one morning, I was walking, my parents' dogs with my father. I had gone over to their house early to get the day going. We were walking and we were talking about a contract renewal. The renewal was forcing us into a lower margin position with the client. We couldn't afford to lose. And I just said to him, I said, the growth of margin, the growth of EBITDA, the growth of profitability in our company is most largely dependent on our ability to just drive more operational efficiency. That we have to find the ways to reduce costs and do things more efficiently if we are going to create a more profitable business. Because in our space, the additional margin dollars just weren't going to be there otherwise.

SPEAKER_03 9:09

So they weren't going to magically appear. You just basically laid out in a completely different industry what I fight with operators every single day who hire us to value their businesses when we send them the results based on knowing the market better than anybody, they're like, I think my business is worth more. Right. Okay, it's not rocket science. These things have to change. Yeah. Top line revenue, margin increase, lower your expenses.

SPEAKER_02 9:40

Yeah.

SPEAKER_03 9:40

That's it. So you sold your parents' business, they retired.

SPEAKER_02 9:45

They did. And we actually just interestingly for the podcast audience, it was interesting. We actually went into the conversations just before in March or January of 2020. Wow. We went out, we met with the potential buyer. We're excited about this. It was a strategic acquisition. And we had, you know, met with other buyers over the years, and nothing had ever worked out. And so we were feeling good about this one. We get home and the next week the lockdown started for COVID. We convened with our you know the colleagues and the counterparts. And it was okay, all bets are off. Let's get through this. And then we did. And we went through that whole process. We did not have any layoffs during COVID, went through the whole play retention credits, PPP loans, all of that, fought through it successfully. Came back around into January of 21. Conversations reconvened, and then we sold in August of 21.

SPEAKER_03 10:39

So and so you've been consulting since then?

SPEAKER_02 10:42

Ever since, yeah. The 12-year foray into industrial distribution was incredible to me. And I can't say enough about uh manufacturing and all that I learned and the wonderful people I met and the wonderful towns I got to visit. But I was ready to be done with it. So organically, a consulting business grew for me from there. And uh so I started doing that. And then about two and a half years ago, or almost three now, a couple things happened. Chat GPT came out. And at the time I remember people talking about AI, and really the application that I was leading with that was saying was the most AI uh native that I was working with was probably Grammarly at the time. And then but then chat came out, and I had uh I had a client and I had an intern uh who was helping me on a data cleansing project for this client, it was a furniture rental business, and I was working on uh this this data cleansing project for an ERP system that we were gonna implement. And the intern was a college student, had not ever done any uh Excel work in his life. And so I gave him kind of a large task on the first day to kind of see what he could do. I also gave him a $20 a month premium ChatGPT membership, which was the highest end one at the time. I think he came back 24 hours later with all of the work done as well as I would have done it. I said, How did you do this? And he had JackGPT help him write some Python code. He fed the Python code into Google Script Editor and then created all the sheets in Google Sheets that I needed, did all the data cleaning work with these scripts. I sat there in the office and I thought to myself, I'm irrelevant. I love Excel. I am an Excel wizard, as I'm sure.

SPEAKER_03 12:27

My business partner does things with Excel that I don't even think the original Excel programmers knew how to do. Everything we do is in financial packages, is in Excel.

SPEAKER_02 12:39

So I had this moment and I said, Oh, okay, I need to put all of my workflows and all of my client work through these systems. So I started the time, I was working with Chat GPT, uh, Anthropic had launched Cloud, and then also I was working with Gemini. There are other tools and things that came along. I started working with Perplexity as well. And I just said, okay, the future of how companies operate, especially when we're handling key operational departments, accounts receivable, accounts payable, customer service, inventory management, all the key operational tasks, organizing of data for sales teams. I said, Well, this is all going to go through these systems. And so I started learning how to train models on the time, like building GPTs was really the way you did that. And so I was learning how to train models on client pricing information to help customer service people more quickly calculate discounts and deals that the salespeople were working with leads and how to manage inventory, eventually how to begin uh connecting the reporting and data analysis that we were doing, and then feed that back into ERP systems, CRM systems, and whatnot. And so it all just evolved from there. And so now what I would say today is we talk about AI. I want to teach people to become AI fluent in terms of being able to push their entire workflows through these systems and be fluent the way you would become fluent in a new language. And then I want to help companies to become AI native. So I want first principles, workflow, and operational thinking fed through these new systems for how to build agentic teams and workflows uh that can help companies to uh operate more efficiently and help their best people to spend a greater share of their full-time hours each week doing the work that is most critical for their customers or that is most helpful given the various types of skills that their teams and employees have.

SPEAKER_03 14:38

So driving transactions is the only financial analysis, strategic consulting, and MA advisory service that does nothing but passenger transportation. We have my business partner and I, and two researchers. We started this in 2018. Okay. We went full-time during COVID because banks were going out of their mind. They were going to repossess things, and all the banks had gotten rid of all their analysts. So we actually started working. We sold a few companies before. We started working with lenders, buyers, and sellers. Anyway, since the start of the company, we have financially reviewed and analyzed KPIs for over 330 companies, all in transportation from a million to 500 million. The biggest we ever did was a $500 million motor coach company. We were brought in before the bankruptcy to figure out what they wanted to separate and keep anyway. And our industries, most of what we do is on the Schauford side and the taxi side, and then we also do motor coach, but I'd say about 70% revolves around the Schauford. Schauford and Motorcoach is about a $20 billion industry in the country. Schauford has been disrupted by Uber et al. since 2012. They really started kicking ass about 2016. To say that our industry, the Schauford industry, is technologically and technology challenged, is like saying I'm challenged as a basketball player. We are so challenged that even the biggest companies in our industry that we've reviewed, and we've been blessed, we consult for, and literally every single president of every network is in my cell phone. And if they have any kind of questions, we're there. We have a lot of retained clients. We've reviewed a lot of the big networks before they came up for sale and as they've come up for sale.

SPEAKER_00 16:34

Interesting.

SPEAKER_03 16:35

Would it surprise you if I said that let's just say for the sake of argument, a hundred and fifty million dollar company that has 750,000 reservations a year to go to and from the airport, groups and meetings, et cetera, 80% of those reservations are taken manually. And they first of all, they're almost all manually input, but they're always scrubbed. But about 80% of them come in by phone or come in by email, and they have to be manually key-punched. It's killing the industry as far as market share growth. I've I sometimes um the canary in the coal mine, other times I'm a pain in the ass because I grab onto something and I don't let it go. The market share for sedan and SUV service, which mostly goes to airports, is about seven billion dollars. Passenger, airport trap, passenger trap.

SPEAKER_02 17:28

I have to tell you, I love these are stats I did not know prior to this conversation. And this I love that this is fascinating.

SPEAKER_03 17:35

Okay, so seven, John, it's all I do. It's all we do. I don't have any hobbies, right? That's all I do.

SPEAKER_02 17:41

So I don't have any hobbies either. This is all I do.

SPEAKER_03 17:44

So this yeah, it's all data, and it's all data. Okay. So the Sedan SUV business is about a seven billion dollar industry, right? Okay. But if just three, if you could just transport the top three percent of air air passenger airline passenger travelers, the wealthiest that sit in first class or go private, it's a $35 to $40 billion industry just in the United States alone. So what's holding it back? Every time you scale by a million dollars or maybe two million, you have to add a person in reservations and a person in dispatching, right? So knowing that 80% of what we do is a manual process, knowing what you know about AI, how can AI help an industry like ours? Service industry, in sales intake, reservations or order intake, 80% of it's a manual process, dispatching logistically managing that trip, assigning the driver, tracking the vehicle and the driver, and making sure the trip gets done is another manual process. Where do we go from here from an AI perspective?

SPEAKER_02 19:38

There are a number of places to go, but a couple things to start with that I'm very clear about. Number one, the next shift that we are all going to be talking about and experiencing is not going to be the robots from Tesla, though that will come and that will, you know, robotics and whatnot will eventually become part of this. And it's not going to be autonomously driven cars. There's a place for that somewhere in the future. But the next revolution that will hit with all of this that will impact all your consumers, because the thing you're describing here too is that this is a business to consumer play. You have to have all of these individual people that you're providing this quality of service to and this delivery service. It's a very personal service. They get off of a plane, they're away from their families, there's stress, they get in the cars, then they want to have personal conversations. And it's all is a very personal thing that these companies do. Here's what I would say. I'm clear on it being B2B, but I would say that the level of service experience and the seamlessness that needs to be in place for this kind of thing to work is, I would say, higher than a lot of other B2B businesses I've worked with.

SPEAKER_03 20:47

Ritz-Carlton experience, federal express efficiency.

SPEAKER_02 20:52

Yeah.

SPEAKER_03 20:53

Those two things. Yeah.

SPEAKER_02 20:54

So what I would say is this that the next thing that is coming that is already happening, but that is going to be a wave, is that we are going to move to a voice-first world. And so what that means is that voice-based agents, chat-based agents, and voice-based agents are already becoming much more predominant and much more capable than they were even six months ago, much less 12 months ago. But the voice first experience and our comfort as consumers with speaking to AI agents who speak back to us is something we all know and we experience now in certain customer service environments. But the quality of the questions, the quality of that experience is going, uh, is going up. And we are also going to be shifting to a world where we're going to be doing a lot less typing on our phones and typing on our computers, and we're going to be dictating. Uh, the the biggest shift that's happened in my work because of all of this over the last three, four months is I put WhisperFlow on my computer, I sit here, I click my function key, and I talk into chat and Claude and I talk into all my systems all day long, telling them what I want them to do. The biggest, most complex work I do, I don't start by saying, Oh, I need to type all this. No, I say I need to dictate exactly what it is that I'm looking for into these things. And so I think as the voice agent becomes better and becomes world class, which that is happening, we are going to get there shortly. In some instances, I would say it's already there. As that happens and as we're able to begin distributing a lot of those interactions and engagements to more of a voice first agent approach first of all the that will dramatically control your cost it will also lead to a much more accurate um and timely experience for the customer because the voice-based agent is able to perfectly reference against the database that underpins the business that tells all the specifics that need to be understood about logistics about traffic patterns about flight delays about all the minutiae all of granular elements that create the best experience for the customer who is being picked up in a chauffeured car at an airport the agent is able to have perfect recall against the underlying data set and so that creates a I think a more reliable and higher quality customer experience and some look some of this will be voice based some of this will be text based people are comfortable using Uber and using some of these other applications and it'll be omnichannel.

SPEAKER_03 23:46

If I want to call it whatever I want to do your point is those things will be available and on the other end it's going to be an AI agent.

SPEAKER_02 23:55

It will and what I would also say is this I think in talking to my friends and in my own experience I think people are going to get excited about not supporting the Ubers of the world and instead supporting the local the local company that provides way better experience in Uber. I have some great experiences with that at times I have some really not so great experiences at times. I think that the opportunity from a customer service perspective and the relationship building perspective with some of the companies you're describing is enormous and I think the consumer of that service is going to prefer that I would much prefer that I know personally I need to stop you there.

SPEAKER_03 24:42

Sure and I want the audience to know that you and I have never spoken before today we've emailed we've emailed not a single word.

SPEAKER_02 24:51

We've never scripted this okay no yeah I no questions in advance I had I had no idea what I was was I was going to sit down for today.

SPEAKER_03 25:00

What you just described is what I have been arguing with some of the largest networks and the tech people in this industry for the last year. Hi this is Ken I need to go to Salisbury Airport tomorrow morning American Airlines flight 231 what time should I be there? Pick me up at the house I have one house I have one home airline right airline that airport right I have one office typically you know just to send me a text message with whatever time I should be ready. And at the end of the day did a lot of traveling this summer some of the reservations I had to make with customers and non-customers in the industry they were excruciating. You make a phone call they never use your name right my credit card is on file because I know when I call in the guy didn't take my credit card but he never used my name it was a five minute call to say take me from the airport to such and such a hotel it was excruciating. Absolutely I don't get a text message I don't get text messages saying my car's on the way a vehicle on location what I get is a phone call from the driver in broken English mispronouncing my name asking me where I was going to meet okay so the bottom line is you hit the nail on the head in reference to the experience the experience is our secret weapon and people will pay for it they will it's like this if I'm just mailing a pill I'm going to use a stamp okay but if I'm going to send a contract I'm using Federal Express. Our industry is not going to capture every single trip a $25 trip 20 minutes downtown that's not what we are we don't want that trip. So how does this happen? We as an industry are small we have a grand total of four major softwares four reservation and dispatching softwares and they're all owned now by a fantastic company that's got more money than God. I hope the people from full steam are listening because I said you were a fantastic company but I also said you have more money than God.

SPEAKER_02 28:33

So the question becomes how do we get to the point where we can offer our clients a seamless AI concierge if you will to do what you and I just talked about I mean look there are companies and there is technology out there some of which I work with on a weekly basis that is uh uh top grade when it comes to both voice and chat based agents and and what will also be happening is the frontier models so when we talk about frontier models we're talking about chat GPT's models, anthropics models, Google's models with Gemini so those models in those platforms are going to become more flexible and capable and some of this will be enabled there. However I think the voice-based agent side within companies I think that is something where there's a specific niche of providers who do that work. And so I think that is a big part of it training uh those models on accurate information is critical. One of the things that I would say based on you know I've spent my whole career working with small and midsized companies give me some revenue when you say small to mid size what do you mean? I would say companies doing 3 million to 20 or 25 uh million a year in private equity terms they would say well small goes all the way up to 250 million and then anything above that becomes mid-size and then so on and so forth relative to context sure I understand that but when I think about this I'm looking at the different uh stages of scalability and professionalization that happen when you're going from three to five five to 10 10 to 15 15 to 25 25 to 50 there's also different amounts of capital that those different size companies have to be able to invest into the right technology to move them forward. One of the biggest challenges you see with enterprise software companies is a five or $10 million company buying an $80,000 a year Salesforce instance or something that is way more way more plain than they need to operate their company. So I think there is this question around okay, we would use voice and chat based agents and there are clear providers out there to work with and to get that work done. However, the other first step I would say first most important and most challenging but also the space where there's the greatest opportunity is when it comes to the quality of the underlying data that these models are calling against and the quality of the information that they are able to pull against. So for instance when you're talking about logistics and you're talking about the different customer service standards and how the companies want the agents to handle different tasks and different questions and different outcomes and inputs, the companies have to get very clear on the customer journey and what are all the all the different decision points along the way. How do we want the agents to handle X or Y? Oftentimes with models people say oh the model's hallucinating it doesn't know what it's doing. It's giving me crap back from the queries I'm making and what is happening is this it is usually a problem of context. So the user has not inputted or prompted enough context enough clarity around what it wants the model to do. So what does the model do? It makes assumptions. My intern with the spreadsheets, he's gonna go make some assumptions and there were some things that were a little off with what he did, but it was great work and the places that it was off were based on assumptions he made because he didn't have enough clarity about exactly what I wanted in a couple places. Same things happen with models. And so then to the extent that you're going to now deploy voice and chat based models to interface with your customers well you better be pretty darn sure that they have access to all the right information and that they understand the logic of your customer journey.

SPEAKER_03 32:22

Let's just stop there for a second. This is no different our industry after COVID we couldn't get anybody to come back to work in reservations or dispatch before COVID there were companies that were going over to Serbia to use their call centers. What you're describing to me is a complaint I hear operators talk about with remote workers they just don't know I said okay what have you provided them for training what workbooks what training have you put them through you're making the assumption that they know how you want that handled. And what you're talking about is the AI learning models you only get out of them the good data that you put into them and at every crossroad you have to say this is what I expect or if this happens do that correct because you have to be specific it's why if I sat down with Claude after this call and I tried to start talking to it about building out valuation models for transportation companies I would feed it my best guess on some of these things.

SPEAKER_02 33:34

But if you sat down and had that conversation with Claude your output is going to be much much better than mine because you can provide all kinds of context clarity and specific market data and examples market data spreadsheet all this stuff that granular metrics past transactions the whole thing. But that doesn't mean that just because we bought that therefore we suddenly have uh the same level of expertise that someone was talking about the other day talking about Warren Buffett having gone through like the Moody's and he would read about 800 companies and consume all that information. Well Clot or ChatGPT could do that in a heartbeat for you. And the thing that I said in that conversation, I said, sure it could, but just because Clot or ChatGPT could do it doesn't mean that I would then be able to take the time to consume all of that information that it put together and learn it and know it the way Warren did after he went through Moody's and did all that studying and that work. And so the things that we know from our prior experience how we've built our expertise and how we will also choose to continue building that expertise matters deeply with the quality of what we can deliver to these models to produce the right output.

SPEAKER_03 35:04

No question about it. What you're saying to me makes perfect sense. You have to train it like you're training an athlete with the fantastic genetic starting point. Right? Correct there are in every professional sport we know them. Genetically they're superior genetically they come to the game with much more than any other player but they still need the trainer they still need the coach. So it's the same thing with these AI models. Give me some prognostication on the voice models I hate to say it right now I can order pizza okay from a local pizza shop and I don't have to talk to anybody I can do it by phone I can do it on their app right sure I don't think I can do it by chat on their website but I can call it I can call a special line and I can say I want a well done medium pepperoni this is Ken Lucci same as my last order. Sure you can't do that you can't do that in our industry it drives me out of my mind all I want is a favorite all I want is to put my favorite reservations in and say to the company hey pick me up at the house I'm going to Salisbury airport flight 125 just text me when you want to pick me up in the morning I just we don't even store favorites a person makes a reservation in certain reservation systems they have to repeat everything. Now the smart companies create accounts for every single person that calls in sure there are some reservation systems who shall remain nameless who don't think that private individuals deserve an account and we go into our customers and we take all that data apart and we say here look at the zip codes of where all of these clients are that's where your next private client is coming from. But anyway so when do you think the voice agents are going to be as good assume they're well trained as a standard reservation agent.

SPEAKER_02 37:06

I think within the next 12 months I think if I were running a company like this right now, I would be going all in on it in the immediate to learn it and to build that underlying fortress source of truth database that has all the customer details think about it like this one of the customer service opportunities in an environment like this is if the customer is aware that the calls that are happening are also being transcribed, that things are being mentioned think about one of the greatest things in customer service is this if you know your client's kids' birthdays, if you know the wedding anniversaries the whatever the significant dates are in their lives, you know those things, you track against those things, you send them a special gift on those days hey you're doing a pickup on one of those days they might be traveling on one of those days and need one of your cars for a wedding anniversary whatever the case may be and you are showing up having an awareness of that when I talk about the models having full awareness and perfect recall against these data sets I think many companies have tried to execute on what I'm describing here with really disciplined wonderful teams and some do it really well and some don't do it so well. And because it's hard when it is all human-based and we're relying on so these kinds of tools enable that level of service to then be delivered and remembered and hit every single time and so I think that we are within 12 months of the models being in a place where the quality of the experience is akin to what you would experience on the phone with somebody it doesn't also have to be that it is the same as what happens if you call the Ritz or a four seasons or whatever. But the thing is this what additional value could the customer get maybe the customer doesn't expect it to be just like calling John and John helps them. Maybe if they know that the call is also going to produce query them against oh well do you want us to have flowers waiting for you? Where would you like us to pick you up? Oh what are your preferences once you get in the whatever it is like there are all kinds of additional services and additional value that can be delivered from a customer service standpoint in those interactions. And if the models are able to either handle it via voice or via chat in a more reliable way than a person might be able to, I think the customer is going to be on board. The other thing I would think about is this if I were running a company right now in the concierge and limousine space, I would be saying okay some of my customers are going to want a premier tier of service where they still talk to a person when the person no longer needs to handle all these details and all this other stuff because it's already been handled, then wow, what are the upselling opportunities and what are the kinds of things that getting to talk to Ken is going to enable for my for my company and what kinds of additional concierge services could I provide for the customer on that trip and what kind of relationship do I end up building with them because of that. I think the the opportunities are I mean are significant.

SPEAKER_03 40:25

I'm gonna tell you you're a hundred percent right I'm gonna tell you about an onboarding experience I had so part of what I do is I do a lot of travel on my own and sometimes I don't want to use customer right I might be going to New York to meet with an investment bank and I don't really want my New York customer to know where I'm landing right so I was using a company that now is owned by Uber or I heard it closed yesterday called Black Lane and I won't use them anymore because they're owned by Uber. Anyway so there's a there's a new company in New York called Wheelie W H E E L E Y. So I signed up on their website next thing I get an email saying Mr. Lucci I'd like to have an onboarding call with you I said okay I'm a single traveler I'm a consultant I'm not a big corporation no no we'd still like to have an onboarding call long story short the guy nice kid he's in London Monday morning we talk tell me about your travel where do you go what do you like it was the fantastic onboarding company that experience alone was more than anybody else in our space does. But then he said Ken I I see that you're a consultant in the industry and he kind of threw me he said because my CRM pulls everything I can find about you you really have a great reputation in the industry. Why are you using Wheelie? And I told him look sometimes I have to fly to London and I don't want to book for one of my clients because I don't want them to know who I'm meeting with and I was using Black Lane but now that they're owned by Uber I won't use them. He said yeah Ken I've got your LinkedIn profile pulled up I've got your website pulled up I've got all this and I said how are you doing that he said it's our own internal AI CRM I was floored.

SPEAKER_02 42:13

Yeah I I know I know the CRM they're using right to finish the build with it but yeah it's unbelievable you can get all that yes yeah but the reality is what you're and again you and I have never spoken about this.

SPEAKER_03 42:26

No we have not you're preaching the same thing as someone who didn't know the industry we literally nailed it the experience is what is our differentiator. Absolutely and I don't care who our competition is from an Uber perspective or a taxi perspective there's a level of clientele where the trip is so important the passenger is so important they have to use the highest level of ground transportation possible and that's our edge and unfortunately our tech needs to catch up fast. And what I would say is the ability to the ability to expand into additional types of services and things that would drive more revenue that would create that would create a broader company all of that is tech dependent just the ability to proactively know that John's birthday is the second week in October or John's wife's birthday is the second week in October but to be able to send John a message John do you want us to have flowers delivered are you thinking about taking your wife out are you going to need any transportation in the future they don't need to know it's an AI that found that out I think that that's one of the things that I feel pretty strongly about is you know all these debates that we have right now around AI writing versus non-AI writing did an AI do this did an AI not do this the models are going to become so ubiquitous across our it's going to be like water and it is they are going to be so omnipresent it is just a new type of computer.

SPEAKER_02 44:00

And so it will yes obviously AI did this or AI did that and that's not really the point. The point is what is the output what is the outcome what is the ease of experience that a customer has if you look at any of the the data that's coming out of McKinsey Boston Consulting when it comes to marketing and customer experience in an AI first world what you see is that they're talking about increasingly more and more individualized customized experiences for each customer so that Ken gets one experience John gets another experience they're both equally as good but they are specific to Ken and then specific to John and that is what creates loyalty. And so I think that's just one of the critically important parts here. And I think that the venture capital firm Andreessen Horowitz released at the start of the year all of the top market sectors to be looking at for AI investments for this year. And overwhelmingly you look into the luxury goods space and you look into luxury experience and concierge based services for people, people are going to want more and more and more customized concierge grade personalized experiences that help them navigate their life. And yes if AI enables that well that's great. But it's really about what is the what is the work or the thought that is being taken away so they can focus on the things they most want to focus on is time being the most valuable asset. There's an extraordinary opportunity for the right companies thinking in the right way. And what I would close with on the topic would just be to say that the the ability for small businesses to do this in a highly cost effective way is unparalleled To prior technological revolutions. The current legacy enterprise grade software is much more expensive to go out and buy and implement and manage for any of these companies right now than it would be to do the necessary investment into the right AI platforms and tools to do all the things that we're talking about right here. It's just the cost is the unit economics of it are better for small business and mid-sized businesses than has traditionally been during moments like this.

SPEAKER_03 46:15

Okay. So I'm going to interpret that as founder-led businesses. I'm just going to say any founder-led business can do this easier than the biggest conglomerates that are out there.

SPEAKER_02 46:27

Yes, this is a thesis of mine that I write about. And, you know, Ken, I'm I'm I've been wrong about more things than I've been right about in my life. And so I, you know, I put these ideas out there respectfully. But what I would say is this I strongly believe that the stories about AI transformation not moving along fast enough, the problems that large companies are having in their organizations, I don't believe that those are technology problems. I believe that those are bureaucracy problems.

SPEAKER_03 46:56

No question about it.

SPEAKER_02 46:58

And what I would say is that the opportunity for small and mid-sized companies in any B2B space that I've worked in right now to become AI native faster than their much larger competitors, to lead them to a better set of unit economics than their larger competitors, to lead them to more market share, more price competitiveness, whatever the case may be, depending on the market, the opportunity there for small and mid-sized business is, I can't think of another time when it has happened in this way. Historically, these things happen and the large companies first take all the advantage and then eventually it trickles down to the smaller companies. I think in the 12 and 24 months to come, where we're looking at what are the big lessons for how AI transformation happens inside of companies, I think we're going to be looking at the small businesses that have 10 and 100x in that time and what they did by becoming AI native faster than the big guys and then taking market share from the big guys. I think we're going to be looking at those stories in case studies more so than we're going to be looking at what a large conglomerate did.

SPEAKER_03 48:11

I a thousand percent agree with you. And let me tell you why you're absolutely right. The small businesses are closer to their customers. The small business owner is, and I don't care, go up to 50 million or 100 million. The founder-led business has got to manage his client relationships and is much closer to the people who are delivering that service and much closer to the client, the client journey, and has the ability to change it faster. We have a huge client that we do business with, and it's a level of frustration that I haven't felt since I've worked in corporate America, right? Anyway, what you're talking about, the small business has is the agility to move quicker. First, they know the granularity that needs to happen on the customer experience level. Whereas the big companies that, especially the ones that were built solely on tech to begin with, they're gonna have a tough time. At the end of the day, I I do believe that the you're right from the perspective that back in the day when all of us could build websites that made us look like a gigantic company, it was an equalizer. In this case, I think it is the faster moving business owner that knows the pain points that they need to solve the fastest, and also knows the level of customer intimacy and experience that they want to deliver. I mean, we did the birthday cards, we did the proactive phone calls and emails saying you took your wife out on your anniversary to burn steakhouse last year. Can we make that reservation? We did it manually, but you hit the nail on the head. It was extremely tedious. You're talking about now having an unlimited ability to do that.

SPEAKER_02 50:09

What I would do there's a book called Unreasonable Hospitality and another book called Set the Table. Uh that are Danny Myers. Yes. And these are the best customer service books I've ever read. The history of Four Seasons at Hotel, I forget the name of that book, but it was written by the founder. It was also very good. But what I would do is this I would take those books, I would try to get them in digital form, and or get an audio and transcribe them or something, which I maybe you're not supposed to do that, but I would do that. And I would then take those files, I would feed those files into Claude or Chat or Gemini or wherever I was, and I would explain my business to the models, but the models don't really have context around it, and I would say, hey, I want to understand based on all these ideas in set the table or unreasonable hospitality. I want to understand what are 10 ideas for how we could build agentic teams that could help us execute on these strategies for our clients in the limousine business and walk me through what the ideas are and how we could do that, the types of data we need to store, the questions we need to ask, answers we need to create, the database we need to keep. And then help me figure out how do I go about the business of building those skills, scheduling those tasks, building out the capacity to do it. And then I would start executing against that. In some instances, take out the voice agents and all of that. It might just be what kind of an interface can I create that is feeding back to my in-person call center team and just giving them the right questions to ask based on the conversation that's having and the right data in front of them.

SPEAKER_03 51:57

Hey, Ken, you're still at 4146 Rivermere, correct? Do you want us to have your coffee ready, four skim milks and one sugar? Do you want us to have that in the car? You're a thousand percent right.

SPEAKER_02 52:06

Are these companies transcribing the calls that are coming into the call centers? Are they recorded? Most of the larger companies have them recorded. Yes. The moment the calls are recorded is the moment you can have a transcriber that then takes that transcription and you can then run the models over top of that transcription after every single call to say who's the customer, capture all the details that are described in it, place it over here into this database. I mean, you can that is simple. Like once you understand the sequencing for how to do that, the ability to stand something like that up, that is a matter of weeks, not even months, to get that stood up so that every call from a customer, all of those details, how they like their coffee, oh, they mentioned their wedding anniversary in here. Great, we got that nailed down. And the the customer, the only way they realize is oh, they're really paying attention to me when I'm talking. And that functionality is already there. I'm telling you, just based on having the transcript from a call, I mean, that's gold. And you don't, you don't, it's not expensive, and you don't need, I mean, it's just like, but here's the thing figuring out all of the underlying parts of the customer journey, the questions to ask, how to then run the agents against those calls. So every call gets that service, building out the right database to do it. It is very doable work over a short timeline, work that used to take five, six months to put together, you can now do in a matter of weeks. So it is not that considerable uh thinking and work has to be done to get these things in place. The point is it's very doable and achievable at a much lesser expense than would have been required previously.

SPEAKER_03 53:55

And you know, you're preaching to the choir, and again, I'll say it for the third time. We didn't rehearse this. We did not, but we are building a course for our retained clients on a growth flywheel. I've become obsessed with growth flywheels. Sure. And and and it starts with our competitors, and many of them in our industry actually, but our biggest competitors are all transactional. They're all transactional. So therefore, we have to be more relationship-driven. We have to drive the relationship. Everything you're talking about is moving us in that direction. And I would just encourage the software companies that are listening, or even a new software company or programmer. We've done a masterful job in years past at designing software that dealt with the transaction. In the future, to increase market share, we have got to build a full enterprise software suite that not only manages but enhances the relationship. Every single client should have their own, every passenger should have their own profile, every corporation their own profile with their likes, dislikes, hot buttons, etc. etc.

SPEAKER_02 55:14

It should be a fair family, and so you should the corporation is the parent organization. But then when you go into the subfamilies, that would be all the individuals who use the service, the same level of granular detail is calculated.

SPEAKER_03 55:26

How often do CEOs or even executive assistants or management change jobs? Right?

SPEAKER_02 55:32

I've sold a lot of new business over the years on the basis of people leave one company to go to another. Someone calls me and says, Hey, I'm leaving ACME and I'm going to spacely Sprockets. Uh great, let's go talk to Space Lee Sprockets. I'm gonna take you out for lunch your first week there to just see how it's going because that's the next opportunity.

SPEAKER_03 55:49

100%. And now there's so much data out there in the ether. Yep. And like I said, when I was onboarded by that company, I was shocked how much they knew about me. And I was very impressed, and I think that's where we have to go. So, John Bruton, this is not going to be our last podcast, and this is not gonna be our last conversation.

SPEAKER_02 56:11

Just two things in closing here. Number one, one thing I would say is this for anyone listening to this who is a business owner, and you're looking at how do we use AI, how do we optimize, I would imagine most any of the business owners listening here have deployed chat or Claude or Gemini or one of the things.

SPEAKER_03 56:29

In the most rudimentary ways, but you're absolutely right.

SPEAKER_02 56:31

We're using them. But what I would say is this in the past, when you deployed a new piece of software, when you had to learn to use Excel, there was one way, maybe two ways, to go about doing things. You always went to the same module inside the ERP to perform that specific function. And the process had to be performed the same way every single time. And remembering that process, training the people on the process, learning, oh wait, I'm doing this, I'm going here to do this, but oh, that's actually for this over here. People they struggle to remember all the specifics because there was a limited number of ways to get things done. What is true about working across OpenAI's platform, Anthropics platform, Google and Gemini's platform, Perplexities platforms is that these are the most flexible application and computational platforms we've ever worked across. There are many ways to do things. To learn how to do something on one of these platforms, the best thing you can do is ask the model, how do I do this? Can we do this? What do you need from me in order to do this? Teach me how to do this. And so what I'm saying to small business owners out there listening to this is that that means these tools are more easily trained on and learned and implemented and integrated into your operations than I would imagine any other piece of software or tool that you've purchased and tried to use. Uh, it doesn't mean that there aren't challenges and that you don't need to be really thoughtful about how you do it, but it is the space between wherever you are now and becoming AI fluent or becoming AI native as an organization, it is a shorter delta than between any space that you've ever looked at in terms of technological capability in the past.

SPEAKER_03 58:22

As soon as you take the first step, you're that's number one. You can't sit there and not change. Yesterday is gone. Today's a new day. John Bruton, tell people how to reach you.

SPEAKER_02 58:33

So you can find me at uh operating by johnbruton.com. That's my best-selling Substack newsletter. Uh, there's an absolutely a free tier to that. I would love to have you join that and start reading what I'm writing. You can find me on LinkedIn. I'm over there every day. And then you can also reach me at John at sixap.com. So feel free to email me, ping me on Substack or on LinkedIn. And I would love to hear from you. Or ask, if you know Ken, ask Ken for my details. I'm sure he has them too. And the absolute last thing I would say, Ken, is the ERP system that you're talking about that you had such a great experience with, with the new company you're working with. Here is the statement on AI. I know the ERP system that they're using for that. And what I can tell every other small business owner out there is that it is the best and most affordable ERP or I'm sorry, CRM system that you have ever bought. It costs a fraction of what Salesforce or HubSpot or any of the other tools would cost. And it does exactly what Ken was describing. There's there's immense opportunity uh on the CRM front in this space. So anyway.

SPEAKER_03 59:39

John, this has been a fantastic episode. I know that my ground transportation podcast audience, the owners that are out there, are going to be blown away by this. It was absolutely more than I expected. It's not going to be our last interaction, I can promise you. John Bruton, thank you very much for agreeing to do this and ground transportation podcast audience. All we're here for is to add value and get you thinking about what the next step in building enterprise value is. So thanks and have a great day.

SPEAKER_02 1:00:11

Thanks so much, Ken. Have a great day, everybody.

SPEAKER_01 1:00:15

Thank you for listening to the Ground Transportation Podcast. If you enjoyed this episode, please remember to subscribe to the show on Apple, Spotify, YouTube, or wherever you get your podcasts. For more information about PAX Training and to contact James, go to PaxTraining.com. And for more information about driving transactions and to contact Ken, go to driving transactions.com. We'll see you next time on the Ground Transportation Pod.