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Why AI Needs to Understand Your Dealership Before It Can Help with Mike Gilson · Auto Collabs

• 0:00
  It's not uncommon for a great salesperson, as an example, inside of a dealership, to have five different screens open, pulling together kind of that breadcrumb of information on a customer across your CRM, your DMS.
• 0:10
  Imagine if that person no longer has to do that, and they can spend more of their time engaging with the customer, developing relationships, being that friendly, trusted voice to a prospective customer.
• 0:20
  [upbeat music] This is Auto Collabs. I have the wildest thought. You? Oh, no. Yeah. Hear me out.
• 0:34
  So you know how like with AI stuff where- The last time you said that, it was right before you asked your wife to marry you.
• 0:38
  [laughs] You know with, like, AI, there's this, like, kind of narrative around Skynet and, like, robots taking over the world? Kind of, yes. Kind of.
• 0:49
  Um, you know what I just thought of is, like, how gnarly are things gonna get when I tell my AI agent to go run a covert operation and make suggested edits to somebody's Google business profile?
• 1:01
  Like, that is the war against, right? Don't even put that into the world, MC. That, that- That's messed up...
• 1:05
  it's already there, dude, and I'm thinking about, like, what is gonna happen in th- like, the fight has already begun. Do you know what I mean? It's gonna get nasty. Bro. You said that out loud.
• 1:17
  I said it out loud because- You said the, you said the quiet thing out loud, MC. I'm just saying. Yeah. Listen. And that's the other podcast that n- never is gonna see the light of day. [laughs] Yeah.
• 1:25
  But it gets me thinking about, like- No, it's true... what's gonna increase in value, and what's gonna become most important, and what do we need to, like...
• 1:31
  You know, tho- those are all the things that are coming to my mind as I think about this. In-person events, real touch points, all those types of things. Yeah. I mean... Ugh. Well, like, and anchoring to what's real.
• 1:42
  You, you broke my brain a little bit. And what? Anchoring to what's real. Yes. Mm. Mm. Well, let's- Hey... that's a great space segue... our guest today is real. Our guest today is for sure real.
• 1:52
  It's Mike Gilson, CEO of Conversica. And, uh, without further ado, we hope you enjoy this conversation. [upbeat music] Mike, welcome to Auto Collabs. We're glad you're here with us today, man.
• 2:06
  Thanks for, thanks for having me on. It's good to see you guys. Absolutely. Okay, so look, we, we, we, we send out these, you know... Uh, all good podcasters do this.
• 2:14
  They ask their, they ask some questions beforehand to prime the pump. I'm gonna start with this, because you said that you did rowing back in, I think it was college, right? That's right, yeah.
• 2:24
  Th- this is a sport, actually, and, and this is gonna launch into something. This is a sport that n- nobody gets to talk about a lot.
• 2:30
  But I have kind of a, like a, it, it's one that I always catch during the Olympics because there's something so special about that many people rowing,
• 2:42
  like, that synchronously together and keeping the boat as straight as they do. I'd, I'd love to hear from you, like, the rhythm of practice, the rhythm of, you know, like, team bonding.
• 2:55
  Obviously, you've got the, I, I don't know what they call the captain at the, at, at the front of the boat.
• 3:00
  But, like, give us a little background, because I think that probably sets up a lot of how you perceive the world and teams and organization. Yeah, absolutely. So rowing is a very interesting sport.
• 3:12
  It's, if I hadn't, if my t- high school team didn't have a team, I would've never gotten into it. So I was just lucky I got exposed to it through, through my school then.
• 3:21
  Um, rowing's very unique in the sense that it's, on one hand, it's a very difficult endurance sport, and on the other hand, it's, it's very technical in scope.
• 3:31
  So you have to really understand the technical nuances of how to apply pressure and the stroke and the rhythm, and just the complexity around that is, can be challenging.
• 3:42
  And I think the, the, um, the endurance aspect of that also, um, is something that most people aren't aware of, just how physically intense it is- Mm-hmm... and just in some ways, how violent it can be- Yeah...
• 3:54
  during race time. It's a very, kind of call it power endurance. It's kind of a mix between cycling and, and football is how I would describe it.
• 4:02
  So it's, um, it's really about, you know, applying power and, and training and, and the team aspect of it too is also very unique.
• 4:10
  Um, there's different boat classes, but in, in college, that was primary boats, what we call an eight, so eight people to a shell, and then you have the person called the coxswain who kind of steers and keeps people in alignment.
• 4:22
  And so how all these people come together, um, and, and, and try to eke out a win is, is something that, um, it, it's very interesting, and it's a great sport from that, from that perspective.
• 4:32
  Kind of the ultimate team sport as well. It kind of, it is. I'm realizing in this moment that we don't have enough business rowing analogies. Like, we go to football. Yeah. We go to soccer.
• 4:42
  Like, this thing, like, I'm thinking about now this, this concept of, like, the weakest link. Your, your, your shell is only as strong as your weakest link.
• 4:50
  Like, you're gonna know immediately what team member is creating drag. Right, 'cause that thing's going sideways, right? [laughs] Yes. So I'm curious then- Yeah. Yeah...
• 5:00
  how often do you think about this in terms of building an organization, measuring against- I think about it all the time... your understanding? [laughs] Yeah, I think about it all the time.
• 5:08
  Uh, you know, it's, it's, I've had the pleasure of being part of s- some great crews and then also kind of experienced what can happen when, you know, there's one or two bad apples, and what that could do to a crew or, or to a boat and just the importance of culture, of what a high-performance culture looks like versus one that might not be functioning at that level.
• 5:28
  Um, a- and there's just so many corollaries between t- between that sport and, and business, you know, everything from building companies to chasing new ideas, to getting people aligned, to the kind of the, the work that's required to really do that in the right way.
• 5:45
  Um, there's, there's just some incredible lessons that I, that I learned through the years having done that, uh, you know, at an early age that I carry forward all the time, you know, especially in today's day, day and age where,
• 5:57
  you know, obviously in my world, AI is definitely top of mind, and- [laughs]... this, this technology shift is shifting so dramatically and so quickly. You almost have- Sure...
• 6:05
  you're forced to innovate, if you will, and- But it's not as simple as just putting some ideas on paper and, and, and away you go.
• 6:12
  You know, you have to bring teams of people a- around you, you have to get stakeholders to buy into your vision and, and where you're going, and then how you execute in that dynamic is, is something that I can all trace to my, uh, to my rowing roots, if you will.
• 6:25
  So you, you talked about, you know, in this AI environment, and they're just different... I don't know, there's a different pace of adoption necessary than there's ever been. And,
• 6:38
  you know, especially if you're a tech company, uh, you know, we were just having a conversation about this in our, our last little session that, where we were just talking.
• 6:45
  Helping people understand, like, there's two ways, there's two avenues where people need to understand.
• 6:50
  On one side, uh, the tech industry is much more in its face right away, because you're watching the way people can develop and deploy ideas like they never could before.
• 7:02
  And so you're forced, and you're facing down obsolescence and what is our mode at every single turn, every single decision, every single m- you know, product cycle. It's in your face.
• 7:12
  And then on the other side, the people you're serving are not, right? It's a slower moving change, but they hear, you know, our tech community saying, like, "This is changing. This is happening."
• 7:24
  And then you have this other, actually there's like a third player, and that's, like, the voice of retail.
• 7:30
  And the voice of retail is also, like, a- being adopted, and from an AI sense, at record pace because consumers are like, "Oh, I can now have my AI agent do this," or, "I can just ask this," and these are happening.
• 7:43
  So, you have, like, these three competing things, and you're tasked as a tech leader to say, "How do I keep this team together? How do I get my team to adopt as fast as possible?"
• 7:51
  Because you understand the stakes more than the other people do right now, right? So you see it. How does that all process through your brain as just for you as a leader? Yeah.
• 8:02
  I, I think the, the biggest thing for me is you have to tune out the noise, right?
• 8:06
  And I, and I think, I live in San Francisco, and we have, I don't know if you, if you've been recently, but when you drive along the freeway, there's all these billboards of these different software companies and the kind of their- I understand...
• 8:16
  variant of what they're trying to accomplish and what have you. And there's just, like, everywhere you look here, there's AI buzz and noise everywhere. Yeah.
• 8:24
  A- and, you know, to the point where I, I get annoyed by it, but I'm in the industry. Maybe I shouldn't say that.
• 8:29
  [laughs] But I think what it, really what it comes down to is it's very easy to, to kind of shift away from the core underlying business case or value prop or things that you can deliver to an industry that can either transform that industry or not.
• 8:46
  But getting very specific about that and being able to communicate kind of that vision or what the technology can do in a way that people can understand it and take action on it, I think really is the key.
• 8:57
  And, and so I think communication, either internally or externally to, to prospective customers or n- in the automotive world, large automotive groups, just tying everything back to, you know, business case, and what challenges do you solve, you know, for this, for this major shift like AI?
• 9:14
  How does it actually change the landscape of what's out there currently, and why should I care about it as a dealer principal or a GM or a service advisor?
• 9:22
  And going very deep on, on the industry from that perspective is really the key in my mind. Um, that's- Have you-...
• 9:28
  how you build trust with customers and that's how you get people aligned with wherever you wanna go is, do you have the intellect and the ability to actually do that, first off?
• 9:36
  If that's something that's very challenging to do. You see a lot of noise where people can't do that, and the customer ends up having to figure out where they're gonna deploy this technology. And so- Hmm...
• 9:46
  getting very specific, I think is the key. I have a follow-up to that question. It's a two-sided question. How do you, you said having to get them to care about it. How do you get,
• 9:56
  how do you get a dealer to care about what's happening? And then also the, the other side of the question is, like, how do you get your team to care about what's happening in the tech space? Yeah. It's a great question.
• 10:07
  So I think i- in this industry, you know, in the software world, you really have to have a lot of empathy for your customers. And when I've...
• 10:15
  I've, I've gotten exposed to automotive over the last year and a half and, and I really do empathize with a lot of the GMs and dealer principals and service advisors and those frontline employees.
• 10:24
  This is a ve- rather complex, uh, kinda set of factors that, you know, these dealerships- For sure... have to face every single day, right?
• 10:32
  And I think now there's so much risk and uncertainty and ambiguity of what that future might look like for them, with huge concerns.
• 10:41
  Everything from geopolitical risk, to the OEMs getting more aggressive, to this AI landscape now that has emerged really in a, a very, uh, I would say, uh, emerging and threatening way over the last kinda few years.
• 10:54
  I think there's a lot of people that are staring into the abyss of the future and wondering what the next few years might look like, and they're, they're forced to really think through what they need to do to position themselves the right way.
• 11:04
  Mm-hmm. So I think that, from my standpoint, I need to meet them where they're at, right?
• 11:08
  And they need to look at me as a partner as they're making some very, um, complex decision points right now, and I think it's really, uh, it's really important for me to be able to help them, help educate them on what's possible and kind of, kind of tune out the noise, if you will, and really bring it back to the way in which it can transform their business, and that's how you get someone to care- Can I-...
• 11:28
  which is, you know, really being able to speak their language a- and show them what technology can do for, for the things that they're responsible for. You're inspiring a thought process in me that's enraging.
• 11:42
  [laughs] Not you enraging me, but it's, this is what it's inspired in me. You, you spoke so poignantly about anchoring back to the business case, case, which I can't underscore enough,
• 11:56
  and things are about to get so gnarly because you, we are, we've now put something that can be weaponized against every business case and company in the industry. Like, I, you know- For sure...
• 12:10
  our marketing agency, already getting reports from a person who doesn't know a thing about marketing saying, "My agent said bipbitybop." Automated every Monday morning. Right. [laughs] And it's like, "Hey, hold on.
• 12:22
  In the same way you can weaponize this tool against me, void of all context, I could do the same thing to you."
• 12:29
  And, and we pick up-- we kind of like become that Spider-Man meme where everyone's, like, pointing at each other. Pointing.
• 12:34
  [laughs] So I just feel like what you're inspiring in me, you're not enraging me, Mike, but the thought of the weaponization that we're starting to see happen with AI because now everyone's the smartest person in the room even though they're not- Mm-hmm...
• 12:47
  is what you said, anchoring it back to, okay, well, what is your business case? What problems d- are you genuinely needing to solve? What's the bigger picture here?
• 12:56
  Because in so doing, we introduce the necessary context and nuance needed to really make th- things tick, not the perception of things ticking. Mm-hmm. AI's, like, really great for, for most people, right?
• 13:10
  The, the non-early adopters going deep crowd, it's really great at making them think that they're ticking forward when it actually might be hindering more than it's doing good.
• 13:21
  Curious to your thoughts and commentary on that. I couldn't, I couldn't agree with you more, Michael. I think the key word that you, that you kind of referenced there was context, right? So,
• 13:29
  um, there's no substitute for domain knowledge. There's no substitute for being able to understand the core revenue drivers of a dealership, or how to run these teams, or the nuances of a specific brand or market.
• 13:43
  There's just so much complexity here. And, and I feel like, you know, we're, we're now in this world where many of us, we're used to working with these large LLM companies, GPT, Claude, you know, on some level
• 13:55
  there's kind of a false sense of, uh, security in the sense that you think you can just kind of do anything in that regard.
• 14:01
  And I think there's, there's a-- that's a very common misconception when you start getting into the nuances of an industry, right? Hmm. For sure.
• 14:08
  And being able to understand these complex processes and these workflows and how this data is structured and, and what context matters for a specific type of opportunity.
• 14:17
  You know, and just take something, not simple, but the language of this industry, right?
• 14:21
  So everything from what context is required to facilitate a payment swap or a trade-in, or identify a set of customers with an open recall, or ones that have declined services, or someone that might be a good fit because their lease is maturing in three months.
• 14:36
  What, you know, what is all the context that is unique to each one of those opportunities? And that's not something you can just plug into GPT or Claude and away you go, right? There's, there's very complex information.
• 14:49
  There's building what, what I call a context graph of how all these complex relationships tie together and how you can action this data. How do you actually surface these opportunities at scale, right?
• 14:59
  And I think that's something that, um, is very nuanced in nature from a technical standpoint, but also being able to do it and communicate with, um, these dealership groups on how to do this effectively and how to activate all this data is, is really the key.
• 15:13
  And so, but if you're missing the context, if you don't have that data foundation, there's no AI system that can reason across data without that underlying context that powers the industry. Not a chance.
• 15:27
  I have been obsessed with this for the greater part of, like, I'll call it eight months. February was probably the first time that I really started, like, working through this. The context window of a dealership, the,
• 15:38
  the operational documentation of offline decision-making protocols that aren't available. Like, the, the easy things to do is like, "Yo, this person came in four months ago. Let's hit them with a..."
• 15:49
  That was machine-- We did that in- Right... twenty twelve, right? Like, we knew-- Conversica was actually super early in that, right? Mm-hmm. That's the easy stuff. It's, "All right, uh, you know, this person
• 16:03
  has four cars in the gara-" You know, like these complex-- I can't even go into it, but these complex things. Or, "Someone called my dealership.
• 16:12
  They were upset about this, but it relates to this over here," and we would make decisions based on, you know, these types of, like, complex things that people haven't really well documented, uh, in a lot of cases and need to be documented in order for any tool that's being brought into the, the organization to be able to consume that context window.
• 16:32
  You, you probably know, um, you know, from a, uh, if you're developing anything, you know, your, your entire code base has a RAG model. Mm-hmm. And, and like an AgentsMD.
• 16:41
  Like, AgentsMD and RAG are, are the two things that are super important because it, it goes, "Here's, here's the way the web is mapped," right? And I think that, that honestly what...
• 16:53
  Uh, and, and I'll, I'll ask you, do you think this m- moment, this technology moment, is actually forcing any operator to get better at their core business principles because of the requirement of the technology to understand it as well?
• 17:09
  That's, that's a great question. Uh- Hmm... this is the, this is the age-old question in software, which is does this enable a new paradigm, or does it just kind of
• 17:18
  create more complexity if your underlying systems and infrastructure aren't in place to really meet the, meet the moment as, as you described it? Right. Yeah.
• 17:25
  And I, I think there's a couple things that are different this time around than traditional software. Traditional software stores a lot of information, very good at automating specific types of workflows or processes.
• 17:38
  What it was always bad at was reasoning across complex information. You know, this is, you know, h- the, the example that you referenced earlier.
• 17:47
  If someone's part of a household, you know, where in that household is there opportunity? Is there more than one vehicle in that household? Where are they at in their life cycle, right?
• 17:55
  All those things, that's, that's context and information that's not stored in any single system, right?
• 18:01
  So you have to, as a software practitioner or an application, it needs to be able to, to tie together all those complex things that are disconnected and create a coherent picture out of that, so an operator can take action on that, or the system can take action for the operator on its behalf.
• 18:17
  And I think that, that paradigm shift I don't think it's dawned on a lot of people just quite yet. Mm.
• 18:24
  And, and I think people are still thinking about it in terms of complex screens, and lists, forms, and a traditional UI.
• 18:31
  But the actual underpinning of this, you know, how the, this context comes together across your, your DMS, your CRM, your unstructured conversation data, any type of third-party market data that you wanna, you know, bring in as well, and how do you reason across that picture to actually take action in certain areas and move things forward?
• 18:49
  And, and more specifically, how do you identify opportunities and know what to say to a customer or what campaign to run at a given moment in time? That's a new paradigm shift. And, and I think this moment, if you will,
• 19:01
  it's, it's important for this industry to realize that that's here, that's possible right now. Yeah. And these old systems of record are not there yet, and they're not talking about the paradigm shift in that way. Mm.
• 19:13
  They're talking about layering AI on top of an old system. But the actual new intelligence system of record, that's something new, and then that's creating entirely new ways of, of working.
• 19:23
  And that's really my job is try to help educate the market on, on what's now possible with this new technology. Are you- So-... starting to catch a through line? Because a lot of people have said, you know...
• 19:34
  Th- there's always this question, like, how much of, of my job, the proverbial my- proverbial my job, is gonna be overtaken by AI?
• 19:42
  In retail operations, are you starting to see, outside of, like, a technician picking an engine up and shoving it back up under the car, right? Mm.
• 19:51
  Are you starting to see the through line on where, where the human is going to continually stay the active participant and where AI is going to get to? I- is there, like... I- in your mind's eye, do you see that
• 20:08
  in, in the future- A- absolutely... where that line is drawn? I'll give you, I'll give you my perspective, you know, having been in this industry for a bit and understanding just where this technology is at.
• 20:17
  I think over time, the, the human-- I think the, the conference that you guys had this year was very telling, right? It was kind of the year of the human, I, I believe, was the- Mm-hmm... the punch line, if you will.
• 20:26
  Yeah. And I think really, in my mind, the human going forward owns the relationship with other people, right?
• 20:31
  Th- their job is to manage, engage with that customer, kind of be that trusted point of contact with them throughout the vehicle, and the-- and th- throughout the vehicle life cycle, right?
• 20:41
  The AI systems now a- are more focused on kinda automating all of this back office or all the, the manual assembly of this, this data, this context that powers this industry.
• 20:52
  This industry is so unique in the sense that there's so much data, there's so much context that goes unused. Mm-hmm. Meaning, we're capturing all this transactional data.
• 21:01
  We're ca- capturing the entire life cycle of a customer across their sales transaction, their service history, uh, their promotional offers, you know, what they responded to, what they didn't, what they communicated to over, over time.
• 21:12
  We have all that data today. And, and I think the problem really has been not being able to activate it, not being able to use it in an intelligent way.
• 21:21
  And I think as a result, human, human teams over time have had to, the best teams, kind of piece together all that information manually.
• 21:29
  So it's not, it's not uncommon for, you know, a great salesperson, as an example, inside of a dealership, to have five different screens open, pulling together kind of that breadcrumb of information on a customer across- Sure...
• 21:39
  your CRM, your DMS, you know, email log, call logs, what have you. I think that's kind of what the best people do. Imagine if that person no longer has to do that. Mm.
• 21:49
  And they can spend more of their time engaging with the customer, developing relationships, you know, being that friendly, trusted voice to a prospective customer, right?
• 21:58
  That's what differentiates dealerships in my mind, especially... You know, look, if you run a Toyota dealership in one market, and there's a Toyota dealership down the street, how do, how do those two stores compete?
• 22:09
  It's not just on price, right? People go to- There's no way... a trusted vendor.
• 22:13
  They go to someone that they have trust in, that they believe in, that they're friendly with, that doesn't think that they're trying to get over on them with trying to- Yeah... make one dime on price. That's everything.
• 22:22
  Right? Yeah. I think the whole idea of what this technology can do is it's enabling them to compete more effectively in that regard.
• 22:29
  And so I think AI is gonna take a lot of that heavy lifting off their plate so they can focus on what they do best, best, which is that relationship s- aspect. So we're, we're rounding the corner.
• 22:39
  We're just about out of time, but I, I, I think the, the one question I wanted to leave with is you've talked a lot about the dealership side, the tech side.
• 22:49
  You've kind of brought us to the point of this relationship between person to person.
• 22:55
  We're in an environment now where, back to the agents, more and more people are using AI to do the outreach and the shopping and the context. That's only going to increase.
• 23:03
  How should, how would you advise a dealer to be thinking about how they handle that communication?
• 23:07
  Because now AI agents are reaching out on behalf of customers, and they have to be answered in a certain way, or we b- we have to be prepared to handle that in a certain way.
• 23:16
  So what is just your general thinking about that, and what's your advice? A- absolutely. So I, I think the key, the key thing is trying to remove as much friction from the sales process as possible, right?
• 23:27
  So we, we now live in this age where we expect immediate results. You know, you ex- you get food delivery. You got DoorDash. You can pick up your phone. It can be delivered to you in 20 minutes- Absolutely... right?
• 23:36
  Yeah.
• 23:36
  I think the days of going into a dealership, waiting five hours, going through a complex F&I approval process, finding out what, you know, incentive might work for what I'm trying to buy, or the different comparisons between different makes and models.
• 23:49
  Like, all those things that traditionally took a ton of time now need to happen within seconds or minutes because that's what consumers expect, right? Absolutely.
• 23:58
  We now live in this age where I can go online and get almost unlimited information about every vehicle make, model in the world. Mm-hmm. And, and so- And banks- You know-... and the insurance and, and, and. Exactly.
• 24:09
  Right? Yeah. And I can compare financing offers, and I can run the, the trade-in math of what my vehicle might be worth and what that might mean for my financial situation. All those things now need to be lightning fast.
• 24:20
  And if these AI systems aren't enabling that- That just means you're creating a lot of friction. And I would be very worried about that point. Yeah.
• 24:28
  Because if a deal- if, if someone exploring a vehicle purchase comes to your dealership and they're met with endless friction, they're gonna go somewhere else. Mm-hmm. And they can do it within minutes. Mm-hmm. Right?
• 24:39
  And so I think that's, this whole next new wave needs to be about how do we simplify this entire process, remove as much friction as we can, and empower your dealership teams to focus on what they do best, which is managing those relationships.
• 24:52
  Well, Mike, there's definitely, uh, no loss of things to think about or be concerned about. Thank you so much for joining us today, sharing some of the stories about the rowing.
• 24:59
  And I th- I'm gonna be thinking about that for a long time. But as always, thanks for joining us today on Auto Collabs. Thanks for having me, guys. [upbeat music] All right, Kyle, why must you ask those questions?
• 25:14
  Uh, you, you led us to a point in that conversation where you got right to the edge of, I think, where we started the conversation about, like, what are people gonna do with it? What are people gonna do?
• 25:24
  What are people gonna do with it? What is the team gonna do with it? What are the retail public, what is every individual person going to do with it?
• 25:31
  And I think that the, the bottom line is nobody knows, and the nimblest, sh- most streamlined, most rowing together teams will be able to handle it.
• 25:42
  I think that's what I got from- Here's, here's the interesting thing-... the takeaway with Mike... just, just so people know.
• 25:46
  Less than 1% of the population of the world has access to the fastest operation, o- operating frontier models. I heard this stat. Right now. I heard this stat. Okay?
• 25:55
  So when you- It's like, it's like point, it's like real low. It's like.7%- It's real low....2%. Like, like the people that have a premium or pro subscription or API access to the world's frontier models is- Yeah...
• 26:08
  less than 1%. Right. Right? It's closer to, like, 20% that have access to some sort of model, right? That be it through their phone, it be through their Google account.
• 26:19
  Maybe they have a ChatGPT free or $20 account, things like that. They know how to hack Amazon customer- Right... service chat. [laughs] A- any of those things, right? So, so the, to start, like, remember,
• 26:31
  not everybody in the world is gonna be texting you tomorrow using AI- Mm-hmm... to try and buy a car. Mm-hmm. Right. But the, but the pace
• 26:40
  at which it is getting consumed is much faster than any other technology in our history. Mm-hmm. Right?
• 26:46
  Well, this is what I appreciate about what Mike brings to the table is y- you know, I, I heard him say, "You know, I've been in this field for a really long time, and because of that context, I know," like, he, he kinda doubled down.
• 27:00
  This is why I asked such a doom and gloom or made such a doom and gloom statement in the beginning because I'm like, people are gonna be wild. Where you're connecting it is there's only a small...
• 27:08
  Like, because we talk about it and we're in it, it seems like it's bigger today- Normalized... than it actually probably is. Normalized, yeah.
• 27:14
  And also, despite all of that, all the billboards he sees with the AI this and that, he's anchoring in on, but what does the human need to get good at? Yep. What do they need to anchor to? And, and here's the thing.
• 27:26
  What's the business case? Like, what's the reality? Here's- Hmm... I, I'm gonna, I'm gonna give you this. Let's say it's 100%, everybody has access to it.
• 27:34
  Everybody is utilizing at some level, at least for the shopping journey- Mm-hmm... with a car purchase, right? What's the existential truth that as people in the car business that we need to reconcile with, right?
• 27:50
  The existential truth is that they still want to purchase something that makes them feel something, right? Mm-hmm. And gives them access to the comfort, the humanity that they desire, right?
• 28:06
  And so the, the, the distance to that is the only problem. And so if we just shorten the distance to that and meet them where they're at, people will, will slow down enough to look us in the eye, right? Mm.
• 28:21
  And I think if you can realize that, instead of being like, "Oh, here's another person just trying to AI shop me with a bunch of other dealers and jerks," right?
• 28:30
  And just realize they're just trying to get their proximity closer to the thing that they're, they at least they feel their heart desires. Mm-hmm. And you meet them where they're at,
• 28:41
  your, your speed to that relationship is gonna be significantly higher than the person down the road going, "I don't even know what they're doing over there at their computer," you know? You just
• 28:53
  said something that I have not thought about in this way, which is there is so much narrative. This is the ignorant narrative: AI's going to replace you. No. Mm-hmm. Stop with this nonsense.
• 29:07
  What you just said is, "We're not trying to replace you. We're..." What if, what if the paradigm, Kyle, is that what you just said? I'm not trying to replace you.
• 29:15
  I'm trying to shrink the proximity with which I can get to you in a meaningful way. Oh. Ooh. Oh, boy. Get on 'em. Good night. Get on 'em. I don't know. Well, we're ending on a high note.
• 29:28
  Y'all better skip that because we're watermarking this part. We need another episode for that. I gotta wrap it. I'm not even gonna try. [laughs] I'm not even gonna try. As always- Kyle, what you got?
• 29:35
  On behalf of Kyle Mountsier, the mind-blown Michael Cirillo, and myself, thank you as always for joining us on Auto Collabs. [upbeat music] Welcome to Auto Collabs.
• 29:52
  [laughs] Welcome to Auto Collabs. [laughs] Why are we recording? Are we rolling yet? Not yet.