Clayton Collins: What leaders are still getting wrong about AI

Name: Clayton Collins: What leaders are still getting wrong about AI
Uploaded: 2026-08-14T08:00:51+00:00
Duration: 33 min 22 s
Channel: HousingWire

00:00Welcome to Powerhouse. Yesterday, we wrapped this year's AI Summit. So today, while it's still fresh, I'm sitting down with

00:08Clayton Collins, a guy who's probably been a part of more of these conversations than anyone I know.

00:14We get into the biggest takeaways from the Summit and what actions leaders need to be taking now.

00:19We also turn the lens on ourselves and discuss what all of this means for HousingWire.

00:25Our AI Summit on-demand sessions and exclusive AI Summit playbook are available now on HousingWire.com.

00:36Thank you for joining me.

00:44Thank you for having me, Zed.

00:44All right. So we're just the day after about the corporate office, day after our AI Summit has wrapped.

00:51And I wanted to grab you for a few minutes and pick your brain about thoughts on the AI Summit

00:56and the topic of AI in general in the industry.

00:59Looking forward down the road. So thank you for joining me.

01:01Yeah, no, it's, you know, coming off an event, as you know, like the day after, the evening after is

01:07always like a high.

01:10Like there's like the dopamine hit of like hosting a great event, the, you know, awesome learnings from the onstage

01:16content, awesome conversations that happen in the lobby over breakfast, lunch, and coffee.

01:22And then usually some great phone calls and text messages afterward of like, hey, I learned this. This was valuable.

01:28We'd love to see this next year. We love the feedback loops both directions.

01:33So, you know, the day after event's always fun because we're back here in the office.

01:36We do a little bit of postmortem. We're working on getting ready for our next event, the Mortgage Banking Summit,

01:42but also working on a lot of digital content that flows off of the onstage work from yesterday, the AI

01:49Summit.

01:50Really killer video, social, audio content that we've already seen.

01:56And we also have some great summary work that's going to take a lot of the key learnings from the

02:00stage and get it out there to our attendees and our subscribers.

02:04So, uh, a lot of work to be done in the back of an event, but, you know, uh, for

02:08the most part, it seems to get down with the team having a smile on their face, which I appreciate.

02:12Yeah. I think everybody did a great job. And I, whenever we wrapped yesterday afternoon, I took, I was about

02:1715, 30 seconds in the, uh, in the green room, took a deep breath and then went out and then

02:21feedback immediately.

02:23Yep.

02:23You know, which is great. I really look forward to it. We've got plans for, uh, improving next year.

02:28One of the things I wanted to talk to you about ties into, uh, I mean, I guess overarching feedback,

02:33you've been a part of the, uh, you know, the AI conversation in our industry, in this space.

02:39I feel like kind of from the, from the get-go and from your perspective, one of the, this is

02:45not unique to specifically to the mortgage industry, the, the, the hype versus substance of vaporware, you know, POS platform,

02:55just, you know, whatever.

02:55What do you feel has changed most recently, especially coming out of our AI summit around the, the, the substance

03:03versus hype?

03:06All right. There's evidence from on-stage conversations that we don't even have to have that conversation anymore about like,

03:13um, substance versus hype.

03:14The evidence of substance and that the people we have speaking, the folks that we have attending actually have real

03:22AI solutions implemented in their, their workflows and businesses.

03:25It's the number of people who talked about governing token utilization and, uh, the expense side that comes from the

03:33variable expense of AI utilization.

03:36You don't have that conversation when you're talking about vaporware and like what could happen in the future.

03:41Now we're actually talking about like, oh, this is working. It's happening at scale and it costs some money.

03:47So we're talking about governance protocols and token, um, utilization policies and bringing LLMs, uh, in, in house and like

03:57self-training and putting inside guardrails to make sure you're not using more tokens than necessary.

04:02To me, that was a very clear signal of the, the stage of substance that we're at, but also a

04:09little bit of the maturity of the technology.

04:12Now it's hard to say maturity of a technology that had more innovation in the month of July than it

04:16did in the whole year of 2022.

04:17We're still in a rapid growth phase, but we are at a point where there's financial evidence of implementation.

04:24I agree.

04:25On the cost side and hopefully, uh, on the, you know, the up and the down of, of, uh, financial

04:30evidence.

04:31Right.

04:31Well, you were tied to one of the larger news stories of the year, which our summit actually had a

04:38little, a ripple effect into our summit.

04:40But originally you were slated to have a session with, uh, Vishal from better and we pivoted out of that

04:47and, uh, Ryan Grant stepped in.

04:49Uh, I thought your session was particularly, uh, it was very, it was very interesting and, uh, and I thought

04:55it was great, but what surprised you the most about the conversation with Ryan?

05:00Yeah.

05:00I mean, I assume most of the people listening to this show or watching this conversation, like have, I've seen

05:07like the headlines, Vishal Garg, the founder of better is, is no longer the, the CEO.

05:12He's out in that operating capacity, but still, um, uh, apparently very involved from a, a board and investor perspective

05:20on a good chunk of the business.

05:21One of the things that came across in the conversation with Ryan and that may, maybe this is evident to

05:27everybody, but as a founder of Vishal's fingerprints, uh, are all over that business.

05:32And, um, there's a, like common phrase I've heard from Ryan and others in the industry that Vishal has a

05:39certain zone of genius and a, and a vision for what he wanted to do for, for mortgage, for housing,

05:46for housing affordability and using better as the vehicle.

05:51Um, and it sounds like that zone of genius, um, the evidence of that is still proliferates throughout the business.

05:58And there's a lot of folks in that team who want to see that vision through.

06:02So Ryan, um, who is a, you know, fabulous executive, uh, great speaker and very focused person, uh, delivered a

06:12very clear message of, of consistency that I think, um, was heard from our audience, but, and attendees, but has

06:20also been heard.

06:21And one-on-one, one-on-one conversations and podcasts with, with, with Greg share and others, as, as well

06:27as, um, in, in town hall formats that like they're continuing the charge.

06:32They're working toward a more efficient housing transaction.

06:36Ryan talked about his costs to originate from stage, um, uh, pretty transparently, like what they include in their costs

06:42to originate, why they think of it a certain way, the Delta between their consumer direct costs to consume costs

06:49to originate and retail.

06:50And why retail is a little more expensive, still much lower than the industry talks about, but, um, but a

06:57little bit higher.

06:57And we had a pretty transparent conversation on that, but the, the North star continues to bring down that cost

07:03to originate, which has positive downstream implications to the, to the mortgage lender, um, who we know lenders have fought

07:11with profitability issues for years, especially in a down cycle.

07:14Yeah.

07:14Has positive downstream impacts to the originator.

07:18And the other big talk track of yesterday is like helping people get to their highest and best use and

07:23spending more time talking to their borrowers, talking to the referral partners, less time and administrative tasks.

07:27That's a big administrative win for the originator, hopefully lets them do more volume and helps the real professionals win.

07:35And then last, but certainly not least is the downstream impact to the consumer.

07:40Um, when you run a more efficient mortgage origination process, the cost of manufacturers lower, we can sell mortgages for

07:47cheaper, AKA lower interest rates.

07:50Um, I don't know if we've seen that broadly yet, but like, that's the vision, right?

07:53Like we, you're going to be able to originate mortgages, um, that benefit the consumer in a better way.

08:00If your costs are originate is two, three, $4,000 opposed to $12,000.

08:05Um, that's a, that's a hefty manufacturing cost to push through, especially, uh, um, entry level first time, like a

08:17lower cost, uh, housing stock.

08:19Right.

08:19Well, and, and, and you spoke to this as well, not only is the, you know, the reducing the cost

08:24for originate, uh, but also using AI to lift the low, the, the, the, the cumbersome things that loan originators

08:30aren't more than just not wired to do in the first place.

08:34A loan originator is a certain type of person.

08:36And part of the origination process, unfortunately, still to this day requires originators to do things that they're just not

08:43best suited for or wired to do.

08:45And using AI to lift that burden from them allows them to lean into the aspects of what they do

08:52best, do it better, which also ultimately benefits the consumer because it's a better relationship.

08:57There's more time to invest on the person.

09:00You know, it's a.

09:00The things that made them become an originator in the first place.

09:03Yeah.

09:04Yeah.

09:05Uh, one of the things that I wanted to, to get your perspective on as well, it's, this is, again,

09:09this is not AI is just a larger example of a systemic problem that we have in the industry, which

09:14is adoption.

09:15Right.

09:16Sort of tech adoption, uh, CRMs, LOS adoption, you know, you name it.

09:20AI adoption is, uh, you know, front and center for a lot of companies.

09:25And, uh, Lindsay Riccidelli from, um, uh, from, uh, American Pacific Mortgage.

09:30She had a session about, I think it was titled engineering the aha moment.

09:36Right.

09:36And I spoke about that in, in my session with, uh, with Drew Parker and Adele, where everybody has this,

09:45uh, this moment with AI where they realize like, oh crap, this can, this unlocks so much.

09:53It's like magic, right?

09:54I can do so much with this.

09:56This is going to change my life forever.

09:58This is going to change my business forever.

10:00And the way that she, you know, sees this aha moment is that is the responsibility of an organization to

10:07engineer this magical moment much and approach it like a, uh, like a marketing issue.

10:13Right.

10:14Then a, then a training issue.

10:16And I'm, I'm really curious because of the, the circles that you run in, you know, the, the conversations that

10:21you have at the executive level with our partners.

10:22Like, are you, are, are you hearing how, how are, how are executives, how are organizations thinking through adoption at,

10:35at that level?

10:36Like engineering it perhaps as a, as an emotional experience, much more than a top down tech imposed, uh, um,

10:45action item.

10:46Yeah.

10:47Well, I mean, I think executives have a lot of different priorities and every technology innovation enables execution on different

10:55priorities.

10:56Now we can rewind in history and think about the tech innovation of the, the automobile that didn't just unlock,

11:02um, the ability for families to, to take vacations.

11:06It also unlocked, uh, the, um, like, uh, interstate, interstate commerce and trans transporting goods and like some healthcare impact.

11:15It unlocks a lot of things.

11:16You can't tackle it all at once.

11:17The, the internet was the same thing and under lock, uh, unlocked the ability, um, to get access to information

11:22faster and, and, and use search engines for things.

11:25Then it, uh, enabled workflows and enabled social media for better or for worse.

11:29Um, AI is similar, right?

11:32Like we, there was a lot of use cases talked about yesterday.

11:35We talked about very, um, enterprise level workflow capabilities and, and loan servicing and underwriting.

11:43We talked about, uh, marketing and brand outcomes.

11:46Like that Wong talked about how that Christie's their intelligence layer is helping them better connect with, with luxury buyers

11:54and, and like build this connection with the auction house side of the business that, that wasn't there previously.

11:59Um, uh, here we're unlocking content creation and editing and, uh, uh, video and, um, and photo asset creation opportunities

12:10that, you know, would have been tedious and, um, inconsistent, uh, and, and, and previous technology models.

12:16Right.

12:16So like you're, you're unlocking different things.

12:18And I think it's just really important in executive circles to know what you're trying to operationally achieve in any

12:24given moment.

12:24And not just say, we have a strategy of bringing AI into our business because that, when I talked to

12:31you about bringing AI into the constant content studio and event team, that's a very different conversation.

12:37And then when I talked to Holden about bringing, uh, AI into our, our, our, um, coding and development process.

12:44Defining your why.

12:45Yeah.

12:45Defining the why.

12:46So like, I think the big, like direction that I take away, the aha I have, um, out of that

12:52event is that executives need to define their why.

12:55I think you can have a lot of different wise, but when you're going into a conversation with your team,

12:59understand what you're trying to achieve, um, how fast you're trying to achieve it, who's going to achieve it.

13:05And then what you hope the outcome is or the KPI of success.

13:07Is it cost efficiency?

13:08Is it revenue acceleration?

13:10Is it, um, capability building?

13:13Like we're, we're building, uh, features in the housing wire right now.

13:17Capabilities that we didn't have previously.

13:19And like, that's like, that's awesome.

13:21Like, like we've had local market data for a long time, but, but couldn't.

13:25Like, could we do, uh, scripts and analysis for every zip code in the country every single week before AI

13:32was in our toolkit?

13:33Like, heck, heck no.

13:35That'd be a lot of man hours.

13:37Um, and, uh, you know, every, I talked about acceleration, like how much innovation happened in July versus like the

13:43whole years in the past.

13:45Um, like we're stepping forward as an organization and to, uh, with housing wire intelligence, but also a layer of

13:51launching an MCP model context protocol to help access housing.

13:55Our intelligence where the user lives.

13:58And as a media and content org, we've learned for years that people digest and consume information in different ways

14:04in different formats.

14:05Somebody listening to this podcast only knows housing wire because of the podcast.

14:09They don't come to our events.

14:10They don't read the newsletters.

14:11They don't go website.

14:12Shame on you.

14:13I hope you do it all.

14:13But, but somebody, somebody else knows housing wire because of our events or knows them because of the, the, the,

14:19the us because of the news content or like, or, or something else, real trends or something else in our

14:23product suite.

14:24Um, people consume information differently.

14:26And as a media operator and an information operator, it's long been ingrained in me.

14:32You have to meet your user where they are and AI is enabling that and in new ways.

14:36So that I'm sorry if I'm rambling here, but that conversation flows outside of media and content into, to mortgage

14:43lending, to, to real estate sales, to, to software.

14:46Like I haven't talked to a software operator in months who, who isn't like kind of rethinking the world of

14:51like seat based utilization and like having to think about like, Hey people, the future might not be people coming

14:59in and using, using the password and coming to my platform.

15:01I need to embed in the workflow in a different way.

15:03And in the rewards for that might even be richer than they were in a SAS based seat based model.

15:08Um, and there's still a lot of unknowns there, but like, that's the, the crazy stuff of like business model

15:14evolution and meeting your user where they are.

15:16As people have new demands and, um, access points for what they expect out of technology, what they expect out

15:24of information, what they expect out of business outcomes.

15:27And that's all, it's all changing right now to piggyback on that.

15:30And, you know, from the session was so cool.

15:32I thought at the session or the summit yesterday, it was that we had sessions that moved.

15:37We, that they covered, you know, AI in, uh, and, and land search to MLS data protection to LOS shifts,

15:44you know?

15:44And so we're, we're seeing the integration and the adoption of AI at literally every stage of all things tied

15:53to the home.

15:54And I curious from your perspective, what are the sections of the industry can be either, you know, in the

16:01mortgage space and the home building space that you've been most surprised with the, the, the level of AI adoption

16:09or the, the, the, the innovation tied to it.

16:15Okay.

16:16I'll start.

16:16Mine has been in the home building space.

16:18Yeah.

16:18Uh, I did, uh, I did a podcast with a Carter Merloy from acres and his, their, their land, uh,

16:25search, uh, AI platform is just like the, the, the democratization, uh, that it is affording people that used to

16:33be able to, you know, you would spend weeks on the road, just trying to survey land to find a

16:38place for development.

16:39Where you could say, I want to, you know, I want to 10, you know, 10 home, you know, call

16:45the sack within 30 minutes of the, uh, of the local HUB.

16:49Yeah.

16:49Like this city in Texas that has this drainage and you just talk to it like a person using their

16:55satellite imagery and it will map, it will find the land that you're looking for.

16:59It will map out the possibilities that has all sorts of other implications.

17:03But that just, to me, that just blew me away at a level that I didn't, that's not an area

17:07of the housing industry, the home building industry that I, it even crosses my mind for that sort of, that

17:13level of innovation and then the implications that it unlocks.

17:17Yeah, it's, uh, I think that's a surprising one because it, it, it's taking technology into the physical world where

17:23like we all expected AI to play an important role in digital content and data.

17:29Um, but I'm gonna take a different angle.

17:31Yeah.

17:31And like, I think the most surprising is also one of the most obvious, um, but I'm surprised that it's

17:37like happening at the scale of this.

17:38So like, um, mortgage underwriting, like this was a very clear, obvious space where AI should be, um, enabling more

17:48efficiency and loan processing underwriting, helping, uh, loan originators go from client conversation application to, um, scenario analysis analysis and

17:59approval faster through the underwriting process.

18:02That's the, that's tricky because this is an industry with a lot of inertia.

18:07Yeah.

18:08Um, certain staffing models that are built around certain processes, uh, regulatory oversight.

18:15Um, well, just, and then just, and the, the implications of drift.

18:19Yeah.

18:19Right.

18:19Like, but because the, with underwriting, there's such a, there's, there's a finality to it that, that almost requires a

18:28human that you, the initial, you know, obstacles, like it requires a human being to be responsible.

18:34If you F up.

18:35You're living in inertia land.

18:36You're living like, so the, um, you're exactly right.

18:39That.

18:40And so because of that concern and, and the ultimate downstream, the mortgage has to get sold at some point.

18:46So like you need capital markets and like, and servicing integration and approval acceptance, but for certain mortgage products, not

18:56all products yet.

18:57That's another complication there.

18:58You know, we got, we have Gubby products and like our Fannie Freddie and like some VA products and like

19:03they're, they all have a little bit different process.

19:05And like there's a starting point for different lenders, but there are many lenders and we're not just talking about

19:10better that are running fully automated underwriting processes for certain products.

19:15And like that, that is for like certain scenarios, like pretty like plain vanilla loans.

19:20You got your W two borrower wealth in the ratios, but like in those scenarios, those loans are flying straight

19:26through, um, AI driven automated underwriting.

19:30And, uh, and that's exciting, but living in inertia land, we still have underwriters and ops leaders who are in

19:39some lending institutions going back and checking like the work of, uh, those AI driven underwriting process.

19:46Now the concern there is that, um, once you see it, you can't unsee it.

19:51Right.

19:51And like we, we actually, as an industry, if we want that to become practice, we have to get people

19:56out of that.

19:57Like, I can't let go have it and, and, and let it go.

20:00You can't like what it breaks the process so much.

20:03It break one, it breaks all the efficiency and we're just wasting money.

20:06If we're spending money on tokens and compute to audit, like use AI to underwrite a file, then having a

20:10human go back and, and redo it.

20:12Yeah.

20:13Um, you're, you're, you're also potentially avoiding some reps and warranties and like, and creating major issues.

20:18Yeah.

20:19Um, so like I am impressed with how many lenders like at different scale levels, um, whether you're talking about

20:25a, one of the few venture backed lenders who like is motivated and incentivized to build as much tech as

20:31they can into the process to smaller IMDs who say, Hey, we're going to do this too.

20:34And we're going to partner with a great, um, great technology partner to bring this into our business.

20:39It's, it's happening like this is, we are getting past the inertia.

20:43Right.

20:43So I'd say that's what I'm like kind of in awe about that.

20:46Like we're breaking past the inertia.

20:48Right.

20:48What do you, what do you think about the role for AI in, in non-QM products?

20:52Because I mean, ever since I've, I started, I was originating 15 years ago and it's a very, you know,

20:58in the, in the mortgage industry, there are a few, or there are several kind of, uh, phrases or promises.

21:05Kind of like in the reverse side, the silver tsunami that people have been talking about for 20 years, you

21:09know, there's like right around the corner that it's not, that's a, it's a, it's a glacier.

21:12Like it's a slow roll or anything.

21:14And the new non-QM side, it's been a very similar thing.

21:16Like non-QM is about to break through non-QM is breaking through.

21:19It's going to, you know, it's a, it's going to be a mainstay in your, in your product suite.

21:23Do you feel like AI really has, do you feel like AI has a much better chance of normalizing non

21:32-QM than any other, you know, promise surrounding non-QM and its normalization in the market?

21:38We are seeing AI use cases and, and product understanding.

21:44So it's helping originators like better research and understand the, the product suite they have access to.

21:50Yeah.

21:51Um, understand the, uh, there's several new and existing tools out there that are using AI to better understand guidelines

21:57and, and, and underwriting requirements.

21:59And I think AI surfaces knowledge and education in a way that was in a way that's much easier than

22:08like past technologies.

22:09Yeah.

22:10So anytime you're trying to help a product break through, whether we're talking about a new iPhone or non-QM

22:19mortgage education becomes a curve.

22:21And we've done enough content here at housing wire with non-QM companies over the years to know that the

22:26charge of the marketing effort is product awareness and product education.

22:29So, uh, I think one of the, the AI capabilities that will propel non-QM or, or, or any other

22:38like product innovation forward is helping the originators better understand that it's available.

22:44Better understand if their borrower, um, home buyer or seller fits inside of the framework and guidelines for that product

22:51and be able to deliver that advice with confidence.

22:54And, um, I think that will help all new products, all existing products help find their way to the, to

23:01the right borrower.

23:02Um, we all know, like if you've ever run any sales organization, your sales teams usually comfort sells the product

23:08that they're most comfortable with the most.

23:10Um, even if they have a, uh, a diverse product suite and a bunch of tools in their toolkit, you

23:16know, to people go back to what they're comfortable with.

23:18AI can help expand the number of products that originators are comfortable with.

23:23Yeah.

23:23Well, uh, one of the, the reason my, my entire perspective of the housing industry changed the moment that I

23:30started working here, right?

23:32Coming from, cause I came from within the, well, I just came from within the machine, right?

23:36As an originator and then working at the corporate level at a, at, at a lender.

23:41And there's just, it's a, it's a, it's a perspective, right?

23:44You're, we're, you're kind of removed from the, a lot of the day to day and a lot of the,

23:50uh, the, the, the, the muck, I guess that practitioners have to deal with on a daily basis.

23:55And then exposed to people in tangential industries to kind of sit, um, uh, in a, in a different seat

24:02to see how all of the things work together.

24:05And from a, from a, from a problem solving standpoint, that can be quite, that can be quite beneficial.

24:11A lot of times it's difficult because if you're talking to other leaders and, you know, and, and, and giving

24:16like perhaps feedback or advice because they're responsible, you're not in it.

24:19You know, you're not living, you're not dealing with this stuff.

24:22I'm not, but I'm, but I'm having conversations that you're not.

24:26I'm, I'm talking to people in different industries that you're not, because it's just, you're, it's just a different seat

24:31of perspective.

24:31And as it ties to the AI conversation, I'd really like to hear your, uh, perspective on, you know, if

24:39you're, you know, when you're, if you were to talk to other executives and partners of housing wire based off

24:44of, of, of yesterday, once one strategic leadership call that you would recommend that leaders take now, um, and for

24:54the immediate future.

24:55The, the, the best advice I have as it relates to AI and, um, and leadership communication is that the

25:04most successfully launched, integrated, um, implemented AI initiatives have been CEO led.

25:12Take that across all sectors.

25:14Um, this doesn't, this isn't just housing.

25:16This isn't just mortgage.

25:17It isn't just real estate.

25:18Uh, the promise, the potential for AI and business will require.

25:24Business model transformation, staffing model transformation and operational process transformation.

25:31That level of business transformation is very hard to achieve.

25:35When it's delegated too deep inside of an organization, organizations by nature are resistant to change as much as people

25:42may say they're comfortable with change or they like change.

25:44Um, organizations are not.

25:47Often accepting of change.

25:49Um, and to really drive change in a business, you need initiatives to be.

25:53Not just executive led, but, but CEO led because there will be hard decisions that have to be made hard

25:59decisions on investment, hard decisions on staffing models, hard decisions on business models.

26:04So that's the, the most like general, like across industry learning that I've, I've had, I've seen it reiterated inside

26:11of our, our, our, our market here and mortgage and real estate.

26:15And I, I, and I've seen it from friends and peers and other companies that I follow in, in other

26:19sectors.

26:20Um, this is not a moment where a CEO can say, I'm not, I'm not technical.

26:26I don't understand this.

26:28This is something that.

26:29The tech team's going to have to figure out, yes, you need good partners in the organization.

26:32You need executive, um, uh, leaders and sponsors and some, and probably some extra hands for execution.

26:39But this is not a moment or a time where CEOs can, um, remove themselves from what could be a

26:48transformative technology in your business.

26:50Okay. All right. Well, not Mr. CEO.

26:52And I got another question for you.

26:53Is there anything that came out of the summit yesterday that either changed the way that you might have caused

27:00you to think differently about the way we approach AI in the newsroom and our content creation and our, our,

27:07our, our market offering or, or re further reinforce something that you'd already believed.

27:13Yeah. I will do two things. I mean, to reinforce the point I just made, like Joe, will you from

27:19total expert and awesome presentation and he talked through his five key learnings from AI.

27:24And I, if you want all five of those, you can come watch the content of housing wire subscriber.

27:29But the last one is like your organization will resist change power through the change power, like resist, like your

27:36organization will be resistant power through the change and power through the resistance.

27:39I'm sorry. I'm gonna get that quote right for Joe power through the resistance. Um, I mean, that's just such

27:44a core, like executive message and an organizational message right now. Um, what was the second part of your question

27:51there?

27:52Well, it was either, it was something that came out yesterday that caused you to think differently about the way

27:56we approach it or just further reinforced.

27:58Yeah. And I'll go back to using like old technology as an analogy, like something we've talked about internally is

28:06like AI is now a tool.

28:08And all of our team members toolbox and, uh, the same way in, in publishing or media, the typewriter was

28:16at a certain point in time, like you didn't become a better reporter because you said, I'm not using the

28:21typewriter.

28:22I'm going to keep like, I'm not, I'm not using that new technology or when, like when the word processor

28:27came out and like, you know, in the, in the office, we got PCs before our day.

28:31But like when that happened, um, you, you weren't a better employee or like more productive because you said, I'm

28:37not using that technology.

28:38Like, like curmudgeons will be curmudgeons. And, uh, the people who say, I'm not like going to use AI. I

28:46need the creative genius to flow through. I have to touch every word. I have to touch every, um, part

28:52of the process.

28:53Like that's, that's not going to work. Like this is the new technology is here. It's it's use it. It's

28:58part of the job. And, um, and I guess that goes back to Joe's message of power through the resistance.

29:03Like this is a, um, this is not a tool you can ignore. This is the internet. This is the

29:08word processor. This is the typewriter. Like, like this is just the way things are done now.

29:12Right. I would have an addendum to that, which is, you know, which I see played out so well here

29:18at housing war, uh, which not just because you're, uh, my boss and I'm blowing smoke or anything, but I

29:23do understand like resist, uh, power through the resistance.

29:26A large part of that though, uh, I believe is, uh, is tied to culture, right? I mean, we, I

29:33run our content studio and there's not a single person on, on, on, on my team that is anywhere has

29:39been anywhere remotely close to concern about the loss of their job due to AI. Right. And, and that is,

29:47you know, in, in, in the workplace, you, that, that's a, that is a common fear that people have, right?

29:53The AI is going to replace their job and they're going to be hesitant to change because they don't want

29:56to implement the thing that's going to put them out of a job. And that's a, to me, that's a

30:01large part of that's a testament to leadership in the culture of an organization.

30:05Cause that is not where, I mean, we, we run pretty lean here, you know, anyway, but, uh, you know,

30:11you and, and, and Diego, y'all have been very clear about the use of implementation of AI, the adoption

30:16of AI to make you better at what you already do, not to re not to replace you.

30:21It is an inevitability that you do need to get better at AI. We want you to be able to

30:26do more, produce more, not re not replace you. And that is not, that's, that's a leadership issue. That's a

30:32culture issue. And, uh, I, I think that that's something that's been, that, that you and Diego have communicated very

30:38well here that we're, this is the way of the future and you do need to get on board because

30:42it is, there's no going back, but it is not to replace you. It's to make you better at what

30:47you already do.

30:48And there there's like, I agree with that a hundred percent, but there's nuance in that across different businesses and

30:55across different industries. Sure. So like we, yes, here, we need everybody to, to utilize the tools that they've provided.

31:02AI is one of those. Um, I promise I won't use any trite phrases about AI.

31:07I will, um, I'm, I'm sick and tired of like the, the, the, the trait, um, AI will replace the

31:13people who, right.

31:15AI won't replace your job. People who use AI will like none of that trite crap. Like, but this is,

31:19um, this is a message. Like you've been given a tool, like use it, use the tools in your toolkit

31:24in some industries.

31:26And I think mortgage is one of those, there will be job categories that really do change. Sure. And, um,

31:33and it, this, this does become a moment that you have to think about, Hey, if I'm in a job

31:37category where my task was extremely administrative and I'm, you know, the, my relatively tried analogy is like moving paper

31:46from one side of the desk to the other.

31:48That's a job category. That's not going to exist forever. And it's shrinking quickly. Um, we heard it from Ryan

31:54Grant yesterday. Like there's, there's roles that aren't going to exist anymore in that organization, but there's also new roles

32:00being created and the new roles are getting closer to the client. And like, so this is where, um, humanity,

32:08like, you know, maybe hopefully it's a good thing. And I know there's some introverts who might not, might not

32:11love it, but, uh, like humanity is a real thing.

32:14And like, people want to talk to people. And if every Monday morning, someone who used to be a, um,

32:19a loan processor who operate largely behind the scenes is now like hopping on the phone and calling like Zev,

32:24like, I hope you had a wonderful weekend. Just wanted to let you know that your loan is at this

32:27stage of the process by tomorrow. It'll be here. And like, it's not an AI generated message. It's not a,

32:32it's not an email. It's actually a phone call with a relationship. I think there's going to be more of

32:35that as people seek humanity. Yeah. And, um, so there might be roles in our, in the mortgage industry or

32:42even in the media industry that aren't as important anymore.

32:44But it will likely come with the creation of another role that meets the moment of what the business needs

32:51and, and what people need as they have so many parts of their lives, like digitized and automated and AI

32:58away. Um, they, they're, they're seeking, uh, that human touch. And, um, so I, I think there's gonna be more

33:06of that.

33:06I agree. All right, man. Thank you so much for taking the time to sit down with me and yeah,

33:10we'll do it again.

33:10Thank you very much, Zeb.

33:11All right, man.

33:12Boom.

33:14Boom.

Clayton Collins: What leaders are still getting wrong about AI

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