Artificial Antics
Artificial Antics is a podcast about Artificial Intelligence that caters to the skeptic and uninitiated. Join this unlikely trio Mike (the techy), Rico (the skeptic) and A.I. as they dive headfirst into the world of artificial intelligence. From debating the social implications and ethical concerns around AI to figuring out how to break into the lucrative AI market, no topic is off-limits.
And with A.I. on board, you never know what kind of shenanigans are in store. Will A.I. turn out to be the brains of the operation, or will it be the source of all their problems? Tune in to Artificial Antics to find out!
Artificial Antics
Episode 15 - AI and Wrangling Your Data with Tim Hayden
In this episode of Artificial Antics, Rico and Mike explore data management and AI with Tim Hayden, CEO of Brain Trust Partners and one of the founders of "The Human Side of AI." Tim shares his experience in digital transformation, data governance, and customer experience. Learn how to "wake up your data" and use AI to improve efficiency, cut costs, and enhance customer interactions.
We also discuss "The Human Side of AI", a community-driven initiative co-founded by Tim, focused on exploring the ethical, practical, and human implications of AI. Tim explains how this forum unites professionals across various industries to share insights, best practices, and real-world AI use cases.
📺 Catch the full episode on YouTube: https://www.youtube.com/watch?v=5kovJvnHWgI
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✨ Chapters:
00:00 - Welcome to Artificial Antics
00:31 - Introduction to Tim Hayden & The Human Side of AI
01:04 - AI in the Automotive Industry
02:08 - Building a Future-Ready Business with Data
05:22 - The Value of Known Customers & Data Integration
07:02 - Private Language Models vs. Public LLMs
12:09 - Custom AI Solutions for Businesses
18:00 - Challenges in Deploying AI at Scale
19:29 - Onboarding & Implementing AI in Business Operations
24:41 - Data Intelligence Task Forces & AI Ambassadors
34:43 - Tim Hayden's Journey into AI
47:48 - Empowering Human Performance with AI
53:01 - Contextual Customer Interactions
58:00 - Final Thoughts & Wrangling Your Data
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Special Thanks:
Episode mastered by: Nomad Studios (https://nomadstudios.pro)
Description: The team behind mastering the Artificial Antics podcast audio. Big shout out to Nick and the team! 🎉
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Connect with Us:
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Natasha: [00:00:00] Welcome back to Artificial Antics, where Rico and Mike will talk about the implications and opportunities around artificial intelligence, machine learning, and deep learning. In this episode, AI and Wrangling Your Data, the guys talk with Tim Hayden, CEO at Braintrust Partners. Tim is a seasoned expert in data and customer experience, helping businesses navigate the complexities of digital transformation and data governance.
Rico: What's up everybody. And welcome back to another exciting episode of artificial antics. I am Rico with my cohost, Mike, and we are here with Tim Hayden from brain trust and the human side of AI. So we'll get the show started with having Tim kind of explain how he ended up with AI and talk a bit about some of the projects he's working on.
Tim Hayden: Rico, Mike, it's great to be here. Uh, really appreciate you guys having me on the show. And, uh, I'll say this on behalf of the human side of AI and unpack what that is in just a second, but thanks for all the support you guys give, thanks for being there on Wednesdays and, uh, you [00:01:00] know, hooting and hollering for us on LinkedIn and all the other places, um, Um, you know, the human side of AI was, was really built as a forum.
Tim Hayden: It was built as an exchange for, uh, people that are across the car business. Really, right. The retail automotive world, dealers, um, people that are vendors and consultants and agencies and software, you know, gurus and of course, artificial intelligence products, um, To really talk about what's happening in that industry, which is a whole lot of change, which is coming from all directions, going in all directions.
Tim Hayden: And because of that, I, you know, Wendy Reeves, uh, being, being the fearless leader of that group and the, and the folks that she put together with it, I think, you know, we're, we're doing our damndest to talk about use cases, what's working, what's not working. Um, even spotlighting some technologies each week when we can.
Tim Hayden: And in hearing about, you know, what is this looking like [00:02:00] for everybody as they employ automation, intelligence of a different kind and moving forward in the business, um, you know, while I'm introduced myself, I'll tell you, you know, I'm the CEO of brain trust partners. And at Braintrust, you know, we help companies build themselves into a future ready position.
Tim Hayden: Um, because of everything I just said, right, there is a tremendous amount of accelerated change with technology. And with that behavior, um, employee happiness, employee churn, customer happiness, customer churn, we're seeing it happen. We've seen it happen a whole lot just over the last 10, 12 years with the web.
Tim Hayden: Digitization, smartphones, Amazon, it's a whole lot has changed in a short period of time, and now it's changing faster. Um, I think with even more cadence, what does all that mean is, um, we help people build a single source of truth and understand the DNA of their organization, which comes down to data. Um, we [00:03:00] do total integration of a hundred percent of the systems that in this case, car dealers are using.
Tim Hayden: And with that. They're a able to check a big box with a lot of the compliance that is shown down on them by the FTC state legislatures and the like, but at the same time, improve their operations, reduce their media expenses, um, you know, cut their call times in half. Have their bays filled. Uh, talk to customers that they haven't talked to in eight or 10 years.
Tim Hayden: Uh, cause that's dark data. That's buried in the organization. Wake it up. Let's, let's see what we can do, right. To, to really light a fire in the business. And that's what we do. We do with customer data platforms and master data management solutions, like Axel Automotive. Um, you know, so, uh, exciting times right now for the industry and certainly exciting times with all that's happening with AI.
Mike: That's, that's awesome, Tim. Yeah, like we, we talked a little bit before we got started [00:04:00] here about how there's a, there's a huge trend in, um, that's starting to emerge. Well, I guess I don't know how long ago it started to emerge, but I've been hearing about it more and more, um, which is the, um. You know, the fact that people are sitting on gold mines, right?
Mike: Like there, there are a bunch of on tap gems and minerals that are sitting right there. Right. And, and you got me started thinking this way, honestly, the first time we talked where you said, Hey, this is like 12 years of data. And you said specifically 12 years. I think it was because. That's where he started getting the social media stuff and the different channels of data.
Mike: And it's, you know, it's, it's there and people are going for these, um, you know, top, top of funnel solutions to try and acquire these new customers. But it's like, no, bring back the old ones. I love what you said, wake up your data, wake up. I've never heard that. And so to me, I'm like, wake up your data. I'll never forget that.
Mike: And that's, that's a great way to say like, Hey, let's, let's take this older [00:05:00] That you don't, you know, you probably realize it's there. You've forgotten about it. You've swept it away and let's reinvigorate that and take that, put it together to build that total picture, right. Of the business, your customers, your market, and, um, and, and really, you know, move things forward, uh, and, and get that value out of that data.
Mike: So, yeah.
Tim Hayden: You bet. I mean, Peter's Peter Smith, who is, um, a part of that human side of a group that forum, uh, Peter Smith about every other Wednesday will mention the value of the known customer, right? He will talk about the fact that your propensity and an opportunity. To close business with people who've bought from you in the past is much higher than someone who's net new.
Tim Hayden: You're trying to reel in. And to that point, you know, dealers tell me all the time that they'll spend, you know, 500 to a thousand dollars just to get somebody to matriculate from cars. com or auto trader and, you know, building price on the site to [00:06:00] get them to the lot, they'll, they'll, they'll invest that much in most of their marketing automation is set up to automatically spend that money for them.
Tim Hayden: When what we're talking about is a respectable investment in the systems you have today to bring them together. And two is we've, as we've said a few times, wake up that dark data actually will point you in the direction of people who probably have a history of spending a lot of money in the parts department, spending a lot of money in services, um, you know, not just buying vehicles from you, but there's a total value that you're not, you're not seeing when you only look at that marketing and that sales and that F and I data, you're missing the picture.
Tim Hayden: So with that. You know, really leaning into, uh, that and, um, I won't quote it and, and misrepresent it. But Peter, Peter, when he gives the stats on that, it's pretty, it's pretty impressive what your close rate is with a, with a known existing customer versus a net new lead. It's, it's amazing.
Rico: I was just going to say that I [00:07:00] know from my personal experience, you know, with the dealerships around in my state, uh, that a lot of families shop at the same dealership, right? You know, it's like, Oh, your parents will say something to you.
Rico: And if, if your family had been shopping there for years and then just started going somewhere else, you dig that stuff up. Run it through some gpt Right? Then find that trend analysis and then figure out, okay, well where are we gonna go with it? You know what, let's contact them again. See what happened.
Rico: You know, tell that story of the dealership and why the business, you know, started losing people where they went
Tim Hayden: Rico, be careful though. We don't run that through GPTs, right? We don't,
Mike: I knew it. I saw
Rico: right. Yeah, yeah, yeah.
Mike: here it
Tim Hayden: information in GPTs. We do not do that. Yeah, yeah,
Mike: That's huge. so yeah, exactly, Tim, what you said, you, you're never running customer data through public GPTs, LLMs. Um, you know, I, I think that there is an interesting line because like, if you look at some of these tools, like let's say chat, GBT team, [00:08:00] right?
Mike: Like everything's private. They're sock to compliant. They're this. They're that. The reality is though. You're still running that through, through, um, you know, open, uh, the open internet and external LLMs. So this was actually one of the things I don't think I threw on the agenda, but I was really wanting to hone in with you on a little bit more and to understand.
Mike: So what's the difference between, let's say people taking their, their data, they've got their data, they throw, they throw different sets of their data into. Tools that are on the internet, like let's say chat GPT or even others and what you're doing there at brain trust, like the solution that you're providing.
Tim Hayden: you bet. You bet. I mean, I, um, I just want to, uh, I was looking at my phone cause I look it up. Um, the company, uh, Zenity and their, their CEO, Michael Bargary. Um, you guys may have seen that he was at the black hat security conference in Vegas just about a week ago. And he got up [00:09:00] on stage and demonstrated five different things you could do to manipulate Microsoft's copilot to become a, a, a phishing malware, right?
Tim Hayden: To basically come in, yank data off the computers in which it's installed. That's scary because copilot is now being brought to market as part of. Everything in office three 60,
Mike: yes.
Tim Hayden: uh, it's, uh, three 65. I mean, it's, it's, it is, it is there. It's omnipresent. It's there with SharePoint. It's there with teams.
Tim Hayden: Um, and you know, lo and behold, I shared this on LinkedIn, but the CrowdStrike, you know, the, the CrowdStrike event, we'll just call it that. Right. It coincided with an update from Microsoft. My belief is that. CrowdStrike was just doing its job. It was stopping people from bringing this in because it proposed some type of vulnerability or threat, you know?
Tim Hayden: Um, and, and that brings us back to, um, you know, the difference [00:10:00] between applied artificial intelligence and private language models versus those that are public, the differences are pretty market and pretty obvious. Once you start to explain them. Is that, you know, chat, GPT, um, anthropics, CLAWD as another example, these are systems that are trained on data that is at best, maybe six months old, even with rag, it's still just pulling in public data, right?
Tim Hayden: It's only pulling in public data. So there's two problems with that. One is. Um, if you wanted to do research and you wanted to ask for certain statistical research about current trends, a lot of the current trends are not gonna be able to be modeled or pulled by these models because the data's old.
Tim Hayden: There's that. The other side of this is that as you and your business are wanting to employ. Some type of language [00:11:00] model to help you do things faster, to help you generate content, to give you direction, give you a head start on an email or a blog post or whatever it is you're doing as you're doing this.
Tim Hayden: There's the security threat we already said. You don't want to share data with a third party, but at the same time, you want to have that model trained on your business, you know, and we can unpack that in a little bit because it's a little bit of a story to tell you. But, but, but the first order of business is to get your data together.
Tim Hayden: Right. And that's where master data management comes into play in outside the automotive business. This is where companies like Databricks have just taken off like wildfire. Databricks is a fantastic, uh, system. If you want to call it that, that allows you to bring all your data in and to cleanse it, resolve it and structure it, which what a lot of customer data platforms do with marketing data.
Tim Hayden: It's what, it's what all master data management systems do for [00:12:00] performance data warehousing. And to do that and to get the performance out of it, you got to clean it, you got to
Mike: Oh, yeah.
Tim Hayden: You gotta, you gotta segment it. You gotta, you gotta do all the other things with it. And then the use cases from there are endless once you're at that point.
Tim Hayden: So a nice next step as we've looked at both the capacity of some firms to build private language models and, and then others to capitalize on open source models like, um, like LLAMA3 is a nice next step as we've looked at both the capacity of some firms to build private language models Bring llama three into your environment, close it off and make sure it's secure.
Tim Hayden: And then from there, let's look at building a logic tree based on the decisions and the workflows of your business of a certain human or certain team members. Let's train, let's train the bot to act like those team members. And then let's train it on your data. And when we do that, everything becomes brand centric, customer centric, [00:13:00] and, and, and the questions that you ask it, if it's trained to create content for you, it'll be specific to you, your brand, brand style, styles, style guidelines, all of these things, right?
Tim Hayden: And it's just markedly different than when you just go up to a public model and you ask it to do things for you. Right. Um, you know, there's, there's, there's fewer hallucinations and there's fewer, just wrong answers when you're dealing with data, you control.
Mike: Yeah, absolutely. And I will say a couple things there, you know, one is that, um, you know, with, with custom GPTs, which I, you know, obviously I'm, I'm telling people, Hey, like PII, like Nothing can go in there with that and all these things, but I'm still helping people to build tools. And I say, here's the starting point.
Mike: Cause you know, they're thinking I want an outcome and I'm like, that's cool. We'll talk about the outcome. How, how would a human get to that outcome? Right. How would a human get to that outcome? Right. And then, [00:14:00] so. Build up right. A core set of data that transcends across GPTs. This is like your brand voice, your brand identity, um, your tone, you know, different things like that.
Mike: And then it's like, okay, the next layer is like more specific knowledge and training, right? Which is like the stuff that's, that's, you know, all right, we're going to have, uh, we're going to build a, you know, a sales and marketing or go to market. Right. Uh, GPT to do these things based on, you know, some, some, you know, specific data and then it's like, okay, now what, what our inputs are decisions where it's like, okay, select this, select this.
Mike: And then it's like, what's your actual data? Like, okay, put the brand name in that you're looking to look into market too. Right. And, um, so, so that, you know, that no matter what, you have to figure out how a human is going to do that effectively, which means, and I love Wendy says, get your house in order.
Mike: Right. And I was talking to our CEO today. And I was like, yeah, you, you have to have that process down and it has to be efficient
Tim Hayden: You bet.[00:15:00]
Mike: you build a custom GPT to do the same thing. And if you build it, maybe it's more efficient, but it's not effective. Right? Like it's not because you're not effective with humans doing that same thing.
Tim Hayden: Right, right. I mean, I think that's just it. I mean, we, uh, we've done this since the earth cooled, right? We've, we've manufactured machine mechanics systems that best conform to what the human operation looks like, right? It's we are the ones, Who are looking for the outcomes, as you already said, right? It's we have objectives.
Tim Hayden: We have qualitative and quantitative intentions with what we want to achieve with businesses. Respectively happiness and revenue. Right? I mean, uh, let's, let's be, let's be honest, right? We're, we're looking at how we can build margins. We're looking at, as I said before, you know, if we can cut call times in half and reduce our media spend by 20 or 30%, [00:16:00] maybe there's a little bit of savings we can pass along to the customer and the rest we can put in our pocket.
Tim Hayden: Right. Um, you know, that's, that's what technology has always promised to do. And I would argue that, um, that AI is the first one to holistically afford us an opportunity to, to make things like that happen. And the old, the old adage, you know, faster, better, cheaper. AI is the first thing that allows us to do all three of those things, right?
Tim Hayden: You couldn't, in the past, you could not do all three.
Mike: of three. Two
Tim Hayden: do two of the three, but you couldn't do all three, but AI, when it is configured and when it is implemented and it's put in practice with, you know, in a thoughtful way, and it is centered around how the humans could get value out of it, that's where you can really get into this, right?
Tim Hayden: You can get into the faster, better, cheaper, and that does all those things. It creates what Wall Street wants to see. Lower capex and more revenue, right? That's, that's what we're after[00:17:00]
Mike: Right. Right. Yeah. Well, exactly. Because like when you're looking at growth overall, right, you can, you can grow the revenue, but you're all adding value. I should say, right. You can either add revenue and grow as you want to do that, obviously. But you can, you can also add efficiency gains, right? Like, and save money, right?
Mike: And save and do, and do more. And I, I saw a quote that I really liked and I put it in the AI Bites newsletter, uh, either last week or the week before. And it was like, you know, if a company finds that it can do something, uh, a hundred times faster, it generally, they generally will do that operation. X number of times more rather than saying, okay, well now we can just do it faster.
Mike: Let's do it faster and walk out the door. Right?
Tim Hayden: More volume, more volume.
Rico: Increased volume. Yep.
Mike: The increased volume velocity. Um, and, and I, I do, I do agree with you. Um, I I've talked to a few people about that, where I'm [00:18:00] like, you know, faster, better, cheaper, um, it's to pick two, right? Pick two forever. And.
Tim Hayden: go. Yeah,
Mike: And I do think that you're right.
Mike: This is the first time we've ever had it where it's like, okay, it's, it's like on the it's on, it's not even just on the horizon, but you do have to do it. Well, you have to do it. Well, you have to have the adoption. You have to, you have to do it mindfully. I think you said a second, a few minutes ago, um, and intentfully, right.
Mike: Do it with intent. And you really have to have what I'm going to call like a really good framework to reproducibly do it. Well, right. So, and I guess that's kind of what, um, uh, I'd like to segue into is you don't have to give me the mix of the secret sauce, but what I find even personally is like, sure, we can build, um, you know, uh, LLMs and, you know, open source libraries are fantastic.
Mike: We can host it on our own servers. We could do this, we could do that. Keep it all in house. Um, but to, [00:19:00] to reproduce that and deploy that at scale, that's where my mind is not quite there yet. Even though I know people are doing it, I don't think a ton of people are doing that well yet. Right? Like the ML ops or the biz ML ops.
Mike: Um, so can you speak to that a little bit about, you know, some of the challenges that are presented. Faced and again, without giving away the secret sauce, like how you're solving some of those challenges and what that onboarding ramp looks like for a business, that's going to use brain trust to accomplish the stuff that you talked about.
Tim Hayden: Well, you bet. There's a sequence to still have, you know, an order of events, right. And, and order of priorities, I think is the better way to say it in terms of how we do this. But all in all, I think, you know, let's, let's face this. We have these hats. I wish I would've brought one in the studio with me. I'd show it to you.
Tim Hayden: I'm not, I'm doing that for the next time. But, um, yeah. But we have these hats that we wear at brain trust when we have team meetings and every once in a while when [00:20:00] we know we've got a a lighthearted, fun client with us. We'll, we'll wear them when they walk in the room and they, it says on the head, it says, actually, this is my first rodeo.
Tim Hayden: And, um, and it's, and it's more of a mindset, right? It's a mindset that we all have to have is that. There is no such thing as best practices. There hasn't been for some time. For some time, there's not been best practices. There's really not much room for playbooks that apply for more than one company or more than one department within the same company.
Tim Hayden: Right? Um, you can have guidelines. You can have policies. Absolutely. We need those. We have to have those in place, especially when it comes to data governance. But at the end of what we're talking about here, Okay. For people to capitalize on this and to weave it into their, their, their workflows, their work streams.
Tim Hayden: I think we have to everybody have everyone embrace really the fact that we're going to experiment, [00:21:00] we're going to explore, and we're going to figure this out together. And honestly, when you think about that and you think about the accelerated rate of change. We need to also understand that we're going to iterate how we optimize and how we leverage what it is we have licensed and what it is we're building in terms of that digital experience, which is just a customer experience and certainly a human experience.
Tim Hayden: Right? Um, You know, for us, it all starts with a data intelligence task force. Some companies like to call them A. I. Councils. Um, but bringing leadership in from each of the business units in the organization. This is not just a marketing thing, right? This is this is a this is a holistic enterprise opportunity, and we need to bring in representation and and hopefully leadership.
Tim Hayden: From each of the business units and the operation centers, cost centers, sometimes they're defined branches if they're banks, right? Um, even then within each [00:22:00] branch, we need representation. They all come in and for a few months, we build a consensus of digital literacy. And a consensus of the prioritization of their use case desires.
Tim Hayden: What do they aspire to do differently? Um, which all starts with the current state analysis. How do you do business today? And, and us suggesting to them ways that they could employ automation, ways they could turn processes that take five steps and turn it into two steps. Um, that lasts a couple of months and that's discovery.
Tim Hayden: And then that task force. who becomes our point of contact. We may still have a CMO, a CPO or someone else involved in the car business. It's a dealer principal. Usually who's, who's tuned into what we're doing. They may be there, but they're, they're lieutenants, right? Who are on the front line of the business are also going to be part of this, not always committee approval, but always community [00:23:00] discourse, right?
Tim Hayden: Community. discussions and pondering what it is we're doing and what we expect to get out of the investment. So all that does is for the software vendors that are listening to this is It better informs the scope that your company is going to put on the work order for the CRM, the marketing automation system, the chat bot, or anything else you're going to configure for them.
Tim Hayden: If you don't invest in that early diligence, and that's what consultants like we do. You know, if you're not, if you're not bringing that in to get that nailed down, then I'm sorry for you because that's, what's going to have them not renew their license with you. That's, that's what, so it's going to find you up the creek without that paddle within six months, eight months, certainly 12 months when things start to happen.
Tim Hayden: Um, because you just weren't clear in what their needs were because you tried to sell it to them the way you did the last person. Um, And AI takes that even deeper because it has to be bespoke. [00:24:00] It has to be customized. Um, no two companies are operating the same way. They don't have the same audiences.
Tim Hayden: They're not selling the same stuff. That's it.
Mike: excellent. Uh, yeah, no, that, that definitely clears up. I, you know, the thing is like, um, you know, I, I, so what, I guess what I'm wondering is how long, so you said it takes about two months to kind of go through that first stage of, let's call it discovery, right? Once you've discovered, once you've kind of got aligned with, um, your, um, what did you call it?
Mike: Data, data intelligence team, data intelligence group. Yeah.
Tim Hayden: Data Intelligence Task Force.
Mike: Okay. Yeah. Like, like at Clarity, I actually call this group, the AI ambassadors. Right? Like, so I just came up, this was last July or whatever, when I really started like saying, Hey, we need to start building and, you know, be intentional about this, start building policies, start doing this.
Mike: And so I've got a group, I think we're about 10 people. Right. And, uh, [00:25:00] and so, and again, yeah, it's exactly what you said. Right. It's. I didn't just want this to be the Mike Onslow show, right? I'm not the AI godfather. Um, I want this to be really omnipresent throughout the whole company and, um, you know, and have, and have really every, everybody enabled and on board.
Mike: Otherwise you just won't get the adoption, right? They'll say, Oh, Mike's doing cool stuff with AI or they'll
Rico: He showed me something once.
Mike: Yeah, they'll kind of expect you to feed it to him, right? Whereas, like, you could feed it to him a little bit, but then you need to, they need to learn how to cook, right? Like, I think about it with kids, too.
Mike: It's like, sure, you could feed them and everything, but it's like, oh, let's make French toast together, you know what I mean? And like, so, step that that way they could, they could actually go and, um, they're part of the process, right? Literally part of the process, which then gives them that skin in the game, that buy in, right?
Mike: And, um, and, and so I, I find that, you know, even there are challenges even with having that [00:26:00] group, right? I mean, just cause, you know, People are time strapped and everything else. Right. As we all know, we're, we're all busy. We all have stuff going on, but it's, it's really, um, I think just having the conversations that a lot of times, right, like in the office, I was there yesterday too, and I literally talked to three different people about, um, some of the capabilities and different stuff that we're doing within the company.
Mike: And they're coming up to me and saying, well, what about this, and I have this idea. And I'm like, Oh, yeah. Well, let's go take a look at how we could do that. Right. Draw on the whiteboard and sort of like work through things. And, um, which gets everybody involved. And I'm very fortunate because our, our CEO, Gary is literally like he'll do sessions, like when he's doing something, he's working on a project, he'll actually have somebody involved in Hill, you know, the people involved, like, Hey, now you do this and try this and whatnot.
Mike: And I don't, I don't think that's like that at every company. So I'm very fortunate that. I have like a serious advocate at the very top. He's the founder of the company [00:27:00] that, uh, that, that is similar to me. And like, he is ensuring right. That we're, that we're, uh, you know, using this stuff and using it responsibly as well.
Mike: Right. Cause that's extremely important. Right. I mean, you can't, you can't just. Go and let's just throw our sales, uh, information for the last, you know, 10 years in the chat, GBT, it'll crunch some numbers for us. Uh, the free version, by the way, the free version, by the way, just,
Rico: The free version.
Mike: out there.
Mike: And, uh, so, yeah, so, so there are definitely some, um, you know, some things to watch out for. And that's, that's another thing that I found is extremely important is like. When we're doing our quarterly sessions, you know, we have a virtual events. We have in person events where we bring everybody in like every one of those, I'm doing some sessions on, you know, using it responsibly where you can find the data and, uh, and, and that is, I feel like.
Mike: That sort of reminds people, uh, as well as that enlightens [00:28:00] people who especially are newer to the company. Right. Cause you're going to have new people on the teams and whatnot. And, uh, and Oh, another thing that we've done too, is we've incorporated it into our onboarding process. Like it's actually part of the process and it's not just, Oh, here's the handbook.
Mike: Right. It's like, Hey, no, here's some real things. And we're going to kind of test you on that comprehension and run you through some role play. Um, so. You know, that type of stuff. Uh, otherwise people are, they're not going to know what they don't know. Right. So, and, and, and so that's what I find with AI, especially or AI ML, especially it's like people just think, Oh, wow, this can do this really amazing.
Mike: This amazing stuff really fast. And. You've got to look at, um, you know, we had a guest on our last guest was Tim Kukur, another Tim, right? He's the CEO at Task Drive. And he, he mentioned this thing that I really liked, which he puts a, um, when he's, he does like a 12 week AI first mindset and [00:29:00] helps people build the tools and everything, but also really trains them on that mentality and safety and security.
Mike: And he said, you know, Uh, we teach them to kind of like put a sticky note, uh, with AI question mark on it, like somewhere prominent where, you know, it's like, Hey, you know, I'm about to do this thing. AI, you know what I mean? It gets you thinking. And I was thinking after that, I'm like, so I did like a little graphic of like AI question mark, securely, safely question, like on a different post it note, because it's, it's just extremely important.
Mike: So, and I'm not just paranoid. I mean, it's like really important. So,
Tim Hayden: It absolutely is. I mean, yeah, and and and amen. Good for you for being in a situation for having the support from all around you, um, to be able to socialize this, right? I mean, that's That's what this has to be. I, I chuckle a little bit when I see announcements that a company has created a chief AI officer.
Tim Hayden: Right. I chuckle and I do so out of [00:30:00] ignorance. I don't know what these people's responsibilities are other than what they share and post, but, but at this, but the same thing, it's, it's not always going to be this, this of all things cannot be top down alone, right? This, this has to be one of those things that's very flat in terms of how it's managed.
Tim Hayden: For, for one simple fact that at this current moment in history, most of the software and the dashboards and the systems you use right now on your desktop computer, most of those systems are starting to bake some level of automation, some level of AI, if not generative AI. And you have people in different divisions, different departments who have by themselves, uh, a credit card put on a website or, um, you know, they've got the license for a piece of software and they're not always going to the CTO or the CMO or the CFO, [00:31:00] you know, they got their budget and they spend it and they do so within their wing of the building. And we need to do exactly as you, as you said before, in the same similar way is we need to ask everybody is what, how would you do this different? Or what ideas do you have? Um, um, and I'll, and I'll back that up for a second is to say one of the things that we do when we get into the whole five steps to two steps type thinking is Is we ask everybody in the conference room, we say, quit by open your calendars and find something that you do two or three times a week on your calendar.
Tim Hayden: Because most often it is generating a report. Most often it is checking in with somebody. It's, it's a very tactical, it's a very turnkey thing that they're trying to do. If it's there three times or more, a machine can do it. Right. I mean, and if you don't think you can feed your dog, um, that it can, that a machine can feed your dog, go to Amazon.
Mike: That's right.
Rico: Right
Tim Hayden: time on the [00:32:00] right now,
Mike: Or clean the litter box. Or clean the
Tim Hayden: Litter box. You know, you have, you, you know, you're not gonna let a robot bathe your baby anytime soon. But, but, but, but I can tell you right now that, um, most of the cars on the road have got lane assist and adaptive cruise control. They're, they're driving themselves already.
Tim Hayden: So, you know, there's, there's not a whole lot that we're not gonna be able to take out of the, the ordinate task parts of our lives. Right. And start to have. You know, start to have intelligence, neural networks and all kinds of other mashups of things that disparate people are working on right now. Just imagine when they start working together are going to do our lives.
Tim Hayden: It's going to be fascinating.
Mike: Yeah. Absolutely.
Rico: Tim, I don't know if you mentioned, I don't think you mentioned it here, but uh, do you wanna talk a little bit about how you got your start with ai, like how recent that was and what kinda led you there?
Tim Hayden: Sure. I mean, I'm happy to happy to talk about it. I mean, You can go [00:33:00] back to, um, you can go back to around 2010 and 11 and, um, I was a mobile strategist at that time. Um, uh, I was working for Edelman, the world's largest PR firm, the world's largest independent agency. I ran their mobile program in North America.
Tim Hayden: And we had different things we were doing for different clients where we were looking at, um, sensor technology. Um, we weren't calling it low energy Bluetooth. We were calling it near field communications back then. Right. Um, and it was something different at the time. It was more a radio frequency than it was anything else.
Tim Hayden: And, um, we started to look at different ways that we could do just, as I've already stated. We could cut corners in operational processes. Um, we could do the same thing in terms of, uh, mobile apps that could create utility for people to order a coffee remotely and do other things. Right. And, and with that, we started to [00:34:00] look at very early days of algorithms.
Tim Hayden: Right. Is, is, is what they were. It was fantastic mass and it was fantastic mass that had been digitized. Right. And put us into this ultimate string of if, then, then, that, and not that, and do this.
Mike: Right. Yeah.
Tim Hayden: so, early days of that kind of statistical logic, um, you know, which is what we're dealing with right now with Chad GPT and Claude is statistical logic.
Tim Hayden: Um, but early days of that, uh, you know, that's. That's probably where it was. We weren't calling it AI though. We were calling it automation at the time. We were calling them sensors. We were doing that. It was later, 2014, 2016, I was living in the Bay Area and I was working for a company called Signal Labs, which was a media intelligence.
Tim Hayden: Um, we used to say, stay ahead of what the world thinks. And it was real time analysis of everything that was happening in print media, television, because you can, um, cause you can capture closed caption television [00:35:00] everywhere right
Mike: Ah, yeah.
Tim Hayden: you can do it then you can do it, you can do it really well now.
Tim Hayden: And, um, and then of course, anything's happening around social blogs, websites, anywhere else, right? We were looking, um, there were issues back then of, you know, There were these bot farms that were in Asia and Australia, Europe, and actually one here in the Americas at the time, that every time a certain political candidate would tweet, um, in a matter of milliseconds, 20, 000 accounts would retweet it, right?
Tim Hayden: Um, there were the other things that are not political where, um, you know, because that gets us into a conversation about disinformation and
Rico: Right. . Right.
Tim Hayden: Swaying
Mike: Right.
Tim Hayden: public opinion one way or another, right? Um, and, and, and here we are in an election year, but anyway, um, uh, you know, where I'm going with this is.
Tim Hayden: Um, there was this fascinating thing that was [00:36:00] happening where some of these groups were basically bringing up old news, like an oil spill or a pharmaceutical company who failed FDA approval. Um, and, um, the, the news could be 10 years old, but they could make a trend on Twitter and, and CNN had it. go on their ticker if it was a trending topic on Twitter.
Tim Hayden: And there were companies who lost almost billions of dollars in market cap because of it, because of the negative sentiment associated with what they were reading. Right. And they called the brokers and wall street just dumped stocks. So, um, what we found was our ability to. Do a couple of things. We were able to put a wildcard operator in the Boolean search that we were using for the social listening.
Tim Hayden: Um, that would help us understand that the things that were making this story trend were a bunch of accounts that were just open two days ago, right? [00:37:00] Um, cause Twitter, cause Twitter was doing its job to shut them down. It was trying everything, right? It was, it was trying, um, but, um, they would be back the next day.
Tim Hayden: Right. And so we, we basically put some rules in. to say, let's, let's not analyze this or let's analyze it differently. Let's sequester this different analysis on really what's happening. What do people really feel like and what are the robots doing to us? Um, so with that, um, we started to look at. Not only how we could do all of the above, but how could we create, and we weren't even calling it generative AI at the time, but how could we create AI that could produce text that could give somebody in the communication suite or the marketing suite, um, The public affairs suite, give them directional guidance, not just a dashboard, but also something that says, Hey, right now, um, you should reach out to this person and this person and, um, and, [00:38:00] and, and put an update on Facebook that says something contrary to this, right?
Tim Hayden: It would basically prescribe a next best action. So, you know, we knew that was a I at the time. We did know that was. was artificial intelligence. And, um, and it's still today when you think about it, um, it is legacy machine learning and it is artificial intelligence that was around then, which has been, is manifested into contemporary artificial intelligence, AI models today that are deep in the pipes of companies.
Tim Hayden: That are doing this and they're working along technologies like robotic process automation and things like that to make, to make things happen that we think is just simple connections with technology, but it's actually, it's a digital workforce that is, is going to work on the inside of the, The majority of the global 2000 and many companies who are adopting present day contemporary systems, right?
Tim Hayden: It's, it's happening. [00:39:00] Yeah.
Rico: Wow. Uh, that's, that's one of my favorite things is hearing how people ended up there and I love how it always starts with like cutting corners or like, you know, trying to like simplify a task, but, and the bot farm issue, you know, I've seen a bunch of videos on that recently and it's, it's crazy to see a person sitting at a laptop with, you know, however many hundreds of phones ahead of them.
Rico: And just clicking buttons and watching those scroll. And a lot of us that are, you know, uh, I guess, uh, people who use social media and that type of thing, you don't really give that much thought. I mean, some of us do, right? You're like, there's a ton of bought accounts that are driving this, but, uh, the danger of that, like you said, with, with, uh, knocking off a bunch of market cap off of a company that with old news, that's insanity.
Tim Hayden: A company whose nose has been clean for the 10 years since, right? I mean, there's, there's, there's, there's that kind of situation and there's, um, you know, there's the general thing that people have to understand on the cybersecurity front, period. That a I [00:40:00] widens the footprint, right? It widens the vulnerability range that companies have today because no longer with all due respect.
Tim Hayden: Is it the 12 year old Romanian boy waiting for his mom and son? breaking to get a million credit card numbers. It is not just that. It is the fact that there are very sophisticated bad actors who are knocking on millions of doors every second to find the vulnerable hole in the wall or door left open to get in and get information.
Tim Hayden: Not to mention what they're doing in countries like Myanmar and uh, and uh, Cambodia right now. And, uh, training people how to get phone numbers off the dark web and to send us texts all day that say, um, Hey, there's a package waiting for a USPS right at the postal station right now. Click this link and give us your address and your credit card number or, um, uh, you know, or getting an email address and saying, [00:41:00] Hey, impersonating happened to one of my employees last week.
Tim Hayden: They got an email. It looked like it was coming from me. The email address was not mine, but it said Tim Hayden sending an email to, to that employee and saying, Hey, I'm trying to pull a secret surprise on everybody. I'm busy. Can you go to target and buy three 50 target
Mike: Get some gift cards! Yeah!
Rico: the gift card.
Mike: that,
Tim Hayden: know, this is, this is just part of when you think about A.
Tim Hayden: I. and A. I. agents. This is what bad actors can do to go find the information that enables them to go do stuff like that. And, um, and, and this is what everybody has to understand is that there's a lot of systems we use that are built on code that's 30 years old, right? It's, it just, it just, it can't be held together.
Tim Hayden: It's a house of cards. And we're starting to see that in the news with data breaches and outages and hacks right now. We're seeing, we're seeing these things start to happen right now before our very eyes. Um, I'm afraid it's going to get worse before it gets better, [00:42:00] but it's, it's the part of AI that people don't want to talk about.
Tim Hayden: Right? It's just, um, this and the bot farms are just two of those things that I think a lot of people just, they may watch 60 minutes and be educated on it, but it's not in the news every day. It's not something that, you know, that, that Mike's going around and educating everybody at the office, you know?
Tim Hayden: Yeah. Yeah.
Mike: Well, and you know, you're right about that. And I think that a lot more people, um, are, are looking at what thinking of remembering the Terminator movies and, you know, these other things and thinking, oh, that's how it's going to get us and that's how the world. No, it's, it's, it's not going to be that it's going to be bad actors using AI and a flurry of that.
Mike: And accelerating upon acceleration about acceleration. Right. And that's going to compound as things do right, like to cause a lot of havoc. And I'm not saying exactly how the world's going to end, but you get what I'm saying, right? Like in my mind. It's it's bad [00:43:00] actors that are driving this, right? It's um, it's I'm much less concerned Uh, like I think that hey, maybe someday we might have a terminator situation I think well well before the terminator situation.
Mike: We'll actually have a a human situation Uh where they're they're just a lot more efficient at driving The the bad actors are much more powerful than they used to be now. I also think to myself You Well, how do you then combat that right? Security is one of the things in my mind. I feel like AI can be the most, like, like do a lot of good, right?
Mike: Because if you've got a crazy velocity on these bad actors, well, you kind of need a crazy velocity, right? Like to, to combat that. Right. So I do think there's some opportunities there as well. Right. That, um, you know, you, you've got, we, we just have, we have to be resourceful. We have to. Understand that, um, that this stuff is, is going to [00:44:00] change on both sides all the time, right?
Mike: It's always changing. Yep.
Tim Hayden: Totally. And you, and you had mentioned earlier, I mean, um, uh, a lot of the software that, that folks are licensing today is SOC2 tested, SOC3 tested, right? Um, and then companies themselves can have a SOC put in place, right? Um, um, and, and that usually has a price tag associated with it. Even, even when you do that though, it's, it's something we've talked about a couple of times already about building the, the literacy within the organization among the employees, right?
Tim Hayden: Is having them understand how they can be better about governance and how they can be better about protection of their employees. changing their passwords on a regular basis and not using the same password in more than one place. Um, simple things that, uh, that a system like Dashlane can do for you, right?
Tim Hayden: Can just automatically do for you. Um, there's, there's that kind of thing. There's multi factor authentication, there's updating your operating system when you're, when your system tells you, I know you have [00:45:00] 52, uh, tabs open in your browser. I know you do, but guess what? You need to shut your computer down and let it restart and download.
Tim Hayden: The, the bug fixes and the security patches now. So, you know, it's all, it's funny because this gets back to the human side is. A whole lot of the reasons that bad things happen and a whole lot of reasons of why AI won't perform the way it said it would on the wrapper, um, pun intended, um, the, you know, is, is because humans And humans make mistakes, you know, they squirrel, I mean, they, you know, humans, just make missteps and that's the best way to say it.
Tim Hayden: And, um, and it goes back to what we were talking about before. It's, uh, everybody just has to respect and not give themselves a hard time. That it's, this is our first rodeo,
Mike: Yeah. I like, I like that take. And it's, it's funny that you mentioned rodeo and I told Rico, I was like, we should, we [00:46:00] should name this one, like wrangling, wrangling your data with Tim Hayden, because I know your LinkedIn is saddle up, right? Like I'm like, we gotta, we gotta add this theme in there. So, um, I love the take.
Mike: I love the first rodeo thing. Um, it just, it just being real with. Um, you know, exactly. Nobody's an AI expert right. Now. If you say you're an AI expert, I, you're not Right.
Tim Hayden: not,
Rico: let's see the certificates. Where did you go
Tim Hayden: no.
Mike: right.
Rico: to Coursera courses? What did you do?
Mike: Yeah,
Tim Hayden: That's right. That's right. I mean, you, you may have experience. You may be very proficient with python. Um, you may, you know, there may be a lot of college students that I talked to these days, interns that I've had come out, um, like from comms and journalism who been taught are as a language right to to gen up analytics within excel spreadsheets and things like that.
Tim Hayden: Right. And, um, I just, you know, it's people are at different steps in their journey. They're coming from different vantage points, different starting points to the point you made Rico, right. [00:47:00] Is, um, it's, it's going to be different for everybody. Um, and, and what's funny about it is we talk about AI and like, it's a one thing.
Tim Hayden: It's just not, it's, it's, it's coming to market in. A million different ways and it will change business over time. It will change most of the fundamentals on operations. It won't do much to change the fundamentals on business performance, right? Um, it may influence business performance, but it won't, it won't change how we measure success.
Tim Hayden: I don't, I don't think. Um, and, but, uh, it, it will help us to the points we've already made. It will help us do things faster, cheaper, better with more volume. Um, you know, that's that's what we're here to do, right? We're not here to replace humans. We're not, we're not, we're not there to do that. We're, we're here to let humans do what humans do better already, which is be creative and thoughtful, um, have a smile on their face and ask your son.
Tim Hayden: What does he play baseball or not? Right? [00:48:00] I mean, This is, this is, this is what you do in sales. This is what Dale Carnegie taught us, right? So
Mike: Exactly.
Tim Hayden: yeah,
Mike: Go ahead, Rico.
Rico: I was going to say, so we're going to get into that part of the show where we're usually we kick it back to them. And, uh, if you have anything, Tim, that you have going on that you'd like to say, any, uh, exciting projects, that type of thing, go ahead and hit us with it.
Tim Hayden: You bet. You bet. No, um, you know, we're, um, you know, we've got a number of master data management projects underway. Um, some of the automotive industry, we do work in other verticals. Um, but we, um, you know, we've got a bank who's on year two of, uh, using treasure data, which is a enterprise customer data platform that has, uh, Um, a very thoughtful maturation curve, right?
Tim Hayden: As, uh, as the data and the machine learning, um, he starts to mature, right, in terms of emulating. What humans have done with querying audiences, building audiences, those kinds of things. It's fun to see [00:49:00] that happen. That's, that's a, that's a bank we're working with right now. Um, it's, it's doing that. And then, um, we've got a couple of clients right now where, um, they're asking us to build bots that emulate their top performers, right?
Tim Hayden: They, they want to see what they can do for the purpose of building more volume, right? More throughput. Is what they're trying to do is to say, how do we get, how do we emulate that decision making and the workflows of this person who from a productivity and performance standpoint is stellar? How do we, how do we learn from them?
Tim Hayden: How do we transfer knowledge from them to the bot itself, the model itself? Um, the, the logic tree and decision tree we use to configure it modeled after that person. Um, and we're doing one in the medical space right now, um, with insurance claims processing. So, um, Um, you know, it, it all falls in that folder that says first rodeo on it.
Tim Hayden: It just, it, it falls, it falls into saying that, you know, we, we have no two clients that are [00:50:00] trying to do the same thing right now. Um, even, even when it comes to in the same vertical. Um, the car dealers we meet with. Um, you know, we're hearing different objectives. We're hearing different KPIs, if they want to call them that, but different, um, quantitative goals that they have with the business that are different from the store across town that we might've worked with already, or the, or the, or the store in another city, they're selling the same brand.
Tim Hayden: I mean, it's, it's, it's just awesome. Uh, um, you know, I like to think of it as DNA is when we get in there, And we start to bring all the data in, in, in this capacity from fixed ops, you know, from repair orders and service and, um, and, and warranty claims and all these things, right? Everything that happens on that side of the business, combining with everything on the other side of the business, which everybody calls variable sales, F and I, internet sales, all of that marketing.
Tim Hayden: Combining all of that together, you know, that's, that's [00:51:00] what gives you true business intelligence. It's what gives you the true opportunity. And we have a couple of dealers right now who are ready to go in that direction. They are excited about that. And they know enough about what we've talked about, about training AI models on that data, once it's all been ingested, once it's all in operation and, uh, cleansed and structured all the things that we do.
Tim Hayden: And, and they're starting to look just like with the insurance claim processing. They're starting to say is, ah, how do we get this to become representative of what the people on the sales floor need to know from our information? How do we get them to talk to our data? Um, how do we tie it into the phone system?
Tim Hayden: So when, when a call comes in using caller ID, the record for that, that record associated with that phone number pops up on the screen, that's So you can have the most empathetical. Hey, Mike.
Mike: Yeah. Yeah.
Tim Hayden: Tell me, tell me the last four digits of the, of the credit card you used [00:52:00] last Wednesday, right?
Tim Hayden: Creepy, creepy stuff like that, right? You know, but you know, verifying who you are and then immediately saying, are you, are you calling about your 72 GMC Jimmy, you know? Because we see you've been in a number of times for air filters and lug nuts. And you know, what can we do for you today? Right? I mean, that, you know, that's different than the personalization that everybody's been talking about for a decade.
Tim Hayden: That is, that's individualization. It is. It's where we're headed. And I think it's, you know, I have the opportunity to be one of only a few people talking about it right now in 2024, at least August of 2024, but a year from now, I bet we're going to start to hear stories where it's happening to people, right.
Tim Hayden: In terms of their retail experiences and, and, and hopefully in the car business, right. They're starting to see that kind of thing happen.
Mike: Yeah. So Zachary from Numa on the [00:53:00] human side of AI. One of the things he said that hit so fricking hard was the scariest thing for the person who's about to pick up the phone is, is truly who's on that line. Like you could see their name, but the name is not enough. Right. You have to understand where they're at in their journey.
Mike: Right. And like these different pieces of information, the more that you can pick up the phone armed with that data so that you can immediately, um, you know, uh, act on that, uh, act appropriately per where that customer is right. Like in their, in their journey, the better off that you and the customer are going to be, right.
Mike: They're going to be like surprised that like, wow, this person was exactly what I needed. Well. I mean, it's so, it's, it's, it's human performance powered by ai, really. I mean,
Tim Hayden: That's it.
Mike: thing.
Tim Hayden: That's, well, that's it. I mean, you, uh, um, um, you know, in that vein, um, people who've, uh, heard me speak more than once or see me on more than one podcast will always [00:54:00] hear me bring up the Sewell experience, right? The Sewell dealership experience. I grew up in the Dallas Fort Worth area. It's, the story goes like that.
Tim Hayden: And my parents always had a Lexus or a Cadillac in the garage. And for 15, maybe 20 years. My dad got every one of those cards from the same person, right?
Mike: wow.
Tim Hayden: They never called service. They'll call service. You call, you call your guy, you call you, you call
Rico: Yep.
Tim Hayden: guy. And he would call us, he would call us and say, Hey, I got a new LS 400.
Tim Hayden: I want to bring it by and show you what the next year model is going to look like. Right. And sure enough, we'd, we'd buy the next year model LS 400. And there would be in their garage. I mean that right there to the point, you just made, I mean, there are, there are companies like Like Sewell, there are companies like Southwest Airlines, right?
Tim Hayden: Southwest Airlines has a culture to have every single team member be contextually relevant and empathetic with you at every point. And they do a great part of that through [00:55:00] storytelling and humor, right? Um, and, and, and it relaxes you, it disarms you. As that's happening, you know, you can always tell there's people on the flight when they, when they, they, they're flying Southwest for the first time and they always fly American and they kind of, they, they don't like it.
Tim Hayden: They don't like the jokes. Right. But, um, but everybody else, everybody else is on the plane. As soon as they ask us to sing happy birthday to the kids sitting, you know, over the wing, you know, we all sing happy birthday and we clap at the end of it, right, because it's Southwest airlines and it's because it's because of how they're dialed to do it. The, the hope I have, if this, you know, if there's an opportunity for, you know, at least one parting shot is that if you want to think about what AI can do for your company, it can put you in a position to where you're delivering indelibly positive customer experiences, right? Not just relevant and converting, not
Mike: right, right. Yeah.
Tim Hayden: It is, it is that people will look at the [00:56:00] email or they'll, or they'll leave the chat or they'll hang up the phone and they'll turn around and tell somebody 15 minutes later and say, I just had the best experience. I just, you know, it just happened to me, right? You know, and, and there are, there are those, there are those companies who have invested heavily in culture and heavily into operations that are customer centric and customer, customer empathetic, right?
Tim Hayden: And they're the ones that are going to be able to really leverage this AI to take it even further, right? They're going to be able to do that, or they'll mess it up and they'll try The human side of it. Right. I mean, let's be fair. It's just, it can go one of two
Mike: You'll get a, you'll get a mix for
Tim Hayden: It'll go one of two ways. Right. Yeah.
Tim Hayden: But, but that's, that's where we are. That's, um, you know, um, because I'm a data guy and I, and I know what should happen if you have your data together. I know what my experience should be. I, you know, [00:57:00] I, it's, I feel sorry for the people at the service desk at rental car companies because, um, it never works the way it's supposed to.
Tim Hayden: And I just looked at him and turned my head and I said, really? Um, You have the credit card on file. Do I have to show it to you again? No. Uh, and, and, and really, I didn't ask for a caravan. I asked for a midsize Impala. Come on. You know, I mean, um, you can just tell there's an inventory issue there. I understand.
Tim Hayden: I understand there's other things at play, but the fact that things aren't reconciled, I didn't get a text before I walked in that said, Just to let you know, this thing's happening right now, have your credit card ready. We can't seem to find it. You know, I mean, just getting into that and, and getting, you know, getting me prepped for it.
Tim Hayden: When I started thinking about what AI can do, it's things like that, right? Is let's, let's, let's have better communication, more empathetic communication, more direct communication with our customers, instead of just trying to be funny on Facebook and [00:58:00] Instagram and
Mike: right, right.
Tim Hayden: buy a pair of socks on our website.
Tim Hayden: Right.
Mike: Yeah, for, for sure. And I mean, you're absolutely right there too. Like when I call, even like when I call to order a pizza, if the person on the, if I've ordered at the place before and they asked me my phone number again, or you know, certain after the, after they asked me for my phone number, it's like they asked me for all these other, it's like.
Mike: Dude, you don't have that? Like I worked at Domino's like 20, 30 years ago or something. like, man, we had that back then. Right? Like, so it's, it does blow. It does blow my mind at this point. You should be well far ahead of that and you should actually understand how I'm feeling today. You know what I mean?
Tim Hayden: Well, you bring it up. I mean, that's, that's actually an example I give it at many of the conferences I speak at is like, how many of you, you have your favorite pizza place, right? How many of you, when you call your favorite pizza place, tell them that you want the same thing you got last week, you know, and if you're not, if you're not doing that, try it this Friday, right?
Tim Hayden: I mean, if you're not doing. But they're [00:59:00] all do it now, right? They all say, Hey, the last, the last time you were here, uh, uh, you ordered this, this exact pizza, but yeah, I'll do it again. Right. I mean, um, it's data is all it is. It is,
Mike: Right. It's not even AI. I mean, that's just like data.
Tim Hayden: it's not even AI, right? It's just, it's better data governance.
Tim Hayden: Right. And it's the stepping stone for what you can do. When it comes to automation, it can take you in that direction of really learning about, um, you know, let's not say cut corners, but build efficiency and, and make the experiences frictionless, make the, make them the kinds of things that people turn around and tell their friends, right?
Tim Hayden: They tell their friends, their neighbors, their family, their coworkers. And so, you know, you know why I'm driving that car? It's because, you know, life is so easy with that dealer, right? It's just so easy with that dealer, right? That's what you want to have happen. I mean, that's, that's what your grocery stores are trying to do, [01:00:00] is to put you in that routine, and they've done it a long time, you know, is to, is they get you dialed up.
Tim Hayden: They know what's in your bag, they know what everything else is, and they communicate to you in a way, and they give you customer service in a way that, you know what, That's your place. That's your place, right? Yeah.
Rico: Love
Mike: Yeah, no, exactly. Um, so before we wrap up here, Tim, any, um, so any, uh, advice, like direct advice to the listeners, uh, as, you know, as we're kind of wrapping down here, um, you know, that you want to give,
Tim Hayden: You know, um, I mean, nothing that we haven't already discussed really,
Mike: I know we, we covered so much. I'm thinking, gosh, he probably does. Yeah.
Tim Hayden: no, I'd say, um, you know, think twice before you upload anything to a public model. Um, obviously. Change your passwords. Um, look into Dashlane, uh, LastPass, some of these other, these other systems that can be on your phone and your computer, um, to help you use, uh, make [01:01:00] up passwords, right, to generate passwords for you.
Tim Hayden: Um, not ones that are super comfortable in your head that are your mom's maiden name and your dog's name, right?
Mike: Yeah, exactly. Your birth, your
Rico: Now I got to change my password. Thanks, Tim. I'm going to go change my password right
Tim Hayden: both your mom's maiden name and your dog's name are out on the internet and somebody found
Rico: And then one, two, three, four after,
Tim Hayden: And 4, and they're knocking now, and they're using every combination of digits after it.
Tim Hayden: To knock on the door until they get in and they get all your email and your credit card numbers. Right. So, um, you know, let's, you know, let's, let's do that. And I think, um, a lot of what you guys offered, right, is how do, how do we get collaborative and how do we get cooperative with our coworkers and people who work up, up above us and down below us and to the sides, left and right of us and have conversations about.
Tim Hayden: You know, what else can we do together? You know, or how do you get things done? How do you get things done, right? Because I, let me tell you how I get things done. You tell me how you get things done. Really? Well, I'm going to try what you do, right? I mean, that, that kind of thing. I mean, it's [01:02:00] the, it's the, it's the thing I told everybody when I, you know, as a recovery mobile strategist, I still say this every once in a while, people say, how do we get started with this?
Tim Hayden: And I say, really simple. How many of you handle, How many handle social media, right? How many, cause a lot of people in AI came from the social media world.
Mike: Right. Right.
Tim Hayden: Or how many of you are digital marketers and, and, and do, uh, social content and, and, uh, content strategy, community management, that kind of thing. Lots of hands go up and say, how many of you also run direct mail?
Tim Hayden: Maybe two hands stay up. That's what you guys need to do. When you walk out of here and you go to the office on Monday, if you're the digital marketing team, go find the person who runs direct mail, because the person who runs direct mail. Is, is, and, and certainly was historically the most analytically driven person in the organization.
Tim Hayden: And they're sending stuff to the same people that you're posting content for.
Mike: Right.
Tim Hayden: what they do, ask them what's working. You share [01:03:00] with them what your analytics look like, right? Just start that over a cup of coffee once a month. Do it tomorrow and then call me if you're ready to pull it all together and we'll make it happen in real time.
Mike: That's awesome. Excellent. Rico, any parting words on your side? Any questions? 11.
Rico: know. I just want to thank Tim for coming out again. You know, every time we've had a conversation with you, you'll always walk away like you literally have to Mike and I think last time we talked, we sat back, we're just like, what just happened? Like we just, we just absorbed so much stuff. We were so excited to have you back on.
Rico: So just thanks again, Tim, for all of your insights, all the information you gave the listeners and stuff. And hopefully you'll come back and join us again in the future.
Tim Hayden: You bet. No, you guys, you guys are, you guys are doing it, man. I mean, you guys are, uh, you know, you, you're, you're, you're, you're on that bronc right now. You're trying to hang on or that bull hanging on for eight seconds. Every time you, you try to do something with AI every time you experiment. And, um, I just appreciate you guys.
Tim Hayden: I appreciate, I appreciate what you do again, too. Support the human side of [01:04:00] AI to be interested in there and to leverage the people we bring to that on Wednesdays. I really appreciate that. It's on Clubhouse every Wednesday morning at 10 o'clock Central. 10 o'clock Central, 11 o'clock Eastern.
Rico: right. Time
Mike: by your time. We'll
Tim Hayden: Yeah, yeah. Here in Texas, it's at 10
Mike: They're in Texas. Yeah.
Rico: That's where the time is, Mike.
Tim Hayden: yeah,
Mike: in Texas here,
Tim Hayden: yeah, yeah. But, um, but you guys are great. And I, I, I, I love, I love the way you ask questions and the way you're exploring it, the way you explore it with your guests. Um, I've, it's privileged to be here with you and I want to thank you for, for me being here for definitely enjoyed it.
Mike: Yeah. Thank you, Tim. And, uh, absolutely. I mean, I agree with everything that Rico said. I also just want to say like, you know, we really appreciate the human side, you, you and your position as well. And the human side of AI. And you and the other founders, I mean, the reality is like you are, you are doing, uh, the community of service, right?
Mike: Like when you're building these checklists and you're [01:05:00] building awareness, right. And you're bringing people in. This is not really directly for any of your benefit, right? Like as, as the founders and you are really like, it's a labor of love and. That's why we, we truly believe like there's, there's a huge power in that.
Mike: I've also always believed that it's like, Hey, the human side of AI, gosh, who doesn't, who doesn't that make sense to, right? Like, um, so, uh, so yeah, love what you're doing to appreciate you being on the show. Uh, I love the, uh, actually this is my first rodeo. I'm going to have to remember that. And, uh, yeah, maybe you'll have to get one of those hats.
Mike: We'll have to cut, we'll have to come
Rico: Yeah.
Mike: Texas and visit them then.
Tim Hayden: I'll send it to you guys. I'll take a picture of it. Um, it's on the other side of the building or I would have just run and got it.
Rico: Right.
Mike: No, no worries. No worries. Very
Tim Hayden: mindset. It's a mindset. We're all, we're all in this together, right? We're, we're all, we're all going to figure this out. It's what the human side of AI is about.
Tim Hayden: It's what, you know, Mike, you're doing in your company. It's, [01:06:00] it's what we try to do to help companies take those. Those, those crawl, walk and run, you know, motions to, to get going and get moving in a direction of, of change. Right. Uh, uh, it's a, it's a motion of change. It's a motion of, of embracing an appetite for doing things different.
Tim Hayden: Right. Showing up different in the marketplace, operating differently. Um, it's not always gonna work. It's some of it's gonna fail. Um, some of it's not gonna work. But at the end of the day, if you're not trying, you know, that's that's the failure, right? That's if you're not trying, you're not giving yourself a chance.
Tim Hayden: You're not giving your colleagues and your co workers, your customers a chance. To try to do things more fluidly, more frictionless and to the benefit of the business performance and your happiness. I mean, it's, it's that short, right?
Mike: Yep. Absolutely. And you know, I kind of thinking about that there, um, you know, when, when you're doing these experiments, here's a quick tip for me when you're doing these [01:07:00] experiments and mention your company, um, and even by yourself, what I would suggest everybody do right. Is. Before you get started, write down like, Hey, what I'm, what am I looking to accomplish?
Mike: What does success look like? What is my efficiency at this now? Right. So that at the end, right, you can go back and, and, and really an experiment. Like if you're a scientist and you're doing experiments, you're documenting everything before, during, and after we need to do the exact same thing with AI. So that, that,
Tim Hayden: It's the exact same thing. It's.
Mike: out.
Tim Hayden: Exact same thing with, with AI. It's what it's, it's, it's, it's for the, the financial, um, modelers of the world, right, your CFOs, your business managers who do last year versus this year modeling, right, it's the same thing. It's just much more frequent. It's, it's, it's going to be more frequent in terms of the projects and, um, you know, the initiatives that you're, that you're trying to manage and you're trying to test, um, you know, that's, that's really what it comes down to is what's our current state look like and [01:08:00] how can we.
Tim Hayden: And how do we think we can manifest something that's better, cheaper, faster, all those
Mike: Yep. Yep.
Tim Hayden: Um, saddle up. Let's do it.
Mike: Let's do it. Awesome. Tim. Thanks so much. Uh, have a great rest of your evening. And, uh, we're absolutely going to have to do a follow up, uh, episode or segments. I mean, this, this has been great. So
Tim Hayden: you bet. I mean, things, things will be different in six weeks. I mean, it
Rico: That's
Mike: we'll have other things to talk about. Yeah.
Tim Hayden: absolutely. You bet. No, thanks again, guys. Really
Rico: Thanks, Tim.
Mike: Absolutely. Thanks a lot. Yup. See you later.
Tim Hayden: Peace.
Mike: Yeah. So, uh, man, Rico, that was a heck of an episode with, with Tim. Uh, I, I feel like there's so much content there. I'm like, man, we, we, we could probably split that into a few segments and just do
Rico: Another season.
Mike: Another season, right? Do them by themselves. So, um, you know, uh, heck of an episode, uh, you know, data is so important folks, just to, just to kind of bring it back to that.
Mike: And, um, we, we are [01:09:00] sitting on, businesses are sitting on fricking a lot of on top fricking gems. So, um, these are, you know, these are the kinds of things that, uh, as you're starting to have conversations in your business, you're Don't forget about your data. And, um, and so, uh, I also want to give a quick shout out to, uh, Nick and the folks at Nomad Studios.
Mike: Nomad has been mastering our videos, mastering our audio for our videos as well. Um, Nick and the crew over there, just absolutely fricking amazing. Thank you guys. And, uh, and they've done a heck of a job. It's like every time I listened to watch one of the new episodes, I'm like, Ooh, you know, this sounds so
Rico: Compared to the old ones,
Mike: Yeah. Even the flow on the way in and everything. I'm like, man, you know, it's so much different, uh, to, you know, to, to be sort of fumbling around with it. Uh, and then, you know, you see what a professional does and you're like, there we go, so thank you, Nick and the crew at Nomad and, um, yeah. Rico, any, any parting words here?[01:10:00]
Rico: No, I really don't have it. I, again, I'm going to double down on that with Nomad studios. They do a fantastic job. And, uh, you know, again, a big shout out to human side of AI for everything they're doing over there. And the folks that they allow us, you know, would not allow us, but allow us into those conversations to meet some of these people, uh, who are doing great things.
Rico: And if you're a person out there that has a business that has yet looked at AI, um, you know, By all means, like dip your toe in the water. Like, don't be afraid. It's not all tech people that are in there. It's not people who came from coding backgrounds. They're everyday folks who are looking to solve solutions.
Rico: And, uh, you know, if you want to fly high with the Eagles, right. You're going to, you're going to hang out with them. So you want to get in there with those folks and listen to what they have to say.
Mike: Wow. You, you got a new quote on every one of these episodes. Happy cows make more milk. Like now we got the fly high with the Eagles. You got to hang with them. I love it. We'll have to do one of these each, each episode. Uh, folks. So one thing that I'd like to ask, uh, is that, you know, if you like the content that we're providing here, uh, please subscribe to our YouTube channel.
Mike: Please [01:11:00] subscribe, uh, to the YouTube channel, uh, subscribe to our podcast. And, you know, this is the first time I think we've asked this, but, um, we would love to get some more reviews on the, on the podcast, uh, for Apple and Spotify, you know, let us know what you think. Uh, and, uh, and, and so, uh, we're excited to, you know, uh, continue to forge forward.
Mike: Uh, I feel like, you know, We've got a heck of a momentum here. The guests have been just amazing that we've had. I honestly can't every one of them like, Oh my gosh, like, how's that so good. And, uh, we, we love, absolutely love putting out content for you all and really raising that awareness. Uh, don't, you know, don't be shy, reach out to us.
Mike: Um, if there's something you want to understand more about, AI bites newsletter that we have weekly, uh, let us know and, uh, Yeah, we're looking forward to seeing everybody back in the lab soon. See ya, folks.
Rico: See everybody.
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