Meet Jack Siney: AI Beyond the Hype

Jaclyn Strominger 0:22

Hello, everybody, and welcome to another amazing episode of Unstoppable Success. I'm your host, Jaclyn Strominger. And on this podcast, we hear from amazing leaders and intellectual people who are doing the things out there right now. They're actually going to share their insights, their tips, their strategies so that you can be unstoppable. And today, I have an amazing guest to share with you, Jack Siney. Get that right? Great.

Jack Siney 0:47

Yes, yes, that's perfect.

Jaclyn Strominger 0:49

So let me just tell you a little bit about Jack. So he is a seven-time entrepreneur. He has had five successful exits, one big learning experience, and one moonshot new adventure, new venture, which is what he's doing right now, front race. And everybody's talking about and worried about and excited about AI. But there is a big shift coming, a shift on how we work, a shift in what we work on, and the shift on what is perceived as valuable.

Jack Siney 1:18

Amen. Amen to that.

Jaclyn Strominger 1:20

Right. And Jack, you are heading up and the co-founder of Front Race. And so talk to us about the AI as we know it today and where we think it's going to be going.

Jack Siney 1:37

Well, to your guest, to all your listeners, I don't know about the intellectual part, but I'll do my best to give you some real stories. Yeah, I no, no news flash here. I would just say almost every business conversation today circles around AI. What do you do with AI and where does it fit? I think it's so funny as somebody who deals with a lot of companies every week, every month, every single company I've seen, no matter what industry, like a furniture company or a just random companies you think have no AI in them. Every single company, if you go to their website, has AI above the fold. Some uh some verbiage around AI, what they're doing, like companies you would even think couldn't even like, how does AI fit into a bike company? Or it's so amazing. And so obviously it has infiltrated everything we're doing. I'll date myself. It reminds me so much of dot-com era, the dot-com boom, where everyone's like, Do you have a website? Are you up and running? And so the same proliferation of craziness is taking place. And as we talked about before the show, I think the most interesting part of what's happening right now is everything we're doing right now, five or six years from now, we're gonna look back. It's gonna look like the early days of AOL. So when you first those of you don't know, when you had to get on the internet, you had to get a little CD or disc from AOL, you had to put it in your computer, it would connect, it would make that fact sound. Shh, shh, right. You had to wait like 30 seconds, and then finally when it connected, it would be like, oh, you have mail. And so it's so interesting today. Anyone that still has an AOL email, you're like, but uh, that's clearly almost infathomable today in how we operate with the internet and all the things we do. But that's really that's where we are in the AI world. It's so new, and it's we're in the first year, first two years, however, you want to, whenever you want to say it started, but everything we're doing today is gonna look very outdated a couple years from now. And so we try to help folks deal with that, make smart decisions, and and get ready for what the future holds.

Jaclyn Strominger 3:32

You know, what which I I love, and there's

The Biggest AI Mistakes Companies Are Making

Jaclyn Strominger 3:34

so many different little things in there that I just want to touch on. But first of all, you know, it is like things are changing at the speed of light. It's so fast and so and moving so fast. So, and you mentioned cut like every single company, it's like they have to have AI in somewhere on their website, otherwise they're not relevant. Right. So talk about these companies and how you're getting people prepared. Because as you just said, it's going to be so different. And you know, there and I and I think and and one thing I want us to kind of talk about too is you've got AI for programming. I'm gonna say AI for task management, which I kind of think is different, and then AI for queries.

Jack Siney 4:29

Yeah. Sure. Yeah, I think I think the way the way we separated similar to that is is kind of on the tech side. So let me just on the tech side, if you're in software programming, if you're an engineer, I don't deal in that space. What AI is doing today over there is amazing. It is ready for prime time, reducing the time to market on numerous things, coding, you name it. I don't play in that world and uh have some smart people. I mentioned our CTOs in Reno, where you are, and so God bless those folks. And and that and the change and all they're dealing with is unprecedented. It's it's amazing. The world we try to speak into and the world that I operate in is really the business side. When you bring that technology over to the business side, humbly, I'll just say it's not ready. It's it's not ready for prime time, it's it's 70% ready or 80% ready, whatever number. I Mark Cuban had the best summary of it the other day. I I copied it, I'm gonna tweet it out, uh, LinkedIn, I'm gonna message it 10 times probably the next month. But he said, you know, we're not ready because when you take the same data, run the same query, and get a different answer every time, you know there's a problem, right? You should in if you're in Excel and you run the formula, whether you're in Excel or in Google Sheets, it should always be the same. And so you know we're in where we have issues when if you use the same platform, put in the same data, run the same query and get a different answer every single time, and people are trying to base their job on that or the strategy of their company, and it's like, no, no, no, no, don't do that, don't do that. And and by the way, if you don't believe that, go do it. Go try to run the query and then ask again. And then if you even, we've all experienced this, if you push back just a little on Claude or Chat GPT, if you're like, well, I don't really like that answer. It'll change it. It'll change, it'll change the total answer. Like, hey, what strategy should we have? Is this verbiage right? And should I should I put agents here and blah, blah, blah. And so, oh on again, on the tech side, what AI is able to do is really amazing. The efficiency it's driving and the makeup and what tech teams look like is already changing. It's amazing. When you bring it over to the business side, as soon as you get outside any basic, it creates great content. If you're trying to do marketing, email, great content. But if you're trying to do basic, really basic queries, it works great. But as soon as you try to do a complex query, or if you're trying to lay out the strategy for your company, or you say, hey, what was our deal flow, last quarter, number of uh outside activities with a certain rep, it'll it doesn't work. And by the way, I'm not an anti-AI person, just the way the joins work and the way the LLMs are set up, it can't piece together the data consistently. And so that's what we help companies with. Hey, what what are the pieces you need to have in place so you're ready to deal with AI and use it in the right way and be strategic? And that's what we help companies with to do. And and I I just want to give the framework or the the foundation of it's it's just not perfect today. And if you think it is you you may not be employed six months from now, if you if you follow the recommendation of one of these LLMs, please do not do that uh without a model support.

Jaclyn Strominger 7:39

So right. So when you're when you're talking about getting a company ready for AI, you know, so and what kind of like the framework you took. So what does that really look like?

Jack Siney 7:47

Sure, sure. Let me let me go through it. Yeah, so I I don't want I don't want to bore people with that, but my little commercial, I would say there's four things we talk about. And so what what I really what the framework I want people to have is

The 4-Part Framework for AI Readiness

Jack Siney 7:57

get ready, just say the second half of the year, or just say in January, imagine January 1st, 2027, if you had the following four things done, you can then execute against AI well and have the best of. And so the areas we talk about are systems. What systems do you have today? Most companies have six to 12 different systems. When you talk about CRM, email, video conference, data support, you name it. All pipeline management, tickets, support tickets. It's amazing. Crazy. And what's quick sidebar, what's amazing, we've been at that for about 40 years. We're no better. On the business side, no better predicting, reaching forecast. We're no better for our sales team. If two get two people in your sales team are crushing it, the systems we have today, don't let the other eight people know what those people are doing so they're better. It's it's amazing. All the time and money we spent building a tech stack on the business side, we're no better today. That's a little, I'll bring that back. But so it's systems. What systems do you have? Uh are are the people using them? Are they helping you with winning? Whatever you however you define winning, whatever the your purview of your team is. So we do that. Next is the data. Big thing for AI is the data. Most people, Larry Ellison, great quote a couple uh a couple weeks ago. Hey, all the all the LLMs are using open data, public data, whether you use Gronk or Claude or ChatGPT, they're all pulling from the same data. The magic is in your data, your company data. All the answers are in there for most people. If you have six months plus data, the answers are in your data, but most people are not ready. Their data is in three or four different systems. An apple in one system is a banana, and the next system is a pear in the next system. So getting the data together, consolidate it, normalizing it. Again, sidebar, much easier today than it was 10 years ago. Those of us have been around a while, hear that term and go consolidate your data and normalize. Oh my God, that's a three-year effort, forget it. It's not nearly as painful today. But so the second piece of the data, the third of the process, so here's what's happening today process. People think they know. So I'll just use an example on the sales side. If you're a sales leader and you have a sales manual, you say, Here's our chart, here's our flow chart, 22 steps to get a deal. Or you hire a new person, you're like, oh, we outreach, then we send an email, and then we schedule a demo, then we do the demo, then we answer questions, then we send a proposal, and like you have this whole thing, yes, no boss, the diamond, yes, here, no here, and we think we know.

Jaclyn Strominger 10:25

Right?

Jack Siney 10:26

And the reality is the following that's not how it works. That's it for your best people. Those boxes, if you have 22 boxes, the real world is really probably 72, right? It doesn't handle all the steps, the things your best people are doing. They build relationships, they send texts, they follow up, there's questions. It's amazing how complex it is. So then if we say it's 22 steps and it's really, say, 50 or 72, right? Then we want to go out and get an AI agent to automate it. Well, we only put the agent on the 22 steps, and then we go, why is this not working? We it's it's perfect. AI perfectly, but it's only doing the 22 steps you told it to do. It's not doing the other 22 that really actually doing the human stuff, right? It doesn't, and we don't know. So one of the things we help people do is really understand their process, all the steps. I want to just repeat, all the steps. You can't automate a human being that fills in the gaps. The technology doesn't. If you don't tell it to do it, it doesn't know to do it. So the third step is what is what are your processes to whatever you want to target? What are good processes to target with AI? And then what are all the steps in that to have it documented? And then you can try to do it with an agent. So that's number three. And last part is the people. So I'm not a I'm not a purveyor of, oh, everyone's gonna get fired and AI's gonna come take your job and blah, blah, blah. Like, is AI AI gonna change our HR mix and the job functions in companies? No doubt. I wouldn't want to be an entry-level person in an analytics company. I wouldn't want to be a doctor or lawyer because those are gonna be big data things. But what it's gonna, the people part of it, it's gonna be think about if you had an example, if you had a good manager back in the day, we had these managers, some were um good at the details, the tech piece, and some were good people, right? They're great at managing people, inspiring them. What are their goals? Well, what if in the future half the people are really agents and it's a piece of technology? Well, then that skill is very different. If you have, you used to have 40 people. So what if you have 20 people and 20 agents, right? So, what are the skill sets of what your team needs to have a year from now so that they're ready? Because you need your best people. It's easy to say, oh, we're gonna do a, you see these companies, we're gonna do a riff or get rid of people. Okay, so let's say all that you get rid of all the dead woods, which you should do anyway, Jack Wells, you should get rid of the bottom 10%. But if you don't get your people ready, they're not mentally ready, they're not skilled ready. When you need them, you need your best people to stay. When you need them to stay here for now and they don't because they're frustrated or they have a new opportunity, you're gonna be in trouble. You're gonna be in trouble because the tech's not ready, your best people have left. And so we really like to do a people analysis. What does your team look like? Do they have the right skill sets? What's the skill sets are gonna be valuable two years from now? Because it's very different than the skill sets that were valuable two years ago in the middle of COVID when there was a lot of hand holding, or what is it, five years ago now during COVID, a lot of hand holding, getting people through a pandemic we'd never experienced. So those are the four areas systems, data, process, people. We help people, we help companies get ready for.

Jaclyn Strominger 13:37

So, so I I want to go to the people

Why Human Skills Matter More Than Ever

Jaclyn Strominger 13:39

part because I think that's and what you just we because because so many people are afraid of the people. And I and I'm like, oh, well, this is great because I teach people I teach people relationship capital. Right. And I think that's actually, you know, what I'm hearing you say is the relationship portion and people being able to actually connect with the people is going to be just as important as the person who is able to understand the agents.

Jack Siney 14:08

It's it is, it is, but I I would think the job going forward, you're gonna have to have some tech affinity two years from now. So I I'll just say my my in my soapbox. 10 years ago, there could be technical managers and kind of people managers, let's say, you know, people who are great people, motivators. By the way, I fall more in that category. People person, love to see people develop them. Well, there will those people still be needed as people managers? They will. There's still gonna be people, but you're gonna have to have tech. You're gonna have some tech of like, hey, AI agents doing this, or or some technology is doing this, or we're gonna have a different framework because it may be the same amount of people, but they're doing vastly different things. And so all the right way to think about it, in my from my perspective, anything, I'm not, I'm just repeating what everyone's saying. Anything that's repetitive and doesn't require you to do brain power is gonna be gone in the next five years with AI. It's gonna automate anything that's repetitive and annoying, great, that's gonna go away. But now it's like, hey, that time, that free time, now it's got to be dedicated to really strategic things. How do we grow? How do we solve problems? How do we increase our sales or retention in our business? That's gonna be where the magic is. Instead of spending 30, they uh a salesforce put out their study, their sales study they do every year. I think they said like only 35% of the salesperson's time is in sales, and the rest of it's doing admin and putting stuff in VRM and blah, blah, blah, blah, blah. And they're not really selling. They're they're doing you know, administrative.

Jaclyn Strominger 15:41

Well, just think about I and I share this when I when and I tell people, use your phone, right? So it's like you're done with the sales call or you're done with the sales meeting, or you're doing a Zoom, it's you have it transposing for you, then it can automatically just take the summary, turn it into an email, say, Thank you so much. Here's what we talked about. Here are the five key points, you know, or even when you go out and talk to somebody and you're at a networking event or you've met somebody, you get in, you know, you get into your car and you record a note and you say, Okay, I just met, I just met Jack, and he runs, you know, he runs, you know, front race and he's got blah blah blah blah blah. And so now I can take that recording and I can stick it into my AI, whichever bot I'm seeming to use. Okay, send Jack, send Jack an email, make sure, oh, by the way, I didn't get your I didn't get your cell number. What's the best way to reach you? Put that in the email, right? You know, so like those things can definitely be automated.

Jack Siney 16:37

Yes, you know, it's gonna be amazing. The the the connectivity, like I one example I would say in the in the sales business world, this has been classic for decades. Hey, I gotta reach out to 100 people. So I actually connect with 30. Of the 30 I connect with, 15 are interested. Of the 15, I meet with seven. Of the seven, I close two, five, whatever. Right, right. We've been doing that for years. So imagine if we're able to, as AI, because I think the the initial bang in AI, bang for the books, is gonna be in the marketing end. Imagine if you didn't have to talk to 100. Because again, of the 100, 70s wasted time, they didn't pick up, they're not interested, you're annoyed them, whatever it is. Imagine with marketing and AI, you're able to get down to, hey, I only call the 30. And because I know something about them, or they're calling their signals, they're buying signals. I talked to imagine, imagine in sales. Right. Every person you talk to was near or closely aligned to what you're selling. How like how isn't that where we're going with all these LLMs? Like, they're not doing it yet. Uh uh sidebar, uh, what is it, uh, PSA public service? Like, yeah, we think we're typing into chat GBT, my back hurts. I fell yesterday, my wife was mean to me. You know, I want to buy a dog, and and all that's gone into a computer, and it's gonna come back one day. They're unquestionably gonna sell that data. They're gonna be like, Jack is in outside of Houston, he's 50 some years old, he has two dogs, he's got high cholesterol. You know what I mean?

Jaclyn Strominger 18:05

They're gonna know you more than you even ever wanted to know.

Jack Siney 18:10

Oh my god. And all the things you're gonna see are gonna be like, how did they know that I'm looking for a new car, that I have two dogs, that my cholesterol is too high. You know, it's gonna be you're gonna you're gonna be inundated with like, you know, we we thought maybe the internet was listening in years past, but with with what we're doing, because people are just typing in there freeform, you know, here's what's happening, uh my boss with a jerk today. Like, you don't like your boss, you know what I mean? They're gonna it's gonna be so right, it's gonna be so connected to whatever you're doing, and that that's where we're gonna move to of the things that's how it's gonna change how we work.

Jaclyn Strominger 18:43

Right. I I want to go back to the part of about about data, because as you were talking about data, yeah. Something

The Hidden Power of Your Business Data

Jaclyn Strominger 18:49

that I think is I I find data fascinating. So I'm a little bit of a weird geek in some ways. When I went to college, one of my favorite classes was econometrics. And I used to sit there running minitab. What if I change this variable just like this? And what results would I get? And I would say, I would get, I would run statistical software. So minitab is a very old statistical software. I'm really feeding myself here when I say minitab, AOL, okay. So, but I literally would sit there for hours. I would be fascinated by what like one variable change could do in a process, right? Yep. And right. And and so, you know, it's so the the data part of it, I find it's it's fascinating. And I've I guess kind of two questions about this. You are people forgetting about their own data.

Jack Siney 19:58

Well, well, they so we come from a background of big data problems, so that we're we're more biased of our ability to deal with it and analyze it. But I agree. Uh again, Larry Ellsman said it. I I I when we when I hear quotes in the market, I'm like, thank goodness, somebody else is you know preaching and yelling at the wind. But the answers are in our data. And I think for those of us again that have been in the tech world for last 20 years, we hear normalize, consolidate your data. We're like, oh my gosh, that's a that's a two-year project with six people, and who's gonna run it? And oh my lord, and and so again, on the tech side, AI is doing amazing things, and one of the best things is the ability to bring data together, normalize it. But without that, you're just flying blind. I mean, I the answers, if you have more than six months of data with a core team, you have the answers. You have the answers. I just want to repeat this is a scenario every everybody in sales deals with. Uh, you have a sales team, you have two reps, their metrics are basically the same, same pipeline, number of calls, uh, number of emails, number of video meetings, whatever it is. One is outselling the other by three times, right? Everyone has this on their team. If you have a team, you do. You're like, it all looks the same. Why is Mary selling three times as much as Bob? Why? And when we get asked that question for decades, every sales leader makes up an answer. Every sell, well, Mary's just she's better at closing, or Mary had she's more industry contacts, or she's just better demo, and it's all made up, it's all fake because we don't know. We don't know, and for years we've not been able to take whatever Mary's doing and share it with the rest of the team so that the whole thing you mentioned start your show, the rising tide, list all votes, right? You know what I mean? Like that paradigm. It's like we don't know after all this year, all this tech stack, all this stuff, we're still not sure. And so we need to dive into the data. AI provides this ability now to start not only to normalize the data, standardize it better, but provides the ability to start measuring all these soft skills. In our world, the difference between these two people, the 3X and the 1X, are 20 little things. That's the when I came into your This um webcast you mentioned, doing repeated things every day, right? Small things, right? It's 20 little things, it's not the big things. Everyone knows the pitch and the pricing and FAQs. Everyone knows that. Everyone knows that. It's 20 little things. And so we haven't really been able to measure those in the history of sales. And now AI, for the first time, opens the door to be like, hey, what is the quality ratio for this person? What is their tonality? When did they introduce something? What's the gap between things? It's not just when you do something, it's the gap between when you do it. We've all had this experience. If you don't think that's true, here's the experience. We've all had if you're on LinkedIn, we've all had this experience. Somebody sends you a connect notice, you accept, and eight seconds later, they're like, You're like, oh my gosh. Relax.

Jaclyn Strominger 23:07

Pitch lap right, right? Right. Sorry. I hate it. I hate it so much, it's not even funny. I so I'm gonna share my response to people. Thank you so much for the pitch. I work on relationship capital. I teach people how to actually have decent relationships, build and foster those relationships so you actually get to know people so you can know, like, and believe in them, not just trust, but believe in them. Yep. So that you would might, so that you might, might want to do business with them, but you would probably want to refer them. So if you're interested in that, I'm happy to connect with you.

Jack Siney 23:48

Right. So that but that thing you just thought about, how do you share sharing that with a new person's really hard? Think about it, you have a company, you're doing well, you hired a new person, they're great. So forget if you hired a knucklehead, but you hired a good person, they're really good. So they say to you, what's the first thing they say? Train them. How do how do I repeat what your best person's doing? Right? You uh you just hired me? Right. Who's your best person? What do they do? Every type A I've met says that. That's what they ask me. Right. If we don't know, we don't know how to tell them, hey, get on LinkedIn, you can't connect, but listen, you gotta wait, you gotta send them something in between, send them something of value. Like to explain that really hard. And because we do this, this this is a fail point that somebody has numerous businesses. This is this sentence is the death almost every company. That's common sense.

Jaclyn Strominger 24:35

It is so not common. Common sense is also not common. But I love what you said about learning, you know, taking that that that major producer, right? Now you can, because of AI, you I mean, it is big brother watching, but you can take uh the if the conversations are recorded, and obviously I think they have to, you know, that's transcribe usually have a note that says this message is being transcribed. Please make sure you hit okay. So you've got people transcribing the messages. You can hear what the what you know your star Mary is is saying. You know, Star Jack is just doing amazing. He's just killed it. He you know, so you can hear, you can see that all those things. Now you can also see, I guess, depending upon how you have it set up in your system and in your serum, if they've connected the outreaches of LinkedIn to the individual person contact, you could see all of it together along with all the transcription. So now you can, now you do have that data to say, okay, our top, you know, our top two people, our top four people have done all of these things. This is what they do. Now you can then take that and put that into, you can systematize that. And the language, it's teaching, and I think this is something that I think is really important. It's language and how we speak is is something that can be taught.

Jack Siney 26:17

Yeah. And so yeah, I would uh the the real world part about that for people is no one has perfect data. Right. No one does. And so how we started this segment was hey, what do you do to help them get ready? So what why it's so important today? Today it's way more important to get your house in order than it is to go buy an ace AI solution. Because if you're analyzing

Go Slow to Go Fast: Preparing for the Future of AI

Jack Siney 26:39

the wrong data, garbage in, garbage out. If you're not ready, it's it's that's the most important thing is to get ready. And so one of the things, talk about what you just said, most people don't have all the data, but they have a core thing about this. If you looked at your people or your process, you have just say 60 to 70 percent of it in order. Now you have to decide, like you just said, do we want to see what our people are doing on LinkedIn? Maybe, maybe you do, maybe you don't. I it depends on how how quantitative it is and how how much it affects the outcome, right? Or or texting. Hey, do we send a lot of text or don't send text? And do we want a system to help put that in place? But it's not big brother in any way, shape or not. Like, think about gung, gong, where people are like, you're gonna record my call and do transcripts, and people are like, What? As as type A's, we're like, you're gonna watch me or you're gonna look at it? We're trying to help you as a type A, even you're not the perfect in anything. How do we take the best of what everybody's doing? And so our first swipe of the data, again, there's there's chunks missing. So again, then companies can spend the next couple months. Hey, do we want to dive in and get data in this area or do we not care and it's okay, right? That's what I'm talking about. Getting your house in order. It's not trying to be perfect tomorrow. No one's no one's perfect, but it's starting to have good conversations about what data elements are we gonna care about in February 2027? Because if our competitors have all that data and we don't, then we start to start gathering it in February. You're gonna be a year behind, you're never gonna catch up, you're gonna wonder why they're eating your lunch. And so, again, we try to help companies get ready because the world is gonna look so different in 2030. And so, if you're planning just to be great in 2028, we're what that's not we're front rain says, don't, that's not what we're about. We're trying to get companies ready for what's coming and the new way we're gonna work and the new way your organization's gonna need to put different AI tools in. But the tool, again, you're so anxious to buy today, it's gonna be outdated two years from now. Well, no, without a doubt. So stop rushing to do the tool, get your house in order, and then then you can plug in any tool you want as we go. That's our whole thing. We the last mile is gonna keep changing. These tools are gonna keep changing, but you want to have your house. Right, the analytics, right. And now, as you plug a tool in, we give you the analytics. Is that working? Is it helping? Hey, you you got rid of your some program, you added this other program. Is it are you closing more? Is your is your are your sales better? Is your retention better? That you're trying to analyze. So the key is to having a good foundational platform. You keep analyzing as you're gonna plug and play different things in over the next five years. That's the secret. It's not running out and be like, are you guys doing AI violent? Well, you can go look at the stats last year. I think US companies they say invested $650 million last year, and 90% of those initiatives never got deployed throughout the company. That's a lot of wasted money.

Jaclyn Strominger 29:34

That is a lot of wasted money.

Jack Siney 29:36

Yeah.

Jaclyn Strominger 29:37

So I I love this because one thing that you just said that listeners, please know this for a fact. It's a tool. It's a tool. So I love what you just said. Get all the things ready so that you can plug the tool in. Because, you know, sometimes you're gonna need, you know, a different size wrench depending upon what tool you're gonna use. But it's a tool, it's not it's not all the other things. It is something that you use to make things better or to analyze. It's but again, I'm gonna say it again, it's a tool.

Jack Siney 30:23

It's a flip for those of you who are internet school, flip phone. If you like if you you know, what was that the one black phone? I think it was Motorola, the black, like, like not a chance today, right? It'd be so antiquated. And so that we're you're not you're rushing to get a product that's gonna be out of date really quick. And so it it go slower, get your house in order, and you'll be ready. The company that's gets their house in order and is ready for each evolution of AI, is gonna crush these companies that are rushing out to be like, are you guys have an AI pilot one? Oh, yeah, we do. We're we're automating our SCR team, or we're we're putting agents in to get rid of half our sales team. You're like, okay, well, good luck with that. So six months from now, when you're still flat or it's not working the way you should, what are you gonna bring those people back? Then you're not gonna have any data because now you've had these agents in, it's not even gonna be the correct data. So it's a it gets into like a death spiral. And so just want to encourage folks, full stop, find if front race agreements will help you like get ready. Like, get ready. But but if you're not, if you want to rush it, we're not don't don't call us. I don't I don't want to help you deploy an AI solution tomorrow. We want to help you get ready. We we'll do some, we'll do some AI stuff and in you know, interrupting you, we'll create content and do some basic, but for for getting yourself ready and making sure that AI is a part of your business going forward, that's what we're trying to help companies do.

Jaclyn Strominger 31:44

I you know what I you know, Jack, I could talk to you for hours about this because I think it is so important. But listeners, there's a few, there's a few other key nuggets in here. Number one, something that you just said, we have to go slow to go fast.

Jack Siney 31:58

Amen.

Jaclyn Strominger 31:59

Right? And so go slow right now. As a matter of fact, I mean, not to not to bring in working out, but like this morning I did a whole workout and the whole thing was was tempo. What's tempo? Going slow and doing fewer to to build, right? So go slow to go fast and focus, be be focused on what you want. Not I would say, you know, I would also say try not to do it all at once.

Jack Siney 32:29

Well, what what one thing in the process part of what we help folks do, help companies do is start to delineate, we start to put in buckets, likely AI implementation, unlikely successful AI implementation, right? But things that are high touch factors, things you need, a lot of human, very dynamic answer changes, it requires those challenging for AI, right? But order a taker at a restaurant, great, you only have 32 items, there's only so many mastinations of that, we can AI it, right? So, so so though though trying to put your process into buckets and you can start then, obviously, the ones that seem more AI a whole and more prone to AI success is where you want to start. But there's some that are gonna be really complex, and the more, the more human intervention, the more dynamic it is, the more the answer is different every single time. There's gonna be hard to AI in the near term.

Jaclyn Strominger 33:23

Yeah, you know, and I I I'll share this with you. This past weekend, I was traveling to Napa with a friend of mine, and we were doing a tasting of some sort, and we kept having to move the time. And so it was the AI agent that was doing it. And then actually at one point, then it got when it got to the point where we couldn't switch the reservation because it was getting too close and kind of weird, it went to a human.

Jack Siney 33:46

Yeah. Yeah. It's get listen, it's it's gonna be great, but it I just don't want to repeat it. It's it's it's so much happening in every on the business side. Like if you if you don't believe in anything I say, take whatever platform you love, put in the same data, run the query three times. I guarantee you get three different answers. Right.

Jaclyn Strominger 34:07

Right, you get three different answers, yeah. Right.

Jack Siney 34:10

And if you push back, if you push back at all, and by the way, a bait beyond a basic query, beyond like, hey, what you know, what day of the week it is, or who was my leading sales rep last week? Just ask a question within a second variable. Hey, who was my best sales rep last month who had the least amount of meetings or something? Yeah, and you'll see it'll it'll go around and around. And it's just the way an incredible tool, but but has some glitches in it, or I don't know, uh the the part I'm not a tech person. I don't want to say glitches, um, has some issues to provide you concrete data going forward. And we have some, we haven't talked about we have some tools, we have some widgets to help you plug into your system. So the analytics are the same every time.

Jaclyn Strominger 34:49

And and I love that, you know, date again, because data is so important. So, listeners, this is such an important top, important topic, and and and really to have that unstoppable success. Again, you know, learn to use AI as the tool. Let's not rush out, you know, again, on the on the tech side where it's programming for you. Great. I still think there's lots to be learned and done. Yep. But everything's evolving. Again, it's time to go slow to go fast. So, Jack, how can everybody get in touch with you to learn more about what you are doing and learn? Because I think what you are doing is just really incredible and so needed right now. Amen.

Jack Siney 35:39

Thanks so much. I appreciate the uh appreciate the endorsement. I'll send you your 10 bucks. Thank you so much. You can go to um frontrace.com, frontrace.com. In the upper right hand corner it says join the race. If you just fill out the form, we'll do an AI readiness assessment for you for free. That's how much we believe in it. There's so much to be done. Just want to give you a sounding board. So if you go uh fill out the form, we'll we'll we'll give you a readiness assessment that for no for no cost. I think you'll find that it's again for free. You'll you'll find so much about your company, totally worth doing. Or you can follow me on LinkedIn, Jack Siney, S-I-N-E-Y. We post regularly on LinkedIn. I have a notable LinkedIn uh following. And so uh try to comment and keep folks up to date as we see uh real-world things to help folks. So those are probably the two best ways to reach me. Uh, Jack at frontrace.com is my email.

Jaclyn Strominger 36:31

So okay, and we will put all of that in the show notes. So please, listeners, do me do me the favor and connect and reach out to Jack. Follow him on LinkedIn and see all of the great things he's doing because he is truly knowledgeable and has uh, I think, a high intellect as to what is happening with AI. And you really need to have different perspectives. So please do me the favor of follow following Jack. And then, listeners, please do me the other favor and share this episode with your friends, your business colleagues, because this is a topic that we all need to stay up on, and so do your friends. And then, lastly, if you haven't subscribed, I should say second last, if you haven't subscribed, make sure you've hit subscribe to this podcast. Give us a great review. And then, lastly, for sure, please go over to our brand new school community. It is Unstoppable Success on the Skool Platform, where you can be part of a community where we share information tips. We have a couple of power hours that we do to work together and monthly roundtable discussions from experts. So jump in there, be part of that community. Jack, thank you so much for being a great guest. Listeners, thank you for listening. And this is the Unstoppable Success podcast where we help you leap to your greatest success.

Jack Siney 37:50

Thanks so much.

Jaclyn Strominger 37:51

Thank you.