Intro: Broadcasting live from the Business RadioX studios in Houston, Texas. It’s time for Houston Business Radio. Now, here’s your host.

Trisha Stetzel: Hello, Houston. Trisha Stetzel here bringing you another episode of Houston Business Radio. Is my pleasure to introduce you to my amazing guest today, Daniel Friker, who is a transformational, driven executive with 20 plus years of experience leading global sales organizations within HR services, servicing fortune 500 clients within energy, manufacturing, higher ed, life sciences and tech. Daniel holds a masters in HR focused on HR analytics and has several AI certifications. I know you guys heard that because that’s where we’re going. Daniel, welcome to the show.

Daniel Friker: Thank you. My name is Dan, and this is the sound of my voice.

Trisha Stetzel: This is the sound of my voice. Hello, everyone. I’m so excited for you to be here today, and we are going to have a little fun. Although we’re talking in this realm of air and I, it sounds like it would be the most boring conversation on the planet. But I know you a little bit and we’ve already had a few laughs, so I think we’re going to be okay. Yeah.

Daniel Friker: I try to be one of the good air people.

Trisha Stetzel: One of the good air people. So many kind of fun, kind of fun. Kind of delightful. Maybe a little of both. Um, why don’t we just dive right in? Why don’t you talk about Dan, tell us a little bit more about yourself, and then let’s jump into this topic of I.

Daniel Friker: Sure, sure. So only in hindsight does my career make sense. Um, graduated with an undergraduate degree in accounting. Found myself joining a manpower group, which spanned 20 years. So started off as a as a local salesperson and then went back to grad school. Um, because one of the things that even I was seeing as we kind of entered, you know, the 2000 that the digitization of our systems was well underway, and I went into national roles and global roles. And, you know, that really kind of cemented the type of conversations in terms of working with some some pretty large fortune 100 customers, from BP to Exxon to three M to Microsoft and Cisco. And it one of the things that really shocked me, especially working with a lot of Silicon Valley companies, is the level of sophistication that they were going through to build teams with the right skills to help develop some of the solutions and platforms that we see today, and how applicable that was, not just to other fortune 100 companies, but all the way down to SMB. Well, you know, A.I. has kind of completely upended that today. And we feel that if you’re a candidate looking for a job and there’s some really interesting data there around how actually harder it is to get a job because of the implementation of these AI systems. Um, there’s there are some success stories. But, you know, quoting McKinsey, which came out with a report last summer that basically said 75% of all businesses will be impacted by AI, and they’re looking at the adoption wave.

Daniel Friker: And the probably the best analogy, um, is thinking about e-commerce, right? E-commerce comes out in the 90s, but it wasn’t until 2018 that companies that hadn’t adopted and adapted to e-commerce were out of business in 2018, because that was the high watermark of more companies going out of business in the retail space. Now imagine that same curve. But now you have individuals that are saying, if you don’t have an implemented AI strategy, you’re out of business by 2030. And that’s just giving a lot of people from boardrooms to senior executives to to business owners to go, okay. You know, there’s a moment right now that incorporating these type of tools and technologies will give you a competitive advantage. But literally, as we’re knocking on the door to this next decade, if you don’t have it, you’re it’s really going to negatively impact your business. So, um, like all good conversations that started as a boardroom conversation around, um, you know, how how can companies know? My purview is a little bit more narrow, uh, within the area of HR. Um, and I was convinced at the time that there were good AI. In HR examples. And it wasn’t until. And this is about 11 months of research and conversations and talking to PhDs that I realized that there’s actually more evidence right now of how it’s creating entropy. Um, this is not working as well. Um, but I think there is hope here. And so this is kind of what I like to talk about in my free time.

Trisha Stetzel: Yeah, I love it. I think it’s fantastic. So because this is your the AI space we’re talking about is very much inside the air. Space. Can we talk about what tools we’re talking about? The AI is so broad we use that. We use that for everything, right? Anything that’s automated, it’s AI. Um, and some people think AI is just a chat bot, which is way more right. It’s not all encompassing, but it’s also not so narrow. So from an HR perspective where the industry that you’re playing with AI in this space, what does it actually mean.

Daniel Friker: So you kind of so there’s things called applicant tracking systems. It’s a type of software that I would say certainly most if the time, all the fortune 500 years. But I would even kind of tail that off into the fortune 1000. And there’s, um, so there’s, you know, kind of the big boys in the, in the, in the marketplace would be, uh, organizations like Bullhorn and Workday. You know, like, again, it’s kind of the 8020 rule, right? And what you really started to see over the last 2 or 3 years is because their customers were saying, hey, do you have a module? They started plunking in a bunch of AI modules. Well, what I was seeing on the other end is, and you’re probably going to hear me talk a lot about military comparisons, and there’s going to be a lot of good examples of this just because you incorporate a new tool, a new weapon, a new platform. Sometimes it does take some time to kind of figure out, okay, what are the best weapons and tactics with that new tool so that you can have the maximum effect? And what I was seeing is that these new software packages were being, you know, incorporated, but people were still trying to use the old processes with them, and what that can create in a lot of organizations is something called the efficiency success paradox.

Daniel Friker: And what I mean by that is if you’re a business professional, the biggest platform out there is LinkedIn, right? You can now go and click, you know, easy apply. You can literally submit to 100 or 200, you know CV’s a day. Well that’s very efficient. But what’s really the success factor. The success factor is getting the interview and getting hired. And what’s been crazy is I’ve been following the data. January, February, March, April I think. I don’t know if I had the May data yet, but certainly through the April data and you can literally see. So looking at LinkedIn’s own data, looking at glass doors data, you can see how the average number of applicants per opening went from about 100 110. As of right now, it’s 250 applicants per Her job opening. So now think about you’re on the other end of that. You know, you’re the recruiter. And so now you just have a bunch of needles in front of you, and you’re being tasked with trying to select the best person. And you might only interview 4 to 6 people. So how do you stand out? Well, the data’s even more interesting when you take a look at less than half.

Daniel Friker: That’s about 40. 43% of people are using AI to help custom config their CVS or resumes to the open role. Another way of saying that is half the people aren’t even doing that necessary step. And what you’ve also seen in that same amount of time frame. So we’re not we’re not talking 2024 data. We’re talking about 2025 data is the response rate of actually submitting your CV or resume to an open role. Went from 10%. Right now it’s less than four. So the one thing that I will tell you, because it’s graduation season here, is it doesn’t matter if you’re high school bachelor’s, master’s or PhD student. Um, and I do actually sit on the advisory board at the University of Minnesota within the College of Science and Engineering, and the job market has gotten more difficult. Um, and so if you’re not adopting and adapting to the kind of what the new environment looks like, um, it will prolong your search. And on on the other side, if you understand what the landscape is like, that will help you achieve what your ultimate goal is, which is hopefully a job offer.

Trisha Stetzel: Right, exactly. All right, so I’m getting it. I have a small brain. I’m kidding, but I’m getting it. I’m understanding. So what I heard was, from a candidate perspective, if I’m applying for a job, a lot of people who are applying for jobs are just pushing the button, and they’re not making any, um, customizations to their CV before they send it out to the people who are looking for applications. So I get that. But I also understand that there must be tools or processes on the hiring side that can help me sift through all of those needles that are now sitting in front of me. Is that true?

Daniel Friker: It is. But this also gets back to it’s a two sided problem, right? So we just talked about the candidate side. And what I have been seeing on the business side is companies right now aren’t changing how they’re putting things out there. So on the one hand one plus I would give the industry is they are using AI to write better job descriptions. This has been the bane of every HR person or hiring manager for decades. You know, you put out a generic, you know, job description. Now you can and you should be doing this. Um, and certainly anecdotally, I know that this is the case. Not only can you write a job description that is bespoke to your industry, but even down to the company, right. And if you want to get bonus points, there are AI systems. So there’s a good platform from a company called Talent Edge. I believe actually a Texas based company that. So envision a world where pick a business, pick an industry. It doesn’t matter. You’re able to write a job description that’s specific to your company. And then you can utilize a tool like Talent Edge. And there’s a couple of them out there that can even predict what are the skills that you’re going to need.

Daniel Friker: So now you’re not just talking about past tense type of skills, but that future tense type of skills, so that if you are bringing on a person and it’s expensive, it doesn’t matter if you’re a big fortune company or small business, every hire that you need to bring into your company, you know, has to have a return. So so that’s the good news. Is that okay, better job description. But here’s the thing that’s driving me nuts is when I’m there’s a key variable called hires by source type. Right. So ultimately when a company makes a hiring decision, where did you get the applicants? Because there’s no question they’re getting by volume from like, the job boards or LinkedIn. But what’s been interesting is to see the bar increase. So you’re talking about at the start of the year, it was about 15 to 20% of companies were hiring based on employee referrals. Right. So someone in the company saying, oh, you should interview this person. That number is now up to 40%. So you have all these AI systems that can do all these great algorithms. But just because someone’s walking up saying you should hire this person. But the why the explanation is now again, put yourself in that person’s the talent acquisition person’s shoes.

Daniel Friker: You get 250 applicants, right. So again you have a great tool. You have a great weapon and you’re not using it. But that’s where I think you’re going to see good examples of organizations that are starting to mirror the to, you know, leverage what the tools and technology can do really well and put people. Really kind of in that part of the hiring equation that has the most value. So maybe you can do your initial prescreening. You can you can do all the necessary upfront things in an automated way. So now as a recruiter you don’t have to do all that kind of stuff. Right. And probably one of the most interesting examples comes from the US military. So the US Army actually has now been working on this for the last two years, which is part of the recruit 360 program. Right. And, you know, I mean, Trisha, I’m sure you remember, you know, what it was like to go with the recruiter. They didn’t want to be, you know, like, yeah, there’s a delta between. What do you want to be? You know, like, I want to be a seal. And they’re probably going, sure. Sign here. You know, guess what?

Trisha Stetzel: Yeah, we’ll talk about that after boot camp.

Speaker4: Exactly. You know.

Daniel Friker: What? You know what? The army, in fact, all the branches are doing now is they’re taking all that intake data. Right? And that could be based on your cognitive abilities. You know, they’re smart, you know. Ah, and really kind of break it down and try to use less subjectivity in terms of where you can add the most value in the armed services or in this case, you know, the US Army and actually at least give you a higher probability of kind of mutual value, mutual benefit for both. Right. So yes, you might have some desire of what you want to do in the service. But you know, I mean again it you know, seals are what, less than 1%, you know, you know like.

Trisha Stetzel: 1% and 1% and 1%. Yeah.

Daniel Friker: Correct. You know so but I so that is what I’m starting to see are some companies that are actually starting to kind of mirror both those weapons and tactics. And again, That gives them a competitive advantage. Right. And now there’s more ways to essentially you know. Now, also, I want you to kind of think about another major trend that’s been going on for several years, which is this idea about blockchain, right. So I think linked in, but now your skills are a little bit more quantifiable. So what I mean by that is I can write I’m a good public speaker. Right. Because, you know, your job description says you want to be a good public speaker. Now, what it can do is actually start to kind of scan, okay, has this person done seminars and podcasts and whatever. And essentially give you a score on that. So, you know, like if you get a certification, um, you know, I work with Cisco, so like you get a CCNa, right? Right. You get certain certifications and that will give you a bump in pay, you know. And there’s a lot of industries will have different certifications and everything else because it demonstrates to the employer to, you know, hiring community writ large that you’ve achieved a certain mastery in a certain area. That’s great when you get those certifications. But what about all these other soft skills? Right. So now some of these AI tools are out there to to at least take some of that mystery out. So better hiring decisions, more efficient hiring decisions, um, kind of more merit based systems. And that’s hopefully kind of combining both your strengths and weaknesses with the strengths and weaknesses of the company.

Trisha Stetzel: So yeah, absolutely. So better match. Even in the military putting you in the right job I remember yeah, I remember walking down the hallway with the recruiter and him saying, hey, you had a really good score on your Asvab. These are the jobs that you could do. Which one would you like? Yeah. Like well I don’t know. What does it mean. I have no idea if I, if I would be good at that job or not. Um, okay. So if folks are already interested in having a conversation with you, Dan, what’s the best way to find you?

Daniel Friker: I think the best way to find me is just find me on LinkedIn. So just Dan Fricker um, there aren’t many of us.

Trisha Stetzel: So there are not many of you. And his last name is spelled f r I care. I’ll put a link to his LinkedIn profile in the show notes as well. So, Dan, as you’re going through this conversation, there’s so many great things that are happening with AI. There’s a lot of buzz in the news right now that, um, A.I. is, I don’t want to say damaging, but that’s the only word that comes to mind, um, damaging the ability for our entry level workers to get a job. It’s all over the news, right? So is it worth just having a conversation about.

Speaker4: Sure.

Daniel Friker: So when we talk about adoption and adoption. Right. And again, I think what is one of the big red, red flashing lights out there is unlike in years past, like when I graduated from the University of Minnesota with an accounting degree. It was actually my Excel skills that got me hired at good old Time Warner. So essentially, I was a business analyst, right? And because I really needed someone that that knew how to do all these kind of price per point and all this kind of, you know, stuff and everything else. So I think with everything being truncated, with everything being shortened, you know, I think this also applies to individuals. So those that adapt and adapt to learn some of these AI tools more effectively. So there definitely needs to be more cross-training retraining. I think there’s also, you know, some more fundamental things that have to happen. So what I have seen in terms of failed AI projects is and I kind of made reference to it at the top of the interview, which is companies that buy these packages. And from an IT perspective, they can do some really great things. But what where they’ve kind of fallen apart is saying you have to create the Venn diagram between the technical needs and of of the system, and then what the business value is. So as you’re starting to see more examples, not just across industry but in job function, right. Walmart decides to incorporate AI with the idea of how do we create Walmart stores with a five mile radius so that it can have 10,000 SKUs at full capacity? Because the Walmart that you have in Texas or even spring, Texas, for that matter, versus Maple Grove, Minnesota. Those are going to be different, right? And that’s going to allow them to do same day delivery. That’s going to allow them to essentially compete. You know, model a model with like the Amazons of the world, right. Um, HSBC with what they’re using for fraud detection. Um, there’s a phenomenal example with John Deere and how they’re essentially, you know, John Deere is now calling themselves an AI. Agribusiness.

Trisha Stetzel: Yeah. Okay.

Daniel Friker: Well, think. Sorry. I’m from the Midwest, so I am the embodiment of corn. So, yeah, one of the most expensive things for any farmer is overlap. So if you’re in a field and everything else, you know, you might overlap 5 to 10%. Um, and that’s become part of the field. You’re putting down your herbicides or pesticides or whatever. Um, John Deere has really been doing this since the 90s. So they started with data science. And so now that you have self-driving combines, that your overlap has gone from 5 to 10% to less than 1%. They’re using facial recognition software so that as they’re towing, you know, their you know, the dispersing systems behind them. It’s not just putting down herbicides just all over the place. It’s looking for the wheat. Jason Wheat puts it down. What does this mean? It means if you’re a farmer, you spent a half $1 million on pesticides the year before. Or herbicides? Now you’re spending $100,000 and now you’re seeing Agco companies trying to catch up, because now they literally have better farm equipment than what you see, you know, vis a vis. So that that is a huge competitive advantage for them. Um, you see this now also in some small businesses where they’re able to use a variety of fractional skills. So, you know, McKinsey made a comment. Mckinsey likes to throw out like huge Hail Mary kind of things. By the end of the decade, you’re going to see your first trillion dollar company with one employee, the founder, because they’ve been able to create these kind of really dynamic HR models to basically get the skills that they need right now.

Daniel Friker: If you’re an individual, you have to be paying attention to these emerging tools. And if you’re in sales, you’re probably familiar with things like Salesforce and HubSpot and, you know, but I can go down the list around if you’re in marketing, like in there are good and bad examples of this. So in marketing, you know, one skill that has been decimated are photographers, you know, so if you were, you know, you know, you used to be like, if you’re doing a thing for North Face and you’re taking a bunch of pictures of skiers and everything else, that’s great. But then now if North Face is like, no, we want that jacket from black to red and we want the sun over here, you can do that all digitally. And so you don’t have to literally do reshoots. And so this is where you’re going to have some, frankly winners and losers. Now does that mean photographers are skills are irrelevant. Absolutely not. It just means that that cycle time for them to learn some of those new skills, you know, I mean, you probably remember the first time you I mean, I remember old, um, I remember like, you know, going Lotus one, two, three, you know, then learning WordPerfect and you go to work.

Trisha Stetzel: Oh, I am. I’ve been there. Yeah. I say, I may not look that old, but I am.

Speaker4: Well.

Daniel Friker: But I’ll give you another example. So within the College of Science and Engineering, um, our sole mission is to help improve landing rates of students. Right. And to be clear, I don’t want to oversell this. I’m talking about, again, the College of Science and Engineering. So any major school from Texas A&M, you know, you have your liberal arts, you have your business school and everything else. So it’s just so think physics, astrophysics, chemistry, engineering. Right. And I want to say this with all love and respect, um, really good scientists, not necessarily great soft skills, you know, and when we first started seven years ago, um, even giving getting in some of these really brilliant folks that are doing some really cutting edge stuff and just you’re saying like, well, tell me what you do, and you don’t even know how to answer that question. Um, and so, you know, the impact that we’ve been trying to work on by other members of the board as well is to say, okay, how do we get them to articulate why an astrophysicist? And this is a real example, by the way. There were two astrophysicists that were all excited this about two years ago because they got jobs with the Minnesota Twins, because they’re the Moneyball guys. Because if you can figure out where an asteroid is going to be, because they’re using AI tools and Python and R and all these kind of, you can probably figure out what the best lineup is against the Cubs. So like it’s but it’s a real example of like, you know, the more exposure to you that you have with these tools and you see a lot of these younger students. I mean, I have a younger daughter, she’s using AI to do like graphic arts and like, so I would actually argue her actual practical application of those skills. It’s almost native to her. Like, doesn’t even she doesn’t even know any better. It’s our generation that are the ones that are going to have to kind of be more adapted.

Trisha Stetzel: Yeah, absolutely. Okay, so I think this is a good place for us to kind of wrap up our conversation because I, I like to auger in on that. I meet a lot of, um, SMEs, the owners, president, what CEOs, even the people, the managers under them who have not adapted or adopted any AI tools. They’re doing it the same way they’ve always done it and they’re uncomfortable trying something new. So what would you say to them?

Daniel Friker: It’s it’s I guess this is a little bit more personal for me, and I’ll use this example as well. Okay. In the late 90s, there was a product that Time-Warner had called Roadrunner. This was what they were trying to do to sell companies high speed internet. And it’s funny now to say it, but at the time, in fact, all the way through the early 2000, um, it was like 2003, 2004. It was with the big switch that we went from dial up speeds to high speed internet. And we had to create all these like marketing slicks and everything else to kind of. Help business owners to say, like, why would they need to spend more money? Well, the light bulbs started going out and it happened relatively fast. Once they realized, wait a minute, I can sell products 24 over seven whether I’m open or closed. You know, if I adopt not just the high speed internet, but essentially kind of this whole e-commerce platform, I like to use that analogy because I’m sorry, I don’t know any business today that doesn’t have a website or some type of ability to market or sell their services or products. And so and then using that example to say, like those companies that resist and resisted, resist it.

Daniel Friker: Um, and how they went out of business by 2018. I mean, I think that is the harbinger, right? And, you know, it’s funny because I you know, in our pre-interview I talked about, you know, if you want to see some really interesting practical applications in the non-business space. Is the war in Ukraine? And when we talked about it, that was way before, you know, what just happened. You saw over the weekend in terms of this kind of asymmetrical warfare that’s going on. And so that is kind of the call of action to get people to is saying, look, you need to look into this. You need to adapt to this environment because you don’t want to be on the receiving end and suddenly realized, oh, darn, I have a competitive disadvantage. Right. And what is really unique and we can talk about this as well, is that the private equity space, having done consulting with them as well, it’s not just that there is kind of a.com rush going on right now. If you have an AI bot or an AI platform, it’s not hard to get anywhere from a half million to $2 million in private equity coming your way. Right. But one of the things that they’re looking for is practical application of AI in the real world.

Daniel Friker: And the John Deere example is probably one of the best examples of how this was part of their long term strategic vision. And now every other manufacturer is trying to catch up to what they have, right. And so that’s the thing that I would say to small to medium sized companies, which is there’s an opportunity to run your business more efficiently, right? And reduce your operating costs in half, if not more. I mean, that’s the call to action within the HR services and staffing services space is AI has the ability to literally cut the cost per hire in half, if not even more so. Right. Because if you only have people at the very end of the process and you have all these other tools, um, you know, you can definitely see this in it and technology. Um, I was actually shown a demo of a, of an AI tool and I’m like, oh, how did you write this? And I’m like, we didn’t. We had I write it, so they actually came up with the idea, the business idea. And then normally you had to spend a lot of money for developers, programmers and everything else. No, I just did it.

Speaker4: It was shocking.

Daniel Friker: And so, you know, that small to medium sized companies, so much more of an advantage because if they’re on the street and they see something, they can pilot and test it, and then now they can have a huge competitive advantage. But if they stick their head in the sand, someone else is probably doing that.

Trisha Stetzel: Yeah. Okay. So a few things that I’m taking away from our conversation today. I know our time flew by like so fast, but a few things. If I play the modem sound right now because that’s all I can think about.

Speaker5: When you were talking about moving to Roadrunner.

Trisha Stetzel: If if the SMEs today that are listening, if all you take away today is that modem sound in your head and you don’t want to get stuck there. Then we made a difference, right? The second thing is my granddaddy had a John Deere tractor. We got John Deere in Texas. So that’s going.

Speaker5: To resonate.

Trisha Stetzel: With people as well. And the third thing you said that there will be $1 trillion solo owner out there. And it’s because they’re adapting and adapting to these tools. So those are the three big things that I took from our conversation today. I really, really appreciate you coming on. We may have to have another conversation. I’m just saying there’s so much more. There.

Daniel Friker: You just hit on the head that there is so much more there. We’re only looking at a small vignette, but I would love to come back.

Trisha Stetzel: Yeah, I love that. So Dan, what would you like to leave folks with today as we close?

Daniel Friker: You know, I would just say this, um, I mean, this is certainly a hot topic. You can definitely find me on LinkedIn. Um, for those in the upper Midwest. I’m actually having a workshop with everything from small to medium sized businesses, to even some fortune 100 companies at the Minnesota Twins stadium. Um, that’s actually on the 10th of July. Um, but I based on the demand, it sounds like we’ll be doing more of these either virtually or in person as well. And but I you know, a lot of people have reached out to me because I have done a number of these type of speaking engagements and I’m super interested to hear and there’s some really good examples of people using AI, and it’s almost coming out every day, every week. Um, and that’s just how crazy fast this, this is really evolving. Um, so it’s a topic that I love talking about. And certainly when I hear really good examples of practical application. Um, yeah. So reach out to me or maybe attend one of my seminars. And, um, but thank you so much for having me today.

Trisha Stetzel: Yeah, it’s been great. Daniel. Thank you. So if you want to find Daniel on LinkedIn, it’s Daniel da an ial fricker f r I k e r. And his event at the Minnesota Twins Stadium is on July 10th. I’m sure he’d be happy to give you more information about that. All of his contact information will be in the show notes. Dan, thanks again for being with me.

Daniel Friker: Thank you.

Trisha Stetzel: That’s all the time we have for today’s show. If you found value in this conversation that I had with Dan today, share it with a fellow entrepreneur, a veteran or a Houston leader ready to grow. Be sure to follow, rate, and review the show. It helps us reach more bold business minds just like yours. Your business, your leadership, and your legacy are built one intentional step at a time. So stay inspired, stay focused, and keep building the business and the life you deserve.