Mark Prices - AI Is a Change Management Project, Not a Technology Project

Welcome everyone to the Conversations on Applied AI podcast. Today we're speaking with Mark Price. Mark brings academic experience and a strong foundation in business analytics, change management, and curriculum development.

He serves as a distinguished service professor and AI faculty lead at the University of St. Thomas, Opus College of Business. In this role, he focuses on designing and teaching innovative AI courses, training faculty and staff to leverage AI, and contributing to university-wide initiatives on AI's transformative role in education.

Mark previously worked as chief data officer at CaringBridge, where he spearheaded the establishment of their first enterprise analytics function and supported a cultural shift toward a data-driven, customer-centered approach. So I'm truly excited for our conversation. Thank you, Mark, so much for being on the podcast today.

If you are interested in learning how AI is being applied across multiple industries, join us at a future AppliedAI Monthly meetup and help support us as we plan future Emerging Technologies North non-profit events!

• Applied AI
• AppliedAI Meetup
• Emerging Technologies North

Resources and Topics Mentioned in this Episode

Crossing the Chasm — Geoffrey Moore's classic book on the technology adoption lifecycle, applied by Mark to AI adoption within organizations.
https://en.wikipedia.org/wiki/Crossing_the_Chasm

Shadow AI — The use of AI tools by employees on personal devices without official organizational sanction or oversight.
https://www.cisco.com/c/en/us/products/security/shadow-ai.html

Ethan Mollick's AI Productivity Research — Professor at Wharton studying AI's impact on work and productivity, including the Procter & Gamble studies referenced by Justin.
https://www.oneusefulthing.org/

Microsoft Copilot — The AI assistant referenced in the Chevron cautionary tale about deploying 20,000 licenses with zero results due to lack of training and change management.
https://www.microsoft.com/en-us/microsoft-copilot

Bayer — Global life sciences company whose new CEO restructured middle management to accelerate innovation and flatten approval layers.
https://www.bayer.com

Applied AI (podcast community & nonprofit) — Justin's organization hosting events, meetups, and conferences on applied AI in the Twin Cities.
https://appliedai.mn

Bonus links from the episode:

• University of St. Thomas, Opus College of Business: https://business.stthomas.edu/
• CaringBridge: https://www.caringbridge.org
• ChatGPT: https://chatgpt.com
• Mark Price's Substack: https://substack.com/@profmarkprice

Transcript

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[00:00:00] Mark Price: And this is something that I wrote one of my Substack newsletters on, which is you interview the top salespeople. What do the top salespeople love to do? Talk, right? So you interview them for an hour, two hours, three hours. You turn it into a transcript. You take that transcript, you put it into gen AI, and you create training materials.

[00:00:20] And by doing that, you level up your entire sales organization based on the wisdom of the top salespeople. And so utilizing it in ways like... So what do you do then? That means that you probably have a lower lead rate, but a higher close rate, will be the metrics that you will see with it. By federating the knowledge of the people who really are successful at what you do.

[00:00:49] AI Announcer: Welcome to the Conversations on Applied AI podcast, where Justin Grammens and the team at Emerging Technologies North talk with experts in the fields of artificial intelligence and deep learning. [00:01:00] In each episode, we cut through the hype and dive into how these technologies are being applied to real-world problems today.

[00:01:07] We hope that you find this episode educational and applicable to your industry, and connect with us to learn more about our organization at appliedai.mn. Enjoy. 

[00:01:20] Justin Grammens: Welcome everyone to the Conversations on Applied AI podcast. Today we're speaking with Mark Price. Mark comes to us with experience in academia and a strong foundation in business analytics, change management, and curriculum development.

[00:01:31] He serves as a distinguished service professor and AI faculty lead at the University of St. Thomas, Opus College of Business. In this role, his focus is on designing and teaching innovative AI courses, training faculty and staff to leverage AI, and contributing to university-wide initiatives in AI's transformative role in education.

[00:01:50] Mark previously worked as chief data officer at CaringBridge, where he spearheaded the establishment of their first enterprise analytics function and supported a cultural shift toward a [00:02:00] data-driven, customer-centered approach. So I'm truly excited for our conversation. Thank you, Mark, so much for being on the podcast today.

[00:02:06] Mark Price: Thank you, Justin. I'm glad to be here. 

[00:02:07] Justin Grammens: Awesome. You know, I've met you quite a few times at a number of our Applied AI events, and I've sort of known you from your work at the University of St. Thomas, and I know we'll touch a little bit on that, but I also was not aware that you also were at CaringBridge here for quite some time.

[00:02:21] But oftentimes when I introduce people at the beginning, maybe you could paint a little bit of picture with regards to how you got to where you are today. 

[00:02:27] Mark Price: Sure. The piece that you didn't mention was that I actually was an entrepreneur prior to going to CaringBridge. So I have an MBA from the Darden School of Business at Virginia, came out to the Twin Cities, fell in love with it, haven't left, and I ended up being in a consulting firm which got acquired, another consulting firm that got acquired, and a software company that got acquired all in three years.

[00:02:54] At which point I said, "I'm not God's gift to management, but I think I may be able to [00:03:00] do better than these guys." So I started my own firm called M Squared Group to start, and eventually became known as LiftPoint Consulting, and I ran a data analytics consulting firm for sixteen years focusing on marketing analytics and supply chain analytics.

[00:03:16] I then sold the firm, went to the company that acquired us for two years, and then went to CaringBridge. While I was at CaringBridge, even before that, I had been teaching one course a semester at first St. John's and St. Ben's and then at St. Thomas, and it was mostly focused on digital marketing analytics, marketing analytics, even branding, promotion, sales, all of those kinds of core marketing functions.

[00:03:47] So when I was ending up and kinda winding up at CaringBridge, I talked to the associate dean at St. Thomas, where I'd been doing one course a s- a semester. It was the [00:04:00] capstone for, for business analytics. I said, "I'm gonna have a lot more time." And he said, "Oh, could you teach this? Could you teach that? Could you teach this?"

[00:04:08] And the next thing you know, I'm a full-time adjunct professor. So I was teaching five classes a year, and then the fall of two thousand twenty-two came along. In the fall of two thousand twenty-two, ChatGPT came out and went public, and I got really excited about the opportunities and the potential coming along with it.

[00:04:28] Now, the fastest way in academia to get anything approved is to do it for executive education. So I created a class called AI for Professionals, which was a two-day class, which is now a three-day class, and we taught it the first time, and then it's grown since then, and I now teach it four to five times a year, where I teach the fundamentals from a business perspective of what generative AI is, how do you use it, and then the third day became how do you use [00:05:00] GenAI with Excel.

[00:05:02] And that's one of the pieces that people tend to fall over about. I also created AI for Marketing, which is another executive ed class Then they asked me if I would teach a graduate school class in AI, and I created Harnessing AI for Competitive Advantage, and that class sold out in the first semester.

[00:05:23] So now it's a prerequisite in the graduate school for the Master's of Science in Business Analytics, the part-time MBA, the STEM MBA, and so it's become a very popular class as well. And then in the fall, I'll be teaching business analytics, business applications of AI rather, in the undergrad for the first time.

[00:05:43] I also speak at conferences, I do consulting, and I have a Substack newsletter as well, because my students all ask me, once they finish my class, how do they keep current? And I said, "First off, you can't keep current," 'cause as you and I know, every [00:06:00] seventy-two hours, this darn thing reinvents itself. So the only thing I'm doing now is I've p-produced a newsletter to help my participants in executive education, my students in graduate school and undergrad, do as close as they can to staying current, not with the technology.

[00:06:18] It's how do they use it in business applications to improve their performance in the company and improve the company's performance overall. So I say it's almost absurdly practical advice that I focus on. 

[00:06:34] Justin Grammens: This is why you're perfect for this podcast here, 'cause we're called Applied AI, and one of the things we like to do is talk about applications of it, and you're right at the forefront of all of that.

[00:06:43] And I think what's interesting is you were doing marketing analytics and business analytics in the early days. Marketing analytics I don't think was even a term much back in fifteen, twenty years ago. Do you feel like you were in this revolution here with AI as well? I mean, maybe that's a simple question, but do you feel it's still the early [00:07:00] days as you think back?

[00:07:01] Mark Price: For marketing analytics, it's clearly relatively sophisticated, but for AI, I don't know whether to call it the early days or not, because the days are changing so fast that it feels like dog years. Every time we turn around, a whole new capability comes online, and things we never thought were possible are things that are n- possible, and then you find out within three months they're easy.

[00:07:25] And so I have a strong growth mindset, so for me, constantly learning new things is the most fun I could have in the entire world, and then sharing it with people who can use it. 

[00:07:36] Justin Grammens: Did you ever think you'd be a college professor, I guess, if you kinda rewind your, the clock back a number of years? 

[00:07:42] Mark Price: I always thought that eventually I would retire and teach one course a semester and do a little consulting, was my plan.

[00:07:51] And then, yeah, I went from an adjunct professor, to finish that story, to now I'm a distinguished service professor, which is like clinical faculty. So I'm teaching [00:08:00] five classes with all the speaking, and my wife thought that we were gonna slow down at some point. And she's like, "What's with this?" And I'm like, "Well, this is the most exciting thing I've ever done in my life, and I'm having so much fun with it, I can't tell you."

[00:08:14] We're negotiating at home, let's put it that way. 

[00:08:17] Justin Grammens: No, I know. I think you and I are, are cut from the same cloth in some ways too. I, yeah, that is probably where I will end up, I've told people, end off my career in that, in this education space. I'm just so busy in industry, but obviously I've been teaching at St.

[00:08:30] Thomas as well as an adjunct part-time- Yeah ... since 2015, focusing more on the data science and the engineering side. But what I love what you're teaching here is, like you said, practical applications, right? It's basically the tech is kind of irrelevant in a lot of these things. It's gonna happen, it's gonna change underneath the covers, and yes, there's engineering that's going on, but your angle really is the how do you help the business professional leverage these tools that are there?

[00:08:52] Mark Price: Exactly, and that's really where you make or break it. Because we know that with all the news that's come out with AI, [00:09:00] all the boards of these companies are leaning really hard on the executives to be able to execute with AI because the boards have FOMO. They're afraid of missing out and having the competition pick up something that their company isn't and find themselves in bad shape.

[00:09:19] So the executives who have almost no experience with AI at all now go to the next level of management, to the VPs and the directors, and say, "This AI thing, figure it out. I don't know what we should be doing with it, but figure it out and figure it out quickly because next quarter I've got to report to the board and tell them what I'm doing."

[00:09:39] And so you've got FOMO combined with a fear of God in the, uh, upper level of the operational management. And so there's a lot of pressure to figure out these common sense, practical ways to improve efficiency and improve performance [00:10:00] as quickly as they can figure out to do it within guidelines and guardrails that are safe.

[00:10:07] Because, you know, I would say the first rule in consulting is do no harm. So what you wanna do is make sure that you're empowering your organization to be able to move ahead rapidly while not triggering anything that really could come and get you, you know, on the back end, something that could damage your reputation, something that could leave you in legal or financial liability.

[00:10:31] All of those things are critical things for people to understand. 

[00:10:36] Justin Grammens: The fact that you put this course out and it basically sold out right away means that there's hunger for people to send their staff and other people of the organization into a higher education institution to kinda learn this stuff.

[00:10:48] We'll definitely talk about guardrails because I think that's definitely a component that a lot of businesses aren't really thinking about. But let me step back for a second. You and I have been in this space, like you said, for quite some time, right? We were probably one of the first [00:11:00] users of ChatGPT back in twenty twenty-two, and we actually launched the Applied AI Conference actually two weeks before ChatGPT came out.

[00:11:07] We're three and a half years in now, right? It'll be four years here this fall. Are you still feeling like people don't really think it-- they think it's a fad, or they don't really believe it? Or how come this has taken so long, I think, to finally get as hot as it is today? 

[00:11:20] Mark Price: I'll tell you that I run into very few people who think it's a fad.

[00:11:25] What they feel is that it's either a huge distraction for them in their jobs or the latest management thing, and if you put your head down, it'll go away in a little while And people have built their careers out of hearing something from senior management and putting their head down and then waiting to see if it goes away.

[00:11:44] But you have a good question, and the question is, given how transformational this is, and we haven't talked about that because you and I just sort of assume it. This is the largest transformation since the Industrial Revolution, and it will change everyone's job in the company [00:12:00] from the person at the front desk all the way to the CEO.

[00:12:03] And yet at the same time, we've seen slower adoption around this than we would have imagined with these capabilities leapfrogging ahead in the most astonishingly short period of time. The reason I believe for that is because AI is actually not a technology project. AI is a change management project masquerading as a technology project.

[00:12:27] And the biggest challenge you have is as you move towards becoming an AI-enabled and then an AI-first organization, is that you've got people, and you literally will live or die based on the adoption of these people, of this new capability. And people are scared, they're threatened, and they're busy And when you put all of those together, you have stuff where it's not that people are actively [00:13:00] saying, "We shouldn't be doing this."

[00:13:03] It's the best way to lose your job is to say actively, "We w- we shouldn't be doing this." What they say is, "I'm too busy. I tried it, it doesn't work. I don't have the time to learn it. You gonna carve out any of my job so I can learn how to use this now? So when are you expecting me to do this?" And so you run into all the classic kind of objections.

[00:13:25] They really kind of go back to three things. One is people are afraid of losing their jobs. They flat out are, and I have to tell you that in some cases, they're not completely wrong. We have to be straight up and look this in the eye. When I train my participants in exec ed and my graduate students, I say, "I can't tell you that you won't get laid off, but what I can tell you is, do you know who they lay off last?

[00:13:54] The AI person. So you need to learn this technology. You need to [00:14:00] use it. You need to market it." And so I teach them, I say, "Teach it to your cube mate, teach it to your manager, teach it to your director, teach it to your VP, teach it to your general manager, and become known as the person who can help people with problems large and small around how to be able to use this technology."

[00:14:22] People are afraid of status loss, so they're afraid they're not going to be seen as an expert. They're worried about competence loss. They're gonna have to go back down the learning curve, and that is hard, and that's also humbling to people who may have been an expert in their field for twenty, thirty years.

[00:14:42] They're gonna have to learn some stuff, and they're gonna have to learn stuff, again, like we've seen with analytics, where the younger people know it more than the older people. And so that is always one of the challenges as well to go with it. But companies that fail to recognize that this is a change management [00:15:00] project and to take it from a change management perspective will not succeed.

[00:15:06] The organization will eat them alive. 

[00:15:08] Justin Grammens: Yeah. That's what I have seen in all these waves of technology that happen, is that you need to get adoption, uh, in order to actually change the business, and you need to sort of make sure that everyone is sort of all the way from the frontline worker all the way up to the CEO, that everyone is in alignment with regards to this is something that is good and this is something that we should do.

[00:15:26] How have you seen the culture of business change? I- I've done a lot of work around the Internet of Things and gone into businesses and tried to change processes to digitize things that a business might be doing old school ways, and what I have found is a lot of businesses are set in their ways, and they're like, "This is the way we've done this for the past thirty years.

[00:15:43] I don't wanna change." And AI is even more transformational. I would view AI as basically like electricity, right? It can be used anywhere and any process or part of the business. As you've seen different businesses and worked with them, do you see some that are a little bit more ripe, some that are a little bit more standoffish?

[00:15:58] What's the culture that you're sort of [00:16:00] looking for and, and trying to get people to sort of embrace? 

[00:16:02] Mark Price: Well, you're really talking about an adaptive culture inside an organization, and there are very few of them in larger organizations because they fundamentally operate, if you will, like the Industrial Revolution.

[00:16:15] It's a factory. It's a machine. These things come in, these processes happen to it. Here's a product, here's our QA on it, here's how we ship it, and yes, we're looking for supply chain opportunities, optimization kinds of pieces, because who wouldn't? I'm looking for a way to save costs. I'm looking for a way to, to make my customer happier.

[00:16:36] But what I'm not willing to do is essentially embrace a whole new way of looking at the business. And one of the challenges with that is it has to start at the top. This is not something that you can bottom up. The CEO and the executive team has to own a commitment to using AI. And when they do that, they [00:17:00] start to force the next level down to leverage it as well.

[00:17:07] A very simple example, when somebody does a presentation to an executive, the first question that executive needs to ask is, "What did generative AI say when you loaded this presentation in?" And if they didn't, Justin, they have to send them away. 

[00:17:23] Justin Grammens: Hmm. So the expectation is they're actually using the tools in every aspect of what they do.

[00:17:28] Mark Price: Yes. And you see them use it, and then they insist that the people underneath them are providing them with AI-informed insights. The next piece is the rule I always have, which is people will do first as they're compensated, second as they're measured, third exactly what they used to. So you wanna really get people's attention, change their comp.

[00:17:54] And there are some companies that have done that, where they have announced that bonuses for this year [00:18:00] will be 30% determined by how much you leveraged AI, and this is not a joke, and here's the rubric on how we're gonna do it. The second thing is to measure people, so you need to do AI engagement surveys, and you need to visibly reward the innovators and the early adopters.

[00:18:21] So you bring forward the use cases that they do, and you bring them forward, and you publicly recognize them in the organization, and you tell their stories So that you show that it is valuable. And as you get more of these use cases, you start to socialize them through the organization. And I al- I always say give them five shares of stock.

[00:18:42] Give them a fifty-dollar Best Buy gift card. I don't care what it is. It doesn't have to be something dramatic. Chipotle always works, but something that says, "What you're doing is something we value in this organization." And ultimately, you have to [00:19:00] change the comp and the measurement to change the behavior.

[00:19:05] Does that make 

[00:19:05] AI Announcer: sense? 

[00:19:06] Justin Grammens: Yeah, it does. So it sounds like you have some best practices, some rules that you go into organizations with. Have you formalized this into some sort of a operating system, for lack of a better term, I guess? Or is every company unique and you gotta make sure that they can assess where they're at in their AI trajectory, right?

[00:19:21] There's different levels of adoption. 

[00:19:23] Mark Price: The answer is that as every company believes they are unique, right? I've never seen a company that doesn't say, "Yeah, I know that works other places, but we're different here." But fundamentally, there's a framework that I've used to address change in organizations, and I found it to be remarkably consistent across organizations because it's really about people.

[00:19:45] It's not necessarily about the organization itself. That framework recognizes that in any organization, you have two to three percent of your workers who are innovators. They love [00:20:00] to be first. And they're not just first at work, they're first everywhere. So they like new technology. They were the first people with an Apple Watch.

[00:20:09] If you went back, if they have enough gray hair, they were the first people with iPhones, right? And they're willing to handle the fact that it doesn't work perfectly at the start because they get a kick out of it. And then you've got the early adopters. The early adopters don't wanna spend a lot of time with the technology, but they wanna be the first at applying that technology in what they do.

[00:20:33] They get a kick out of it, and they wanna see the benefits coming out of it, of the business. So that tends to be anywhere between five and seven percent. So you have about ten percent of the organization where this stuff is already happening in your organization. It is, by the way, Justin, happening whether or not you've given permission for it or not.

[00:20:57] People are using AI on their [00:21:00] phones and their personal computers in the office to help them accelerate their performance. Okay, so that kind of shadow AI is going on in almost every organization. Then you have a group of people called the early majority The early majority is 15 to 25%, depending on the size of the organization.

[00:21:25] The early majority is waiting for the early adopters to tell them it's ready for primetime. How do you tell them it's ready for primetime? You build case studies and you do training, but it's not you and I, it's not the evangelists who do it. You let the early adopters present it to the rest of the organization so that it's got that kind of imprimatur on it, that it's somebody who's maybe had five, 10 years worth of tenure in the organization already.

[00:21:56] It's not somebody new or, God forbid, a consultant [00:22:00] who's telling them how to do this. And as you package up those use cases, you find that 15 to 25% of the organization starts to get excited about this. And then you've got the late majority, and they're gonna wait for, you know, just kinda widespread acceptance, and that can be another 15 to 20%.

[00:22:25] And then you have the laggers, and you're not gonna get 'em. And so you may have what my, uh, my father of blessed memory said, that sometimes if you can't change the people, you have to change the people. But in this case, there's a group of people, you know, that you will not get to come on board. And you can work around them, you can build other things, but that's, that is to some extent, we should have such trouble as you have 70, 80% of the organization actively using this.

[00:22:58] The problem is if leaders come into [00:23:00] the organization and they think they're gonna get 50% of the organization in the first year, and they're not. This is a change management project, and so it requires... And by the way, this is from an original construct from a book called Crossing the Chasm- 

[00:23:15] Justin Grammens: Yeah, I was gonna say 

[00:23:16] Mark Price: Geoffrey Moore

[00:23:16] written in-- Yes, Geoffrey Moore in the 1990s. I am not claiming to be terminally unique on this. What I've discovered is that it applies to this AI paradigm so well That it becomes a very easy construct for people to be able to understand. 

[00:23:32] Justin Grammens: That's a book that I have used quite often as I've started to evaluate bringing a new product to market.

[00:23:37] That's where it's really sort of, I think, is the idea is, like you said, you're gonna develop a product, you basically have people that are in that early, very early stage, and you have to somehow get them over cross that chasm, right? And, and so like you said, if I were to launch a new product tomorrow that is the best fabric softener on the face of the earth, like, how am I going to get people to [00:24:00] move into that adoption curve as they end up-- And again, knowing all the way to the full end, there are some people that are just not going to use it.

[00:24:08] Yes. But how can I actually focus on walking people through this use case? So I think it applies really well to, to just artificial intelligence in general. As you were sort of talking through these things, I'm like, absolutely, I can definitely see how bringing a new product to market and introducing AI, in some ways it's a, it's a convincing factor.

[00:24:26] You have to convince people that this is the thing that they need to be doing and the thing that they need to be using. 

[00:24:30] Mark Price: And you and I can't convince them. It can't be the evangelists who convince them. It has to be people in their own organization, people who have institutional credibility, because if they don't have institutional credibility, it will not work.

[00:24:44] And there's so many examples of multi-million dollar consulting projects producing huge binders that are never executed on. 

[00:24:53] Justin Grammens: That's what I was gonna ask is, is with anything new that comes out, there's all sorts of studies that show it's not going anywhere, right? [00:25:00] That basically eighty percent plus failure with AI projects, peop-- companies aren't seeing the value in it.

[00:25:07] What do you say to that? I mean, are people just not doing it the right way? 'Cause again, I guess you got studies on both sides too. When you listen to stuff from Ethan Mollick and stuff, he's got some really good papers where they've been showing, I've been out evangelizing this as well, pointing to use cases inside Procter & Gamble, where you're seeing huge improvement with people.

[00:25:23] But seems like those might be the edge cases. Uh, if you read most of the general media is people are saying there's more failures than successes. How do you feel about that? 

[00:25:32] Mark Price: Failure is an interesting thing. Well, there's one reason people fail, really fail, and that's if you toss a bunch of licenses out to people and expect them to do stuff.

[00:25:42] Okay? You know, Chevron bought twenty thousand Copilot licenses six months later, had zero results. Why'd they do it? They just expected people, "Here's a technology, figure it out." And everybody's already working fifty, sixty hours a week, and they're like, "Thank you, boss. When [00:26:00] exactly am I supposed to do this?"

[00:26:02] The second thing is that the first benefits that you see from Gen AI is in productivity. There was a, uh, woman in my executive ed, seventy-five percent of this poor lady's job was building PowerPoint. By the end of the first day, I showed her how it was going to be twenty-five percent. Of her job, not seventy-five percent.

[00:26:23] And here's why I said to her, "Here's the question. What are you gonna do with that extra fifty percent of your time?" And if you go to your boss at the end of the week, and you go, "Boss, here are the PowerPoints I produced for you every week, but I had a few minutes, and I've got four really interesting ideas that could grow our business.

[00:26:41] Can I take you through them?" What does the boss say? High flyer, strategic, motivated, everything that you want about your personal brand in the organization. Plus, you're delivering more practical ideas to help grow the company. But what you see at the beginning is you save time on [00:27:00] Excel. You save time on, on writing documents.

[00:27:04] You should never hand-build a PowerPoint ever again in your life. The amount of time I spent trying to create Venn diagrams and make sure that I could get the words to fit in the center little area was absurd. And now I can go to Nanovanna Pro and say, "Do this for me," and it does, and then I put it in, and I'm done.

[00:27:25] So the first piece is productivity, and productivity doesn't have an ROI on it in the short term. 

[00:27:31] Justin Grammens: Or at the very least, it's hard to measure, it feels like. More of a general sense, oh, I feel like I got more stuff done, but cannot be calculated very easily, I feel. 

[00:27:39] Mark Price: It is a way to get buy-in because people are doing less low-value work and work that they don't feel-- that they feel is just not a waste of time, but is just not helping anybody.

[00:27:51] But then you get to what are the workflows that are going to change your customer experience and your prospect experience. [00:28:00] And those are some of the ways that you start to see the results. For example, putting a bot on a website to answer questions shows to do sort of pre-qualification, has shown a twenty-five to thirty percent increase close rate versus having someone actually do that themselves, and that's across industries.

[00:28:19] The reason why, I believe, is people don't like to feel stupid in front of people. They're willing to ask really dumb questions to a bot. A, uh, pre-call salesperson doesn't wanna make 'em feel stupid, but they're still saying something to a person, and they're like, "Am I an idiot by having to ask you this question?"

[00:28:39] And the answer is no, because it's the same question that lots of people have. But if you have the bot there to kind of nurture them to a point where they say, "Okay, would you like to talk to a person?" And you can say at any point in it, "If you just tell me you wanna talk to a person, I'll go get 'em. But if you have a few questions beforehand, let me take care of them."

[00:28:58] The other place is in, [00:29:00] uh, knowledge management. Every company has gurus. Okay? You've got your top salespeople. What makes your top salespeople different than the rest? And in most cases, it's the top salespeople know which prospects are worth pursuing and which ones aren't. And the more junior salespeople chase their tails, pursuing any lead that will talk to them.

[00:29:22] So how do you take what the top salespeople know and share it with the other salespeople? The answer is you just interview the top salespeople. And this is something that I wrote one of my Substack newsletters on, which is you interview the top salespeople. What do the top salespeople love to do? Talk, right?

[00:29:43] So you interview them for an hour, two hours, three hours. You turn it into a transcript. You take that transcript, you put it into gen AI, and you create training materials. And by doing that, you level up your entire sales organization based on the [00:30:00] wisdom of the top salespeople. And so utilizing it in ways like, so what do you do then?

[00:30:05] That means that you probably have a lower lead rate, but a higher close rate will be the metrics that you will see with it by federating the knowledge of the people who really are successful at what you do. And then there's the whole how do you figure out workflows that are going to change customer experience?

[00:30:30] And one of the top insurance companies in the world, so they still get faxed insurance applications handwritten. 

[00:30:38] Justin Grammens: Yeah. No, I 

[00:30:39] Mark Price: know. And Justin, they don't get a few. They get thousands. They had basically a warehouse of people keying in these applications. By using computer vision and natural language processing, they were able to take those and code them in a fraction of the time [00:31:00] So all of a sudden, they went from two to three weeks for an insurance response and a quote to two to three days.

[00:31:09] They reduced the cost, but they impacted the customer experience so much that their customer satisfaction scores went through the roof. 

[00:31:18] Justin Grammens: Yeah. Those are great stories because ultimately, at the end of the day, yes, you're trying to improve not only efficiency within your organization, but ultimately customers.

[00:31:27] They're gonna enjoy working with your business because of this automation, and it's just so much easier to work through with that. Yeah, I absolutely see that. What's really cool is computer vision's been around for a long time. A lot of these large language models have been around for quite some time, but we're really seeing this combination, sort of this influx here of, of these systems that now are becoming very intelligent.

[00:31:48] They can start making these decisions. This kinda ties back to, as you were talking here, I was thinking about making sure that it makes the right decisions, right? Yes. You talk about making sure that there's guide rails and [00:32:00] guidelines on what it should do. How, how do you sort of talk, uh, organizations through that a little bit?

[00:32:04] Mark Price: That can be one of the biggest roadblocks to getting AI implemented and expanded through an organization. And there's sort of two ways that I've seen to do it. There probably are more. Building AI agents who are validator agents. So if you are concerned about hallucinations, you can literally build an anti-hallucination bot and train it and have it go look at all your content to make sure there isn't any hallucinations in it.

[00:32:36] So this idea of building as we're moving here into agent orchestration, and I don't see a lot of people talking about this, making sure that there is a guardrail bot or agent built into your process takes one level of the concern, and the second level of the concern is what you talked about, which is human in the loop.

[00:32:56] So what I am trying to do with organizations is get them [00:33:00] so that they are not scared of legal and regulatory, and reframe the conversation Instead of saying, "Here's what you can't do," which is a list a thousand miles long, changing it to, "Here's what you can do as long as you meet these criteria. And by the way, if you meet this set of criteria, we can have a thirty-minute meeting and it-- and you're good to go, or even faster."

[00:33:28] The Bayer Company has a new CEO, and he took out five thousand middle managers, and he didn't lay off one. He basically gave them the opportunity to become producers, to get involved on product teams, to get involved on trying to solve hard problems in the organization, which for most of them, by the way, is a lot more fun than being what they might call a paper pusher.

[00:33:51] Which, by the way, is not what a project manager is. I'm understating that for rhetorical purposes. He found out that sometimes there were eight or nine [00:34:00] levels of approval to get something going. To be able to show new products to a consumer, there were eight or nine levels of approvals. That's crazy. He said, "How can we innovate if we need that?"

[00:34:11] So with the set of guidelines, the set is if you meet all of these guidelines, fill out the form, send it in, go. Just go to the next level. You're not selling the product. You're gonna show mock-ups to some customers to see if you get any feedback. Just go. Don't wait around for someone to tell you no. Get to that point where you can get that feedback and find out it's meaningful.

[00:34:35] And then what we're finding is because of the ability of AI to analyze AI and identify risks associated with it, you need fewer people in the room to get decisions made. So Jeff Bezos used to say that there was the two pizza rule. The two pizza rule was there should never be more than the number of people in the room for a meeting who could eat [00:35:00] two pizzas.

[00:35:01] It's now the two slice rule, Justin Two people. You only need two people in the room to get things moving. And if you've had AI clearly delineate what the issues are associated with something, so you're gonna have a meeting and you're gonna address those issues with everybody knew in advance, first off, it's much more collegial.

[00:35:22] It doesn't seem like the people in regulatory and legal are the "no" people. They're in the work with you to reframe what you're doing so you can do it people, which is fundamentally a paradigm shift. These aren't people who keep you from doing things. They're people who keep you from getting in trouble while you do it.

[00:35:41] And so that kind of framing is part of that culture of "yes, if" instead of "no, but". 

[00:35:48] Justin Grammens: Gotcha. And again, everyone, kinda back to what you were saying before, everyone all the way from the CEO down to the frontline worker needs to understand this technology and needs to understand how it plays in their daily life because that [00:36:00] is the commonality that everyone's going to be leveraging as they're getting together through this process and through these workflows that they're, they're gonna be collectively working on.

[00:36:08] You talk about the two pizza and then now, like, the two slice. Do you fundamentally believe, or as you're talking with organizations, that you just won't need as big of an organization anymore going forward? Uh, interesting you mentioned Bayer not having to lay anyone off, but I just-- I see it's inevitable that companies are like, "There's no reason we're gonna need as many people."

[00:36:25] Mark Price: What I see is a shifting and a shuffling of different kinds of roles, and there will be inevitably, organizations will get smaller. And the fact that you can dramatically accelerate product development, that you can target micro segments of customers with unique products and offerings, that you can iterate with customers literally with your laptop in front of you.

[00:36:53] You don't need to go anywhere. The-- You can say, "What do you think about this?" And the customer could say, it's not even a focus group, individual interviews, [00:37:00] "That part works for me, but this part, that doesn't make any sense. This is what I'd wanna see." "Oh, give me a second. Okay, how does that look?" "Oh, that's a little closer, but it doesn't do this."

[00:37:10] "Okay. How does that look?" And so you're doing this iteration gives you the ability to scale and personalize in ways that I think will lead to more people in roles that impact the organization. The places I don't see that as much is in service organizations. So whether that is marketing services, consulting firms, accounting Legal.

[00:37:40] You remember the job formerly known as paralegals? 

[00:37:42] Justin Grammens: Not happening. Yeah. 

[00:37:44] Mark Price: Not anymore. And so when you look at technology, and you know this as well as I do, very often it creates as many jobs as it takes out. The challenge is they're not the same skill set. 

[00:37:56] Justin Grammens: Where my head is most of the time these days as I'm running my [00:38:00] software consulting business is all around software engineering.

[00:38:02] Yes. And the role of someone that's just gonna sit there and write algorithms and code, that role is no longer valuable in the marketplace. Not saying that humans don't enjoy that, though. That's the other thing is it's the other side of it. I actually really enjoy what I've been doing for the past 20 years, and now you're taking that away from me and you're automating it.

[00:38:20] But I, I do think that the role is gonna change, what it means to be a paralegal is going to change, and that you're right, the skills that that person had is no longer valuable, but they should be now thinking about what does a legal career look like. And as you were talking, I was kinda wanting to back up because you mentioned some at the beginning about being an entrepreneur.

[00:38:39] Do you see this technology now opening people up to being their own solopreneur in just about anything they want to do? I'm seeing some huge opportunities as I see a, a need in the market that now I don't need a whole team or a whole bunch of people to build something or to start a business. What are your thoughts on that, I guess?

[00:38:57] Mark Price: I couldn't agree with you more. I've [00:39:00] actually been working with the Schulze School of Entrepreneurship at the University of St. Thomas in the Opus College of Business. I wrote a piece on how to go from concept to launch in 30 days, and the ability-- The single largest, by the way, period of time in that 30 days is trying to find the customers and prospects that you wanna do that rapid iteration with.

[00:39:24] Just finding them is something that's not as easy. But the ability to create mock-ups and even operational full functional capabilities over a weekend is a game changer for people who have ideas that they want to see if they can bring them to life. And the amount of joy you have from creation That comes with this is amazing.

[00:39:49] It has never been easier to start a business or to take an existing business and a traditional mainstream business. I was [00:40:00] listening to something on a podcast this week already about the trades and how a plumber can use AI to automate all the scheduling and the billing and the booking that goes along with what they do and get huge improvements in not just productivity, but they hate that stuff.

[00:40:22] And so they can make a difference in people's lives and get out of the pieces that they really didn't enjoy doing. But the truth is, as you look at the number of places that there are needs and the ability to do it to micro segments, that's the place where it really expands. Small groups, thousands, not millions of people who desperately need a particular type of function that you can offer to them.

[00:40:49] And you basically scale is virtual now, right? It was a bit with cloud. Now it's really virtual with AI [00:41:00] And I think that is so exciting. 

[00:41:01] Justin Grammens: Yeah. It's a very, very fun time to be in this because, yeah, it feels like everyone now is gonna have these superpowers, and they're no longer beholden to one particular job, one particular role.

[00:41:12] Feels as long as you remain curious and you can explore and try different things, really the world's completely open. And I'll make sure that we s- share links to your Substack and any of these other articles. And I-- Also, just a side note, I came across one of your LinkedIn posts where you talked about dictating.

[00:41:29] Basically, you said open up Word, dictate out what you want the structure of-- And I think you were talking about actually just writing a blog post or whatever you're gonna write, a memo, a report, whatever it is. Get those ideas out as your initial creative work, and then use AI to sort of help you refine that.

[00:41:47] And I think, I guess what I loved about that, and correct me if I'm wrong, maybe I misunderstood some of the stuff, but again, it's the idea that you're using AI as an enhancer to what you do. You're not just basically going in there and saying, "Write this thing for me." 

[00:41:59] Mark Price: You're [00:42:00] exactly right. People try to structure content while they're creating the content.

[00:42:07] Okay? That's cognitive load. That's two things at the same time. So what I do is I routinely open a Word document, and I just talk at it for fifteen or twenty minutes, thirty minutes about a subject, and it doesn't matter if, if fifteen minutes in I figure out something that ought to be up at the top in the introduction.

[00:42:27] I don't sweat it. My goal is to get everything out of my head onto the page. And then I go to AI and say, "Take this and structure it for me, and then let me know afterwards." And then it literally goes down the page. It's got all the clean sections on it. And then I say, "What are the key places where I may not have completely fleshed out my argument?"

[00:42:52] What questions are they gonna have? And AI gives me those questions, and I dictate more stuff, and I give it back to it. [00:43:00] So I am the content producer, but I find the structuring of it to be lower value work. And it's so much easier to generate the content when you don't care if it's the beginning, middle, or end.

[00:43:12] Your goal is to get your idea fully formed out there and the ability to just iterate on it as much as you want without worrying about where the second paragraph is. Are you gonna do like a call-out box on it? You know, what's gonna be in the top three points? You may have four ideas for the hook at the beginning and for the closing at the end.

[00:43:35] Just put them all in and then see how you evolve it over time. It allows you to purely create, which in my mind is so much less work than trying to structure at the same time. I find it takes away all the barriers to content. You know, the whole writer's block thing? Just start talking. 

[00:43:55] Justin Grammens: I love it. A hundred percent on that.

[00:43:56] I think voice is something that people haven't really fully explored [00:44:00] yet. And even from, like you said, as you're building something, you're creating something new, you're creating a new article, you're creating a report, whatever, I do the exact same thing with software. I wanna build a website to do X or a system to do Y.

[00:44:12] I will literally hit the record button and then just talk at it. And at the end of the day, there's this thing called spec-driven development, but you basically start building up these specifications on it, and those are the source of truth. And then large language models are very good at taking that source of truth and then generating code from that.

[00:44:27] But I have found that, yes, your fingers can only go so fast, a hundred percent like you were saying, and it's just more natural really for you just to get ideas out and just talk and adjust it over time. And as you speak, you're gonna formulate your thoughts, like you said, and then help AI where the best thing is, which is basically, in my case, as I was saying, writing code at the end of the day, it's really good at that.

[00:44:48] But it needs to be given the right thing, needs to be given the right context on what to work on. So I love that application. Fits right in with our whole applied AI theme. I wanted to share that one. I enjoyed reading that. One quick thing [00:45:00] too that I wanna talk about was I'm hearing a lot that people are having a tough time finding jobs, right?

[00:45:05] And especially people coming out of school. Now, I'm not sure if you're seeing this or not, but I'm just-- I'm talking with other people that have kids of college age, and they're having a tough time finding jobs. And it's interesting because I was a part of the internet, you know, build- building websites, what have you, part of the mobile development craze that happened, part of cloud, part of all of this stuff, and I always found it super interesting in that you could take somebody who was an expert of forty years in X, Y, and Z technology and put them next to someone else who was just coming out of school, and they were kinda both at the same starting point because we're all learning this stuff at the same time.

[00:45:41] So I feel like someone coming out of school should have just as much chance at an organization to have the job than somebody who's been there for twenty, thirty years, for example. But it feels like we're not seeing that in the job market, and maybe I'm just looking at the wrong data or whatever, but I-- curious to get your thoughts on that, of what you are seeing and [00:46:00] what you're hearing for people trying to join an organization as a starting point.

[00:46:04] Mark Price: Well, I'll tell you that it is absolutely clear that there is an issue with entry-level jobs all across the country. Now, we're really blessed at St. Thomas that we have a crazy alumni network who love to help people getting out. We still have the problem. We just don't have it, I think, as much as a lot of other places.

[00:46:24] But one of the challenges is how to combine AI knowledge with domain expertise because AI knowledge without the domain expertise takes a long time to come up to speed, right? And in organizations where they're looking to achieve more with less or they're looking to accelerate, not having the domain knowledge is a challenge.

[00:46:52] One of the things we've got that's great at St. Thomas is internships, right? Internships are the way to get employed. [00:47:00] The other thing is I have been working with St. Thomas on the idea of getting people who don't have jobs to go work for nonprofits. Nonprofits have a tremendous need for talent, and they can't pay for-profit rates for that talent, but they have the same needs, if not more.

[00:47:19] Their technology is older in many cases. They're doing more things manually, and yet they have an audience of people they need to serve, another audience of people who would donate, different kinds of audiences. And if you come in and you become the marketing director, let's say a digital marketing manager of a, you know, a nonprofit who has 12 people in it, what do you have on your resume?

[00:47:48] "I'm a digital marketing manager. I have experience. We increased traffic by 38%, we increased donations by [00:48:00] 8%, and we increased the amount per donation by 15%." So what do you have? Real results from a real company that enables you to be even more And to have a greater chance of getting through, you know, the networking.

[00:48:17] Justin Grammens: That's great. Yeah, we've hired probably at least six students through internships from the University of St. Thomas over the past ten years in my business. And then even Applied AI. We're a nonprofit, we're a 501[c][3], and actually last summer, yeah, we had someone work with us, and he actually was graduating from high school, going into college, and he ended up going to college out west.

[00:48:38] But in that summer, he came in and did some amazing work with us, and again, leveraging AI to help us do a number of things on the social media front. And some of the stuff is irrelevant of technology. It's really, at the end of the day, I've been hiring people for the past twenty years since I've been out of college and starting businesses at various layers, and I always tell people that are in school, "Don't just do the grades.

[00:48:59] Don't [00:49:00] just do the homework. You gotta do more." Because if you're coming out of school and everyone else is coming out of school with basically, yes, it looks nice that you have As on everything, I'm actually gonna view that as table stakes. I, I'm more interested in what have you done outside of that. And so it re- you really need to sort of position yourself as like a brand, really.

[00:49:17] Like, "This is who I am, and these are the things that I have done." And it's very-- It's the most important part. 

[00:49:23] Mark Price: Internships, like you said, are great because even if the company can't hire you, if they love you, they'll put you into their network everywhere to help you get a job. And it starts to build a credible network for people just coming out of school where they don't really have a lot of business contacts necessarily.

[00:49:43] The more internships you can have, the more different kinds of internships, the more-- the deeper you can go into companies, the more you can make a difference. You get amazing recommendations, and they will reference you everywhere. 

[00:49:57] Justin Grammens: Yeah, and I would say our meetups too. I [00:50:00] always encourage people- Yes ... to go out to these networking events.

[00:50:02] I count at least five people that I know that have personally come up to me and said, "Because of Applied AI, I got my next job." It was just because they came to an event that we had and met somebody and turned into something that they needed. Yeah, huge. It's that whole personal side of it, which is I keep going back to.

[00:50:18] Like, AI can automate a lot of this stuff that we don't wanna do, but it's still the human connection Mark, how do people, uh, get ahold of you, I guess? What's a good way? 

[00:50:29] Mark Price: Well, my email would be price4635@stthomas.edu. You can reach me through LinkedIn, posting things every week, usually in relation to something that I'm writing or thinking about.

[00:50:45] You can also get access to me if you want to explore the executive education. My exec ed classes are often a good way if you need to move ahead in your, your ChatGPT or your Copilot [00:51:00] and you need to do it quickly. A three-day intensive gets you way down the pike versus where you would've been when you start.

[00:51:08] 'Cause my goal is, because I call it absurdly practical, at the end of the first day, that night, they should be able to do something that they couldn't do in the morning, and I make sure that's true all three days. And then I tell 'em, "Tell everyone." 

[00:51:23] Justin Grammens: Yeah. Yeah. I call that the aha moment, right? It's just like- Yes

[00:51:27] you just, you never thought that a computer would react this way, that it actually did something. So that's just so amazing. You're like, "Wow, that-- now my eyes are open." This has been fabulous, Mark. Was there anything else you wanted to sort of touch on at all? I guess I've been starting to do this with people that are on the podcast that I know certain things that we talked about, but I always wanna open it up and say, was there maybe one other aspect, something I didn't cover?

[00:51:48] Mark Price: Two things we haven't talked about. One is people ask me often when their kids are going to college, what they should major in. So parents are scared, right? They're scared of their kids coming out and [00:52:00] jobs not being available when they're putting in somewhere between thirty and sixty thousand dollars a year or more.

[00:52:06] It's one of the largest purchases in anyone's life, going to college. And what I tell 'em is that what we're striving to do, what I believe strongly is what you need is critical thinking and critical reading and critical writing ability. And you can get that in history, you can get it in literature, you can get it in psychology, you can get it in-- philosophy is incredible for the precision of the thinking that people come out with.

[00:52:38] Do that and take every AI thing you possibly can. Because if you've got that thinking, that kind of critical, how do you tear things apart? How can you look at something that's AI generated and find mistakes in it, find places where the bias may be wrong? And I told my students this week, I said, "Hey, look, [00:53:00] I've always done it because you produce something from AI, and you're gonna have to show it to your management.

[00:53:05] But I realize now you're gonna be receiving from a lot of other people in your organization AI generated content. So it's not just what you do. You gotta look at what other people are putting on your desk, and you've gotta put that critical thinking lens on to tear it apart." And I created a, an in-class lesson this semester, which I'm gonna continue to iterate on, where I give different teams AI generated work, and they have to lear- they have to tear it apart and show me everything that's wrong with it.

[00:53:36] That's one of the critical things. It's critical thinking. Get some business skills. I think the business education is really important. Ethics is always really important on it as well, particularly with our focus on the common good at St. Thomas. But overall, the ability to critically tear something apart Turns out to be an [00:54:00] unbelievable benefit for the rest of your life.

[00:54:03] So if you do the critical thinking, you get internships, you teach yourself as much AI as you possibly can, and you're gonna be in the best possible shape you can be going forward. 

[00:54:14] Justin Grammens: Yeah, I mean, nothing's gonna be perfect. E-every time you come out of school, there's always that sort of on-ramp, and sometimes it's a lucky break 'cause somebody knows somebody, gets something good.

[00:54:24] Sometimes it's an internship. Sometimes it's someone you met in school. Sometimes it's just-- Part of school, I think, is actually working in teams, building communication, really just good communication skills, whether it be typing or even verbal. That's been very-- So all those things, I think, are all levers that I think you can turn, and you wanna try and get all of them up to probably as close to a hundred percent as possible to give you the best possible chance.

[00:54:46] Mark Price: Yes, I completely agree, and I tell them, "Don't lose heart, okay? Don't lose heart, and, and don't, don't go into accounting unless you love accounting." Yeah. "Don't go into it for security 'cause it's not gonna be security [00:55:00] anymore. If you love it, you should do it. If you don't love it, don't choose it." Now, the accounting professors are gonna come after me afterwards.

[00:55:08] But that's another s-- You can't save everybody. 

[00:55:10] Justin Grammens: Good. I know. I love that we touched on that sorta education perspective on it. I was just on a podcast just a couple days ago that really w-was focused, is focused on people in the K twelve space and parents. That's the main thing that they kinda were asking me.

[00:55:25] I was wearing multiple hats as I was being interviewed on this podcast. One was as a business owner, how do I hire people? The other one was basically, you know, the work I've been doing in AI here and running this organization. But the third most important one that they really wanted to hear about was, yeah, as a parent and even as a teacher, like, how do you bring it into the classroom, and how do you prepare your kids as best as possible?

[00:55:45] And the major thing that most teachers are really worried about, obviously, and that's-- this has been the talk of the town for the past couple years, is it's just cheating. And I love how you just flip this around, Mark. You basically said, "Let's u--" 'Cause k- the kids are gonna use AI regardless [00:56:00] of what it is.

[00:56:00] And I, I say kids, I mean, I'm teaching people that are thirty-five, forty years old or more. But students, let me say students, are gonna use it regardless. And so your techniques that you're talking about is really picking apart the generative AI that happened and then essentially getting better on top of it, right?

[00:56:17] Mark Price: Think so. And then there's a whole piece-- I spent the whole summer working on AI-resistant assessments. So how do you actually-- Assuming that everyone's got gen AI ChatGPT at home, okay, what I do in my classes is I actually assign-- First thing is I say, "You can use it anytime you want as long as you cite it.

[00:56:37] It's another source." And I say, "Don't hide it." Said, "If you hide it, you're gonna get in trouble," 'cause I just took the penalty away. You can use it, but give me the date, the time, the prompt you used, and the tool you used. But the other piece is I send them home to do research, and then they have to come into class and take what they learned and [00:57:00] combine it.

[00:57:00] So I might have six students on a team. I will give each of them one-sixth of the assignment to go home and research, and I'm gonna assume they're doing it with ChatGPT or any of the tools. I'm gonna tell them to. But they better read it, because they're gonna come in, they have one hour to put together a presentation and a point of view, and then they present it.

[00:57:20] And Justin, then I change it, and I send them back out with a half hour to redo it. 

[00:57:25] Justin Grammens: Ah. 

[00:57:26] Mark Price: So what am I teaching them? Teamwork, collaboration, leveraging AI for what AI is good for, right? And the ability to think on your feet and synthesize data. So you start to increase the relationship. I wanna do it with debates also.

[00:57:42] You know, go home and research. Go home and research it, but then you're gonna have to figure out how to deliver it in a compelling argument, and I think that's another really valuable skill for business going forward. 

[00:57:54] Justin Grammens: Yes, and 'cause this is... these are all skills that business leaders are gonna be looking for, sure.

[00:57:58] So [00:58:00] all very marketable stuff. Well, Mark, thank you so much for the time today. This was great. We had a nice talk here. My pleasure. Time flew by super fast, but I appreciate- Mm-hmm ... all the time and all your perspective. And thank you for all the good work that you're doing, and wish you the best, and I know I'll see you at future Applied AI events.

[00:58:15] Mark Price: You can count on it, Justin. Well, thank you for the opportunity. 

[00:58:19] AI Announcer: You've listened to another episode of The Conversations on Applied AI podcast. We hope you are eager to learn more about applying artificial intelligence and deep learning within your organization. You can visit us at appliedai.mn to keep up to date on our events and connect with our amazing community.

[00:58:38] Please don't hesitate to reach out to justin@appliedai.mn if you are interested in participating in a future episode. Thank you for listening.