AI For All, Future of Work, Tonya J. Long

In this episode, they dive deep into the transformative power of AI, how it’s reshaping industries, and what leaders can do to harness its potential for positive change. Learn why no one should have to beg to work in the future of work, the importance of creating FOMO in business strategy, and how AI empowers SMBs and startups to compete with industry giants and be successful.

Key Discussion Points

• Tonya Long’s Origin Story: Tonya shares her journey from growing up on a farm in Tennessee to becoming a leader in AI and technology. Her experience underscores the importance of hard work, understanding your audience, and recognizing the value of purpose in work.

• Journey into AI and ChatGPT: Tonya discusses how she was captivated by AI, particularly generative AI, and how ChatGPT revolutionized her approach to creativity and collaboration. She emphasizes the power of AI to democratize technology and foster creativity.

• The Wizard of Oz Analogy for AI Leadership: Tonya uses The Wizard of Oz as a metaphor to explain the complexities of AI leadership. She highlights how diverse skill sets can be unified to achieve remarkable outcomes, much like Dorothy's team in the story.

• AI Investments and Enterprise Adoption: The discussion includes insights into the rapid pace of AI investment, particularly in generative AI, and the cautious approach enterprises are taking towards large-scale adoption.

• Leveraging AI for SMBs and Startups: Tonya explains how AI is leveling the playing field for SMBs and startups by providing access to advanced infrastructure and enabling automation and efficiency at a scale previously inaccessible to smaller companies.

• Implementing AI on an Ecosystem-Wide Level: The conversation delves into the importance of integrating AI across an entire organization, rather than in isolated projects, to fully realize its potential.

• Creating FOMO (Fear of Missing Out): Tonya shares her strategy of creating FOMO among potential clients by highlighting what their peers are already doing with AI, motivating them to take action to avoid being left behind.

Maxims

"No one should ever have to beg to work." — Tonya emphasizes the importance of creating value and purpose in every job.

"Ethics is who you are and being innovative is how you do." — A reminder that innovation and ethical leadership go hand in hand.

“Market perceptions, market share, and regulatory awareness of what’s going on in industry is key to navigating how the advancement of technologies such as AI can impact your company’s valuation.”

Connect with Tonya

+ LinkedIn

+ Website

+ Book, AI and The New Oz

Resources Mentioned

Agentic AI

AI for Social Progress

Digital Deepak Chopra

Greenlee’s Bakery

Massed Compute

McMurray Stern Automation

ChatGPT, Generative AI

Claude, Generative AI

LLMs (Large Language Models)

Why You Should Listen

This episode offers a unique blend of visionary insights and practical advice on how AI is reshaping industries. Whether you're an entrepreneur, business leader, or simply curious about the future of work, you’ll find actionable strategies and inspiring stories that will help you navigate the AI landscape with confidence. Plus, discover how industry leaders are already leveraging AI to gain a competitive edge—and why you can't afford to miss out!

• Transcript

  Introduction to NextGen Industrialists Podcast

  Hello. Hello. Hello. And welcome to another episode of NextGen Industrialists Podcast: Rebuilding America's Dynamism. I'm your host, Belinda Ephraim, Founder and CEO of Katalyst Point dot com, a strategic advisory firm where we represent founder led manufacturing, distribution, supply chain, and industry four point zero technology businesses, providing mergers and acquisitions and capital financing advice.

  Today, we're diving into a topic that's reshaping the future of industry as we know it, artificial intelligence.

  Today, my guest is Tonya Long, the brilliant CEO of Quantum Crew Advisory with an impressive track record in AI leadership and digital transformation.

  Tonya is at the forefront of helping businesses harness the power of AI to drive innovation and value creation.

  In this episode, we are going to explore how AI, including generative AI and large language models, are leveling the playing field for start ups and SMBs, enabling them to enhance your workforce potential, improve their competitive edge, and navigate the challenges of digital transformation.

  We'll also delve into the ethical considerations and strategic frameworks that can help you maximize enterprise value As you integrate AI into your business, whether you're looking to stay ahead in the AI race or simply curious about the future of work, this episode is packed with insights you wouldn't want to miss.

  Chapter

  Tonya Long's Origin Story and Values

  Before we begin, Tonya, I want to thank you so much for spending quality time with me here today. This is a real privilege for me to invite people I admire into conversation.

  When I do these things, I always like in my interviews to the indigenous oral traditions, and that is telling our stories in communal experience.

  I am going to start with that question.

  But before I do, I want you to know that you are in absolute control.

  You can choose to not answer the question or answer the question any way you want to. So, Tonya, welcome. What is your story?

  Well, you've played me up, but I'm gonna start with my my origin story, which is, it actually, I fought to get out of the farm on Tennessee, but but it informs everything about who I am. I grew up on a tobacco farm in Tennessee, and so much of what I'm about now and who I've become started there because it was on the farm that I learned what mattered and how to be.

  It didn't matter that I was a girl or that I was young.

  I still did every job on the farm.

  I hauled tobacco. I cut hay, and I sewed, and I and I, cooked the meals with the women. So I did all the jobs, which, of course, you can see how that would translate into a corporate career.

  It didn't matter that I was a girl or that I was younger or smaller at the time.

  I rolled up my sleeves and worked right alongside the men.

  On the farm, I also learned very quickly to know your audience.

  Sometimes that audience was a five hundred pound sow, and most of you on this call probably don't know and farm animals.

  Pigs are very aggressive, and I was terrified of of my granddaddy's sow. But that was my job to feed her. And I learned that when you when you look an animal or a person in the eye, you know your audience and you know their motives, whether it was that sow or or my granddaddy's Clydesdale or or my my crazy uncles who just wanted to pester me. Knowing your audience, understanding what they're trying to do, can help you move through almost any situation.

  I also learned on a farm that people are not all the same.

  And and that's by choice, and it makes them interesting and beautiful.

  And with that, I also learned on the farm that people all deserve to have purpose.

  And purpose is often tied to work. Whether that work is paid or not, everyone, deserves to have value in what they do.

  I didn't understand it then, but I do now.

  I have words for it, that no one should ever have to beg to work.

  And so that is what I live for and what I try to create with the value that I drive in society.

  So because my life and my career took a turn through technology, how I tried to achieve that with my time on the farm and then my my work through leadership, through international work, is to demystify technology.

  Chapter

  Tonya's Journey into AI and ChatGPT

  Fifteen years ago, now - there's fear around technology.

  So I've led big teams, but that's not what's in the technology piece to me is not what's important.

  It's to get people to be curious, to get people to be unafraid, to be willing to try to let down their egos.

  And so as we move forward with AI, I think that's more important than ever to get people to be willing to try new things and and to be willing to accept new ways of doing things. And so my work is evolving in that direction away from the technical, more toward helping people understand how we can live differently and still better through collaboration.

  And so that's my story that as we move toward a world where no one should have to beg to work, we're going to need to be willing to change.

  But change is going to involve collaboration, and that should lead for all of us to a better quality of life.

  I really like, your approach to this, you know, the mindfulness, the consciousness around this. Especially prior to AI, you know, it would have sounded very, you know, woo woo hoo, I guess, you know, in in in that sense. And a lot of leaders struggle with that. You know? How can I be an effective leader, from a numbers perspective, but then also how can I lead mindfully?

  And when I think about AI now, I think that message is actually even more relevant alongside the technology. So how did you get into AI from the farm to corporate America, and now you are pretty much a wealth of knowledge and an expert in this space?

  I've been doing change management and corporate tech for more than twenty years for more than twenty years. But AI specifically, I'm I'm a writer. I've been doing thought leadership pieces for a long time. I I write to express myself.

  So so when when ChatGPT three five came out and people were talking about it, I said, that sounds like an application I'm interested in. Oh, little did I know how much it would change my life. I just thought it was a the newest the newest toy to download, and it turned my life on its head because it opened up and enabled more creativity than I'd ever experienced and more collaboration.

  I would say that January after the release, it it was released, right after Thanksgiving.

  But that spring, that January to March or April, there was a group of us all in our fifties, all up until midnight, texting each other, sharing what we'd figured out, working forty and fifty hours late at night, doing these projects just for us, back up at six AM, checking in, and then OpenAI would come through with a feature two weeks later that would automate what we'd spent forty hours working on, and we'd be so upset. But then with with wisdom, we knew we'd learned so much in the process of of stringing together these things. I mean, I was I was doing things with Python. I was I don't write code anymore. I haven't written code since I was in college.

  But but we were all doing things that were so creative. And then it was collaborative because we had this network of people that were all, like, jumping on to using this this this tool for things well beyond the things we had intended. So that's how I got started with this newest generative AI. Of course, AI, most of us realize, has been around since the forties or even before, depending on how far you go back with neural networks. But, but my real my my to be fair, my real true true true hands on journey, started with generative AI with plain old ChatGPT.

  And, from there, it just it just it just has not stopped. It took over my life.

  Built a little primer for my friends. I was, like, sending it out to all my friends and family on, you know, on a Google Drive. Right. You gotta do this, and everybody was creating keto diet plans and and travel itineraries for their weekend trips. And and, it just became a thing, and and I think we'll talk further about how I used it. But, but but, wow, it really took over. It was addictive.

  It was addictive because of its simplicity.

  Yeah.

  I think that's is what is ingenious about at least ChatGPT and the user experience.

  Now we have Gemini.

  We have Copilot. We have Meta. Okay. But prior to the latter three coming on board, ChatGPT really revolutionized and made AI accessible to everyone. Right?

  And you wrote your book I did.

  AI and the new Oz, leadership's journey to the future of work, which was really intriguing, during the time that I read it. And it really I love how you drew a parallel, between AI, artificial intelligence, and using the Wizard of Oz sort of as the cultural reference to frame the context of embracing AI.

  Chapter

  Using The Wizard of Oz as an Analogy for AI Leadership

  How do you see what were you thinking in terms of the analogy to help leaders better understand and navigate the AI landscape using this cultural reference?

  So I was having so much trouble getting my peer group, if you will, to buy in. Okay? Mhmm. Socially, I'd be out like, I I I have an Airstream, and I'd be out on weekend junkets with buddies. And they'd be like, oh, you know, you know, you're ruining my campfire.

  A friend of mine who's an architect, he might be on this call. He said, AI, it scares me to death. And he was very sincere.

  And and I realized if these highly technical, highly educated, highly evolved senior executive leader types were unwilling and hesitant to move forward with AI. I realize I'm on the front end of the change curve, typically.

  But if they were unwilling to do unwilling, I'll use that word, unwilling to do it, then what was going to happen to less technical leaders? You see, I've I've lived in this privileged bubble where I've always led technical people, so I so they're all ready to go. Right.

  What's gonna happen to the other people?

  And that that's what started to consume my thoughts was the leadership of the rest of the world that didn't live in the in the tech framework.

  And so the book idea really happened almost overnight. It was not like this long drawn out thing I always I never intended to write a book, but it happened almost overnight. And I was I've never shown it. I I was in my jewelry box, and these little my mama, she's gone, but my mama had given this to me, like, in grad school. I don't know why. It was not a thing for us.

  But I was in my jewelry box, and and I saw these slippers, and I thought thought, you know, it reminds me Dorothy reminds me of what I see right now that is so fantastic about AI because Dorothy took all these different skill sets amongst her team. They were all so so dis disparate. Right? They were all different.

  They all they all contributed unexpected things, and she was able to pull them together to build something beautiful, to get to a better future, to get to to get to Oz, and then ultimately for her to get back home. Right. I ran straight from my bedroom into this room, sat at the computer, and said, ChatGPT, what if?! And I was here for hours working on, you know, the table of contents, and it just all started to flow. And the book the book literally happened because, ChatGPT was like, well, I hope the table of contents might be, and then we played and we started doing chapter development.

  And, but the reason was all the qualities that are necessary to lead are all the qualities present in the major character arcs that you see in the wizard of Oz.

  And then those chapters gave me milestones, if you will, to land modern day stories that people could relate to to say, I can do this.

  And then my the book's a year old now, but my friends at the time were like, what what they enjoyed about it. My tech friends were like, you wove in all the stories of the first six months of of AI's big launch. So it was kinda like reading a modern day, and then Sam said, and then, well, then Sam Altman did this. And then it was it was all the modern day pieces woven in with it. It was kind of a fun thing to write. And, of course, I wrote it with ChatGPT.

  So that was like having a husband. It was it was a debate every time I spoke, and then he spoke.

  And Oh my god.

  Oh no. I really I really enjoyed reading it because it was relatable. And, you know, the Wizard of Oz, I it's such a universal story.

  And the characters, you know, you see them develop their skills over time, especially with Dorothy's leadership and her ability to be able to embrace both their strengths and their weaknesses. And so you're going to the story of AI, but then you actually start to give data and tactical insights Yeah. Into how, what you term non AI leaders Mhmm. Can actually do to work with your teams and implement these technologies.

  Chapter

  Insights into AI Landscape and Investments

  But before we go into that, so you started writing the book because ChatGPT launched November thirtieth twenty twenty two, correct?

  If I recall.

  Yes. You do. That's right.

  And that's about we're almost two years into that trajectory.

  Now I just want to give a reference because unlike a lot of technologies that have come out historically Mhmm.

  AI is very unique in the sense that most technologies, as they advance, may be in incremental beats and pieces, usually two year time frames, especially since the Internet became the bedrock of technology of information technology.

  But with AI, I feel like it's almost every two months.

  There is this acceleration Oh my goodness.

  Going on. When I was writing this book Right.

  We were okay. Fact.

  Six hundred products a week were being released.

  Okay? When you said products, what do you mean by that?

  Six hundred applications a week were coming out onto the market, flooding the market with, and I'm gonna be disrespectful when I say this. I don't mean to be harsh. But they were they were largely just, LLM based wrappers, you know, front ends. But still, they were they were products that people were putting a front end to pull data through and people were using and pay and and and and in some instances, paying for, products to do things. There were six hundred releases a week happening to to do everything from image creation to to, copywriting work to, we were starting to do more to do more things with numbers.

  Yeah. In the beginning, it was crazy. And I think that was some of the reluctance for people to engage because it was so overwhelming.

  Yeah. But it's still overwhelming.

  It it is. And I heard you. It is still overwhelming.

  Because it's accelerating, but I just wanna because you mentioned the number of apps that came into existence or were enhanced with AI from a user interface perspective. But then in your book here, you talk about the funding, the behind this innovation. And you mentioned that VC's increased their positions in generative AI, twelve point seven billion in the first five months of twenty twenty three.

  Mhmm.

  And then I was curious, so I looked up okay. So we have VCs, we have private equity, and we have strategic buyers.

  And when I look at private equity, the first investments, the first year, so from November to October is how I was looking at it.

  PE and strategic buyers equally spent four point two billion in the first year in terms of investments.

  Mhmm. But get this. Since October of last year, year to date, PE has a hundred percent increase in investments. So now, I guess, they're slightly behind VC.s Yep. From a total basis.

  But what's interesting with strategic buyers is that they actually just within this last year, they've invested almost forty billion, and that was from four point two billion Mhmm. The first year. Yeah. So in just ten months, that percentage has increased over eight hundred and twenty nine plus percent and growing. Yep.

  So I just I'm curious to know where where your thoughts are because this is moving fast.

  And we talk about the future of work and the idea that no one should be economically disadvantaged in being able to put food food on the tables, but this is impacting people already.

  What are your thoughts?

  Oh, you've mixed several things. What am I gonna talk about?

  I know.

  It's okay. We'll we'll we'll get there.

  So let's start with investments. What are your thoughts on investments?

  Everybody wants to hit the next dozen unicorns because there's not gonna be just one.

  And and in my assessment, and I'm right because we're all saying it, enterprise has not started using AI yet for enterprise business. Okay?

  Generative AI is still very, very much in its nascent stages, still very much a consumer level app usage.

  And we can talk about why. Largely, it's data and scalability and trust and and the profitability, near term profitability of using AI.

  But while enterprise bulks and hesitates, It's like everybody's at this do you remember those old cartoons from when we were young where where it's it's this little dog and they're all lined up and everybody's everybody's in a line. It's a military cart and they're they're and they all step back and he's left out front. Well, there's gonna be one that's gonna step out, and then they're all gonna race to catch up with each other.

  Everybody's afraid of making a big mistake because it'll be unknown.

  The development cycles are different. The predictability is different. The the profit, the profit modeling is is uncertain.

  Chapter

  Predictability and Profit Modeling

  Enterprise is not using AI, but when it starts, I think it's gonna be a herd. It's gonna be a wildebeest herd straight out of straight out of a Disney cartoon, with everyone using AI.

  So I think that's the investment is trying to find find the niches and the companies.

  I'm not being unique here. I think we all believe the big success stories of the future, they're gonna be small companies. They're not gonna be the big sales forces in Google's in terms of corporate size of employees. They're gonna be relatively small companies.

  So, so VC's and private equity are making big bets by doing things, to find those next few dozen unicorns because they're gonna be extremely profitable. They're gonna have they're gonna have great margins because they're gonna have small employee bases, and and they're gonna capture, you know, a tremendous market share and and and revenue.

  Chapter

  Leveraging AI for SMBs and Startups

  Yeah. And so can you talk a little bit expand upon that that thought, with SMBs and also start ups? Because I think at some at at at a certain point, I mean, I I love the terminology start up because it sounds sexy, but it's really a business. Right?

  You're running a business. Mhmm. That's the responsibility of the the leaders. Yeah.

  So let's talk about how smaller businesses can leverage AI.

  So I I do some work with a company on the infrastructure side.

  Okay.

  And the infrastructure side now GPUs, we hear about, NVIDIA is the darling of the industry.

  Mhmm. AMD is is coming in, with some market share. There's, you know, there's other players as well.

  That infrastructure is very expensive.

  Only six or seven years ago, I ran product operations for a large telecom, and I was responsible for tens of thousands of servers. Servers, real estate, people who have managed those servers in Bangalore and in Colorado and a few other locations. It was expensive for the company for me to make for me to manage that process for us to do development work. But now now we can get those expensive pieces of equipment on a consumption model. So these SMBs, can tap into that very expensive equipment based on their usage, which is phenomenal. I can't imagine just using a really high end, GPU, for the amount of time that I that I need to use it and maybe to use different sizes and style, this profiles.

  Chapter

  Supporting SMBs and Startups with AI

  So, that is something that is, I think, very specific to how we've evolved, with AI. We can support different usage types, different different ways of of supporting SMB and start ups to build faster, focus differently, not have to build overhead and structure for operations teams and lab ops organizations.

  So that's one.

  Another is just all the efficiencies that that that AI inherently supports and creates, with with a lot of the cloud work, the predictive modeling, how we're able to optimize supply chain. I know supply chain's near and dear to you.

  But that is all geared to essentially level the playing field for SMB and large business. And in fact, I would propose to you that large enterprises are gonna have a hard time reworking all of their existing workflows because reworking those existing workflows, it's a big ship that they're gonna have to reassemble and make sure nothing breaks.

  Chapter

  Leveling the Playing Field

  And some of these smaller businesses, they'll they they they may never elect to have hardware for one.

  Their their go to market models will will just have fewer moving parts and more of those will be automatable.

  And so they're gonna out of out of the gate, it's gonna be more automation that will be simplified.

  And even the resources that they will be able to hire, what you can do now in a no code, low code environment will enable people to create products in ways that weren't accessible to us five years ago.

  Right. Yeah. I actually did a tour recently, MSI Automation. It's a company here in California, and they actually they have two businesses. So one is a manufacturing company that manufactures this automated shelving systems that are used by military as well as large, research libraries, university libraries, and everything is automated in terms of, you know, when you go to a library now, you know, the, you can just put in the code and it you get access and it brings, the books down to you. And so it's, it's a whole archival type storage system, but what they did is because they want to share this knowledge with other manufacturing companies. So they've created an automation center.

  And it was impressive during the tour how the robots, you know, they were designed from manufacturer to do one kind of task. Mhmm. But right there in front of our eyes, the human that was managing the robot was able to quickly put in some sort of instruction into the AI piece of the robot. And all of a sudden, that robot was able to switch and actually perform another task that inherently wasn't designed to do when they first initially brought on the robot.

  And I thought that was pretty fascinating.

  Chapter

  Different Forms of Artificial Intelligence

  How can companies so when so before we go, because I I want you to really be in your wheelhouse here and use the terminology that you're used to to to to speaking. Yeah. Yeah. So let's take a step back. And what is a what's the difference between LLM versus GenAI, versus no code, low code, just so people don't feel overwhelmed by this terminology.

  K.

  GenAI is one of about seven forms of artificial intelligence.

  Generative AI is is is is is is the form of AI that that we associate with ChatGPT, with Claude, with with with and it's supported by the large language models. It is a natural language supported, form of artificial intelligence. That's that's the differentiator compared to, computer vision is a form of AI.

  Computer vision, is a form of artificial intelligence that, that would see things. Like like like think about and he might be on this call. I've got I've got a lot of friends that we're gonna join that do a lot of work in deep tech and AI, but but there are, computer vision applications to do night vision. And for example, surveillance, whether it's military surveillance or or city surveillance of, of property perimeter lines and to be able to see without a human having to be on a monitor, but to be able to pick up what's happening, that's a form of AI called computer vision. Or when, when when big trucks are crossing borders, that it can almost it's think of it as X-ray vision, seeing what's in a truck to see if other humans are in there being being brought illegally across the border.

  So that's so that's another form. Machine learning is another form of AI. Okay. So those are all forms of AI.

  LLMs, large language models, are are the models that we train, that we feed lots and lots of data, and you hear about the, high cost building those models, a lot of energy, a lot of water to cool, the, components that build those models. The infrastructure piece is very important. I'm I'm very involved in the infrastructure piece because right now, I think that's the layer that's getting very built out while enterprise figures out their workflow processes for what they wanna do first. So, so moving back into LLMs, support, generative AI. And then what was the other term?

  Low code, no code.

  Chapter

  Understanding LLMs and No Code, Low Code

  Low code, no code. That's just we've we've made things so easy.

  And I hate to say drag and drop, but but it is almost if you are if you are detail oriented and you're patient, if you know what you want to do, people without engineering experience can can can can design products. And it's and it's and it's happening. You know, people without formal training are using no no code, low code applications and, and building reason because because all the coding work is on the back end, you don't see it. You don't need to. You can you can identify the the workflows and activities that you that you want to request be created.

  And, and it's and it's a beautiful thing, because it, it's democratizing that creative process so that everyone can be involved in in creating technology and workflows that enable processes for mankind.

  Chapter

  Adaptation of AI within Businesses

  That's interesting because, MIT just released a coauthored article with Harvard Business School and a bunch of consultants, consulting firms. And I think when it comes to the adaptation of AI within businesses, there is this sort of project ad hoc kind of basis when it comes to applying AI and they're making the argument given how rapidly this is transforming and the opportunities with implementing AI, that it is best to do it on an ecosystem company wide level.

  Amen. I'm all about it. Keep going.

  Okay. So pretty much just what the article was pretty much saying, and it really made sense because if if you're doing it on a hat oh, so the premise of the article was because a lot of businesses and start ups are doing this on a ad hoc basis.

  Chapter

  Implementing AI on an Ecosystem Company Wide Level

  What's happening is that they're they're pulling the younger generation of, you know, the Gen Zers and, soon know, Gen Alpha's to actually come on board and teach the senior leaders within the company, which kind of intuitively makes sense. Right? But they're making the argument that and I think you write about this in your book, how leadership should not delegate AI to the to it being taught by the younger generation who are not really the experts in AI even though they use AI frequently.

  So how can non AI leaders actually how can they really bring in the expertise needed to set up and implement AI on an ecosystem company wide level, and that trickles down to the employees. And then the employees being open to using that, and then it also it has to be a two way Yeah. Communication.

  Right?

  Mhmm. Mhmm.

  Chapter

  Employee Access to AI Tools

  Related to what you just said, an another staff that's gonna support what I'm about to say, a good friend of mine, Luis Salazar, he's with AI for SP, and the SP is social progress.

  He just published an article, and I reposted it in the last few days. That's why it's so fresh.

  That over fifty percent of workers are paying for their own AI tools, average of, I think, it was thirty dollars per person.

  And and he goes on to talk more about that. But I made the point that this is terrible, and it's not terrible because of thirty dollars.

  It's terrible because fifty percent of employees then are being left behind.

  Mhmm.

  It's terrible because companies aren't leveraging consistent processes to get the data and the insights that come from what those fifty percent of employees are doing to make processes scale better for everyone to benefit from that.

  Chapter

  The Role of a Chief AI Officer

  I'm a I'm a big proponent of, and I'll I'll call it a chief AI officer just to be simple. I really don't care what you call it, but someone that's looking out for AI across the company.

  One of the biggest mistakes that I think we're making is that we're we're not focusing on AI at all, or we're making it an engineering function or a tech, you know, product e function if if we focus on it at all. So we lack cross functional buy in. It's having to compete with product revenues, and and it and it and we miss we're missing out in in in enterprise type organizations on on the change management practices that need to happen across a company, across all functions of getting people aligned, getting getting buy in, getting engagement.

  Something that you said in your lead in, I do think younger workers should be involved. I think there should be a plan where where strategy is set, where where vision is cast, strategy is set. There's a plan around it. It's multifunctional.

  Chapter

  Collaborative Nature of AI Implementation

  And to me, the beauty of all of this that I've that I've been experiencing for the last eighteen months is just how collaborative it has been because everyone brings something to the table. Those those more mature leaders have wisdom that comes from having made mistakes, having operated in multiple countries, having, you know, having failed companies, having, you know, those things that you just have to experience in order to have learned from that lived wisdom.

  Younger workers are gonna have that near term more immediate experience with specific technologies.

  You can't get both those groups can't get that other experience without meeting in the middle and sharing it.

  And so I think AI gives us that opportunity, but we have to have people come to the table together. And I think we have to have unfortunately, and I'm just gonna speak my truth. I think we have to have some mediation of that. We don't live in a culture corporately where I think there's a lot of, I'll say, value lots of times between those groups unless it's unless it's aided, unless it's unless it's negotiated or helped along, and it needs to be helped along.

  Leaders are too busy. They're too they they're moving too fast. They're they're not setting up, the why very well. They're not helping people, in their organizations understand the value.

  And and those are investments that need to be made, to get people to the table.

  Chapter

  Practical Application in Manufacturing

  Can we can we can we, get practical?

  Can you just That's all I am is practical.

  It's all I've got going for me. Right. Yeah.

  Which is why which is why I wanted you on here because so you're you're talking about this big vision, and the strategy has to be cast.

  Yeah. Yeah.

  And, you know, it has to be a two way street. It can't be top down, and it can't be bottom up. Yeah? And so, like, practically, let's take a manufacturing facility.

  You're gonna do this, aren't you?

  So, you know, we'll we'll try and keep it, you know, broad based, but let's let's get tactical because I and I think this is why it's so important for subject matter experts such as, you know, you you're an AI expert. I'm an m and a expert, mergers and acquisitions.

  I've done twenty m and a's. I've done twenty m and a's.

  Yeah. No. I know. Because, again, the technology transformation is really part of mergers and acquisitions.

  That's a key silo. So but I'm learning not to talk over people. I'm learning to to give people brass tacks. You know?

  Like, okay. What does what what is what I just said?

  What does that mean for your small and I don't I hate to use the word small because there are a lot of very successful companies out there that are, you know, hundreds and and and trillions billions of dollars in revenue.

  So but what does this mean from a tactical basis? So let's say they hire you. I know you're working on the infrastructure side mostly.

  Mhmm.

  But let's just say someone I work on the strategy side.

  Exactly. I work on the on the infrastructure side.

  Okay. Perfect. So so I'm a manufacturing company. Talk to me.

  Chapter

  Identifying High-Value Use Cases for AI

  They have to know their core values. They have to know what they're trying to fix. What is their what are their big pain points?

  Everybody's everybody's hard stop is at use cases because they they, are struggling to come to terms with what is the most important high value use case for me to for me to solve for. And those are those are dialogues around around is it more important for me to drive revenue? Is it more important for me to create efficiencies?

  I'm gonna be honest. I sit down it's it's it's less so in the last couple of months. But in the beginning, every board I sat down with wanted to know how many heads they could cut and how soon.

  Not because they were evil people, but because that was kind of the that was kind of the that was kind of the buzz was and I was, like, and I was always I do my southern thing. I'd be like, that's last thing you should be thinking about.

  And I would turn them toward the top line and how you could because I'd have some easy things in my pocket to pull out with how other companies so you have to focus people on, what the opportunities are.

  But getting people it's also it's hard to get decisions out of senior executives because getting them to choose their one top priority to pilot. Okay? Because we're talking about a company that hasn't done anything. That's our that's our little use case here. Right? Our our little, mock mock, example.

  And and and it really is getting them to choose their first trial of AI. And this is and and this example, this is always a company whose product is not a who doesn't have a tech product that is AI enabled. It's how AI is gonna affect their business.

  And and there's always, like, four. I'm gonna say not three, but four competing opportunities and what's most important.

  Chapter

  Getting Alignment at the Executive Level

  And I've had some funny conversations negotiating, across either board level or executive level conversations, what was most important to the business and why, and what AI could potentially do for that based on what we based on what we know now and what we forecast consumer behavior might be.

  But you have to get alignment first at the executive level and then buy in at the at the team levels for what what can be done. I mean, that's that's really step one.

  Yeah. And it seems as though the you know, obviously, in addition to operational processes that could be improved with AI from an automation perspective, I really like this idea, to focus on the top line.

  Because the reality is that labor costs are labor costs.

  Mhmm.

  And, yes, I know that the quick short term fix is to lay off people because that can immediately impact profitability.

  But it's a lazy approach to business. It's a lazy approach to leadership.

  Then why are you there?

  I have used those words. And and I have and I have said, is is that what you wanna tell the street? AI came in and you laid off twenty percent of your staff? Wouldn't you rather tell the street we used AI to increase our revenues forty percent Right. And had to grow our teams?

  Chapter

  Using AI to Increase Revenues

  And that's possible. Yeah.

  Now let's talk about still be profitable.

  So I I have a good example. I I wrote about it on LinkedIn. I was I think I was headed to the HPE conference with the the infrastructure group that I that I that I do work with and, Massed Compute. And, and I was at the airport.

  And I saw and I've used this in podcast before that even if you're a bakery, you need an AI strategy.

  Okay?

  And lo and behold I live in downtown San Jose. I'm in a high rise. I look out over downtown San Jose. And, and lo and behold, there's this little there's this little bakery, a little two two two two two, two two stores in San Jose, family owned. I had to look it up ninety years. They've been in business. Greenlee's Bakery.

  And their their, their bread is so good, they they redistribute it through local Whole Foods.

  Greenlee's had a bakery in the south in the southwest terminal at San Jose Airport.

  Unmanned. No cashier.

  Twenty four by seven operation. Probably a little fifteen by fifteen kiosk. Yeah. And I wrote about it right there in the airport before I left for Vegas and said, please give this your business. Please don't see this as AI taking jobs.

  Chapter

  The Future Enabled by AI

  This is the future because you can get off that plane that got delayed at eleven o'clock at night thinking, what am I gonna do for the kids for breakfast in the morning?

  And you can pick up a thing of cinnamon rolls, scan your credit card, and be on your way.

  And guess what? It is not losing jobs because nobody wants to work the cash register at Greenlee's at the airport, but they're gonna create more office jobs to handle the increased revenues. They're gonna create more bakery jobs, baking the goods and doing the the the the the the product side.

  I am gonna give them six months. I've got it on my calendar to follow-up and call corporate to see how they're doing with revenues from that kiosk because I'm sure they're gonna do as much business at that kiosk, unmanned, as they do at at their stores. It's a brilliant idea, and and and AI has enabled that for them. AI and sensors that will, you know, use AI for people to be able to self-service.

  Right. And it's a tremendous service to people who are leaving or coming in with my example of coming in late at night, everyone wins.

  Yeah. Yeah. I I believe so. And and and, oh, yeah. It's simple things, that, businesses can actually implement. You know? And especially now with point of sale, you know, like you said, with sensors.

  Chapter

  Implementing AI for Inventory Management

  And then also that can relay back in terms of inventory back to Right.

  You know, to their to their stores, and they can have somebody come out and quickly fill that in and, you know, just be able to repeat that process, fairly easily. And then even on a manufacturer's side, a lot of manufacturing companies use a lot of, distributors, so specialty dish distributors to distribute their goods that they've manufactured. Mhmm. One way, especially now with e-commerce layering AI, a lot of the e-commerce platforms actually have AI integrated right now. And so manufacturer could say, okay, maybe it's not really about distributing my products using a third party. How can I now set up an ecommerce site where customers can actually buy my products directly?

  Chapter

  Improving Margins and Customer Data

  Margins are improved.

  I control the customer data. Mhmm. And I'm able to actually get reiterated feedback directly from my customers.

  And then I can quickly implement and scale up my revenues even more.

  And that answers the question you asked about five minutes ago about how do we simplify for SMB because all those things would have been heavy processes to figure out five years ago. And now interacting with a single vendor pulls all that in.

  I talked to a friend of mine yesterday who who wants to do, basically, I'm gonna call it a master class kind of environment. He doesn't wanna fool with billing. He doesn't wanna fool with with, class enrollments. He wants to do single classes and be able to subscribe to do multiple and store the classes.

  And and I went on ChatGPT and said, you know, hey. You know, what vendors because I'm not for Maven, but I don't know what else. And I went on, and it threw me six or seven different vendors that do it. I'm like, here you go. And Yeah. And and it's it's marvelous because he will do it since he now knows it's so simple. He is the product.

  He doesn't need to deal with, you know, all the administrative storage of information, you know, credit card swiping. He just needs to connect it to his checking account and it and send it to his CPA. Right? Yeah. But it has simplified it so that he can have that as a revenue stream.

  Chapter

  Setting Up Revenue Streams

  Right. We've we've actually done that here at Katalyst Point. We set up, we actually used Maven.

  Again, it's like we're M and A advisors. We're not... That's right.

  That's right.

  We don't have the time to create and figure out the platform and then, you know, put together no.

  It's like we have that class is more than revenue for you.

  It's value for the students who take that workshop. Correct. So it's so it's bigger good than just revenue. It's it's Correct. It's greater good for the world, and it's great that Maven is doing that so that you can offer that service.

  Right. And I and we probably wouldn't have been able to do that maybe three years ago, not even.

  Agreed. Agreed.

  It would have been you would have thought about it, and you would have said, oh my god. This is overwhelming. This is not how we want to deliver value.

  But now with AI, it's it's so it's just oh my gosh, it's seamless.

  Like you, I, you know, I didn't know how to create a course. I was like, what am I doing? And I literally went into ChatGPT, and I was like, this is a course. Here's the thing. Here's the breakdown. I gave it its unique prompts, and and I've been using ChatGPT since it launched.

  Mhmm.

  So now with all of the iterative processes, it's actually learned how we want to communicate.

  It's learning how we think. And so I'm seeing the actual improvements compared to when I even used it a year ago.

  And isn't that beautiful?

  Wow It's beautiful.

  It's learning and growing with us. People get freaked, and I'm not talking about the privacy end. People do get freaked out on an individual level what it's learning with us, and I I can talk about that, and I think it's wonderful. Yes.

  Chapter

  Ethics and Implementation of AI

  But but on a more public consumer scale, what we can do now compared to that crazy stuff I spent time figuring out this time last year Right.

  I just can't imagine where we will be in another six or eight months with what we with what we can affect. But I'm gonna say this. This is my pitch.

  We have to stay curious.

  We are only going to reap those benefits if we are trying to grow. If we are in collaboration, like, right now, and if we are seeking if if you seek it, you'll find it or you'll build it or you'll call somebody else and say, hey. I've got this great idea like my buddy with a master class. I called him and said, you ought to do this because he's a thought leader. People are always asking him for stuff, and I said, you should create office hours.

  And he's like, that's a cool idea.

  So, it's the seekers and the curious that are getting to expand.

  Right. And and I want everybody to be in that position if they enjoy that because it's so much fun. And we are enabled to do that because of these AI applications that are that are popping up everywhere.

  Chapter

  Privacy and Integrity in AI

  And I I think it's great.

  I I you know? And in terms of privacy, you know, it's you don't have to give the details in ChatGPT, you can anonymize that information.

  And it doesn't need to exactly have the name or whatever the case is. So when it comes to privacy, integrity, ethics, those are the things that we think about. Yeah. How do you how do you how do you talk to leaders about the ethics of AI and how they can implement that in their processes?

  Yeah.

  Probably goes back to my raising, but I feel but my I feel like being ethical is who you are.

  And being innovative is how you do.

  Okay? Those things are not mutually exclusive. They go hand in hand.

  I can work really fast on innovation and still be highly ethical.

  And from my perspective, as someone who has frequently been the one who who builds the guardrails, who who defines them, and I define them with collaboration.

  I don't think guardrails restrain you.

  I think they help you stay on the road and drive faster.

  I think that ethics are a matter of, I'm gonna say it my southern way, documenting common sense.

  But but but but it is. Right? The majority of ethics peep people worry about privacy. They worry about bias.

  Bias is something we can fix. I could talk about that all day long. Bias is something we gotta we gotta get in there, use it, find where it's biased, rewrite the code. It's our bias.

  That's it there. It's our code. You know, that's that's my whole thing on bias. Privacy is, you know, an increasing expectation as as as the technology and the devices become more personal.

  I I had a conversation this weekend, a LinkedIn post that, you know, that that picked up a lot of traction with people about my meta glasses. And now some people a lot of people a lot of people don't wanna wear these because of their maker, because they don't trust meta not to collect data when you're wearing them. And and anyhow, the people feel the same way about my friend here.

  Ugh. They turned on.

  My, my my friend that if I say her name, she wakes up all over the house and asks me what I need.

  But, privacy, I think we're gonna have to give up some privacy in order to get some things that we want that are important, and those are gonna be conversations we're gonna have as as a society.

  Chapter

  Defining Ethics in Organizations

  Right.

  But as organizationally, defining ethics, I believe, is helpful for employees.

  Defining what the structures are, what the expectations are keeps employees from having I'm gonna say useless, but but but keeps employees from having time consuming debates that are unnecessary.

  Because when we identify the guardrails, they can go as fast as they want on the highways, right? And be safe, right?

  And be safe for for our customers. So I'm a big fan of document, define, set a structure, and turn them loose. And that's, you know, that's where you give p a people as much creativity as you can when you've done the work to build a solid structure and foundation for them to operate on that they can refer to. And with AI, we'll be able to give them structure that that they're they're gonna feel monitored, but that's the point, to monitor them to say so that it's not personal.

  Chapter

  Implementing Guardrails with AI

  Tonya is not going, I saw you. It's AI going, hey. You're off the road. Get back on the road a little.

  So that it's so that it's a helpmate. It's not your boss coming through. It's the system helping nudge you back onto the road so you don't get hurt.

  And is that part of the setting up initially in terms of that ecosystem structure, the infrastructure, you know, when it so then that way, individually, when people are implementing or using AI, that it actually can sort of act as that guardrail?

  Absolutely. Anything involving, like, data, anything you know, you can you there's all kinds of things we can do, masking names in the interview process as an example.

  You know, masking names in the credit review process when we're approving loans.

  Yeah. Yeah. Yeah. There's there's all there's all kinds of things that can that can help us take personal assessments and bias out of the picture, and keep information away from us that we should not see, that we have no business seeing, and keep us from making, decisions. You know, there can be think absolutely. Anything that involves business logic can be can be can be programmed in. And and when something's you know, it can be either blocked or, alerted between sensors and other other data exception tools, there's a whole lot that when the frameworks are established, there's a whole lot of tool regulation that can occur that leadership doesn't have to do anymore.

  Right.

  Chapter

  The Impact of AI on Job Roles

  You talked about a Chief AI officer, and I think as AI continues to transform, I feel like roles so tasks are one thing.

  Professions are another from an AI perspective.

  So a lot of people worry about AI taking away their jobs.

  And we're, from a task purpose perspective, yes, it can take away their jobs because things become faster, more automated.

  From a profession, so my profession as an expert in my field, it actually allows me because it's taken away those tasks, it actually allows me to even tap more into my creativity my innovative mindset Mhmm.

  In order to even bring in more value because now I'm freed from doing administrative tasks. Yep. Right? So how can we communicate to people? Because we talked about this fear at the beginning of the podcast episode.

  How can we communicate to people that it's really about the task, at least for now?

  Right?

  It's really about the task and not really about what you do and what you bring to the table.

  Chapter

  Communicating the Impact of AI on Jobs

  Because I I with the job security and the future of work, I feel like that is an important point to Yeah. Communicate to employees.

  And it's so it's by communicating. It's not sticking your head in sand, not closing your office door, not ignoring the problem. You can't ignore the problem. You've got to talk to people. You gotta acknowledge that the fear's out there.

  And it's gonna get worse.

  Robots are are gonna be working right alongside humans.

  And I think it's great, but not everybody does because it's it's, you know, because it's a physical reminder.

  Mhmm. It's something that could replace you. But I think it's gonna have to be a collaborative environment. The robot's gonna be doing the dangerous things or the or the or the super, super fast repeating things so that you're not throwing your shoulder out. And you're there managing decisions that need human intuition, if you will, for for a quality or what whatever that can't be assessed Right. More mechanically.

  But Agentic AI, meaning, AI that we we're scratching the surface, but Agentic AI, I'd give us a year, and it's gonna be commonplace, especially as we see application for it. And and I'll give a definition in a second. But as we see it rise up in, enterprise usage, Agentic AI, for those on the call who aren't as familiar with that term, is essentially AI that's able to make independent decisions.

  Chapter

  Understanding Agentic AI

  Now don't go all SkyNet on me.

  I I dealt with that a year ago. That's in my past.

  You know? And and that's and, you know, I thought about something a couple hours ago.

  I I'm pretty open about this.

  I'm a type one diabetic.

  But it occurred to me a couple hours ago when I was thinking about the podcast and some of our some of our, emails we've exchanged.

  But I wear a device with Agentic AI in it.

  I wear an insulin pump that has new technology from about a year ago, and that insulin pump reads my blood sugar, and it adjusts automatically for what's happening with my blood sugar. That's Agentic AI. It's making decisions on my behalf that I used to have to make as a as a long term type one Yeah.

  You have to carry carry the monitor and and and I used to have to calibrate and make decisions.

  Yeah.

  You know what I mean?

  Of sleep last night. Oh, I'm under too much stress. There are lots of reasons type one diabetics, you know, are up and down besides food. And, so I'd have to, you know, adjust. But but now it's hooked into, my blood sugar, and so it adjust it it it self regulates.

  That's Agentic AI because it's making independent decisions, and it has been a game changer.

  So I'm wearing and it it never occurred to me until this morning because I was like, Agentic AI. How do I talk about Agentic AI? And I was like, I'm wearing Agentic AI. It is strapped to my body. Yeah.

  And, so I think what people need to realize is we have this technology all around us already.

  We walk through the airport. There's sensors everywhere. You don't know it, but it's everywhere we're already living with. It's already making our lives safer, better, as it evolves. And you you asked about the workplace.

  Chapter

  AI's Role in Elevating Jobs

  So it's not gonna destroy our jobs. It's gonna elevate our jobs.

  Those those those people, those fifty percent who are paying thirty dollars a month for their own things, they're not, like, leaving at two o'clock every day. They're not saying, oh, I'm done. Right. They're right?

  They're they're doing more. They're elevating their work. They're they're doing more interesting things with their work. You know?

  One might argue, the boss has given them the employee of the month awards because because they're being recognized for maybe an elevated level of value. That would be an interesting next step in Luis's research.

  Right.

  So, you know, it's been said by a lot of people and quoted in a lot of different ways, but you won't be replaced by AI. You'll be replaced by people who use AI effectively. Right. So the whole thing is be curious and and and be excited about it. Be genuinely excited. And then as leaders, I think we have a real obligation to live that and to show people and and to create environments.

  Chapter

  Encouraging Curiosity and Creativity

  And in my book, there's little, there's little, list at the end of each chapter about ideas for each of those those, those traits of, you know, courage, wisdom, vision, love, that you can do with your work teams to promote those things. But you can do some fun stuff. And if you're not fun and creative, there's somebody on your team who is. Get them to help you. I mean, the whole thing is we don't have to carry it all as leaders. We have you know, everybody's in this, and that's what I'm seeing. I I do, there's a meetup I do every month.

  There's, like, two hundred people there. And I see these I see these bald, silver haired men sitting at the table with these twenty two year old young boys wearing wearing their Patagonia vest, and they are in it. They are in these intense conversations, and it makes me so happy.

  Yeah. Because everybody's getting value, because everybody needs to be at the table.

  Yeah. And we need to Here we are. Especially users such as ourselves who and I think because we're just naturally I'm naturally curious. I've always been curious. I think in my circle, I've always been the technologically advanced person.

  Chapter

  Embracing New Technologies

  Yep.

  You know, always willing to say, oh, what's this new thing? I'm just going to go ahead and and try it out. And there are lots of people like us out there in the workforce. It's just really up to the leaders to sort of raise their heads and try and figure out who those people are and leverage what they know to teach the rest of the team. So then that way, nobody gets left behind. Mhmm.

  That's one of my personal frustrations working with boards and executive teams.

  And I I mean, I get it. I'm I am those people.

  And I but I also have to be patient. I'm more interested. Right? And I'm living this. I'm I'm in it.

  And I see all this stuff, and it just juices me up. I get all excited about what everybody's doing with this. But I consistently go into companies where people aren't looking at this. They call me.

  Right? They call me to go, should we have an AI strategy? Then I'm just exploding because I'm like, you're gonna be our calm down, Tonya. Right?

  Chapter

  The Need for Awareness and Education

  But we need to realize not everybody. Not everybody's thinking this way.

  And and the opportunity is to help them see. The truth that I'm beginning to accept is, you know, everybody's it goes back to my farm story at the beginning.

  Everybody's different, and everybody not everybody comes to the table with the same things.

  Mhmm.

  So beautiful.

  Yeah. What I would encourage for the people who are on this call who are not those curious people, well, thank god. Thank you for being here. Right? Somebody sent you here.

  Yes.

  But you've got to invest then to bring those people in because AI is too big to ignore. And and and and if you're not creative or you're not, like, in it watching what's happening, then that's okay.

  You know, maybe you're great at manufacturing, you know, red shoes, but you're gonna have to accept this AI, you know, surge that's happening.

  And other people can help you find the ways to bring it meaningfully into your company with and governance for watching what's happening from a regulatory standpoint, from an employee retention standpoint, from all these different angles to develop a plan for what could meaningfully, materially impact your company. And wouldn't it be great for you to, like, not care about anything but the red shoes, but you know that, you know, hey. I've got this plan here. And, and for you to know what's happening and what you're gonna get from it because Right. You're gonna get from it is gonna be sizable, and I will say and this is gonna be negative.

  Chapter

  Survival and Transformation

  And if you don't do that, you're not gonna survive.

  Yeah. That's that's, especially with mergers and acquisitions and but then from a valuation standpoint, right, whether this regardless whether you choose to exit a company or whether you choose to say, okay.

  We're going to scale our company.

  Mhmm.

  It's not like back in the day where it would take you five years, ten years, and you're like, okay. We're gonna scale to x. No. This this this is revolutionary.

  And people who are on the sidelines because they're waiting for it to be perfected.

  Mhmm. Right?

  The perfection is going to happen the more we use it, the more we embrace it, the more we are creative around it. Of course, layering ethics, governance, risks around that process.

  Chapter

  Active Participation and Governance

  And that's going to change also, right, over time. So it's not just, okay. Here's a governance, and and that's it. No, in six months, that governance roadmap is going to change and you're going to need to come back and revisit the conversation. So there's active participation for everyone involved.

  Mhmm.

  And it can impact enterprise value if your company or leader who decides that you're just going to wait. It is moving so fast, that I that I actually worry about the customers or the clients that actually come to us and which is why we're trying to really add more value around the education of frameworks and integrating technologies, and enabling their companies to be able to scale even more and grow in value.

  What are the implications?

  I know we just obviously, we're talking about this right now, but anything specific that comes to mind when it comes to implications.

  I'm gonna write and I'm gonna write implications down so that I don't lose it because I will come back to it. But you wanna know how I get past that?

  Chapter

  Creating FOMO and Urgency

  How?

  I hope there are no future clients on this call.

  I create FOMO.

  I know.

  I know.

  Going in, they're gonna be like, I don't wanna because it's scary and it's the unknown. And if they wanted to, they would have already done it. I wouldn't be there. Right?

  Right. And I create FOMO by by easily either I already know or it's very little research because I know how to look. But I find out what other people in their segment of industry have already done and had results with. And I'm like, did y'all know that so and so's already done this?

  And did y'all know that so and so's already done that? And they're like, And and and and and they'll call, like, the chairman of that board by first name, and they'll be like so they're like, they don't want anybody one upping them.

  Yes. And and so I for me, the way I get them to engage is to let them know other people are already taking steps and are ahead of them.

  And I and I give them the example of what I've been able to, you know, find online or in in the the networking that I do. And and they're like and and when I talk about what these other companies have done, usually, they've not, like, pivoted in the industry, but they've done something that hit a press release somewhere. And and it but it's something that makes sense. And they're like, oh, we we we could've done that. I'm like, yes.

  Chapter

  Encouraging Outside-the-Box Thinking

  Absolutely. Right. And so as I create that that that that desire, that intent that they don't wanna be left behind.

  And I think that's a it it has so far been a very effective way. And and frankly, shame on them for not, like, just having a minute of interest to see what people are doing.

  Right.

  But I think They don't have time.

  They're just not wired that way.

  And I Well, they're not wired that way, but then they're not wired that way, but they're also so focused on your business.

  But somebody ought to be focused on the industry. Right. And I'm not even a lot of my clients are actually not tech right now. They're right? Because because tech kinda has this buttoned up. So the majority of my strategy clients on AI are they're tech adjacent, but they're not they're not tech proper.

  And, so they don't have the same mindset.

  And so it has been it has been fun to kinda bring them in to Yes.

  The thinking. Now on implications, the big implication for me, it has shift well, the big implication for me is always regulatory.

  No matter really, no matter what you do, the last thing you want to regulatory always takes time. You wanna know when something's brewing because if something's brewing that's gonna hit you from a budget perspective, you wanna know that a year or two out when it starts so you can be forecasting for that. You the last thing you want as an executive is to go to your board and say, I've gotta invest, you know, six million dollars with McKinsey to do this because you because you weren't watching. I mean, you don't have to you don't have to be caught flat footed like that.

  Chapter

  Regulatory Considerations and Market Perceptions

  Right. So regulatory stuff is first. And then, obviously, market perceptions market perceptions and market share. Two different things.

  And they're but but but they're they really they really are tied together because when your market perception drops, your market share is gonna drop fast.

  Correct.

  Correct. Depending on what you do or or, you know, NPS scores, those kinds of things, I I think it's gonna become much more clear. The the companies that operate with a with a forward mindset that do things with their customers, even when their product doesn't include AI components, but when they operate in ways that are more frictionless. I'll give you an example. State Farm, I think it is. Mhmm.

  They're used to. You, you know, you knocked your bumper, and, yeah, adjuster had to come out. You had to set an appointment. Like, I mean, you you drove your car home. You just gotta you know, somebody bumped your bumper. Now you can take a picture.

  You send your picture in.

  AI reads the picture. They already know your car's make, model, and year.

  They reference check prices in your area for what it costs to have a bumper replacement. And they they they tell you and you agree online to what it will cost to replace it, and they send you a check. It's all seamless. An adjuster never comes out and looks at it because AI, computer vision Yes.

  At the dent on the bumper and verifies, it doesn't need a warm body coming out looking down at it and saying, yep. That's a dent. Yep. It's gonna have to be replaced.

  It's not necessary. So, basically, all you gotta do is have a picture with your cell phone, upload it. That's all AI enabled. It's wonderful.

  Chapter

  Impact on Job Roles and Industry Changes

  It's it's it's wonderful for the company, but okay.

  So let's let's let's I I love this example because about the adjusters?

  Let's talk about that. So what should the adjuster do now?

  They have different skill sets. Right? Those people have have I don't know what it but but, I mean, when you think about what they can do, number one, it's a small population. But number two, when you think about they're detail oriented, they're people oriented, they they know I think I think I think adjusters are probably focused on automobiles versus houses. I don't think they cross over. Maybe they do.

  But but I think there's all kinds of things they could do in in the industry related to cars.

  Hey. Maybe they could come up with an app that they could sell to State Farm with the help of ChatGPT and you know, again, it's just like, think I think we are all required to think outside the box right now.

  And some industries, we should acknowledge even, some industries have a population where there's a huge percentage that is retiring out in the next five or seven years. Yes. So some of these problems, I didn't say that elegantly, but I think everyone understands it, are gonna fix themselves in a few years. Because if you stop hiring, then everyone was gonna retire out anyway in, say, ten to fifteen years. It's not a forever problem.

  Chapter

  Adapting to Industry Disruptions

  Does that make sense?

  Yes. It does. It actually does.

  And it also gives those, for example, you know, maybe truck drivers, talking about logistics now Mhmm.

  Who are being displaced, some who will be displaced with autonomous vehicles, autonomous trucks, you know, over time. You know?

  Again, AI can be a tool to actually figure out a way to create wealth, for oneself if one is willing to embrace the technology and actually use the technology.

  Yeah. I I do think it's a broad statement.

  It's incumbent on us, whatever that means, to lead people to think differently.

  Because I don't think that everyone has and I I wanna be delicate. I don't think everyone just naturally thinks this way, and that's why the fear exists.

  Okay?

  I don't think I don't my my uncle, my mother's brother, has been a truck driver all of his life, my uncle Bobby. And, I don't know that he he will never see this podcast. He probably doesn't know what LinkedIn is, and I say that respectfully.

  But he, he's just not wired and hasn't had the experience and his lived experience to think about creating new channels for himself. And I think it's incumbent upon us.

  And I'm not I'm not spatting at you when I say this because we all sit here and we go, and people are gonna have to be creative. And we mean that. But I think we're all gonna have to stop for a minute too and help people think about how to be creative. This is back to my no one should have to beg to work. Right. But we're gonna have to do some work to help that through. And it's not just you it's not just policy.

  Chapter

  Promoting Purpose and Impact

  It's not just government incentives.

  Purpose is so important. Mhmm. People want to feel what they do and understand their impact. And I think that that I think people of purpose and importance and self agency, are gonna be in a position in the next five to eight years to help spread that.

  Yeah. And and that's one of the things that I want to do in my work.

  Yes. I see that.

  Yeah.

  Which is why we started the education piece because the there's nothing more frustrating when I get a client who hasn't really thought about the future just because they just... No.

  They've just been doing.

  They've just been doing. And and now with buyers and strategics and private equity and whoever else is buying a company, you know, they are looking for these things within the companies.

  Yeah. And so it's important to actually share the frameworks and share how little things can be done within the company just to you know, it's like a it's like a a tipping point. And because they're already there, they have the business. It's not as they're like, you know, they're starting up. And so it's it's, I like that point, that idea of purpose. And I think it goes back to how you started telling your story around values.

  Chapter

  Preparing for the Future of Work

  You know, that's something that a lot of companies stick up their values and their mission on the board, but they don't really leave that.

  Mhmm.

  And so I think with the implementation and leave from our values or we lead from our values, into this, you know, future of work, like you said, you know, with your book. So let me ask you, what excites you the most about the future of AI in industry, and what role do you see your firm playing in shaping that future?

  You know, it's hard to think about the future because it's all changing and moving so fast. Mhmm.

  I wasn't doing any of this two years ago.

  And I'm a pretty planful person. I'm not rigid, but I'm planful. Yes. And, and I and I went from, you know, playing with GenAI as a writing tool to writing a book in ninety days to literally I've I've expanded my own portfolio to I'm an investor.

  So I have quote unquote holdings, but I have media, which is my speaking and keynotes and things like that, and my book and other books if I ever, you know, have time. But I have media. I have I have, I have ventures, which is my investments.

  I have, advisory, which is my consulting and my board work.

  So so I have all these different things that are all around AI, which for me is all around supporting what the future is gonna do with technology, which to me supports no one ever having to beg to work.

  Chapter

  Supporting the Future of Work

  It it it all rolls up.

  There are so many ways to be engaged. Right?

  As it evolves, I think it's a little bit for me of a reactiveness to because I wanna help.

  Right? I'm not a I'm not I'm not capitalizing on new things as much as I'm helping bring people forward to the new things.

  And so for that, I'm a connector. So I'm connecting.

  I'm helping founders grow. I'm helping boards accept and utilize, and I'm helping all of them connect to the resources they need, whether that's infrastructure like GPUs or, fractional executives because I have a broad network of talent to align to them.

  I'm just helping everybody get there because my heart, I love to connect good people and resources to good people and resources.

  I'd like to see everybody succeed, and that's that's what I'll be doing.

  Yeah. Yeah. I like I like that because we're we're both definitely with the same mindset is you know, our networks are pretty exten-extensive, and we know the people who are actually knee deep in this and also the people who need the help and to be able to kind of connect the dots for them while they continue running their businesses.

  You know, whether that's, supply chain transformation, digital transformation Mhmm.

  Whether that's, you know, setting up this infrastructure.

  So then that way, it sort of starts to run behind the scenes while allowing them to to continue doing the work with little to minimal destruction, to the business.

  And I think that's why, the work that you were doing, even though your book is titled the leadership's journey to the future of work, I recommend even individuals, employees, people who are unemployed to actually pick this up. And the reason is because, like you mentioned, after every chapter so you're not just talking over people. You're not just talking about the technology.

  Chapter

  Recommendation for Understanding Technology

  What I really liked about your book is this you had tactical things for people to try.

  Right?

  And I think that this could be a very good guide for everyone to really understand this technology. Even though it's, like you said, it's only a year old, but it's still very relevant because a lot of people are still sitting on the sidelines and haven't embraced AI.

  Thank you. Yeah. Thank you. I need to talk to you about this because I'm actually writing a book now.

  Everyone should. Everyone's in place and has something to say, and it's not difficult.

  Yes. Yes. And but I I had I'm I'm also trying to to train Chat... ChatGPT and the other AI tools, that I use so then that way I'm able to bring value authentically, to to my clients and to those who want to understand how AI can actually help from an m and a perspective.

  That was a big experience for me with the book. I cried.

  Did you really?

  It was it was early days. Yeah. I, you wanna hear it?

  I do. I I want people to hear this.

  Chapter

  The Birth of Personal Voice Through AI

  It's sitting right here, and I, you know, I'd done the whole let's write the table of contents, done a few chapters. This was, I'm gonna say, April, and chat g b t four had come out March fifteenth or sixteenth. Yes. And, I mean, this is early days. So this also this is before custom GPTs. This is before digital twins.

  And it was brand new to say, oh oh, you can assemble all these, you know, basically samples of your writing and train it to have your voice. And so I was like all about that. I was like, oh, I'm gonna have it right in my voice. And so I assembled a Word document that was like twenty pages of, like, email memos and LinkedIn posts and some Facebook stuff that was meaningful. And so twenty pages of me, loaded it, Said, alright.

  Because we collaborated on, like, two chapters back and forth, back and forth arguing like a bad husband. Right? You know, I was supposed to go back and forth, back and forth. And so I said, let's have you do my last chapter.

  My last chapter as a summary because you know what the table of contents is.

  And my last chapter is there's no place like home.

  Yes. And I wanted to evoke these feelings, these messages. I want the reader to leave the book feeling this way. And it was late at night.

  It was, like, ten thirty, eleven o'clock. I'm sitting here. And I don't have children. I was married five hot minutes in Tennessee, and, and that's relevant because I say, go.

  And those of you who have ever used ChatGPT knows it it just starts typing. It read it really fast. It just and I sat here watching it type that last chapter.

  And I still get emotional about it. It was it was my voice.

  It was my quirky southern slang.

  I use a lot of ellipses when I write dot dot dot. Right. Oh my god. Those were all over it.

  And it was like I I had birthed my voice.

  I've never you know? And I've I don't know what the reason I said I don't have children, but I had created myself.

  And, later, after the book was published and it was a it was a big moment for me because I was looking at something that represented me.

  Chapter

  Inspiration from Deepak Chopra's Hologram

  I learned later, a friend of mine who is on today's call shared with me that, he was at a finance conference seven or eight years before.

  Deepak Chopra, who most of you would recognize that name, had been at a finance conference and had presented a hologram of himself.

  I'm sure OpenAI helped with this because he and Sam are good friends.

  And, that hologram was an early digital twin, and he could ask the hologram questions because, you know, Deepak Chopra has a deep inventory of his writings. Right. And Deepak told the audience that, you know, he went back and forth with it in front of this finance crowd.

  And he told the audience, he said, you know, I'm not getting any younger, and I want my grandchildren to be able to interact with something and still know me.

  And I thought, how beautiful is that?

  Because, you know, he will have no doubt grandchildren that that never even experience him if he lives to be the normal age of a human. Right. And and for them to be able to have AI be a tool that presents their grandfathered to them, and they can ask him questions about when he was young.

  Chapter

  AI's Creative and Authentic Potential

  So for me, I was hooked.

  I was and my heart was hooked. And anybody who sees AI as just corporate greed or efficiency has really not explored far enough to see the creativity that it can open up or or how it can help us bring our voices to bear, more broadly or become a record of who we are because those things are important that you started out with the, you know, tribal wisdom.

  Those those things are important.

  And if this helps us do it authentically and capture that for time, I'm I'm bought in.

  Yeah. And I think to your point to reduce the bias. Right? We talked we briefly mentioned that. Mhmm. But if everyone engages, then we can start to mitigate the buyers that was actually used to train it because reality is, you know, it was really trained by a bunch of white guys, you know, in Silicon Valley. But we need to give ChatGPT and these other AI models the ability to diversify and expand upon how they learn, from different perspectives, different voices.

  And I and I think that's where we as a people can actually democratize Yeah.

  That. Yeah.

  Chapter

  Connecting on LinkedIn and Contact Information

  Yeah. So where can people find you?

  Oh, I'm on LinkedIn. Anybody anybody can, like, look at LinkedIn and know where I was last night. So so, so you can find me on LinkedIn, Tonya J Long. And don't just find me.

  Join the conversation. I think LinkedIn is not just a one way street. It's a it is about engagement. And, Belinda, you and I have not known each other long, but you've been wonderful at at joining the conversation, and I wanna thank you for that.

  Because, you know, if it's about arguing about whether or not these are recording everything that we say or you know? I I think that's how in this distributed remote world, we can all know each other rather intimately and know how we think on things that we otherwise wouldn't have a chance to. So Tonya J Long on LinkedIn. Or if you want to get an oh, it turned on.

  Or if you or if you wanna get in touch with me the old fashioned way, you can reach out to me at tonya at quantum crow dot ai on email.

  And that's q u a n t u m c r o w dot a i.

  Perfect. Yes. Thank you.

  And that's Tonya with T o n y a.

  Absolutely.

  Chapter

  Closing Remarks and Call to Action

  Alright. So you heard it all, people. Thank you so much, Tonya, for sharing your insights and expertise on today's episode of NextGen Industrialists: Rebuilding America's Dynamism. It is clear that AI is not just a buzzword, but a powerful tool that can drive meaningful change, not only in industry and business, but unleash our individual creative innovations for our listeners. If you found this episode valuable, please take a moment to leave us a review on Apple Podcasts, Spotify, or wherever you listen to your podcasts.

  Your feedback helps us continue to bring up conversations that really truly matter to you. And don't forget to save or download this episode and share it with your network. Someone, you know, might need these insights to take your business and your personal lives to the next level.

  To stay updated with our latest episodes, make sure to subscribe to NextGen Industrialists on your preferred podcast platform and follow us on YouTube for the video content and behind the scenes insights.

  Thank you for tuning in. And I look forward to having you with us in our next episode as we continue to explore the forces shaping the future of industry.

  Tonya, thank you so much for being here. I'm deeply and I look forward to seeing you soon.

  And we will.

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