From Wild West to Workplace: How AI is Transforming Mid-Market Companies - Chris Daigle

Chris Daigle, founder and CEO of Chief AI Officer, helps executive teams deploy real-world AI strategies that drive business results through his flagship Executive AI Immersion program, designed specifically for mid-market companies.

• AI adoption is fundamentally different from previous tech waves because it's accessible to anyone regardless of technical background
• Older generations may actually have an advantage in using AI due to their business experience and ability to provide better context
• Companies that delay AI adoption create an exponential disadvantage as early adopters gain market share and embed AI in their culture
• The Stanford/Harvard/BCG study found AI-enabled workers produced 12% more, 25% faster, and with 40% higher quality
• The traditional "good, fast, cheap - pick two" paradigm no longer applies with AI-enhanced knowledge work
• Leadership teams should get the same AI training to ensure alignment before implementation
• AI governance should include clear use policies with employee training and acknowledgment
• IT departments should handle analytical AI (data science) while operational teams implement generative AI in business processes
• AI implementation is "boring" - it's about systematically improving thousands of small business processes
• Executives should develop the reflex of asking "Can I use AI for this?" for every business challenge

Start using AI today by simply asking it how it can help with your specific role or challenge - the more you practice, the more effective you'll become.

Chapters

• 0:00 Introduction to Chris Daigle
• 3:32 From Growth Architecture to AI Consulting
• 8:06 AI's Unique Accessibility Revolution
• 11:51 Overcoming Resistance to AI Adoption
• 19:49 Leading Through AI Implementation
• 27:01 Beyond TikTok: Real Business Applications
• 32:41 Advice for Executives: Start Using AI

Transcript

Stephen King

And hello, we're back, and this is Stephen King here on the Inconquerment. I realize that I haven't been introducing myself for the past couple of episodes, so this will be the first time. If you don't recognize my voice by now, welcome. And I'm joined today on I think this is episode four with a new voice. Who's my new voice today?

Lovell
my name is Lovel and I am a former student of professor Steve 

Stephen King

Oh, Lovell. How long ago were you with us? When did you graduate?

Lovell

To everyone listening to this. I graduated in 2021. I studied advertising and PR at Middlesex and I had the wonderful opportunity of being mentored by Steve for all three years of my undergrad and he was also my dissertation supervisor, where we went into AI.

Stephen King
Normally I would roast you or attempt to cut with such a lovely, lovely, lovely comment like that that I couldn't do anything. Obviously I'm amazing. Thank you very much. Tell me, who did we just speak to today?

Lovell
So we had the wonderful opportunity of speaking to Mr Chris Daigle. He is the founder of Chief AI Officer and it's a very, very interesting conversation about AI and how he believes that AI is the future, his experience with consulting mid-market companies as well as senior executives yeah, 

Stephen King

So he went from 2023 to today gives us journey, and we talk a little bit about TikTok trainers at the end, and we talk about going into the wild west, the motor cars and stuff like this. We go all over the place, don't we?

Lovell

Absolutely. I love how he uses real life examples and breaks down AI into the most simple of language so that anyone listening to this will get a perfect understanding of the key messages he's trying to communicate, not just to executives, but to everyone out there that has access to.

Stephen King
AI. Yeah, it was a wonderful conversation, so I think we're ready to roll. Here we go.


Lovell
Hi, I'm Label and welcome to a new episode of The Incongruent. And today we are welcoming Chris Daigle, the founder and CEO of Chief AI Officer, a form that helps executive teams cut through AI hype and deploy real world strategies that drive results. His flagship, Executive AI Immersion has become a go-to for mid-market companies looking to boost productivity, reduce costs, and lead in the AI economy. Prior to Chief AI Officer,

Chris spent over a decade advising and scaling tech companies across the US and Europe with deep expertise in automation, operations, and go-to-market strategy. He has partnered with leaders across multiple industries to transform complex operations into efficient, scalable systems. So welcome, Chris. And before we get into the technology, we would like to know about the man behind the plan. You've been an advisor and operator for over a decade. What pushed you to create Chief AI Officer as a dedicated practice.

Chris Daigle
Hi, first of all, thank you so much for the invitation to be here. I'm excited to share my perspective on AI with your audience. That's a great question. So it was during COVID actually, or I the tail end of COVID when I launched this business, but I had been during COVID, I had been helping businesses do what I call growth architecture. I'd never been the person who had taken a company from zero to one. I was always the person who kind of came in once they had stalled out and then helped them.

I guess, eliminate dysfunction that was holding them back from really hyper scaling. So when chat GPT 3.5 came out in November of 2022, I immediately recognized it was going to be a huge opportunity, but I thought it was going to be an opportunity for someone else. I'm not technical, I'm much more operational and business, I guess, parlance. I'd be considered an operator, right? So I was excited about it, but I didn't understand it.

And early in 2023, somebody who wasn't very bright was showing me some stuff that they were doing with ChatGPT. And I instantly realized, hey, wait a minute, this is accessible for everybody. And there's no technical requirements for you to actually be able to use this well. And instantly, my first thought was, this is something that I can do in my own practice of growth architecture development for companies.

The very next thought was there's zero leverage in that. I need to teach people how to do this. I need to teach people a combination of both my perspectives on growing business with generative AI being an accelerant for the application and result cycle from that. That led to about a nine month build out of a curriculum. We brought in faculty from MIT, but not from the technical side.

from their business school. We brought in MBAs and project management professionals because I wasn't interested in necessarily approaching AI from a technical conversation. I wanted the traditional operator or the traditional non-technical business executive to be able to understand AI through their lens, a conversation that they were already familiar with. And we launched in 2024. In the first year, we certified about 400 chief AI officers.

I instantly recognized that we had something that was missing in the marketplace. So for anybody listening to this conversation right now who thinks that they might be interested in pursuing some sort of career or opportunities in AI, do it. There is high demand, there is low supply, and the market is very inefficient for introducing those two parties.

They tell me, AI is like the wild west, that's the saying we have here in the US. And the wild west, if you think about it, if you've seen westerns, you know that you walk out of the saloon and there's people walking and there's buggies. No, it's not like that at all. It's much more like the frontier where you look around and you don't see anybody. And if you do see somebody out there, you're like, hey, like, hey, like you want to collaborate, you want to work with them. So we're still at the frontier stages of the opportunities for AI.

Companies are paying a premium for anybody who can come in and just help them kind of demystify, like how do we use AI in our business? And it's not gonna be the tech, you know, the data scientist. It's not gonna be the computer scientist. It's gonna be somebody who is entrepreneurial, somebody who maybe has an interest in business or experience in business. And if they go and learn this stuff, they're able to be that translator for businesses. And that is a, A, you can bring tons of value by doing that to the companies and in the process be highly compensated for it. So that's what I was doing that led me into the launch of ChiefAIOfficer.gov.

Lovell
So what do you think is different about this AI shift compared to the past waves of technology adoption?

Chris Daigle
You know, man, like it's accessible to anybody, right? I routinely encounter people who says, my, you know, my grandmother uses it more than I do. Right. That's not typically the paradigm when there's a new technology that's released. The the the. However, I would suggest that the older generation actually has an advantage because to get really good at getting ideal output or results from a chat GPT or Gemini or Claude or whatever large language model you're using. It's important that you know how to craft the question, right? And that you have some context on like, instead of saying, write me a marketing plan. If you've got a marketing background, know, write me a marketing plan that's targeting my ideal customer profile who is, you know, this is their description. They're, they're based in this country. this is their demo. The more context you're able to give it give the models, the large language models, the better the result will be faster. There won't be as much iteration required. you know, people with 30, 40, 50 years of business experience, they possess an understanding of what context is necessary to get the right output. So I would even suggest that that might be different. Secondly, the cost. Certainly they all have free models or free versions. There's no question.

But if you want the most powerful version of chat GPT, at least in the US, it's $20 a month. If you want, it's crazy, right? Like there's no impediment, cost is no longer an impediment for individuals to be able to have access to the strongest versions of this technology. So I think those are two of the primary differences. And there's no real learning curve. you're able to have you know, it's natural language input and output that you're getting. So there is no user guide necessary. There are no YouTube tutorials that you need. There's no class that you need to go and take for a semester or two to be able to be pretty good with this. But I will say that repetition is the mother of skill. The more that you use this, the more you'll have those aha moments where you're like, next time I should tell it to do this, I should have asked for that. that's the learning curve, just practicing. Pretty awesome.

Stephen King
There's so much to unpack there. there's obviously some challenges and some other discussions I would love to put in. We've pursued a very similar path, except you've become a multimillionaire and I'm still doing this podcast. Because in 2023, I had the same incidents with the education industry and I produced a paper and we created a course, which is where this all started from. But there is... a question here, you said that AI won't replace you, someone using AI will. You're focusing on the mid market. My experience is that there are tranches of resistance against AI, where it's very clear for me when I was using it in my work, I was so empowered. But trying to encourage others, seemed to be they had, you you said the frontiers, they had rounded their wagons and everyone was shooting anyone with AI. What's your experience? Is this resistance going to succeed or is it going to be overcome? You must be facing this in your consulting.

Chris Daigle
We do. that topic for listeners not familiar with that, that's generally discussed as change management. How do I diffuse any concern, anxiety, negative emotions associated with changes happening in the business? But I want to look at a historical precedent. When the automobile was invented, there were plenty of people that said, not interested. My horse is fine. It can get me to town almost as fast.

The ability to conduct commerce with an automobile as compared to a horse, the automobile allowed for a higher velocity of commercial cycles, let's say, that just the horse wasn't available to do. And fast forward, there's still people that ride horse for recreation, but not many people are using horses, at least in the developed countries, are using it for their primary commercial mechanism. The same thing will happen here with AI. You can resist it, yes. However, I think what will happen is your economic viability will be constrained significantly. The number of careers that will be open to individuals, I don't care if you've been working in an industry for 20, 30 years, if you don't adopt this, the interest in your expertise it's not gonna be as valuable. Now let me run you through a scenario real quick. Stanford University and Harvard and Boston Consulting Group, and this was in 2023, September of 2023, technology's improved greatly since then. They did an experiment to see what was the impact, not of any fancy AI stuff, but simply chat GPT on the impact of a knowledge worker's ability to produce. They ran a 12 week study.

with 18 points of measurement where they established kind of like at a baseline, said, where's everybody performing at these 18 points? And at the end of those 12 weeks, they remeasured. They took half of that group. was about 400 consultants. They said, Hey guys, you're great at what you do. Go do it. The other half, said, before you go, let's give you about 10 minutes of instruction on chat GBT. And that was it. Basic instruction at the end of those 12 weeks across 18 points, all 18 points of measurement. No surprise. The AI enabled

producers were performing much higher. They were producing 12 % more, 25 % faster and at a 40 % higher quality. Now, if you have any experience and maybe engineering perhaps, you've heard this maxim, good, fast, cheap, pick two. Now, and for those of you that haven't heard it, essentially, I if you want it good and fast, it's not gonna be cheap. If you want it cheap and fast, probably not gonna be good. That paradigm is no longer relevant, at least in knowledge work supported by AI, large language models, chat GPT. So an individual who says, well, I've got 30 years of experience. I may not, but if I know how to use chat GPT, I have access to the world's experts in that subject matter. I don't need 30 years of expertise. I can achieve 80, maybe even 90, maybe 95 % of the knowledge that you possess, that you built over 30 years of your career, if I know how to work with the models, I can access almost all of that expertise in minutes. I don't need 30 years. And the end of it, and that translates from whatever your expertise was, whatever any expertise that I might need in my role, I've got instant access to the world's experts. We teach a prompting framework to get that, but so it just doesn't make economic sense for companies to continue to hire unless they were to hire those people who weren't AI enabled at a suppressed rate. That's the only way it would make sense.

Stephen King
So let's just come on, because you talk about speed and if it's fast and cheap, is what this is, it won't be good, right? But we're saying it's almost good. But there are mistakes, there are hallucinations and the models are improving and they're working and there is copyrighted information and there's all these other complaints, bias and what have you. How do you navigate this with management when there are... these widely reported mistakes that the AI makes, whether it's in the law market. How do you address these concerns and address this risk when you're doing your consulting work?

Chris Daigle
So I think that that was a lot more prevalent earlier in earlier models. Now, most of these models have reasoning or even advanced reasoning elements built into it. Now, what that means is that before the AI returns a result, it's now taught to double check and confirm the sources where it got that information. So it's not exclusively looking at the training data.

It's actually going out to the web and finding, in some cases, a dozen different sources to confirm, is this the correct answer? So if you're using ChatGPT for ideation and things like that, maybe you don't need an advanced reasoning model. But if you're going to be preparing a legal brief or a business strategy, you do want to make sure that you're using one of the more advanced models of ChatGPT-5. You can go in there and it would be the thinking or the pro version. So that's one way that they've mitigated that. But secondly, there's a couple of frameworks and we used to call it something else, but I met an AI expert, Chris Tam, shout out for this. Chris did a presentation at an event I was at recently and he called it Him and Her. Him stands for human in the middle. Now we used to call that the 1080 10 principle. The first 10 % of working with AI is you being clear on what you want, just typing that in there, right? Again, going back to that marketing example, I want a marketing strategy as compared to I want a marketing strategy with all that context I shared. The next 80 % of working with AI, that's you hitting the enter button. Most of the work was done, right? But the final 10 % is not copy and paste. The final 10 % is what he called her human enhanced response. I'm gonna review before I... I mean, if it's for creative stuff, maybe not so much. But if it's for something that I'm creating a deliverable for a client, I'm going to review it. I'm not just going to take the AI's word for it. So if you can remember that 108010, you're involved in the beginning and you're involved in the end, that will mitigate the bulk of the hallucinations or the concerns about maybe AI making stuff up.

Lovell
I love your two things. I love that you said. Firstly, the comparison that you used of AI with the introduction of cars. And secondly, the 10%, 80 % and 10 % is a very interesting take, something I've not heard before. But that leads us to the next question you've been emphasizing on the importance of AI and speed over hesitation. But how can leaders balance moving fast with avoiding costly mistakes in AI adoption?

Chris Daigle
Yeah, great question. I don't know that they have a choice. The tempo, the pace of business is accelerating because of the introduction of AI. And I want to give you kind of a scenario that I've spent a lot of time thinking about because there's, work with a lot of clients, some are cautious. Well, let's see what happens. Some were early to adopt it. The ones that were early, this interesting, this exponential event occurred in their business.

They created more bandwidth for their employees, even on the basic level. Maybe it was writing an email, maybe it was reviewing a document, getting a summary, but they created more bandwidth. And rather than saying, okay, Mr. And Mrs. Employee, go take a longer lunch break, they used that time to learn more about AI, which further gave them more bandwidth to learn about more AI until the point to where, so now that company, let's say they had 10 employees, and they can now produce at the equivalent of 15. Their costs didn't increase, right? Because they now have the AI supported bandwidth. Now the company that waited, but I want you to think about this, with 15 employees, all things being equal between my team and another team of 10, which was our baseline measurement, I'm now able to have a fatter pipe at the front end, let's say for inbound leads or deal sourcing or sales conversations or anything like that. So now I've increased my, I'm punching above my weight as they say, right? The company, so I'm gaining more market share. The company that waited, let's say after they watch us for six months and go, okay, now let's do it. They won't be able to catch up, right? They will not be able to catch up because I've now gotten more market share and it's become a cultural thing in my business. It's no longer, the learning curve has been handled.

And as a result of not only learning about AI, maybe I've got somebody on my team that says, Hey boss, I want to build some automations. now I'm gaining more bandwidth, that's, that's. Agentic or AI powered, right? The company that's, that's saying, okay, now let's get off the bench. Now let's do something. They are at a lower strata of business viability than my company is now because they delayed. So is it, is it scary? Sure. No question. Is it risky? Some. 

Is it an option? No, you will not be able to compete unless you do something boutique, maybe you're a hairdresser, maybe you carve furniture. Sure, those are outliers, those are fringe cases, right? But as far as knowledge work goes, if you hesitate or delay much longer, if you aren't aggressively pursuing an upskilling environment for your team through... governance and training and all those safety guardrails that you as a human can introduce, you're in a different category than your competition now. You are now a subcategory of that industry.

Stephen King
I can see that happening. mean, what we talk about is trying to get intrapreneurs, right? You want to inspire these innovative people. And if you give them that freedom, they will do all of the innovation for you. But now, if you've been waiting, now you're gonna have to pay a consultant to come in and do that for you. Whereas you could have had all that done for free. I mean, yeah, I can see that going.

Lovell
Now, what do you think would be the quick wins that a mid-market firm would achieve when they adopt AI with your frameworks?

Chris Daigle
Sure. So it's very simple. What we typically do with a company or advise companies to do is first get the leadership team, have them all go through the same training, right? That way in the boardroom, in the decision-making environments, we're all at the same level, right? So no department head is being left out of that conversation. Once the executive team understands it, then they should really... look at their existing business strategy and say, okay, now that we understand the capabilities of it, how do we introduce this into our existing strategy to accelerate the results cycle, let's say? Yeah, go ahead, Stephen.

Stephen King
There might be an argument to say, let's build a committee under the IT team and let the IT team figure it out first. I've seen that happen.

Chris Daigle
I don't think that's a good idea. Yeah. And I'll tell you why, at least the way we approach it. So we see AI, there's kind of two branches. There's analytical AI, which would be more like the data science side of things. And that's been established. There's, want to go hire a PhD from MIT. There's plenty of them out there that know this stuff. But what we're focused on is what we call operational or applied AI, which is the introduction of generative AI, natural language interaction with AI into my day-to-day, your day-to-day workflows, right? Nothing fancy, no big learning curves, no huge costs associated. IT doesn't understand process. They don't understand operations. So companies that are looking at the introduction on the data science side, certainly, if you want to create your own LLM and you want, you've got large pools of data that you want to extract business intelligence from, please send that to the IT department because nobody else is interested in that and in doing that, right?

But if you want to have an impact on your business, on your operations, on your day-to-day, on employee capabilities, that's not the IT team. it seems on the surface, it would be logical, AI is a technology. We have a technology lead. Let's let them lead that. a few things will happen. The IT team is going to be very cautious and slow about the evaluation of risk. There's not a lot of

If you do the next step, so we talked about educating the executive team. The next step is now let's establish an AI use policy. What do we feel is a safe way for our team to use AI? And then let's train them on the tools we want them to use through the lens of that use policy. At the end of that training, the employee signs off and says, yes, I've learned how to use it and I've learned how to use it safely. If I use it outside of this use policy,

I'm subject to reprimand or termination or whatever, right? So they know that there's consequences for going rogue on using AI in their role. Now at that point, we've established as much as we can, safety guidelines on usage. So where IT needs to evaluate a lot more technical risk as an operator of a business, I just needed to make sure that my people understand, hey, if you put our financials into the free model of DeepSeek, it's ended up training the model in China, right? Like, I didn't know that. Well, now you do, so don't do it, right? So it's different. Again, analytical AI, send it to the tech team. Operational or applied AI, let's keep it with the people who are actually gonna be working with the clients or working with our internal information. Once you've done that, yeah.

Stephen King
And also you mentioned you also mentioned governance. So it needs to be a top management issue, right? You cannot just delegate this down to the person who might be interested. This has to be at the very top end of the company and they're, you know, keeping them awake at night, right?

Chris Daigle
You know, one of the stats that we used to share in one of our trainings was that it was a high number, was maybe in the surveys that were done, 74 % of executives were concerned about AI, their likelihood of keeping their role if they didn't learn AI. So I used to tell people, look, if your boss is worried about this for his own role, shouldn't you be too, right? Like they're paying attention to a little, like a... a further horizon of the business than you are. And if they're seeing something that's got them concerned to the point to where they they're thinking, hey, I need to learn this at any level of business for your own economic viability, for your own likelihood of keeping your job, you should learn this stuff. And if you don't know where to go learn it, I wouldn't say like TikTok is not the spot, maybe for a couple of tactics. But you really want to think about this. it's something that we call thinking in AI.

You want to get to the point to where there's no business activity that you're doing. Maybe you don't use AI, but at least you can, you consider before you do it, say, could AI help me? Like if you're not thinking that way, you're getting behind.

Stephen King
I have to pick you up because you mentioned TikTok and TikTok inspired my research study because the research study I did was said, there's all these TikTok influencers out there. Every single second you would scroll, would AI, forget doom scrolling, it was AI scrolling, 10 this, 10 that and the other.

Now that there is so much free stuff on TikTok, as a corporate consultant aiming at the mid market, and mid market, they don't have the deepest pockets. How do you present yourselves? What is it that you've got, which says, look, I am not a TikTok influencer, I am the real deal. What is it that you have as a solid substance that your clients are gonna take?

Chris Daigle
So we were, I'll put it in air quotes for those listening, we were early. And what I mean by that is we started really our exploration of this in early 2023. And we brought with it 25 years of business experience and private equity and technology and finance and all those things. So I'm not somebody who's trying to get followers, right?

I'm somebody who's interested, not necessarily the sensational, because the reality is AI is not some event that happens to your business. It's a boring process. And you start with, hey, how do you reply to those emails? How do you answer a customer support ticket? How do you run a financial analysis report? That stuff's not sexy. It's not going to be interesting on TikTok or Instagram. But for real businesses, business is made up of a thousand small processes, thousands of small processes.

And that's where AI is a process. It's not an event. You introduce it here, you get a little bit of bandwidth here. Then you introduce it here and here and here and here. It's like the marathon versus the sprint. And I think a lot of what you'll find on social media is these kind of like, they're interesting, but we called it candy. It's fun, but it's not very fulfilling for a business. But it's cool to watch somebody make

you know, an image or a song, but most businesses aren't monetizing those images or songs. They're monetizing the knowledge work. So I don't know that you're going to find a ton of that type of training and then also consider your source. I mean, we started our podcast called Using AI at Work and at the beginning of 2024, one of the top 5 % podcasts in the world now. So like,

I've had lot of, and as I mentioned earlier, repetition is the mother of skill. I've had a lot of rep.

Stephen King
You have so many operations. have so many episodes of that. And it's fantastic how that AI in and how many different iterations that you've already generated, is amazing and it keeps going.

Chris Daigle
So those were great questions for sure. And listen, if you wanna be an influencer, don't listen to what I'm saying. Go follow successful influencers. mean, honestly, like success leaves clues, as Tony Robbins says, right? Like model somebody who's doing something that you're doing well, something that you would like to do well. But if you wanna be a good business person, TikTok's probably not gonna be the main source. There might be some nuggets you get here and there.

But if you're a business person, would say TikTok, Instagram, to some degree, most of YouTube is built on the sensational, the eye candy, the engagement, much more so than it is on watching paint dry, which is essentially what it is to introduce AI into processes. It's not, you know, there's nothing exciting about it. It's just business.

Stephen King
We've gone from the frontiers to the home decorating of Walmart in about 25 minutes. That's brilliant. Lovell, would you like to ask the last question and then we'll close this down.

Lovell
So for our final question, what advice would you have to give to executives who fear that they don't have the technical knowledge that would lead to AI adoption in their companies or within their teams?

Chris Daigle
Yeah, that's a great question. And it's the same answer that I give every time I'm asked this, which is regularly like, what do I do? Start using it, right? And well, where do I use it? Guess what? You can ask AI, hey, I'm a finance professional. Hey, I'm an HR professional. How can I use you? Right? Like it's, it's your, we've got 20 years or 20 plus years of all of us being conditioned to if we want an answer, where do you go? You Google it.

Right? So most of us are taking that skill of learning how to Google something, and that's where you're starting. People maybe have tried ChatGBT and using it like they use Google. And I hear people say, I tried it. It didn't work. Right? Well, you tried to use ChatGBT as Google. Right? So what I would suggest is the more that you start using it, the repetitions that you get with asking it questions, well, can you do this?

Hey, how would I do this? What do you think about this? The more you start learning about it and you start to create the same reflex that you did before instead of calling up the, know, 411 or whatever it was that you did to find information before Google, you just start creating a new reflex is that like, my gosh, I've got this business problem. What am I going to do? let me see if chat GPT can help. And the more you do it, the more you become what, what Ethan Malik, a Wharton professor calls, you become a cyborg. You, you have this,

It's always running in the back of your mind. Can I use AI to do this better, faster, higher quality, whatever it is, right? Doesn't mean you have to use AI, but it also means that that is a default reaction for you as you encounter a challenge that comes up in the business or you've got a task to do, you at least say, huh, how can I use AI for this? And if you don't know how, you ask AI, hey, I need to review a contract. I need to do this. Can you help me? How can you help me? Right?

That's all it is. So anybody listening who's a little intimidated by this or I hear executives, yeah, we're using AI all the time. Well, what do you do? We write emails and summarize documents. There's a lot more to it than that. So you need to really just always be, put a sticky note on your computer that says, can I use AI for this? Just like create that new reflex.

Stephen King
That's a really, really fantastic answer and a series of answers in this whole conversation. Thank you very much, Chris.

Chris Daigle
Thank you.

Lovell 
Once again, Chris, this podcast will be posted on the incongruent. It'll be posted on all streaming platforms. And thanks so much for taking out your time, for talking to us about AI. I feel like I've gained a lot of valuable insights. I personally will make sure to incorporate repetition. And it's been a lot of valuable information. I'm going to be making a LinkedIn post on this as well.

Chris Daigle
My pleasure.

Chris Daigle 
Yes.

Lovell 
To everyone listening to the podcast right now, stay tuned and follow us for more podcasts on AI, where we speak to wonderful people like Chris and learn more about AI.

Thank you.