What if I told you that the business you're running today could operate with just 20% of your current staff? It sounds impossible, right? Maybe even a little scary. But here's the thing - businesses across the globe are discovering that with the right AI implementation, they can not only maintain their operations but actually improve them with dramatically smaller teams.

The traditional business model has always been simple: want to grow? Hire more people. Need more output? Add more staff. But this approach is becoming outdated, expensive, and increasingly unnecessary. The challenge isn't just about cutting costs - it's about reimagining how a modern business can operate in the age of AI.

Today, I'm thrilled to welcome Chris Daigle, CEO of ChiefAIOfficer.com and a pioneer in AI business transformation. Chris isn't just theorizing about the future of lean business operations - he's living it. As a Certified Chief AI Officer and expert in AI strategy, he's helping businesses revolutionize their operations through strategic AI implementation. His expertise is backed by impressive credentials, including certifications from Columbia Business School and LinkedIn's Generative AI for Business Leaders program, and he's become a trusted voice in helping businesses navigate the AI revolution.

The AI Hat Podcast host Mike Allton asked Chris Daigle about:

✨ Strategic AI Integration: Identifying and implementing AI solutions that truly reduce operational overhead.

✨ Human-AI Balance: Understanding which roles to automate and which to keep human-operated.

✨ Lean Scaling: Using AI to grow business capacity without proportionally growing headcount.

Learn more about Chris Daigle

• Connect with Chris Daigle on LinkedIn

Resources & Brands mentioned in this episode

• ChiefAIOfficer.com
• Mark Moss
• Opus Clip
• Submagic
• HeyGen
• Descript
• VAPI
• 11ElevenLabs
• AI Marketing Primer: A Comprehensive Guide for Marketers
• AI Training for Business
• Explore past episodes of The AI Hat Podcast

Full Transcript

(lightly edited)

The Future of Lean - AI's Impact on Business Staffing Models with Chris Daigle

[00:00:00] Chris Daigle: If you don't do it, you will be riding a horse and your competition that does do it will be in a car. You'll both arrive at the destination. However, they will be able to get there sooner. And in the process, they will be able to just really use brute force in the marketplace to just drown your message out.

So I would say, listen, you don't have a choice. Well, Chris, it's uncomfortable or I'm nervous about it, or I'm ethically I'm not. Doesn't matter. Right. The quote from Ayn Rand, you can deny reality, but you cannot deny the consequences of reality. Okay. So regardless of what your feelings are about using these tools, those feelings aren't going to allow you to compete with a technology that can, that can do it better, faster, stronger.

So please just do it, get involved in it.

[00:00:54] Mike Allton: [00:01:00] Mike's got The Hat, the AI kind. Unlocking power in business, you'll find. Cut through the hype, explore the tech. Every week, new ideas to check. All Allton leads us on a digital quest. AI secrets, he'll always invest. Tune in tight, don't miss a beat. Knowledge groove, keep you on your feet. Listen up! To the AI flow. Business growth, here we go. Cutting edge insights, that's the plan. With The AI Hat, you'll [00:02:00] understand. Welcome back to The AI Hat Podcast , where I selfishly use this time to pick the brains of experts at keeping up with and integrating or layering artificial intelligence into social media, operations , advertising, business strategy , and other areas of digital marketing. Do you get to learn to. Subscribe to be shown how to prepare yourself and your brand for this AI revolution and come on ahead.

Now, what if I told you that the business you're running today could operate with just 20 percent of your current staff sound impossible, right? Maybe even a little scary, but here's the thing. Businesses across the globe are discovering that with the right AI implementation, they can not only maintain their operations, but actually improve them with dramatically smaller teams.

The traditional business model has always been simple. Want to grow? Hire more people. Need more output? Add more staff. But this approach is becoming outdated, expensive, and increasingly unnecessary. The challenge isn't just about cutting costs, [00:03:00] it's about re imagining how a modern business can operate in the age of AI.

Now today, I'm thrilled to welcome Chris Daigle, CEO of Chief AI Officer. com and a pioneer in AI business transformation. Chris isn't just theorizing about the future of lean business operations. He's living it as a Certified Chief AI Officer and expert in AI strategy. He's helping businesses revolutionize their operations through strategic A. I. Implementation. His expertise is backed by impressive credentials, including certifications from Columbia Business School and LinkedIn's General AI for Business Leaders program, and he's become a trusted voice and helping businesses navigate the A. I. Revolution. Hey, Chris, welcome to the show.

[00:03:40] Chris Daigle: Hi Mikea, nd thank you for that fantastic introduction. That was It was humbling. Thank you. That was great.

[00:03:46] Mike Allton: Well, I appreciate that. But like I tell folks all the time, first of all, Claude helps me write these. And second of all, you did all the hard work to get to where you are today. So I appreciate you being here, sharing your wisdom.

And before we dive deep, could you share [00:04:00] just first, what led you to realize that businesses could operate with such a dramatically reduced staffing through AI?

[00:04:07] Chris Daigle: Sure. I had been doing what I call growth architecture based on an EOS and a scaling up framework for businesses for off and on for a decade.

So I was very familiar what it took to, I'd seen under the hood of a lot of businesses and saw the dysfunction that's pretty common without strategy or planning in place. And I had heard about GPT 2, GPT 3, and to me, I just assumed that it was going to be this, that AI was going to be somebody else's, Opportunity because I wasn't a technical individual, right?

I didn't really have an understanding of the generative AI side of things. And it was in March of 2023, when I had my aha moment and looking at things through the filter of that growth architect, the one who's going to come in and, and optimize businesses. With the understanding of truly what was possible with generative [00:05:00] AI that's when I, I had that aha moment, knew that this, that there was a huge opportunity sitting right in front of me that didn't require technical expertise.

It required, as, as you called it, the hard part. It required that I had already understood, I understood business, and now I had this tool. So it made it a lot easier to figure out where to use that tool because I already understood business and it was easy to go, Oh, this does that. Ooh, we can use it here or here and that sort of thing.

So that's what got me where we are today.

[00:05:34] Mike Allton: That makes a lot of sense. Longtime listeners of the show know that I work full time for Agorapulse and we use the EOS framework there. In fact, I did a whole interview with Matt Heinz about, about EOS. And so I understand not only the, the. Approach that you're talking about it.

There's an exercise within EOS. For those of you listening, hard familiar where you need to think through all the different seats in your organization, not necessarily what exists today, but what should [00:06:00] exist in six, 12, 18 months. Right. And put the right people in the right seats and so on. But the almost fatal flaw to that approach is it requires that you know what those seats should.

Unless you brought in a growth architect, someone like yourself who can say, yeah, if you're going to craft the perfect marketing department, these are the roles you need to have. This is what you're doing today. So there is that problem. And to your point, then when you bring in someone who knows business like that, who's also familiar with AI, who can say, look these are the roles that you should be having in your business.

You need to have somebody who's responsible for making sure that the emails go out, transactional, promotional. Things on a regular basis. Hey, I can help you with a lot of that. So I know you're already running your business with a really lean staff. You've talked about that before. Can you break down maybe the key areas where AI has made the biggest impact?

[00:06:55] Chris Daigle: Certainly the, I guess what we do is we call it [00:07:00] operationalizing AI. If you're familiar with EOS, I'm much more of an integrator than a visionary. And for those of you who aren't familiar with ES, the visionary would be that the CEO with all the big ideas, it likes to come in and just confuse everyone with all the shiny objects they're chasing.

And the integrator is the one who says, Hey, those are all great ideas. But remember last quarter when we made a plan we're going to stick to that plan, right? So it's it's the the adult in the room, I guess so for us it was very easy because I was already process based and I I understand on a number of levels one I mean increasing valuations of businesses is one of the Results of what we do as growth architects.

So we're I I understand that businesses that investors will pay more money for less risk Right, and they'll pay less money if it's a risky investment and one of the interpretations for them of risk is Like key man situation what happens if whoever's running marketing disappears? Well, if we've got processes [00:08:00] or procedures or sops documented in the business, it makes it less risky Oh if that person, you know gets poached gets headhunted, whatever We can just slide somebody in because a lot of it is already documented.

Well, we've taken it a step further and what we do is, is we, when we're process mining and process mapping, we ask three questions at each activity within that process. Can we automate it? Can we augment it? Which is can this be performed better, faster, stronger if there's human plus technology at this stage?

Or can ai just handle this stage and through we call it the triple a automate augment or aiify and by by reviewing that in our own businesses, we established a protocol that we now teach our Chief Ai Officers are those who go through the certification program with us how to do the same thing how to Identify those areas in the business.

So for us There's not a department in the business where AI isn't doing a lot of the heavy lifting. [00:09:00] There, it's not doing 100 percent of the heavy lifting in any of the departments. That's not necessarily, I don't feel the tech is there yet. And I, I think that it's important that the, we're the arbiters of the taste and brand and the culture that we want to, to have people experience when they're associated with us.

So we still want to have that in there. And a friend of mine taught me a great way to look at it. His name is Mark Moss and he's a Bitcoin celebrity or whatever. But Mark says he uses AI in a 10, 80, 10 framework. He says the first 10%, I do. I identify what I need. I get clear on that. Like I really invest in the initial input.

80 percent I let the models do it. That final 10 percent I come back in and I just make sure it was this, did this output match my intention in that first 10 percent effort. So for those of you who are out there, if you will remember this 10, 80, 10 I think that it'll allow you to manage your [00:10:00] expectations.

AI is not going to do it all for you, right? But still be able to leverage the synthetic with the contribution of the authentic. You being the human at the first 10%, last 10%. And that's pretty much how we do it internally at chief AI officer.

[00:10:16] Mike Allton: Okay. Well, okay. So first of all, for all the visionary CEOs that are listening, we love you.

It's okay. We need you. We need your vision. But we also need, integrators like, like Chris, who can, get you to slow your roll on, on, on the ideas. Cause yeah, trust me, I've been there. But I love that 10 80, 10 approach. It's not new. I've heard many, many people talk about how important it is to be involved and, and, let the, I do its work and then make sure that you're there.

Other who. Human in the loop the whole time, but that's, I don't know if it's the combination of numbers or what that makes that memorable and also deep at the same time, that's pretty cool. I love that. Now, a moment ago, you were talking about risk and you were talking about risk from the [00:11:00] investor's perspective, but I want to talk about risk from the business leader's perspective, because I think when we start talking about reducing headcount.

And reducing seats, that's something that a lot of business leaders get concerned about. Yeah. Not to mention the people who might be in those seats. Right. So how do you address those concerns?

[00:11:19] Chris Daigle: Well, it's election season. I saw a meme and it was like a, an election sign. It said AGI slash UBI 2028.

And it's a geeky reference, but it's addressing this particular issue. What are we going to do once AI gets so good that it, we just don't need people pushing those buttons anymore. And in that joke, AGI is artificial general or yeah, Artificial General Intelligence. And at that level. AGI is defined as being at parity with human capabilities.

So right now we're, we're using artificial narrow intelligence. We're, we're the directors of the intelligence of this artificial [00:12:00] intelligence. In an AGI environment, which is the next big step up in capability, the artificial intelligence will direct the artificial intelligence. It will be able to reason and learn from its mistakes and all those things.

That's when the real disruption will occur at scale in the job force. So one of the solutions that's been proposed is UBI, Universal Basic Income. We like it with all this productivity is being done with compute instead of human horsepower take some of that and essentially tax that revenue so that.

People get a basic income. Don't know if that's the right way to approach things, but I thought it was a pretty funny joke that it didn't address this issue. I, here's what I can tell you. I don't have an answer for that. We do in our certification program, we do address change management wholeheartedly because it's, we tell you how to, how to manage change, but not what that change is going [00:13:00] to be.

And I've got a few thoughts on this one of those I want everybody to just consider this scenario There's an opportunity in the business. Somebody says hey Chris, there's I think you'd be great for this this promotion. Okay. Really just you and another candidate. Okay, great. Let me go apply for it.

And I go in there and I'm ready to apply for this, promotion or whatever at work. And I see the other candidate and I, they went to the same school as me about the same time. On all levels, we're pretty much even candidates, except that person got some sort of a credential when it comes to using AI and that role, that candidate is a much better candidate for the role than I am. Why? Because all of the studies show that with basic training, an individual is producing more, producing faster, and [00:14:00] producing higher quality, less human error deliverables from that role, simply from using Chat GPT, not even tool stacks or anything cool. Not that Chat GPT isn't cool, but so what that means is that if you don't have this on your resume or you're not able to say.

Oh, yeah, I can follow this conversation. I know what you guys are talking about when it comes to Ai You aren't the best fit for that role anymore. There's a new paradigm of business the way that we've done things for a long time is it has already changed, you just may not be aware that or the change hasn't landed in your team yet, but it is coming.

There's no reason other than taste preferences why an individual why a business would choose not to leverage Ai in as many places as possible. When I say taste preferences It might be like well, I know there's a website out there. I think they're They're proudly saying like we will never embrace ai because they're like a creative [00:15:00] there.

I think it was a written creative, right? Oh, okay, but that's like a novelty. That's not a smart play for the, the things that we usually measure about business, which is profitability and, and, and Alec effective allocation of resources and like doing it the old way doesn't work anymore. So I consider learning these, this stuff, an act of self preservation for your career.

And I'm not trying to scare you here. But If you aren't using this as actively as you could, or you're not at least even saying, Hey, I'm going to, if you're on this podcast, you're doing something, of course, but you should be setting aside. Setting aside time every week, every day, actually, if you can to learn something more about generative AI.

You don't have to be on top of all the news. That's not what I'm talking about. I'm talking about how to actually use the tools. And once you start playing with some of these tools, you're going to make a few discoveries. One of them, these tools don't, they're not hard to use. They're designed to have a very [00:16:00] short learning curve, five to 15 minutes of playing around with any of these gen AI tools.

You're going to be able to go like, Oh, like I can get output. That's, that's passable. That's usable. That will mean that I'm doing less effort as a human. And I'm leveraging, I'm augmented by the technology. That's one of them. The second one is that as you start to use these tools, you're going to find that you are introducing efficiencies, which result in you having more time available, right? So just on that measurement, if you're able to produce more, you're worth more to the company and the executives and decision makers are aware of this because all of the surveys, all of the research says that they, your boss is thinking a number of things.

One AI is, if it's not already doing, it's going to disrupt our business strategy. We need to find somebody. Your boss is looking for those people and they're not finding them. It's a very inefficient market to source AI capable talent that happens to know your domain, whether that domain is your department, marketing, [00:17:00] human resources, or it's your industry.

They're not able to just go to Fiverr and, and find a Chief AI Officer or somebody who's that AI expert. So what they're needing to do best case scenario is take individuals within their own company and get that person trained up because that person can do a number of things that person can now hey I already understand the business of Susie has the keys.

We don't do this on Thursday, whatever the the Domain specific expertise that they know about your business and how you do things combined with them learning how to bring the tools They're going to come into the business and it's not just that you have one Worker who's ai powered now that person now gets tasked with teach this stuff to your team Teach this stuff to the executives hold a lunch and learn whatever like whatever it is that individual now becomes the the evangelist for this enhancement to the business and like that problem solved by the boss and as a result of [00:18:00] that, they want to pay you more and they want to promote you.

That's not me saying this is we can pull up the research from Harvard and edX and all that stuff, but over and over again. So the individual, you listening to this is not just a hobby or a novelty or this is cool. I'm going to, impress my friends or, whatever with some AI tricks. This is you opening up the door to serious opportunities that are coming on deck currently and that you wouldn't get unless you were doing this stuff like like going up to the podcasts and trying out the tools. Most of them have free versions that let you you know use them anyway, so a ramble, but that's my thoughts on it

[00:18:43] Mike Allton: Very transparently. I've said from the beginning that one of the reasons I got into AI late 2023 was because I was scared for the future of, of my role, for my career, my professional trajectory.

And I was frightened from my friends and colleagues who've been digital marketing for a decade, many of whom [00:19:00] were at still laughing. AI off as yet another hype. Because if you've been in digital marketing for as long as we have, we've been through the hype cycle of many, many, many things. So I understood where they were coming from.

Cause I was there myself, by, by mid 2023 AI, it's like NFTs or something else. It's, it's not going to mount to anything. It's like, virtual reality, which has really gone nowhere commercially. Metaverse. Yeah. The metaverse. Exactly. But AI is different. And one of the things that makes this the same and yet challenging is that, you talked about how people need to be coming aware of and familiar with how to use A I. It sounded like electricity or computers or the Internet. Betty, who was filing things manually 40 years ago. She needed to learn how to use a computer in order to keep her job.

What's different is the pace of change. Electricity, computers, even the internet. They were adopted over the course of [00:20:00] decades, years, gosh, AI, just wait a month and things will be different. A hundred percent. And so it's harder for people. And I get that. And hopefully those of you listening to the show, that's partly why you're listening to this show is so that you can get yourself ramped up.

And in fact, stick around to the end. I've got a free resource. I'll share with you if this is like your first time really thinking about how to apply A I. To your role, but I'd love Chris, if you could give us an example of how AI has replaced or enhanced one of the traditional business functions in your operations and give folks that, that, that specific use case to help them wrap their minds around how this is working.

[00:20:38] Chris Daigle: Well, I've got a very relevant one and that's what the social media, I know that that's a subject that is of interest to this audience. And at the beginning of 2020, beginning of this year, 2024. We had ambitions of launching a podcast and we did. But I had gotten some advice from a friend of mine who had been high up in the operations team at, at WordPress.

And he said, Chris, [00:21:00] first time founders focus on product, second time founders focus on distribution, getting, getting your message out there. Right. So right from the get go, I said, let's, if we're going to do the podcast, let's get as much distribution as we can. Let's use the tools. So that started us on about an eight month like very, mad scientist experimentation of all of the tools, the generative AI tools that are available out there for content repurposing content creation from scratch, things like that.

So for us now, whenever I do a podcast interview within about 15 minutes of the completion of that interview. It's edited. And we have about 75 to 125 pieces of content that are multimodal meaning some are video some are audio specific some are video avatar Some are pure text, not only multimodal but also platform specific So we know that this works on twitter.

This works on linkedin. This works on facebook and all of this is done [00:22:00] by a tool stack that we've assembled of genai tools. Okay. Well, that's great big deal Anybody can use those tools. We took the mandate one step further. If we're going to use these tools, the output that we get and that we post has to be indiscernible from a human effort.

It can't be easily identified as synthetic. The whole, like anybody can make the bad video of Will Smith eating spaghetti, if anybody, or a pizza hug spot. If you've seen some of the early stuff that was out there, anybody can do that. But to actually master the usage of the tools, to where it becomes people just even the algorithms assume that a human is producing this stuff and therefore those algorithms support that content.

That's where we found ourselves. We've got a fantastic content team and we're not just using tools and people say oh I use Opus Well, so do we but we take that output from Opus and then we run it through. We've got some proprietary Tools, but then we, it might end up in Sub [00:23:00] magic because Sub magic is also a video tool, but Sub magical that has better B rolls.

Or, and then from Sub magic, we might take it into some of that might end up being background and, and Hey Gen, for a video avatar. So it's, it's not the individual tools that we're doing. It's the stacking of their usage and understanding them well enough to go, Ooh, this output would be fun over here. If we ran it through that, what that's resulted in is we have a full time social media person.

He's fantastic. He's an influencer in the luxury lifestyle space. Anyway, when a anonymous brand and we have two part time offshore, I guess you'd call them VAs. And with that, we're producing, if any of you go to any of our channels, you'll see the content. And if I wouldn't have told you you would just assume, wow, this is good stuff because it, it's the genesis of it is a, an authentic conversation that I have with somebody.

Exactly. Yeah. So that would be a, a great example of what's possible and [00:24:00] that right there, I can guarantee you we would need most likely a team of three or four full time. And if I wasn't offshoring, I'm looking at, us rates for that talent. And now we're able to do it for 500 bucks a week instead of, probably 20, 000 a month.

90 percent discount. So it works.

[00:24:24] Mike Allton: Yeah, that is an incredible example. One that I obviously personally relate to. Well, I'm doing this, as I've said several times as a side hustle, I'm using Descript, but even then, I start with that human conversation, just like you're talking about, and I use tools like Descript to help me identify clips.

And they're really not that good most of the time. So I ended up picking the ones manually and doing all the editing. So if you can find the right tech stack that does it for you. Yeah. That eliminates the potential role, or at least it allows you to scale and do more with the stuff that you're already doing.

Folks, we're talking with Chris Daigle about how AI is literally transforming how [00:25:00] businesses are structured and how they operate. And I've got several more questions. You aren't going to want to miss, but first a quick word from our sponsor.

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So Chris, continuing with that example, you've got a tech stack that's seemingly automatically editing podcast episodes, pulling out clips, creating all the repurposable content. How are you maintaining quality control?

How are you ensuring consistent output without having, dozens of people looking at all that output?

[00:26:26] Chris Daigle: Yep. So referencing the 10 80, 10 concept that, that same thing, nothing's getting shipped until a human eye has been on it. And in some cases there, if you were to look at our process map for this output from one before it gets processed as input and the next tool in the stack, it might get manual review, human review as well at certain steps in it. So, that's the only way you can, you, that's, that's the, the easiest way to ensure that the output that you're shipping, that you're putting, that you're posting on social channels [00:27:00] is human. Like if that's your goal, if it's not, then lean into the AI and do the freaky weird.

Funny crazy stuff. So that people do know they're like, wow, that's cool. That's ai But for us, that's not how we wanted to do it. So keeping humans. Giving it the the authenticity thumbs up is is how we do that at different stages in the in the process

[00:27:25] Mike Allton: That's interesting because I've seen a lot of people having conversations about trying to automate entire processes, like what we're talking about, right, where we automatically, upload the recording to a Google Drive and that automatically gets picked up by an editor, which then automatically creates a bunch of posts, which then automatically posted to social media.

And, what you're saying is, no, no, no, we got to make sure that there's somebody looking at the output at each one of those steps. And I think there's a double benefit there because there aren't a lot of tools or, or ways affordably or easily to actually pull that thing through that [00:28:00] entire process today, the suspicion is soon we'll have AI agents that could do all those things hands off.

And what I'm getting at is I've seen people complain that they can't upload a raw podcast episode and then hands free get that social output and I like the fact that we're insisting on humans to be involved because then that that's a reason For not being able to automate it. Yes a human has got to look at those posts before they go to social media because they also need to be the ones to drag and drop them into Agorapulse or where you know the platforms natively or however, you're getting them out to social media. I would never recommend that somebody allow anything to go out to social media that hadn't had somebody's input and visibility.

So appreciate you hammering home that that's a necessary part of the equation. What roles do you see are still essential to keep [00:29:00] human operated in a business and why?

[00:29:05] Chris Daigle: Well, until the technology catches up, there are a number of places where I would prefer to have a human. However, the technology, as anybody who's a regular user knows, the technology is advancing.

I'll give you a good example. Like, like right now, I would prefer to have a human handling client issues, client inquiries, things like that. It's customer service. However, research shows that the user on the other end, they're looking for an answer. They don't necessarily care if it's human generated or the machine generates it.

As long as it solves what they're looking for now, in particular chat. Now I would feel very comfortable using AI powered natural language chat for customer service. I wouldn't feel comfortable having AI necessarily handle my inbound calls [00:30:00] yet. We're testing with some stuff we've been testing, but in particular, we're using VAPI.

ai for the voice agent. And. I don't think it will be long before the logic of that model, the latency of the delay between, them asking a question or interrupting and the eight, the AI agent registering that and the ability of it for it to be able to, I don't want to say deceive, but certainly Introduce doubt into whether or not it's a human.

That that's coming very soon. Now, when that happens, I may not have the same position on customer service, but for now I would suggest. If you've got somebody answering the phones just because you can turn it over to an ai agent I wouldn't unless that ai agent was airtight and I don't know that we're i'm not I got a refined palette when it comes to like, you know understand Oh that sounds like I mean if somebody does an image or [00:31:00] a post or whatever I can look at it and go you probably use this tool in this tool Most people can't but that would be one area for sure.

Obviously Financial any type of analysis. It's very helpful in identifying things that may be identifying things in the financial data that you wouldn't have caught or Identifying things just generally faster than it would take you otherwise. Still want to have that human reviewing and confirming that that's one area where you hear about hallucination I don't normally worry about that but in a financial environment arithmetic is not an opinion.

We need to make sure that the numbers work there. If, if there is something like, honestly, I use HeyGen avatars all the time, but what I do is I record the audio with QuickTime audio. So it's still my voice and my inflection and that sort of thing. But for marketing messages for welcome messages, things like that, my [00:32:00] voice in a HeyGen avatar and the way that we've shot those, you can't tell.

The reason I don't use ElevenLabs or a voice synthesis is because. they may be able to mimic a voice or something, but they don't always get the, Oh, sure. That's a great idea. Like they don't get that inflection. So I wouldn't necessarily outsource my audio content or audio delivery to AI. So that would be customer service finance and then marketing And hr, I would take this is what we do. We when we have a job that we need filled or a role that we need filled we get a very clear idea of what the ideal colby score would be for that if we use the colby index. Hey, click this link, take the Colby index, let's see what you come back at.

That's stuff that could be, I would be fine automating that. The final interview, of course, you want to make sure the person, um, they're not toxic or anything like that. But [00:33:00] as far as matching skills to role, I don't know that you need a human to do that so much anymore. Man, any department I could probably.

I could probably make people pretty scared, right?

[00:33:14] Mike Allton: Yeah. And to your point, the technology is advancing so rapidly. Even today, anybody who's listened to a conversation with notebook LM or even joined into that conversation and had the two AI guests talk to you and ask you questions back and forth, it's getting harder and harder to discern the human from the robots.

So we're, we're, we're getting there. But for businesses, leaders who are listening and they're intrigued, but they're still cautious, what would you recommend as their first step towards leaning towards this leaner model of business?

[00:33:48] Chris Daigle: If you don't do it, you will be riding a horse and your competition that does do it will be in a car.

You'll both arrive at the destination. However, they will be able to get there [00:34:00] sooner. And in the process they will be able to just really use brute force in the marketplace to just drown your message out. So it's not a good plant. Now, look, if you make goat milk soap or something like that, you're fine.

Yeah, maybe. I could be making the same soap, but using AI and my advertising and all that stuff. So even then, I guess you're not super safe. I would say, listen, you don't have a choice. Well, Chris, it's uncomfortable or I'm nervous about it or I'm ethically, I'm not, doesn't matter the quote from Ayn Rand, you can deny reality, but you cannot deny the consequences of reality.

Okay. So regardless of what your feelings are about using these tools, those feelings aren't going to allow you to compete with a technology that can, that can do it better, faster, stronger. So please just do it, get involved in it. Secondly I would find somebody, as I referenced earlier, I [00:35:00] would find somebody that's in the organization already, right?

You don't have to be a big thing that I do as a, an executive is this principle of Who, not How. If I start asking how how are we like when I ask how that means I've got to go learn something, right? Yeah, if who is the solution i'm just able to go. Oh, they're really good at that. Let's bring them in you do the thing I don't care if it's black box and I don't know what they're doing.

I'm busy I'm running a business if i'm getting a result, that's what I'm looking for. So you as the business leader If you, if you have a curiosity, I, I enjoy being tactical with the tools a lot. And I find that the people that we have going through our program, seasoned business professionals, they'll tell me, man, I'm working like 14 hours a day.

And I'll be like, dude, be careful. And they're like, no, I like time flies by because I love it so much. That's my experience as well. Mike, I'm sure it's very similar to you. So for those of you who are, like hesitant understand that it's not going to the learning curve short and you're [00:36:00] actually going to really enjoy it so that would be something. And then if you can lead by example the people who are going to stick around are going to have permission to do this But a couple of things that I would do I wouldn't just say hey, let's start playing with it You need to have what's called a generative AI use policy.

So it's just, it's a document that says, hey, this is how we use AI in our business. This is okay. This is not okay. Maybe this is the list of tools that are whatever it is, but have a policy outline so that somebody, somebody has like the guardrails for use. Then, spend some time training the people who are going to be, who have signed off on that use policy and agreed to follow the rules, then get them trained on the tools.

We have a a recent announcement with a partnership with Microsoft that we're very excited about in support of [00:37:00] co pilot. The issue is, and I heard it on a, another podcast, but the guy was like, Hey, I was out consulting and I kept hearing, at the, at the conference, people would say, oh, is co pilot worth it?

And the guy said, my answer was. If you're using it a hundred percent, if you're not using it, no, it's not worth it. Like that logic tracks, right? So if you're going to have these tools in your business, Make sure that the people know how to use the tools because any initial hesitation about, Like wanting to stay in the comfort zone If you can sit them down for 15 minutes and they can actually produce output and go that wasn't hard. Then they start like once expanded the mind can't contract to its original state right their mind has been expanded They now know oh I can do this the hard way or I can take five minutes and get the same result I'm going to do it the easy way.

I'm going to do it the smart way the faster way, whatever So I think those would be some but make no [00:38:00] mistakes. This is a paradigm shift in business. This is not same business, new tool. This is a, you, you cannot compete. And and the like the existing paradigm is It's waning and you can get ahead of it now and still be early believe it or not Like you'd still be early and boom You're off to the races your competition that's still trying to figure things out or whatever that you're creating an advantage that will be very hard for them to catch up to and I mean if you want to If economic viability is is why you show up to the office every day.

I would suggest that you do not put this off. You find some people internally. You don't have to go out and, there's Chief AI Officers that get paid a million bucks a year. You don't have to go find those people, find somebody in your own organization, but get them trained up so that they can come back.

Right. And say, Hey, I got the answers. Let's go. [00:39:00] That would be my, my advice.

[00:39:02] Mike Allton: Well, I will say if you're listening and you want to hire a Chief AI Officer for a million dollars a year, then reach out and DM me. I'm happy. But we've talked about how AI, allows businesses to scale down their employees because it allows their employees to be more productive, which, which is good.

But to your point, if a business is going to take off or the competitors are going to take off. That's not the only thing that's happening. I think the other thing that's happening is AI's affecting their ability to scale and respond to marketing changes. Would you agree with that?

[00:39:38] Chris Daigle: A hundred percent. Scale, I might've been you that was saying that earlier, or that was in another episode I was watching perhaps of your show, but you were talking about how scale has traditionally been just go get more people.

Get more resources, right? Not so, not so, not anymore. If we want to scale, it's just get the net, get the business plan [00:40:00] versus the, creator plan, spend 30 more dollars per month. And now we've just added on bandwidth of another five people in some cases. So. Yeah, scaling is much easier, much faster, much less friction.

It's incredible.

[00:40:14] Mike Allton: Yeah. So last question, Chris, I'm just wondering if you can look ahead. I know that's really challenging in A. I. So too far down the road. But just in the next couple of years, how do you see this lean A. I. Powered model evolving?

[00:40:29] Chris Daigle: Okay, so one of the first things about generative A. I. That was intriguing that I heard, was somebody saying that this tool would allow for the first one person, billion dollar company, right? Can it really do that? Right? So, that's been the promise or the chatter for A couple of years now. Knowing what I know and seeing the advancement of the technology weekly, sure, [00:41:00] if somebody had the right idea, there's nothing, they had the right idea and the product was like an information based or a software based, it didn't require like physical warehousing and stuff, I don't see any reason why one person that intelligently architected out everything that needed to do and go could do this.

They could maybe outsource some coding if they needed to or whatever. Maybe not have the models build it for them. So I would expect that this And that would be like okay good for that person. That doesn't really affect my life But it does show you what's going, what's, what's becoming possible for sure.

I would say that it, there is some behaviors that need to be reprogrammed in you as a, as a leader or somebody who is leading at least AI in your business or your industry. And that is not the. This, this constant, well, we'd love to do that, but we don't have that resource, but we don't have the [00:42:00] capital, but we don't have the time, but we don't like whatever those are, I would suggest that a lot of that.

Has been mitigated if you understand how to use these tools that We we can't hire enough people to have the budget to hire enough people. You don't have to hire them You know, we it would we don't know what to do ask the models. What do I do? Like you've got access to so I would expect that All who deploy these tools intelligently in their business will end up benefiting the same way that Mike's business is, that my business is, and that other AI powered, AI enabled businesses are.

[00:42:35] Mike Allton: Could not agree more. Chris, this has been incredibly insightful. I know, given all of us listening. A lot to really think on and chew on. Probably folks are gonna want to go back and listen to this episode a couple of times to really just let it digest and start to apply it to their own businesses. But for those who have more questions, maybe they want to reach out and connect to you, where should they go?

[00:42:57] Chris Daigle: I'm very active on LinkedIn. [00:43:00] That's probably the easiest place. We have a great community. It's free. And it's full of business professionals who are exploring generative AI's use in their business. Not, trying to make quick, quick money in AI. This isn't that crowd. It's a crowd who is asking the types of questions that Mike was asking on this episode.

And that's a Chief AI Officer. com forward slash Community against free. Or future podcasts,

[00:43:30] Mike Allton: terrific. Thank you, Chris. Thank you. All of you for listening. Of course, we'll have all those links and more in the show notes. And that's all the time we've got for today friends. But like I was talking about earlier, if this is your first foray into this world of AI marketing, I got the perfect resource for you in the show notes below it's free.

The AI marketing primers designed to quickly get you up to speed on the terms, the tactics, the underlying technology that's powering this AI revolution. Check it out and I'll see you in our next episode. Welcome to the grid.

That's a wrap on another [00:44:00] episode of The AI Hat Podcast. I hope you gained some valuable insights and actionable strategies to boost your business with AI. If you enjoyed this show, please subscribe, leave a review, and share it with your network. And don't forget to visit theaihat. com for more resources and to connect with me.

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