31: Using AI for Business Growth and Innovation with Isar Meitis

Welcome back to Using AI at Work. Today I'm excited to have Isar Matis join us. Isar is an expert in AI and business transformation and is known for his insightful podcast, Leveraging AI. He's actually the guy who encouraged me to launch this podcast in the first place. With his background as an F16 pilot and an experience leading tech startups, Isar has a unique perspective on AI's impact on business growth and strategy. He's extremely active in helping companies navigate the complexities of AI, offering consulting and educational programs through his company, Multiply AI. Okay, let's get started. Welcome to Using AI at Work. I'm your host, Chris Daigle. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. And today on Using AI at Work, I'd love to introduce Isar Matis. Isar and I were connected through, through some of our faculty with the Chief AI Officer program. That was Sean David. He said, hey, you got to check out Isar's podcast. And I did. I listened to Leveraging AI, and I still do to this day, and it's on my. There's only three that I listen to, and Isar is one of them. So if you're not a subscriber to his Leveraging AI podcast, I would encourage you to he. I'm going to be a guest in the future, and you'll get to see it firsthand. But he really knows how to get the information from the guests, so. So it'd be a lot of fun. So, Isar, there's a lot about you, but if you don't mind, just take a second and kind of let the audience know what they know, what they should know about you before we get started.

One second.

You can take more than that.

A few. A few. Three seconds. Awesome. Yeah. So my background, I started my career as an F16 pilot. Actually, that was the very first career I had. I've done that for about a decade. Then I joined a small tech startup that did training and simulation solutions. And that's what brought me to the us. We won some interesting contracts. We're part of the JSF project, the F35, and some other interesting things. And I've done that for about a decade, leading that company into growth here in the US market and in North America in general. And then I left that company and started my own tech startup, creating a new kind of technology for the affiliate marketing world. And pretty early into that Process. My investor, my main investor back then came to me and said, hey, I really like what you're doing. You're really smart. Can you come and help us start an e commerce platform for our company? So he was running the largest wholesale travel company in the US at the time, the third largest in the world, but they didn't have any e commerce arm. And he said, well, you know, you understand all this e commerce stuff, maybe won't you come and help us with that? So I told him, you know, I'm running a startup that you're paying for, so maybe it's not a great idea. I said, no, no, no, you're smart, you'll figure it out. I wasn't smart enough. So I always laugh that that was the first nail in the coffin of my startup. But the e commerce platform we built for their company, I pulled the team together. It was an amazing team of really talented people. And within about five years we got that part of their business to $100 million in sales building a white label e commerce travel platform. And then the bigger company like the Mothership got sold. It was a huge international merger. We merged with our two largest competitors under a private equity that bought all three. It was a. I'll keep it simple, an interesting process that I'm not sure I want to repeat again in my life. And I really did not like the outcome. Even though on paper I got everything I wanted. I got a fancy title and a fancy group and a fancy paycheck and I hate it every single day. So I quit and I left the company and I started another business that focused on helping companies grow communities, leveraging podcasting and live talk shows. And at the end of, towards the end of 2022, my business partner and I got into serious disagreements on the direction of the business. I sold my half to him and left. And then I started thinking what I want to do when I grow UP and. And ChatGPT showed up and as you say, the rest is history. So very quickly I started teaching courses and helping companies. And now I would say I focus on three different things. One is AI education. I have several different programs that I do, either courses or private classes to companies or hackathon for companies and stuff like that. Organizations don't just have to be companies. I do consulting and help businesses figure this out. And I have another tech startup that is in the AI world that I'm running as a side gig. But it's very interesting. So that's on a nutshell, me, in the last 25 years very cool.

So, you know, it sounds like it was perfect timing with the opening up all that bandwidth with your old business partner by selling him your half. And then all of a sudden GPT 3.5 shows up and you're like, wait a minute, I've got time to figure this out. What was that? What was that learning process? That. That aha. Or that oh moment. Do you remember when that happened?

Yeah, I think it was very, very early. Again, I had time, right. So I. I wasn't working. I was. I was thinking what I want to do next. I had a few potential clients doing the same thing I've done before, but I wasn't sure that's what I will continue doing. And, you know, you get to a fork in the road, you want to look at the other options. And I think very early. I started using AI tools before, so I used Jasper before that. I use Descript before that. So these were early signs to me that this thing is interesting. It wasn't defined as AI, right. It was these magical tools that could do cool things very, very quickly. But when GPT 3.5 came out, I'm like, this is interesting. And I had time to find other people that do cool things with it and have conversations with them. And so I think very quickly I understood this is going to change more or less everything we know. And the interesting thing is, can I open parentheses for a second and talk about something? Of course. Completely different. I don't want to hijack your interview. No, no, no.

This is. We're just, we're just having a conversation. It's fun.

Awesome. So, yeah, something I have these. It used to be four laws that you need to know to be successful in the AI era, which I taught in all my courses and so on, and literally came up with the fifth last week. And it's directly related to GPT 3.5. And I call it the law of continuously improving compromise. And what I mean by that is you and I both talk to a lot of people who try to figure this out from a business perspective, and in many cases you can show an incredible demo that will blow people's minds of doing something with AI. Like, holy crap. But then when you try to actually do this in a business context in a consistent way, it just doesn't work well enough. And then you have two options. You can go down the path of, this is bullshit. I don't know why people invest time in this. This was a total waste of the last two weeks. I was trying to figure this out when this is Ready? Let me know.

Yeah.

Option one, which I'm sure people taking that. And there were definitely a lot of people taking that path when 3.5 came out. Hence why it's related to my previous point.

Yeah.

And the other options to say, you know what, I'm willing to compromise here because I understand that yes, I cannot get the full enchilada I wanted, but I can get 50% of that, 20% of that. Yeah, I could do 20% of what I wanted consistently, effectively, and in a, in a way that will work in a business with a procedure and a process and everything around it. And I know it's a compromise, but the reality is two things are going to happen when these systems gets better. You will have to make less and less of a compromise, hence the name of the law, the continuously improving compromise. But you gain two things. A, right now you're gaining those 20%, sure. Right. So you didn't gain the whole thing, but you're gaining a 20%. But the other thing you're gaining, which is maybe more important, is you're getting the understanding of how to implement these tools in a business context. It's not just the tool, it's the tool, the process, the training, the people, the skills. Like all you figure this out and because you figure this out when the next system comes, and now it's a 40% savings, you're up and running in a day because you already figured it out. If you're going to wait for this thing to be perfect, whatever that is, like, I don't know where, where's the line? We're like, oh, this now it does everything I need.

Now I can use it.

Yeah, now I can use. But then you have to figure it out. You have to figure out what tools you want to use, how you choose the right tools, how to implement it in your business, how to develop procedures and guidelines and guardrails around it, how to train your people, how to hire the right people. Or like, you have to then start the process, which means when that moment happens, when it's good enough for your expectations, you still have six months to nine months to actually do this effectively in your business, which means you're losing even more time. So the reason I put the slaw in place of continuously improving compromise is to tell people, start now. Going back to now, I'll close the loop. When 3.5 came out, I'm like, this is really cool, but it doesn't really do this and it doesn't really do that. And when I try to do this, it does it 50% of the time and I sometimes don't know which 50%. So how do you. But then I started figuring out the small use cases was very, very helpful. And as the Systems improve and GPT4 came out and Claude came out, and Gemini and Copilot and all these tools and of course third party tools that do really cool stuff that are built on top of that, then you run a lot faster than anybody else because you already have the muscle on how to implement this system.

That's a perfect way to look at it. So folks, essentially my takeaway from that is start small, start with that 20%. And if that's the. But here's exactly what Isar said when, when they released the next Update. Now it's 40%. You're already in motion, it's already part of your business, part of your process. So instantly you're able to get that, oh wow, things are faster, better, you know, cheaper now. I love that. And one of the things that is interesting about you as compared to other guests is that you're seeing under the hood of a lot of businesses who are like, they're ready to take the leap into AI. And a question that I had this morning as I was thinking about some, some things we could talk about is where do you like? I'm sure it's different now than it was, say even six months or three months ago, but when you go to a company, where do you start? How do you know where to start with a company? We'll be back after a quick break.

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I think that's the million dollar, billion dollar, trillion dollar question, depending the business you're talking about. Right? That's what everybody's asking. And I always look at it from several different directions at once. And it's mostly I'll talk about the two conceptual starting points and then I'll talk about the way to get there. And so the two conceptual starting points are top down and bottom up. And what I mean by that from a top down perspective, you gotta look at your business strategy and really think deep on how your business, your customers, your suppliers, your industry are going to change in the next. And again, some industries will change stupidly fast. If you're writing code or if you're in a call center, well, you have bigger issues and faster issues to worry about than if you're a doctor. Right. But what is going to change in your industry in the next six to 36 months? Right. And it's going to be dramatic regardless of what you do. But you got to think of it from a strategic way. And if you, if, if you own the business, you have to think, what will my clients be willing to pay for in three years? Now some things will go away and erode because it's going to be, I don't need you, I can do this in six seconds. Why would I pay you $200 or $20,000 for the thing or the service that you're providing? Some of the things new doors are going to open of stuff you couldn't do before. I'll give you a perfect example. In my very first course that I taught like serious business people was in April of 2023. So it's just over a year ago.

Congrats.

One of the people in the course, by the way, I've been teaching two courses a month since. And when I created the first course, I invested a lot of time developing the course, thinking, I'll develop a course and I'll be done with it and then I can teach it again and again and again. It happened exactly zero times. Every time, literally twice a month, I go and update the course because new stuff comes out. So that idea of like, oh, do it once and then you can sell it again and again and again did not work exactly as intended. But I'm still at it. I'm still teaching two courses a month, but I'm putting that aside for a second. In the very first course, I had the CMO of Deloitte Israel as one of the participants in the course. So one of the examples that I gave was from Deloitte. Why? Because A, she was there and B, everybody understands what Deloitte does, at least on a high level. So I don't have to explain. And the exercise that we did is we reviewed Deloitte's future offering using AI. That was a large exercise that we did with a group. And the, the example that I showed them in the end, after showing them the whole process that I did, and then they went and did it themselves was. There are things that are going to erode. Doing tax audits is probably going to go away to close to zero. Nobody's going to pay you $2 million to do tax audits. They may be $20,000 to review what the AI did. Yeah. It may not happen today. In the next 36 months, it will happen. Same thing for legal audits, same thing for a lot of stuff that Deloitte does. The flip side was let's start offering AI implementation services. Now, that was April of last year. Accenture, which is another Deloitte, Right. At the end of Q1 this year, shared how much money they made from AI Implementation Consulting. Do you know what the number is?

$1 billion? Was it 600 million? Q1?

$640 million in one quarter?

Yeah.

That's 2.5 billion in a year. And that's the brand new first year they're. They're doing it.

Yeah.

And so for every business, it's exactly that question. What services or products that you're selling right now are going to become less attractive, eroded to an extent, or completely irrelevant anymore in three years? But on the flip side, there's two questions you need to ask. One is what new services or products you'll be able to sell to existing clients? And the other is what new clients you will be able to serve because of these tools. So one of the things we did in the Deloitte exercise, which I haven't seen anybody do yet, but I'll be surprised if it doesn't happen, I'm like, if Deloitte trains a model on everything Deloitte has ever done, which is a stupid amount of data on companies from all over the world, different sizes, different industries, different whatever, they can create a Deloitte consultant in a box. Yeah, Deloitte. Currently, their overhead to start a project is probably $250,000. Like, they will not do a project of less than $1 million because just doesn't make any sense. So I assume what they're going to do, train a model, use it internally first, figure out that it works, and then now you can serve John and Gina's interesting shop that makes half a million dollar a year. Because to use that bot is going to cost you $15,000. Now you have a blue ocean of companies you couldn't serve before, period, that now you can serve because the technology enables it. So three questions. What things are going to erode or disappear completely? What new services or products I can sell to my existing clients? What new kinds of clients I'll be able to serve because this technology will enable it because of whatever. Like my overhead is going to be lower, the things I can offer are better or more adapted to that, whatever the case may be. Right, sure. So this is a question from a strategic perspective. So I'll pause here for a second in case you want to add, and then I'll go to the other two things I wanted to say.

Those are considerations that aren't normally hot topics in a strategic conversation because in the past there hasn't been something that could disrupt things so quickly. Yeah. So you could plan three years out, five years out, 10 years out, depending on the industry. But you just woke me up to a big. So my whole thesis is that we target SMBs because they're underserved, because they can't get the attention of where all the consultants are, but they, because they can't afford them. And it's not worth the consultants coming down to the SMB level. But a bot changes that completely. So I need to be prepared for these bots being produced and entering essentially what has been Blue Ocean for my target, which was SMBs.

So I'll be really, really surprised if it does not happen.

It makes perfect sense. Absolutely.

And so that's the strategic side of it. Right. That's the top down approach that the leadership team, whether it's a board of directors, board of advisors, chiefs, VPs, like whatever you have in your company, that is the people that make the decisions. So this is the top down, the bottom up. There's an endless number of low hanging fruit opportunities that you can start harvesting and benefiting from today. And getting there just takes the right understanding knowledge, the right structure, the right processes in order to figure out how to do this. But it's not rocket science. Again, I teach that in my course. And then people can be up and running and there's a lot of other people, I'm sure you as well teach people how to do that. The thing there, the first thing you got to make sure is that you define guardrails and guidelines of do's and don'ts. Because people can do really bad things for your business if they don't understand the limitations, the disadvantages, the things to be aware of. But once you define that, give people the tools and let them go wild within a structure, within a process on how to actually do things better on the day to day. So if you do these two things, you, you gain both benefits. Like you're going to be ready for what's coming in six to 36 months and you're going to start benefiting tomorrow from small little efficiency benefits. Now the question is how? Right. And the how is assessments. Right. You need to do a strategic assessments, you need to do a skill gap assessment. Meaning, okay, to do these things that I want to do in six to 36 months, what skills do I need? Not what professions, what skills do I need? Because that's going to be the way the world's going to work moving forward. And then how many of these can I train internally, how many of these I want to hire for? Either because it's faster or because I don't think I can train for that. So this is the second assessment. The third assessment is low hanging fruits, which again, there's methodology and process and tools on how to do that evaluation. But once you do those, you take what you've learned in that assessment and you develop a plan. And the plan has, okay, these other people are going to do this. Here's what they're going to do. Here are KPIs that we're going to track. Here are the resources. I'm going to a plan like any other business plan.

Sure.

And then you start execute and evaluating as any other execution according to the plan and the resources and everything and the benefits you're getting from it and so on. But, but there's again, this is a very, very high level. I, I sure I spend hours with my clients doing what I just shared in five minutes.

So do you find like who makes that determination if you're going to do a top down or bottom up approach?

I think you do both.

Okay.

I think you have to do both. That's, that's the whole thing is that's why there's these two separate assessments dealing with two separate things. Like you want to gain the immediate benefits, but you also want to figure out the long term.

Are you as you're having these Because I know that you, you enjoy like the in person the hackathon environment with the companies. I would too. That'd be fantastic because like the energy in the room would be having all of these people have those aha moments. Would be very fulfilling to facilitate that. Are you noticing since April to today, a year later, has the literacy kept up with like as you'd expect it, hey, it's now a more common conversational topic of AI. As a result, more people know about it and they're capable with it. Are you finding that businesses have just kind of been static as far as their, their learning on AI and they're waiting for somebody to show up and tell them what to do.

So it's a great question. I would say it's on a case by case basis. So I think it very much depends on whether the people on leadership really believe in this and are. Maybe forcing is the wrong word but. But making the organization be more serious about it versus the ones who either don't understand what the capabilities are or didn't have the ahaha moment or really just have other things they're more busy doing. But I'll say two things. One, I get to speak on a lot of stages and I get invited to different conferences. None of them are AI conferences. They're other conferences who want somebody to speak about AI. I either do the keynote or like a whole additional day, a day added at the back of the conference, pay another X and you can stay and do that day. Like I'm doing all these kind of things and I start each and every one of those speaking gigs asking the same exact question. And the audience sometimes is 50 people, sometimes it's a thousand. Right. It just depends on the size of the conference. Sometimes it's more and the ask people. I'm like I'm going to give you four buckets of level of knowledge in AI. I want you to raise your hand in right Bucket. Bucket number one is I'm a complete beginner. Like I may have gotten, you know, a login to ChatGPT. I played with it a few times but I haven't really used it in any way. Bucket number two is I have some experience. I've been using ChatGPT maybe another one of the tools, but not in a business context. Like I can see it, I know it, I understand, helps me figure out what to make for dinner or plan a trip, but I haven't figured out how to implement it in my business. Bucket number three is I have several different processes in my business, in my company, in my area of expertise, whatever the case may be for the individual that I'm using AI at. And bucket number four is we have systems, processes, community, like all that stuff set up in the company and we know what we're doing and AI is a major initiative and then ask people to raise their hand.

Yeah.

Still to this day, like again, I do this frequently, several times, at least once, usually twice, sometimes three times a month. I speak in these conferences 75% ish, still self identifies one of the first two buckets. So I think that's a better understanding what's the current status versus going to a company because the company I visited two weeks Ago or a week and a half ago in California, the CEO, highly committed. Coo, highly committed. Several people in marketing, highly committed. So they are at the most advanced level I've dealt with so far by a big spread, but I don't think that's common.

Yeah. Well, just out of curiosity because like we are a. AI forward or as they. However the word is we use AI in our business.

Yes.

So individuals like that California company, what are they looking for you or an AI expert to come and do for them? If they're already like they're thinking in AI, they're using the tools, they've got the processes, what is the lift that, that they think an expert like you is going to bring to the table for them?

It's a great question. I would answer it there. There are three different aspects. Aspect number one is really a more thorough, structured evaluation process. Okay. Right. So they. I what I shared with you, I shared with them. They listened to the podcast. Like, it's not a secret. I literally share everything I know. Like I never.

I'm the same way.

Like I, I have a podcast, YouTube channel, I do LinkedIn lives. Like I literally share everything I know, but there's a difference. I'm gonna quote, this is not me saying. There's a guy that I had on my previous podcast who also has his own podcast, name is Adam King, is from the uk. Brilliant consultant. Not an AI consultant, but a brilliant consultant who wrote a book, who shares his entire process A to Z, like everything, soup to nuts. I'm like, Adam, why would you do that? That's literally giving away the farm.

Yeah.

And he gave me a sentence that's absolutely brilliant. The fact that it's simple doesn't make it easy. And. And it's the same way. Right. So knowing what to do and actually doing it in an effective way are two very different things. Add to that the fact that every single business I talk to or every single business I ran or every single business I partner with in the last 25 years was always at capacity. Sometimes that's the way it happens. Which means every person in the business has a full time day job and then some. So they don't have the time that I have to go and do the evaluations and investigations and alignments and all these things that are required to really dive deep into each and every one of those things. So just even on the evaluation step, you gain a huge benefit by having somebody who has A, a lot more expertise, B, a lot more experience. Because it's not the com. The first company he's doing it with and see time.

Yep.

To do this. Now the other thing that it does, and I always joke about this, but it's true. Half of what they pay me for, I don't know if half a percentage, a double digits percentage of what they're paying me for is being an accountability partner. Right. There's a meeting every Tuesday at 3pm with these two people and they need to prepare this thing for the meeting. They will do it. Yeah. And if I'm not there, again, they have other stuff to do. So they will do it. But instead of doing it in a week, they will do it in three months. Yep. And so that's the other side of that story. So. So one side is doing the evaluation thing, the other aspect is the implementation side of it. Yeah. Again, because this world is moving very, very fast. Keeping track of what's the best way to solve problem X versus problem Y is something that is difficult to do unless you hire somebody to do that. That's perfectly fine. A lot of companies have a chief AI officer. Hopefully that guy keeps track of what's happening and makes suggestions. I suggest to every single company, whether you're people, listen to my podcast, take my course, hire me as a consultant, is to start an AI committee. One of the things an AI committee has to do is to keep track of what's happening. But still these are people that have full time day jobs. And so having another person for a period of time, this could be six weeks, this could be a year, it doesn't matter. That can help you through setting everything up, understanding what tools are out there, knowing what other companies are doing, having connections. So one of the things that I have right now that 99% of the global population doesn't have, probably a few nines after that, is knowing a lot of people like you, people who are better than me in specific niches of AI implementation. And when something I don't know, I'm like, okay, here is Jim, here's Gina, here's Jack, here's Javier, here is whatever people from all over the world who are experts on this thing way better than me, hire them for six weeks. Yeah, I'll be back after that. To help you connect that with everything else or in parallel to that. So there's a lot of aspects, if you try to do it in house, you, you can. It's just going to take you four times the effort and four times the time. And so you might as well pay somebody. Yeah. Half of that money you would have spent during that time and condense the process and get faster, better outcomes.

So there's people that are going to be listening to this, and they're. They're in that bucket, one or two that you mentioned, right. They're like, we're going to get to it. We've just been busy. Right. We're going to address it at the next quarterly meeting or whatever. So, you know, people ask, am I falling behind? And I've got kind of two opinions on that. One is the tools aren't that hard to learn. Right. So if you spend an afternoon with any tool, you'll be as good as you need to be. You may not be a power user, but you can now use it in your business. So there's not a big learning curve on the tools, but if you're not thinking about how to deploy them, I think a quote that I saw was from McKinsey, it's not about the tools. It's how the tools fit together. And what you understand is how the tools fit together. And that role that you talked about with the committee and those things, their job is to understand how the tools fit together. So we've got this short learning curve for. For learning the actual tool, but a long learning curve for how do these categories of tools fit together. So if somebody. What would be your rebuttal? If somebody says, hey, there's. There's no rush. Plenty of companies aren't using it yet. Why do we need to, like, why do we need to get started today? What would you say to them?

It depends if they're motivated by carrots or by sticks.

Okay.

But. But the answer is the same answer. Somebody in your industry is going to figure this out, and they're going to run a lot faster than anybody else.

Great.

Now, if you're motivated by carrots, you can be that company, which means you can run faster than any body in your industry or your niche or your region or whatever it is that you're competing with, which means you're going to win more business. And I'll dive into this in a minute because I have a lot to say about this. The sixth one is somebody in your industry is going to figure this out before you and is going to eat your lunch. And so. And the truth is, they're both probably true.

Yeah.

Because very few niches have two companies. There's 20, 30, 50, 251 thousand that do the same thing that you do. It's very rare that you live in this kind of like, you know, Monopoly duopoly universe. And so Other people will figure it out, some better than others, some faster than others. You probably want to be one of the people that figure it out faster and better because you're going to gain market share. And now I'm going to talk a little bit about what that means. What that means is you'll be able to do everything in your business. Everything. Marketing, sales, customer service, strategy and data analysis, decision making, all these things better and faster and in many cases cheaper.

Yep.

Than the way you're doing it right now. So there's the old joke right in the project world. Faster, better, cheaper.

Pick two. Pick two. Yep.

Now you can actually pick all three.

Yep.

For the first time realization ever. Yeah, first time ever. You can do faster, better, cheaper, but only with AI. You have to helping you in initially the bottlenecks and then everything else.

Yep.

But you got to figure out how to do this and you got to invest resources in order to do this. And again, the problem that most companies have is they're quote unquote busy. Yeah. With their day to day. And I get it. I been the CEO of this is now my fourth company.

Yep.

I understand that there's always a short blanket. Always doesn't matter if you're a one person organization or 450,000 employee organization. It's always a short blanket. And then you figure out AI. So the best example is Klarna. Klarna.

Right.

Earlier this year came out huge international corporation, publicly traded, blah blah blah. Earlier this year they've developed a support chatbot with OpenAI together. So when you're that big you can, yeah, you, you can, you can work and hire them to, to work with you. And they've developed a chatbot that in the first month of its deployment answered 2.3 million chats, successfully removing the need for 700 full time employees, taking the resolve time from 12 minutes to about two and a half and keeping the same quality of customer service per customer.

Reviews better, faster, cheaper. All three.

Now they did it again. So now they had a press release this past week about doing the same thing in marketing. Now what they said wasn't popular. Yeah. But he basically said I cut my marketing team in half. We're doing more marketing campaigns than before and they're more successful per campaign.

It's hard to argue with cheaper.

They took the delivery time of a new campaign. So Mother's Day, fourth of July, whatever. From six weeks to no, from seven weeks to six days. Faster, better, cheaper. And if you can do this, those of you who haven't worked for large Corporations I have. Not a huge one, but again, like after the merger, a big enough one. If you haven't worked for these companies, you don't understand. They do not do anything fast. It's impossible to change. There's overhead everywhere. And if they can do it, like, if a company the size of Klarna can do this that fast, like within six months, tackle customer service and marketing at a level that, that, that is a dramatic shift on the actual EBITDA of the company. Yeah, they're saving again. They shared numbers. They're a publicly traded company. They don't have a Choice. They're saving $10 million a year cost on marketing right now. And that's probably going to get better. This is just after they started implementing it. 10 million straight to the bottom line. So if they can make that process and find a way to change, any company can.

You know, Matt, so here's the question. Well, there, there's the, the human first approach, which is, well, what about all these people's jobs, right? And that's something that, like, at first I was kind of. Well, it's just like that's how things are. Sorry. But the more I've thought about it over the months, I've realized that kind of going back to what I said, the tools aren't the hard part. But somebody that knows my business, right, has, has, like, they know that, that Judy has the keys and that on Thursdays we do it this way. Even if they're in customer service, they have some domain expertise that is valuable to me. There is a learning curve that had to transpire for that person to know these things. So the paradigm that I'm looking to define now is, okay, we don't need as many customer service people, but some of those people know exactly who our customer is. They know, like, common issues. Why would I get rid of them wholesale and just be like, okay, everybody's gone, and then have to bring in somebody and like, spin them up on who we are and our culture and all that. So how are you addressing the, oh, we don't need 700 customer service agents anymore. We need two. How are you addressing that?

It's a tough question. I'll give you the good, the bad and the ugly. Okay, the good, the bad and the ugly. The good is, it really depends on the very specific industry, your niche, your company, and so on. Meaning if you gain a, let's take a small number, 20% extra capacity across different teams because you know how to implement AI successfully, you have two options. One is to grow the business by at least 20%. Right. So if you are saying, okay, because I now have extra capacity, I know how to do better faster marketing, I know how to do better faster sales, I know how to do better faster delivery of whatever it is that you're delivering.

Yeah.

I can grow the business faster than I could before and I could benefit from that extra capacity because now I can do more with less. So if I'm saving 20% on efficiencies, I can grow the business by 30%.

Yeah.

That's the best case scenario. Yeah. The bad is, oh, I don't know if I can grow or I don't know how to grow fast enough. I will let go at least some of these people. Maybe I'll keep some because I've been in the company so long and they know the stuff. And like all the stuff you said, I agree with that 100%. So that's the bad. Right. Is just letting people go. I think that's a bad choice. I think most companies have right now ways to grow faster than they ever thought possible if they figure this out.

Yeah.

Meaning if you get that extra capacity, find ways in your strategic analysis process. We talked about this before. How to grow faster. And so that will allow you to benefit from that capacity and the skills you've already have with these invested in these people. So that's the bad. The ugly is on a very high level. I think we're. Yeah. Meaning as these systems get better and better, we will not have a choice. We will not have a choice. And I'll give you an example. There are several different tools today that do call center, chat and call. So voice and chat customer service pretty freaking well.

Yep. Low latency, like accurate answers.

Concept of contact centers in India, Philippines, Mexico, Colombia, like, you know, lower wage places that can serve you around the world. Follow the sun. Like all the stuff that they've been selling for years, which has been true, is gone. You have a customer service agent that knows everything, that can speak any language, that is up 24 7, that has zero latency, that doesn't fight with his spouse or his kids, that doesn't have a rough day, that was not pissed off but the previous caller and now he's already pissed and he's edgy and he's not going to be nice. In the same call that can be connected to your CRM, your erp, your financial systems. He can give you the refund that you're entitled to. It can upgrade your services that you wanted to upgrade. It can cancel your subscription in six seconds instead of five hours of agony. It can do all these things. Yeah. Better than a human person. Yeah. And it's gonna cost less than 10% of a human person. Forget about the company. Who's gonna use the product?

Me.

As the person getting the service.

Yes.

I want that. Yep. Because if there's something that drives me freaking crazy is having to tell the story again and again and again to five different people in five different departments until I find the person that maybe potentially can help me and spend an hour and a half of my life troubleshooting something that costs $20.

Yep.

If that can go away in two minutes with a machine, I want it now.

Me too.

As a customer. Yep. And so.

And four, I don't know.

I don't know if it'll be three years, five years, seven years. There are not going to be any call centers around the world. They will cease to exist.

The economics won't make sense.

Now take that to writing code, Take that to creating graphic designs, Take that to paralegals, take that to. And so on and so forth. And as we get closer and closer to AGI, this is going to be true for more and more things and both sides of the equation, the people who run the businesses who have to compete, let's say I'm a human lover, tree hugger, call me whatever, you know, optimist, rainbows and butterflies kind of person. And I want to keep my team and I want to keep them happy. And I do. I really believe that in my core. I'm a hardcore people's person.

Yeah.

I will run out of business.

Yeah.

And then I won't be able to help anybody of these people have a livelihood. So I will be forced to, to use more and more AI and let more and more people go or I will not be able to help any people in having a job and having a better life and so on. So I now if you, I don't know how, how gloomy you want to make this conversation. So stop me whenever you want to.

Nothing's off the table here.

I think the other half of that problem is, let's say I'm wrong. And let's say that applies for only 20% of the population. That 20% of population are white collar people who make between 150,000 to half a million dollar a year. So you're going to have a 20% unemployment on the people who drive the global economy. And when they don't buy, oops, everything stops. Everything stops. And so the ripple effect of that is not just oh, you know, more people are going to lose their jobs. It's something that we've never seen before.

Interesting.

So am I worried? I'm freaking terrified. There's literally nights, and I have three young kids and I'm like, okay, what, What I tell them to go to school for?

Yeah.

How do I prep my financials so I'll be able to support them through a bad decade if it happens?

Yeah.

I don't have good answers right now. And the really scary thing, I don't think anyone has good answers. And yet I don't see this as a future we can avoid.

I, I don't. I'm not. I've got no arguments with that. And the, the first question that comes up is, then why are they pushing so damn hard for AGI if that's going to be the impact? Is it just the, the, the hubris of being able to say we did it first and just everything else is like, oop, you know, Rome is burning behind me.

I think it's a combination of that. So, yes, a big part of it.

Is that that's dangerous.

Like, we're going to get there first. The other half is, I think some of these people, some. I don't know if all of them truly believe that the benefits of having AGI overcome the disadvantages.

Oh, wow.

So they're saying, okay, what if this will allow you to do whatever you want every day of your life and it's going to generate enough food, enough money, enough health care, enough energy, enough. No more disease, like all these things, so you can do whatever you want and, and life is going to be the best it has ever been on this planet. Now, do I see that as a realistic outcome? I don't know. There are much smarter people than me, then at least talk that way. I don't know if they truly believe in that. I would like to think that at least some of them truly believe that.

You know, I guess for me, man, I'm okay if the cliff is ahead of me. Like, I'm enjoying what I'm doing with AI today. So it's, it's benefiting me. But that is an area that like, like this, this is basic stuff we're talking about on using AI at work. Hey, how do I use AI at work? Rarely do we get into, oh, now that I've AI ified my entire job, what does my future look like a year from now?

Yep.

And. But it's. Nobody's got the answer. And it's one hell of a question that we all should Be asking. So let me, let me. Okay, so put yourself in that situation. How do we as like AI experts, quote unquote, specifically about generative AI and business application. How do we position ourselves so that. Because even if this comes out, people still like, okay, what do I do with it? Right. It's the simple, not easy analogy you gave earlier. How do we as AI experts prepare for that and position ourselves? What is that narrative? Like, hey, we're still relevant. What does that look like?

Again, I think it's going to be, first of all on a case by case basis.

Okay.

I think different industries, different countries, different social agreements and different cultures are going to play a big role in that. Like, I think it's going to be very, very different, which means it will take longer in different industries and different niches in different areas around the world and, and so on. I don't think it's going to be like flipping a switch and then like, holy fuck. It's going to be a gradual process and if we're lucky, then the parallel process of figuring it out will happen roughly at the same speed. I not that optimistic. But if we're lucky, the, the, the roadblocks that are going to slow it down, whether it's government regulation, whether it's citizen revolt, industries that are more problematic right now, whether it's rev, whether it's. Whatever the case may be, there's going to be things that are going to slow it down. And these might be the things. Again, I don't know, I don't have a crystal ball, but these might be the things that will slow it down enough for us to figure it out. Again. I wish I had a good narrative. All I say when I have these conversations, which is not a lot, usually my conversations are, here's how you do this, here's how you do that, here's how it's going to solve that problem here, how you implement it. Here's the process, here's how you evaluate like all. That's most of the conversations. But when I have these kind of tough conversations, I love having them because the more people know.

Yeah.

The more people know that this might be coming. And some people will say there's a 2% chance, some people say there's 100% chance. And most of the people don't have a clue, myself included.

Yeah.

But there is a chance that this is where we're going into. The more people know about it, both at our level as well as governments, as well as international bodies, the higher the chances that we have to Potentially slow this thing down. I don't think you can put it back in a box. I think that's not happening. But I think if we start thinking about solutions to these bigger problems and in parallel, try to slow this down enough so maybe we catch up before the big catastrophe happens, then. Then that's the right thing to do. So I think education on that is important.

So if any of you listeners have the answers, please email Isar and myself. Yes, the future looks like for sure. Oh, man. You know, I'm glad that we. The conversation actually went there because. Yeah, so, yo, I've saved time. Oh, I'm making more money, whatever those wins are. But if you're not. This is a strategy mindset. If you're not thinking about three to five years down the road, like you're going to get blindsided by something, and this is the most likely. I mean, the predictions for AGI being reached by the end of this decade, like most people think, hey, that's very likely. Right? Super intelligence, different story. But AGI 2029 is the year that I'm hearing from everybody from Elon Musk to Kurzweil to Diamandis, all these people, right? That's not that far away. So if you're listening to this and you're just getting into AI, please don't let. Don't let what could happen in the future stop you from participating today, because your participation today can actually impact the direction of things in the future. You can be part of that solution that Esau was just talking about. So this has been a fascinating conversation you saw. And for those of you listening, the. No, no bs, this podcast. I thought about doing a podcast for years, just seemed like a lot of work. But Isar was kind enough to host me at a lunch when I was in Orlando in October of last year. And he looked at me and he said, the number one thing you've got to do is start a podcast. And I'm not kidding, man. It took me a couple months to get things dialed in, but that conversation was the reason that I was like, okay, finally, like, screw it, let's do it. Let's go. So thank you for the push there. And, audience, if you've enjoyed any of these episodes, you can thank Isar for being the catalyst to getting this off the ground. So, Isar, you've got a lot going on, and I'd love for people to be able to plug into you, because I've gotten a lot of value from the content that you create, the perspectives that you hold and all of those types of things. What's the best way for somebody to get into your ecosystem? Yeah.

First of all, I'll say I feel like a proud dad now when.

I. Loving it. Thank you.

I appreciate you sharing it. I think it's awesome that you're sharing your knowledge through this medium with people. I'll say another thing, like, if you're listening to this podcast, like the Using aiwork podcast, and you're enjoying it, pull up your phone right now, rate it on your favorite platform, give it a review, and hit the share button and share it with 4, 5, 6 people that you know that can benefit from it. Do that. Like, it's.

Thank you.

It's not a given. Like, it's a lot of work to do this thing, and if somebody's working for you and you find it valuable, that's your way to give back. So. So do that now. How people can find me. Yeah.

Thank you.

The easiest way to find me is on LinkedIn. My name is Isar Matisse. It's not an easy name, so you spell it I, S, A R, and the last name is M E, I, T, I, S. The benefit of having a not easy name is that I'm the only isara Matisse on LinkedIn. So found me. It's me. So that's the good news. Another way to find me is my company name is Multiply, but it's spelled with an AI in the end instead of a Y. So it's M U, L, T I, P, L, A, I, and it's AI as well. So Multiply AI. You can find our courses, you can connect with me over there, but you can do all these things on LinkedIn as well, which is probably the easiest way to connect with me. The podcast, as Chris was kind enough to mention in the beginning, is called Leveraging AI. There are two shows every single week and one show on Tuesday. That is an interview that is very tactical and practical on how to do things in your business. And then a Saturday news of what happened in the big stuff. Like, there's always a gazillion things that don't make it in, but the big stuff that happens every single week to keep you aligned with what's really happening. And that's it. I think these are the best way to do that. And as Chris mentioned, I teach courses and I do consulting. So if you're interested in any kind of those, find me on LinkedIn. Let me know. Drop me a note. I'll gladly talk to you. But there are, I will say Something important. There are a gazillion ways to do it right now.

Right.

It could be Chris, it could be me. It could be courses by the big players, the Googles, the Amazons, the Microsofts, the MITs of the world. And there's a lot of people like us who teach courses and do this education. It doesn't matter which one you pick or which few you pick. That would be probably a better thing. Start.

Yep.

Like, don't be afraid of this thing. Don't put it in the bottom of the pile. Start. Because it will change your industry, and you could be one of the leaders or you can fall behind. It's your choice.

And on. On that, I want to. A couple of episodes ago, on leveraging AI, Isar kind of walked through all of the ways that he helps companies. So if you're interested in engag them, listen to that episode. It was maybe two or three weeks ago. It wasn't.

Yeah, something like that.

And another cool thing is that Isar does his podcast interviews. He does them as live casts on LinkedIn. So if you ever see, like, you're scrolling through LinkedIn on a Tuesday and you see Isar, that's what's happening. It's a live recording.

Thursday at noon Eastern. Every Thursday, noon Eastern.

Yeah, every Thursday, noon Eastern. I've caught. That's how I found. One of the first guests that I saw on that was Ashley Gross. Yeah. She's amazing. And now Ashley's been a guest on my podcast. She. I got her a speaking gig at that event that I invited you to in Austin. So. And guys, as you plug into these things, you can see Isar is approachable. Like, he didn't know who I was. In Orlando, we had a mutual friend. I reached out, he came and picked me up at the hotel. Right. Like, we went and had lunch. Reach out to. This is the perfect time for you to be building your network in this space because, like, like, nobody's an og. Isar's an og. And he's only been, like, he's got six months ahead of you or a year ahead of you or whatever it is. Right. Like, but you can see that all of us, there's very little ego at. In. In this world that we're doing. So please, if you've got stuff, reach out. Same thing with Isar. Like, if you love the podcast, go. And, you know, like, all of these things help all of us. It makes it to where Isar can now get bigger guests or whatever it is so that you can learn more. And the immersion idea of like just plugging in, getting started 100 that's the only way the learning curve starts getting chipped away at. So everybody, thank you so much. This is a fantastic episode. Esar I'm so glad. This was a long time coming and I I really think we could have kept going for another hour because I've got questions that I didn't get to, but wonderful stuff and maybe we can pick them up when I'm a guest on your show.

Yep. Awesome.

Awesome. Thanks everybody. Take care.

Thank you. Bye Bye.

Thanks for tuning in to Using AI at Work. Don't forget to subscribe for more conversations about how to use AI at work and a special thank you to our sponsor, Chief AI Officer for empowering businesses with AI education and training. Visit their website for a free AI Readiness Assessment and AI Strategy Guide to help you get started using AI at work. That's www.chiefaiofficer.com. so thanks to our producer Evan Desaulnier for making this episode possible. Follow us on Twitter at the handle usingaiatwork and visit www.usingaiatwork.com for free resources to help you harness AI in.