AI is Here to Stay: Trends, Challenges, and Opportunities with Kurt Stein

Today's conversation promises to be exceptional. Joining me today is our in-house expert, Tim Derrickson. Together, we are thrilled to welcome our special guest, Kurt Stein, for a highly anticipated discussion on AI. 

Kurt is the President and COO of DCT Strategy Inc. and brings 25 years of experience in technology. He specializes in AI, leadership, and digital transformation. 

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Host by: 
Scott Kreisberg - CEO & Founder of One Step

Produced by One Step Secure IT

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Transcript

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Now, here are the main topics for today's discussions.

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AI's role in helping businesses achieve their goals.

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AI Technologies Integration Roadmap,

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AI as it relates to cyber security.

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All right, let's dive in.

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Hi, everyone. Welcome to One Step Beyond Cyber.

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My name is Scott Kreisberg and I'm the CEO and founder of One Step Security.

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I've been helping small and medium-sized businesses for decades and decided to create this channel

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so I could share both my and my guests insights on many topics surrounding safely living in today's complex digital world

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as well as great business growth strategy.

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Today's conversation promises to be exceptional.

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Joining me in a few moments is our in-house cyber security expert, Tim Derrickson.

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And together, we are thrilled to welcome our special guest Kurt Stein for our highly anticipated discussion on AI.

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Now, Kurt's the founder and president of DTC Strategy and he brings 25 years of experience in technology.

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Now, he specializes in future-proofing small and medium-sized businesses with practical AI solutions.

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All right, let's dive in.

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Let's bring in our guest today, Kurt and Tim and most of you probably know who Tim is.

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Tim's our in-house expert and how are you guys doing today?

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Fantastic.

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I agree with Kurt.

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Awesome.

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Well, you guys are not in the technology industry if that's the case.

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Just kidding.

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All right.

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Kurt, I know we've been trying to get this one in the can for a few months but life kicks in and I'm so glad

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that we finally get this one out to our audience.

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AI, it's impacting all of us and all of our businesses.

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So I'm really looking forward to this conversation.

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So thank you for joining us today.

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Thank you for having me.

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Absolutely.

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So, Kurt, just to kick things off for our audience, could you maybe tell us a little about yourself,

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what makes you tick, anything that would be sort of insightful for our audience?

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Sure.

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Sure.

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I like long walks on a beach and not skin.

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Yeah, if you've got time for that again, this is awesome.

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Well, my wife takes me out to the boardwalk all the time.

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Let's go walk and I'm like, okay, fine.

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As my dad would say, let's go take a long walk on a short pier.

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Yeah.

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Well, I mean, the boring stuff, technology for 26 years, I never thought I'd find myself

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here.

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It's pretty interesting the way life goes.

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You have certain ideas or plans or you don't know what you want to do.

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And it's funny where life takes you.

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It's that whole saying of one door opens or one door closes and other one opens.

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I started my career at UPS.

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Completely different in technology and I worked in the warehouses.

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It was a tough job, a great learning experience for sure.

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Absolutely.

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And that's when I found my way to AT&T.

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That's what started my career in technology is working at AT&T where I started learning

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about data centers and MPULAS technology, Internet circuits and all that stuff which I really

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didn't think about or didn't really know that much about.

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I got thrust right into it.

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And that's where I began in technology.

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And I spent the next 16 years at AT&T and I managed just a very large accounts.

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When I left AT&T that was in 2013, BlackRock was one of my accounts and I had a whole bunch

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of other accounts assigned to me.

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So just small accounts.

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But my response was, which one is that?

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Yeah.

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Well that's a big one.

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Yeah.

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So when you found yourself in that AT&T technology and it was a transition for you, did you

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just get bit by that technology bug?

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Because I know I sure did.

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Yes.

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Honestly yes and no, I say honestly because there's two sides to it.

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There are some that go on to research or building things and become very, very technical.

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I was on the technical sales side.

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So I tell you what was very enjoyable for me was the technology piece but also solving

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people's problems in something that was very cutting edge.

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That was of interest to me.

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And look where I am now.

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It's now it's an AI cutting edge, very interesting sales side helping people out.

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So that was the trajectory and that seems like that's followed me throughout my life.

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So I guess in that sense it's bit me in that side.

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It's almost exactly the same story or journey I've gone on.

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I loved technology so much and I can see that people were struggling with how to use it

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in an effective efficient way.

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So that's just always been where I come from.

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So on that note, as you may or may not know, our podcast is dedicated to empowering small

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to medium sized businesses which I know you do as well.

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And we do that through educational initiatives, sort of like this.

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And it's focused on achieving business success with the aid of technology which is what

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we just went over.

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So given that sort of context, how do you envision AI playing a pivotal role in helping

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businesses to achieve their goals?

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Great question.

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Wow, that's, that is the question that people are wrestling with today.

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There are tons of different opinions.

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There are a ton of people with, AI is going to take over the world.

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There's people saying we don't need AI in the business.

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I mean, there is so much, there's so much information.

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And I guess that's the other part of it that's pretty interesting like you just covered.

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It's, we're at the beginning right now of the next, the next revolution in technology.

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Right?

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We weren't around for the horse and buggy, right?

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And the cars, we were there for that.

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But we did get to see the dot com age, right?

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Sure.

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The internet age, the dot com age.

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We get to see the cell phones, you know, apple iPhones that come out to the scene.

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Everyone's like, wow, these smartphones are amazing.

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We get to see cloud technologies.

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And now here we are with, with AI the next, the next realm.

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And it's, it's absolutely fantastic.

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And it's got people very, very excited and very nervous at the same time.

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So, so it's a great question in a sense that, you know, where do you see things going?

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And, and, and I guess I come from a very positive outlook.

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I come from an abundance mentality, from a very positive outlook.

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But I am not naive in a sense that I don't realize or don't understand that, that their challenges,

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probably, that's probably the best way to frame it, right?

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Round out the eggs.

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There's challenges to everything.

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Like I just, I literally just put a post out probably two hours ago.

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It was on Reuters about eight open AI, saying that they stopped five, you know, cybersecurity

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attacks where people are trying to use their technology to be deceptive or use this, you

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know, the open AI platform for deceptive, deceptive means.

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This is, you know, that's the part that I'm not being naive about.

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It is there.

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It exists.

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There's definitely some bad things that can come out of this, like anything else.

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But I come from a positive standpoint, saying this is going to be a game changer for small

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and mid-size businesses.

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And what I mean by that is the following.

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Remember when they talked about the internet being, being able to level the plane field when

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it came to marketing.

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Back in the day, it used to be, if you didn't have a budget of $2.25 million to go work with

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the largest marketing firms in the world, you weren't going to get your company name out

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there, right?

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You probably cost you a fortune to put an ad in New York Times.

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It was non-starter for a smaller business to get into the plane field of the legacy companies.

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Sorry, the legacy company areas.

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So that was like a glass ceiling, I guess you could say.

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And then they came along and everybody said, wow, this is going to be up.

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A leveling of a plane field for small businesses to compete against a larger businesses due

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to that technology.

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And that's been a fact.

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And I have social media that allows companies, or you do podcasts like this to get your name

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out there to help more people, which years ago that wouldn't been the case.

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AI is going to do the same exact thing for mid-small and mid-size businesses, where it's

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going to allow you to compete at a much greater scale with less resources.

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And at a higher rate of speed, that doesn't mean that you should lay people off.

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That just means that if you haven't been hiring as fast, you might be able to do the work

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of five people with your existing staff.

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Then if you were to go out and spend the money for five people over a certain period of

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time.

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So definitely a great time for small mid-size businesses, as long as they understand how

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to work with it.

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That's my long answer to your simple question.

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Well, no.

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And you see the big companies are introducing it everywhere they can.

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So Apple has their big rollout this week and they're introducing their AI to their devices.

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So it's happening everywhere.

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Tim, what about you?

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Do you have any comments?

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Tim, I got a couple of comments actually.

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So what's really interesting, too, Kurt, and I agree with you, in the fact that there's a

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lot of good that comes with us.

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It also opens up new fields of work.

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When we talk about the internet, when we started doing marketing, all of a sudden we opened

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up SCO search engine optimization and started creating jobs, different jobs.

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So it's just more of a pivot than like you were saying, you don't like all your people.

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You might just need to put them in a different seat for a little while until you get a feeling

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of what AI is because you still need to put on those guard rails.

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And you really need to understand which large language model you're working with, how

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they're dealing with it.

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Some companies are actually starting to try and create their own mini pools to create

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their own chatbots, their own AI.

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So it's really exciting to see what's actually where it's moving.

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Yeah, I agree with you.

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Yeah, so, Kurt, when we were speaking and preparing for today's episode, you made an interesting,

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many interesting statements, but this one sort of caught my attention.

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And you said, you're seeing signs of AI fatigue emerging among businesses.

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Can you maybe expand on that a little bit?

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Yeah, yes.

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So, I mean, that comes with everything right in the beginning.

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So take, for instance, the division proglises from Apple.

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Yeah.

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They came out, everybody was amazed by it.

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Everybody started buying them.

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Right, they run it out.

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They see people driving cars wearing them, right?

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You start seeing all those huge clips.

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Yeah.

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We're walking by the street.

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You're like, what are they doing?

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What are they doing?

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And everybody loves that.

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You have those early adopters that rave about it.

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And then as time goes on, you start to get into something to complain, so, of dizziness.

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You start getting to complain, so it's too heavy, heavy on the head.

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It's hurting them.

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And you start getting a lot of returns.

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But the point of that statement is, in the beginning, there's a lot of early adopters

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that jump on and say, wow, this is absolutely amazing, which, you know, I'm part of that

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group.

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After those that say, I'm just, I just love it because it's new.

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There's others that say, I love it because I see what can happen.

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I'm part of that crew.

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And then over time, people say, you know, yeah, it was great, but it's not, I'm not really

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ready for it or it's too much money or don't really have the right use case for it.

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And then you start seeing people return to units, whatever, you know, reason it is.

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And then it takes some time for it to, it slows down, takes some time for it to speed back

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up again.

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Right.

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I see the same things with AI.

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It came onto the scene of November, 2022.

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It was absolutely amazing.

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I'm sure you guys been playing with it a lot, even chat GPT.

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Now you look at where it is.

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Now, you have view.com perplexity.

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I mean, just the list goes on and on of the tools that are out there.

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You have Elon Musk investing in Grockeye, right?

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You have all these different things coming out.

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You have Microsoft making billions of dollars of investments everywhere, Japan, Indonesia,

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in the Middle East.

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I mean, they're, they're throwing billions all over the place.

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You have this happening everywhere.

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The problem is with all that that happens, people do get overwhelmed.

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Those that are in the forefront, saying, look, I get it.

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I'm going to play with it.

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I, I understand the concepts of it.

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I see certain use cases.

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Let me tip toe into the water and figure it out.

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You have others that say I completely understand it.

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They're racing the build use cases, which an example of that is blackstone.

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I mean, they are, I think they have over 50 data scientists right now.

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You have a lot of GPMorgan hiring data scientists.

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You have some of these massive companies that are all in, right?

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All the chips are in.

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They are investing heavily there.

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I see some law firms now hiring data scientists as well to help on that side.

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But then you have others that are looking at saying, wow, it's pretty interesting, but I don't

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know what to do.

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I don't know where to begin or the business is running perfectly fine right now.

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And they're getting overwhelmed with all the media attention, every different LLM announcement,

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apples announcing something, Googles announcing something, it's just constant.

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And I'm sure even a couple of months ago, I remember in Google BARD when they had that,

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the issue with the bias.

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I mean, that was massive, massive hit to Google, but I'm pretty sure that any leader of an

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organization looked at and said, I don't want that to be my business.

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So I'm sure that did have some impact on some of the companies that are on the fence,

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you know, Google is starting to come back and fix things.

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But it becomes the, it's paralysis by analysis.

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It's overwhelming with all the information that's out there.

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And I don't blame smaller companies and midsize companies saying, look, let's just start tip

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towing in the water here.

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Let's see what's going on.

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But the business is doing really well right now.

00:14:27,340 --> 00:14:31,300
Why don't we just see what shakes out first before we jump in?

00:14:31,300 --> 00:14:32,300
That's what I'm saying.

00:14:32,300 --> 00:14:36,780
I mean, it seems like it's a larger portion of the use of ACE2.

00:14:36,780 --> 00:14:37,780
Yeah.

00:14:37,780 --> 00:14:43,500
And sometimes with this newer technology, it hasn't found its groove yet.

00:14:43,500 --> 00:14:50,180
It hasn't found where it's going to do, it's, you know, have its most impact.

00:14:50,180 --> 00:14:58,700
And like you said, with the AI goggles from Apple, or, you know, it's like, what are the

00:14:58,700 --> 00:15:00,340
real use cases of that?

00:15:00,340 --> 00:15:05,300
That's going to take a couple of two, three years before the developers get out there and

00:15:05,300 --> 00:15:07,940
really figure that out.

00:15:07,940 --> 00:15:08,940
That's very interesting.

00:15:08,940 --> 00:15:09,940
Yeah.

00:15:09,940 --> 00:15:10,940
I can totally see it.

00:15:10,940 --> 00:15:12,940
I can totally see the FIT now that you've described it.

00:15:12,940 --> 00:15:17,340
You know, the other part of the issue is you have catalysts, things that none of us can

00:15:17,340 --> 00:15:18,540
predict.

00:15:18,540 --> 00:15:22,020
Like we, we cannot predict what's going to happen in the future because it becomes a

00:15:22,020 --> 00:15:23,700
butterfly effect, right?

00:15:23,700 --> 00:15:26,820
One thing happens here changes this, changes that and all of a sudden, wow.

00:15:26,820 --> 00:15:29,660
I mean, that's how we got here from an AI perspective.

00:15:29,660 --> 00:15:34,500
You had some of the teams from Google that and ones that built the whole attention algorithm

00:15:34,500 --> 00:15:39,940
for AI, which allowed it to understand when you wrote something, it to understand what

00:15:39,940 --> 00:15:44,220
was written prior in order to give a response, a very human-like response.

00:15:44,220 --> 00:15:46,860
If it wasn't for them, would we be where we are right now?

00:15:46,860 --> 00:15:51,820
And the reason I say that is, anything can happen right now.

00:15:51,820 --> 00:15:56,420
Anything can happen in this conversation today says, okay, it might be two years or

00:15:56,420 --> 00:15:58,300
two years, but it's still working on use cases.

00:15:58,300 --> 00:16:02,700
And then somebody does something and it turns it on its head.

00:16:02,700 --> 00:16:08,380
For instance, one catalyst that's hanging out there and we, I've talked about a few podcasts

00:16:08,380 --> 00:16:10,740
and a lot of people have talked about it as well.

00:16:10,740 --> 00:16:14,260
Sam, Altman has talked about it and a lot of people talk about it as well.

00:16:14,260 --> 00:16:18,900
It's that AI first unicorn company.

00:16:18,900 --> 00:16:24,420
The company that starts with one person running AI and is the next unicorn.

00:16:24,420 --> 00:16:26,420
And that happens.

00:16:26,420 --> 00:16:31,540
Tell me how any other business can sit there and say, I'm not going to touch AI right now.

00:16:31,540 --> 00:16:37,940
If they just launch everything and run everything at scale using AI, it's going to be a catalyst

00:16:37,940 --> 00:16:42,460
that forces everybody to either use it, adopt it or be left behind.

00:16:42,460 --> 00:16:48,140
Yeah, it's a, it's a David and Goliath technology, like you said earlier, it is a, it is a game

00:16:48,140 --> 00:16:49,140
leveler.

00:16:49,140 --> 00:16:52,300
So, well, and also it could go the other way as well, right?

00:16:52,300 --> 00:16:56,580
And something completely that we have no clue is going to happen, happens and it turns

00:16:56,580 --> 00:17:00,060
it on its ear, the opposite way and everybody goes a different direction.

00:17:00,060 --> 00:17:01,540
So yeah, absolutely.

00:17:01,540 --> 00:17:02,540
Yep.

00:17:02,540 --> 00:17:03,540
Yep.

00:17:03,540 --> 00:17:04,540
Yeah.

00:17:04,540 --> 00:17:09,780
So, so tell me like, how do you approach companies through the integration process of using

00:17:09,780 --> 00:17:12,300
AI technology with their existing systems?

00:17:12,300 --> 00:17:17,100
Like do you have sort of a standardized roadmap or how do you approach it and what, what are

00:17:17,100 --> 00:17:19,780
some, some of the great stories you've gotten that area?

00:17:19,780 --> 00:17:20,780
Sure.

00:17:20,780 --> 00:17:25,740
So, as we watch it, we're watching how things develop as well and we also have to shift and

00:17:25,740 --> 00:17:28,540
adopt toward the user base.

00:17:28,540 --> 00:17:32,460
And Microsoft co-pilot has had us shift a lot as well.

00:17:32,460 --> 00:17:33,460
Okay.

00:17:33,460 --> 00:17:34,460
And I knew that was coming on.

00:17:34,460 --> 00:17:38,460
I knew that was going to be huge and Microsoft is a great company and look what they're doing


00:17:38,460 --> 00:17:39,460
now.

00:17:39,460 --> 00:17:43,260
They've made massive investments and just continuing and now you see Apple, you're doing

00:17:43,260 --> 00:17:45,520
the same thing with open AI, et cetera.

00:17:45,520 --> 00:17:52,440
So how we were approaching it was from a strategy, an AI strategy assessment.


00:17:52,440 --> 00:17:58,480
So it's a strategy and readiness assessment because we understood in the beginning, if you

00:17:58,480 --> 00:18:01,680
don't different than anything else, if you just jump into something and say, I want it right

00:18:01,680 --> 00:18:07,660
now without seeing if you're ready or understanding where you should do it first, you can spend

00:18:07,660 --> 00:18:11,840
a lot of money in this, you're going to spin your wheels and then you're going to be like

00:18:11,840 --> 00:18:15,400
most of those companies that run on by the product and they put it on the shelf and

00:18:15,400 --> 00:18:22,560
it's a loss in the business because they didn't realize they had to upgrade their databases.

00:18:22,560 --> 00:18:24,280
They had to upgrade technology.

00:18:24,280 --> 00:18:28,360
It's like when your wife comes to you and says, hey, I want to change the furniture in your

00:18:28,360 --> 00:18:29,360
room.

00:18:29,360 --> 00:18:32,360
And next thing you find out that, wait a minute, I have to change the rug, I have to paint

00:18:32,360 --> 00:18:33,960
the walls, I have to go crown molding up.

00:18:33,960 --> 00:18:36,000
I mean, oh my God, I didn't think about all this.

00:18:36,000 --> 00:18:37,000
Right.

00:18:37,000 --> 00:18:39,400
And it's the same thing when it comes to AI.

00:18:39,400 --> 00:18:42,560
If you think you're just going to turn it on and it's going to work, you're going to

330
00:18:42,560 --> 00:18:43,560
have a self-issue.

331
00:18:43,560 --> 00:18:45,920
Now, we're moving to co-pilot.

332
00:18:45,920 --> 00:18:50,080
What we're finding is companies already have Microsoft, a lot of companies use Microsoft.

333
00:18:50,080 --> 00:18:53,960
If you want to turn on co-pilot, you need assistance on that side.

334
00:18:53,960 --> 00:18:56,280
You need to train the model with your data.

335
00:18:56,280 --> 00:18:57,920
You have to make sure you're doing it right.

336
00:18:57,920 --> 00:19:02,880
Otherwise, you're going to be a situation where either it becomes biased, you put information

337
00:19:02,880 --> 00:19:04,280
out that you shouldn't.

338
00:19:04,280 --> 00:19:05,280
It's not working.

339
00:19:05,280 --> 00:19:06,280
It's intended.

340
00:19:06,280 --> 00:19:09,920
You could have an issue where you client see something that you didn't want them to

341
00:19:09,920 --> 00:19:12,880
see or respond to them in a way that you didn't expect.

342
00:19:12,880 --> 00:19:17,480
And now you're going to have agonia-faced, and that's PR is probably the worst part, having

343
00:19:17,480 --> 00:19:19,480
a negative PR situation is probably the worst part.

344
00:19:19,480 --> 00:19:22,560
So it starts with strategy and readiness assessment.

345
00:19:22,560 --> 00:19:26,800
We're finding, we're helping a lot of companies now from a co-pilot adoption standpoint, because

346
00:19:26,800 --> 00:19:31,000
they need their data within co-pilot and do it right.

347
00:19:31,000 --> 00:19:35,680
The downside is with small and mid-size firms, especially you guys can see, they don't get

348
00:19:35,680 --> 00:19:38,320
a lot of support from the larger companies.

349
00:19:38,320 --> 00:19:40,280
The Microsoft's in all these other world.

350
00:19:40,280 --> 00:19:41,680
They need help.

351
00:19:41,680 --> 00:19:44,520
And that's where we come in.

352
00:19:44,520 --> 00:19:45,520
Yeah, it's in.

353
00:19:45,520 --> 00:19:48,640
I'm sure there's going to be a lot of education required with it, right?

354
00:19:48,640 --> 00:19:50,520
So it's such new technology.

355
00:19:50,520 --> 00:19:56,760
I mean, what we do with cybersecurity and IT infrastructure and compliance, all that kind

356
00:19:56,760 --> 00:20:01,280
of stuff, people think they have it covered.

357
00:20:01,280 --> 00:20:09,400
And they think that they're all organized, and it's perfectly handled, but 9.9 times out

358
00:20:09,400 --> 00:20:13,120
of 10, we find out that it's not.

359
00:20:13,120 --> 00:20:18,920
And what you're doing is you're like, instead of just turning on this switch with co-pilot,

360
00:20:18,920 --> 00:20:24,800
that could cause a lot of problems, you need to come in and uncover what they really are

361
00:20:24,800 --> 00:20:25,800
trying to accomplish.

362
00:20:25,800 --> 00:20:30,000
Make sure that's the right tool for them and roll it out properly.

363
00:20:30,000 --> 00:20:32,800
That's the small guy needs that.

364
00:20:32,800 --> 00:20:34,680
There are some challenges, right?

365
00:20:34,680 --> 00:20:38,680
When you're running businesses, because you know that, you're aware of that.

366
00:20:38,680 --> 00:20:43,240
And sometimes customers are not that like, wait a minute, wait, why do I have to pay for

367
00:20:43,240 --> 00:20:44,240
this?

368
00:20:44,240 --> 00:20:45,920
But you didn't tell me what I should do.

369
00:20:45,920 --> 00:20:48,520
And it's like, you think about it from a doctor perspective.

370
00:20:48,520 --> 00:20:52,520
If you walk into a doctor's office, if you're knee hurting, you know, the doctor can't

371
00:20:52,520 --> 00:20:55,440
see a great, I'm going to put you in surgery tomorrow.

372
00:20:55,440 --> 00:20:58,120
It's a surgery for what, right?

373
00:20:58,120 --> 00:21:00,200
So he has to assess you.

374
00:21:00,200 --> 00:21:02,200
We have to physically check you.

375
00:21:02,200 --> 00:21:04,200
He's got to probably do an MRI, I can't scan.

376
00:21:04,200 --> 00:21:08,640
See what's going on first before you get into that situation before he opens you up.

377
00:21:08,640 --> 00:21:09,640
Right?

378
00:21:09,640 --> 00:21:11,800
And that is, you know, that is always a challenge.

379
00:21:11,800 --> 00:21:13,480
I'm sure you guys have run into it as well.

380
00:21:13,480 --> 00:21:15,000
It's like, well, hold on a second.

381
00:21:15,000 --> 00:21:20,480
Let's see what's happening first because you may not need all of this.

382
00:21:20,480 --> 00:21:23,520
It may be something very easy that you can now turn it on.

383
00:21:23,520 --> 00:21:24,520
You're ready to go.

384
00:21:24,520 --> 00:21:26,920
Maybe, you know, we find two is some companies.

385
00:21:26,920 --> 00:21:31,000
They think they have their data in order and it's, it's not, it's not in order.

386
00:21:31,000 --> 00:21:32,680
It's not ready.

387
00:21:32,680 --> 00:21:36,480
And you know, that's, that's kind of, that's kind of a challenge for them too.

388
00:21:36,480 --> 00:21:37,480
Absolutely.

389
00:21:37,480 --> 00:21:38,480
Absolutely.

390
00:21:38,480 --> 00:21:45,560
So we've kind of touched upon this a little bit, but are there any challenges that you commonly

391
00:21:45,560 --> 00:21:51,320
see are faced in adopting AI and you see them?

392
00:21:51,320 --> 00:21:55,240
How do you see them being addressed either by you or internally?

393
00:21:55,240 --> 00:21:56,240
Yeah.

394
00:21:56,240 --> 00:21:58,440
The biggest challenge is return on investment.

395
00:21:58,440 --> 00:21:59,440
Okay.

396
00:21:59,440 --> 00:22:05,240
So, so large companies and smaller companies both understand there's a cost to doing it.

397
00:22:05,240 --> 00:22:09,320
And it goes back to the earlier question of the, you know, analysis, you know, paralysis

398
00:22:09,320 --> 00:22:12,200
by analysis is like, well, what do we do in here?

399
00:22:12,200 --> 00:22:13,200
What's the right thing?

400
00:22:13,200 --> 00:22:16,440
Do we just spend the money and do something and not going to return?

401
00:22:16,440 --> 00:22:20,240
That is probably the biggest challenge is, is explaining the companies.

402
00:22:20,240 --> 00:22:22,040
How do they get that return on investment?

403
00:22:22,040 --> 00:22:26,360
And it has to start with, we need to understand your strategy first.

404
00:22:26,360 --> 00:22:27,360
What are you looking to do?

405
00:22:27,360 --> 00:22:28,840
What does your business do?

406
00:22:28,840 --> 00:22:30,960
What is the core goals of your business?

407
00:22:30,960 --> 00:22:32,680
And the best place to start is to start small.

408
00:22:32,680 --> 00:22:35,800
Do something that actually hits those goals.

409
00:22:35,800 --> 00:22:41,640
If your business is, I mean, everything is based on customer service, but if it was to

410
00:22:41,640 --> 00:22:46,280
return, we get back to customers really fast or have that, that, you know, they love deep

411
00:22:46,280 --> 00:22:50,920
technical knowledge and quickly and they don't want to wait for, to get a person on the phone

412
00:22:50,920 --> 00:22:52,960
to get answers to things.

413
00:22:52,960 --> 00:22:58,720
Maybe a chatbot with access to all your documents that can provide them in information

414
00:22:58,720 --> 00:23:02,400
instantaneously will be something that's fantastic for your business and it'll be a

415
00:23:02,400 --> 00:23:06,720
benefit to your business in great customer experience.

416
00:23:06,720 --> 00:23:11,280
But if it's, if it's not and you will spend money on that and your customer base is with

417
00:23:11,280 --> 00:23:15,240
the, I don't need this, you're going to be in a situation where you spend money and you

418
00:23:15,240 --> 00:23:17,760
not going to have a great, you know, a great experience on that.

419
00:23:17,760 --> 00:23:21,520
So return on investment, it's the hardest part is to, to speak to them, find out what they're

420
00:23:21,520 --> 00:23:26,480
doing and help them plan for what's the right way to move forward.

421
00:23:26,480 --> 00:23:31,480
And that comes back to being overwhelmed with how much information is out there, how

422
00:23:31,480 --> 00:23:36,240
many different tools are out there that they may or may not think they could just turn on

423
00:23:36,240 --> 00:23:37,880
and they're going to have a great experience.

424
00:23:37,880 --> 00:23:40,720
So that's where we spend most of our time.

425
00:23:40,720 --> 00:23:46,040
Yeah, you know, just from my own experience, you know, every business is trying to let

426
00:23:46,040 --> 00:23:47,360
these chatbots, right?

427
00:23:47,360 --> 00:23:52,640
They're all trying to start you off, like contact us, there's no phone numbers anymore.

428
00:23:52,640 --> 00:23:58,360
They want you to start with this, you know, chat with us now, but it's always a chatbot.

429
00:23:58,360 --> 00:24:02,840
So far most companies are not implementing that well, I can tell you that in my opinion,

430
00:24:02,840 --> 00:24:03,840
I don't know.

431
00:24:03,840 --> 00:24:04,840
Do you have any experience in that?

432
00:24:04,840 --> 00:24:09,240
I think I've actually seen a couple do it really well in the fact of, so instead of

433
00:24:09,240 --> 00:24:14,400
getting, remember the, the old days of voicemail or the, when they first started doing

434
00:24:14,400 --> 00:24:19,440
the push buttons on the phones and you'd get stuck in this navigation circle, you would

435
00:24:19,440 --> 00:24:22,520
just go in a circle and a circle, you'd never get that representative.

436
00:24:22,520 --> 00:24:26,520
And I think I see the same thing sort of happening with AI.

437
00:24:26,520 --> 00:24:31,280
You go down those, those rabbit holes and you can't get back out again.

438
00:24:31,280 --> 00:24:35,560
But I have seen a couple, I've seen two companies, I'm not going to say who they are, that actually

439
00:24:35,560 --> 00:24:40,680
after each interaction, it actually gives you the choice to go to a representative or

440
00:24:40,680 --> 00:24:43,920
try something else if you're getting the information you want.

441
00:24:43,920 --> 00:24:45,640
It actually works pretty well.

442
00:24:45,640 --> 00:24:46,640
Perfect.

443
00:24:46,640 --> 00:24:47,640
That's a good idea.

444
00:24:47,640 --> 00:24:51,280
Yeah, that's, that seems to be the, when I went back to you, you start small.

445
00:24:51,280 --> 00:24:55,760
I think that's where some of the larger companies saying, look, we'll get less pushback

446
00:24:55,760 --> 00:24:59,240
on companies, we'll start very small with the chatbot.

447
00:24:59,240 --> 00:25:04,960
That might be something that they will, they'll understand and say, great, let's start there.

448
00:25:04,960 --> 00:25:06,800
It's customer impacting.

449
00:25:06,800 --> 00:25:09,440
So a lot of people, a lot of companies are focused on that.

450
00:25:09,440 --> 00:25:12,520
I've spoken to a lot of large companies doing that.

451
00:25:12,520 --> 00:25:14,520
But that's a small way to start.

452
00:25:14,520 --> 00:25:19,800
I don't know if it's necessarily the best thing for your business to start in that area.

453
00:25:19,800 --> 00:25:25,540
When I say start small, the importance really, I think right now for small mid-size

454
00:25:25,540 --> 00:25:31,060
businesses, probably the smartest thing for them to do right now will be for them to understand

455
00:25:31,060 --> 00:25:33,140
what is best for their business.

456
00:25:33,140 --> 00:25:34,180
Where are they looking to go?

457
00:25:34,180 --> 00:25:39,020
What do they want, when do they want to be in five years from their goals, right?

458
00:25:39,020 --> 00:25:43,980
And then build little teams, internal teams, representatives from different groups or different

459
00:25:43,980 --> 00:25:45,980
organizations within their teams.

460
00:25:45,980 --> 00:25:53,340
IT, not just IT, IT, legal, HR, even if it's a small team, marketing, haven't set down

461
00:25:53,340 --> 00:25:54,340
and start.

462
00:25:54,340 --> 00:26:01,620
So, we start socializing where we think AI can fit in our business by having everybody share

463
00:26:01,620 --> 00:26:07,060
those ideas and bounce it off of what their understanding is of their business, their understanding

464
00:26:07,060 --> 00:26:09,260
of what their customers are looking for.

465
00:26:09,260 --> 00:26:14,660
That's a great place to start because that'll start giving them the insights into where

466
00:26:14,660 --> 00:26:17,380
they should really focus their energy.

467
00:26:17,380 --> 00:26:20,300
At that point in time, companies like us can come in.

468
00:26:20,300 --> 00:26:27,980
You've already socialized that, you started becoming an AI first company by doing so, it's

469
00:26:27,980 --> 00:26:30,540
not new to you, you have ideas.

470
00:26:30,540 --> 00:26:34,620
And then from Eric, be molded to the next step, which is great.

471
00:26:34,620 --> 00:26:36,140
Matt, you've talked about it.

472
00:26:36,140 --> 00:26:37,540
Matt, you understand it.

473
00:26:37,540 --> 00:26:39,180
Matt, you've discussed this internally.

474
00:26:39,180 --> 00:26:40,780
How do you use cases?

475
00:26:40,780 --> 00:26:44,300
Let's now write down to something that actually would be impactful for your business.

476
00:26:44,300 --> 00:26:48,820
Hey, and that approach is awesome.

477
00:26:48,820 --> 00:26:54,780
When you do that approach, let's say you have your different teams doing that, do you then

478
00:26:54,780 --> 00:27:01,220
come together so that rolling forward the technology can work with each other or don't

479
00:27:01,220 --> 00:27:06,140
worry about that marketing needs ways to engage prospects.

480
00:27:06,140 --> 00:27:07,660
That's what they're going to focus on.

481
00:27:07,660 --> 00:27:10,260
They can get an ROI on that.

482
00:27:10,260 --> 00:27:15,260
Accounting sees ways that they can send out bills much easier and faster and blah, blah,

483
00:27:15,260 --> 00:27:17,260
blah, regardless of what marketing is doing.

484
00:27:17,260 --> 00:27:19,260
Which, how do you see that?

485
00:27:19,260 --> 00:27:20,860
It's a great question.

486
00:27:20,860 --> 00:27:25,980
If you simplify it a little bit more, once you start socializing it, you build a list right

487
00:27:25,980 --> 00:27:30,100
of what is something that could be an immediate impact?

488
00:27:30,100 --> 00:27:34,500
And what's something that's nice to have, but may take some time.

489
00:27:34,500 --> 00:27:37,420
And if you rate that up, look, this would be fantastic.

490
00:27:37,420 --> 00:27:42,300
It would gain changing for a business, but that could be a year or two out.

491
00:27:42,300 --> 00:27:47,100
And who knows technically is there some solution that will already come out of a box that

492
00:27:47,100 --> 00:27:48,660
could do that for you.

493
00:27:48,660 --> 00:27:53,740
So you'd move that toward the end of your list and you'd want to look at, let's just take

494
00:27:53,740 --> 00:27:54,900
a hypothetical company.

495
00:27:54,900 --> 00:28:00,020
You say like a retail company, I don't even know if you really matter and stuff, but you

496
00:28:00,020 --> 00:28:03,700
take a real-tell company, every retail company could be different.

497
00:28:03,700 --> 00:28:08,340
But what if it's a retail company that the biggest issue they have is their shelves are

498
00:28:08,340 --> 00:28:15,540
empty at like five o'clock in the day in the afternoon when the rush hour comes in or

499
00:28:15,540 --> 00:28:18,880
they have a, say, they have a low like at 12 or something like that, people come in and

500
00:28:18,880 --> 00:28:23,040
then by five o'clock the next one comes in and they're not stocking their shelves or putting

501
00:28:23,040 --> 00:28:24,460
stuff back on there again.

502
00:28:24,460 --> 00:28:27,780
The customer experience is going to be every time I go in they didn't have anything, your

503
00:28:27,780 --> 00:28:29,500
customers are never going to come back again.

504
00:28:29,500 --> 00:28:30,500
Right.

505
00:28:30,500 --> 00:28:34,580
So if that's really a use case that would be extremely impactful to your business and drive

506
00:28:34,580 --> 00:28:38,580
your top line revenue is it and is a concern for your customers.

507
00:28:38,580 --> 00:28:43,820
And instead you started working on a chatbot, you're going to have yourself a major issue,

508
00:28:43,820 --> 00:28:44,820
right?

509
00:28:44,820 --> 00:28:49,900
What I'm talking about is if you're all socializing internally, you can kind of say marketing

510
00:28:49,900 --> 00:28:53,780
will say, look, I really think that this marketing campaign will be the best thing for us.

511
00:28:53,780 --> 00:28:57,860
But other people in the group are going to say, look, but if you think about it, that's

512
00:28:57,860 --> 00:29:02,860
probably not what's best for us right now because John is saying that, you know, we're having

513
00:29:02,860 --> 00:29:07,300
extreme complaints on the customer side because we're not doing this, this, this, and this.

514
00:29:07,300 --> 00:29:11,700
And when everybody's talking together, people can then say, you're right, you know, we can

515
00:29:11,700 --> 00:29:18,300
do this marketing stuff at a later time, but we really should be focusing on this can AI help

516
00:29:18,300 --> 00:29:19,300
us.

517
00:29:19,300 --> 00:29:24,260
And that's probably a better example of how a company should really think.

518
00:29:24,260 --> 00:29:27,140
Don't look for the pie in the sky like I'm going to build a robot that's going to stand

519
00:29:27,140 --> 00:29:30,660
out front of the store and tell everybody the greatest sales that are going on.

520
00:29:30,660 --> 00:29:33,980
That's probably something you should do right now.

521
00:29:33,980 --> 00:29:38,500
But there are certain things because it's your company and you know your company best,

522
00:29:38,500 --> 00:29:42,940
you'll probably come up with some use cases like three or four use cases that would be extremely

523
00:29:42,940 --> 00:29:48,460
impactful that then companies like us or other people on the outside could come in and say great.

524
00:29:48,460 --> 00:29:52,860
We can do, here's the top five, we can do this one in a week, we could do this one in a

525
00:29:52,860 --> 00:29:56,260
year, like you can give ideas about what can be done.

526
00:29:56,260 --> 00:29:57,260
Right.

527
00:29:57,260 --> 00:30:02,860
I think that is the best place for any small and medium-sized business to start at.

528
00:30:02,860 --> 00:30:10,100
That'll make you start to become an AI understood organization.

529
00:30:10,100 --> 00:30:15,420
And then from there it's like the blinders come off, you start seeing all the opportunities.

530
00:30:15,420 --> 00:30:21,460
And then once you have one successful integration, then everybody starts getting used to it.

531
00:30:21,460 --> 00:30:24,900
Now it's a great, we can start building on this now.

532
00:30:24,900 --> 00:30:27,420
And you no longer, you're riding with training wheels.

533
00:30:27,420 --> 00:30:30,820
Now you're like, okay great, now let's take the training wheels off and we can really

534
00:30:30,820 --> 00:30:32,820
start on some bigger projects.

535
00:30:32,820 --> 00:30:37,180
Yeah, because now you've got understanding, you've got some success with it, yeah that makes

536
00:30:37,180 --> 00:30:38,180
total sense.

537
00:30:38,180 --> 00:30:44,060
And then that same team, that same team you have formed now becomes your internal cheer

538
00:30:44,060 --> 00:30:48,500
leaders because they've been involved in it, they help with adoption as well, they become

539
00:30:48,500 --> 00:30:54,220
the partners of us saying this is a organization, this is great, this is why it works, this is

540
00:30:54,220 --> 00:30:59,340
why we did it, this will be good for the organization because you guys know that the

541
00:30:59,340 --> 00:31:04,460
hardest part for change is people, right, is people don't want to change.

542
00:31:04,460 --> 00:31:07,540
So you can roll out any new technology, any new solution.

543
00:31:07,540 --> 00:31:12,660
If they don't adopt it, the organization is one of two choices, threaten them to adopt

544
00:31:12,660 --> 00:31:18,100
it, or they say, you know what, it just, it's causing so many problems, they're all upset.

545
00:31:18,100 --> 00:31:20,980
Let's just park that on the side and they just wasted their money.

546
00:31:20,980 --> 00:31:25,740
So it's got a twofold effect, they become the cheer leaders, the internal adoption, you'll

547
00:31:25,740 --> 00:31:27,900
help you get the right use case.

548
00:31:27,900 --> 00:31:33,980
And the third on that one, in my opinion, hearing what you said, in the third option is shrink,

549
00:31:33,980 --> 00:31:41,740
go down, go out of business because if you don't get the buy-in or you just don't do it,

550
00:31:41,740 --> 00:31:45,580
then how is that going to impact your business, which is what we've been talking about.

551
00:31:45,580 --> 00:31:49,540
So now we get to the end of the world that Tim and I live in.

552
00:31:49,540 --> 00:31:57,700
So how do you see the intersection of cybersecurity and AI, particularly given potential, risks

553
00:31:57,700 --> 00:31:59,860
associated with AI driven technology?

554
00:31:59,860 --> 00:32:01,660
Do you have any thoughts on that?

555
00:32:01,660 --> 00:32:05,060
Of course, I mean, so I told you I'm very positive, right, but I'm not naive.

556
00:32:05,060 --> 00:32:11,540
And I understand there are amazing, amazing productivity gains and innovative gains from

557
00:32:11,540 --> 00:32:13,900
me, AI.

558
00:32:13,900 --> 00:32:16,620
But the bad guys are just as smart.

559
00:32:16,620 --> 00:32:21,340
And they see this as an opportunity and they're, I mean, it's been the case beforehand,

560
00:32:21,340 --> 00:32:22,500
right?

561
00:32:22,500 --> 00:32:26,300
You have organizations like a JPMorgan spending hundreds, probably billions a year on

562
00:32:26,300 --> 00:32:29,260
cybersecurity and they still can't keep up, right?

563
00:32:29,260 --> 00:32:34,700
Because the bad guys, it's so profitable, they just keep changing because it, you know, what

564
00:32:34,700 --> 00:32:36,500
do they say back in the day, why do I rob banks?

565
00:32:36,500 --> 00:32:38,380
I don't remember which one is Billy the kid or something.

566
00:32:38,380 --> 00:32:39,380
Exactly.

567
00:32:39,380 --> 00:32:40,380
The money is, right?

568
00:32:40,380 --> 00:32:41,380
That's right.

569
00:32:41,380 --> 00:32:42,380
That's right.

570
00:32:42,380 --> 00:32:43,380
They're doing the same thing.

571
00:32:43,380 --> 00:32:47,940
So they're like this massive amounts of money to make here and they understand what I said

572
00:32:47,940 --> 00:32:54,260
earlier on, they are small or even large, but they're able to accentuate their reach

573
00:32:54,260 --> 00:32:57,140
because of AI tools.

574
00:32:57,140 --> 00:33:03,460
So your space is huge and it's only become more and more complex because they're getting

575
00:33:03,460 --> 00:33:04,820
smarter.

576
00:33:04,820 --> 00:33:07,220
They're using AI to their advantage.

577
00:33:07,220 --> 00:33:14,220
And now the selling point for you guys is if a company is not using the same technology

578
00:33:14,220 --> 00:33:18,700
to counteract that, how would they go to keep up?

579
00:33:18,700 --> 00:33:19,700
Correct.

580
00:33:19,700 --> 00:33:20,700
Absolutely.

581
00:33:20,700 --> 00:33:23,820
I was going to say, you have a comment on that.

582
00:33:23,820 --> 00:33:24,820
Yeah.

583
00:33:24,820 --> 00:33:29,260
I think what's also interesting and it goes back to just, we can go back in time, right?

584
00:33:29,260 --> 00:33:30,420
It doesn't matter.

585
00:33:30,420 --> 00:33:31,420
It's a cat and mouse game.

586
00:33:31,420 --> 00:33:33,660
It's always been a cat and mouse game.

587
00:33:33,660 --> 00:33:35,300
It'll always be a cat and mouse game.

588
00:33:35,300 --> 00:33:38,820
Now it's just we're doing it faster.

589
00:33:38,820 --> 00:33:42,500
And when we, when we, when they find the hole, we have to fill it faster.

590
00:33:42,500 --> 00:33:44,860
So we use AI on both sides.

591
00:33:44,860 --> 00:33:48,340
They're using it to push those scripts faster to try and get in faster.

592
00:33:48,340 --> 00:33:52,260
We're using it to block the whole faster and to watch the environments.

593
00:33:52,260 --> 00:33:54,460
And so it goes back to talent.

594
00:33:54,460 --> 00:33:57,660
It's all about, you know, we have to be right, blue team.

595
00:33:57,660 --> 00:33:59,100
We have to be right 100%.

596
00:33:59,100 --> 00:34:00,100
Yes.

597
00:34:00,100 --> 00:34:01,500
Red team once.

598
00:34:01,500 --> 00:34:02,500
Yes.

599
00:34:02,500 --> 00:34:06,020
And so you guys have seen it as well, right?

600
00:34:06,020 --> 00:34:11,780
The social engineering from a workforce is that in email is probably the easiest way to

601
00:34:11,780 --> 00:34:12,780
get in.

602
00:34:12,780 --> 00:34:15,740
So you drop the USB sticks, right?

603
00:34:15,740 --> 00:34:20,460
And somebody plugging it to computer or you'd send an email and spoof the CEO's email

604
00:34:20,460 --> 00:34:25,300
address and send it to them and say, Hey, I want you to open up, you know, do this or do

605
00:34:25,300 --> 00:34:26,300
that, whatever it is.

606
00:34:26,300 --> 00:34:27,780
And they would go do it.

607
00:34:27,780 --> 00:34:32,980
And the bad guys understand that people get overwhelmed and they're, you're right, they

608
00:34:32,980 --> 00:34:37,500
can send out a million emails and one just has to be right and they're fine.

609
00:34:37,500 --> 00:34:40,740
So now add on to it deep fakes.

610
00:34:40,740 --> 00:34:45,300
Now add on to it the fact that they can take, they can take this podcast right here, your

611
00:34:45,300 --> 00:34:50,220
voice, Tam, your voice, Scott, my voice right here, my menu reasons by watchiness and

612
00:34:50,220 --> 00:34:54,060
create deep fakes and send it out to somebody saying, Hey, you know, join my Zoom meeting

613
00:34:54,060 --> 00:34:57,300
and I want you to go do this, this and this.

614
00:34:57,300 --> 00:35:02,020
I think they said it's two seconds now as all it takes of a voice and they have your voice

615
00:35:02,020 --> 00:35:03,500
pattern.

616
00:35:03,500 --> 00:35:04,500
It's crazy.

617
00:35:04,500 --> 00:35:08,300
So if a company is not doing something about it, they're not working with you from an AI

618
00:35:08,300 --> 00:35:10,420
perspective, etc.

619
00:35:10,420 --> 00:35:11,860
How do they expect to keep up?

620
00:35:11,860 --> 00:35:14,300
How do they expect to counteract that?

621
00:35:14,300 --> 00:35:15,300
You can't.

622
00:35:15,300 --> 00:35:16,300
Yeah.

623
00:35:16,300 --> 00:35:22,860
And like you said, I mean, the learning models are, I'm sure scooping up all the social

624
00:35:22,860 --> 00:35:24,060
media stuff.

625
00:35:24,060 --> 00:35:28,660
So those people love to post, you know, what they for dinner last night or where they like

626
00:35:28,660 --> 00:35:33,020
to travel, you know, AI can easily deep fake that stuff now.

627
00:35:33,020 --> 00:35:34,020
You know, yes.

628
00:35:34,020 --> 00:35:36,100
So you have prompting gestures as well.

629
00:35:36,100 --> 00:35:37,340
It's, I mean, we're learning so much.

630
00:35:37,340 --> 00:35:41,940
So, so you take this blue background right now and they put into the blue background,

631
00:35:41,940 --> 00:35:45,140
blue writing that wants system scans at website.

632
00:35:45,140 --> 00:35:47,140
It's going to, it's going to follow the prompt, right?

633
00:35:47,140 --> 00:35:48,980
And do something that should not do.

634
00:35:48,980 --> 00:35:50,220
Well, how do you find that?

635
00:35:50,220 --> 00:35:52,380
Well, you can't, you can't use regular tools.

636
00:35:52,380 --> 00:35:53,420
You have to use AI.

637
00:35:53,420 --> 00:35:57,660
So it's, look, I understand the challenge.

638
00:35:57,660 --> 00:36:02,420
We started off this conversation saying why, why, why, what do you think the issues off

639
00:36:02,420 --> 00:36:06,140
from an adoption standpoint is it is overwhelming.

640
00:36:06,140 --> 00:36:12,820
It is, it's a rapid pace of innovation that is throwing people off balance.

641
00:36:12,820 --> 00:36:18,060
The, the, the part that really anybody should come away with on here is educate yourself

642
00:36:18,060 --> 00:36:19,660
around AI.

643
00:36:19,660 --> 00:36:23,860
When you educate yourself, you won't be so overwhelmed with what's happening.

644
00:36:23,860 --> 00:36:24,860
You'll understand it.

645
00:36:24,860 --> 00:36:26,020
You may not know every nuance.

646
00:36:26,020 --> 00:36:30,900
You may not know every new tactic happening out there, but at least you'll understand it

647
00:36:30,900 --> 00:36:32,740
from a very base level.

648
00:36:32,740 --> 00:36:36,340
And then from there, you'll understand when you guys come in and say, look, we need to

649
00:36:36,340 --> 00:36:41,100
attack this and, and it'll be so much more open to it, especially from my side as well.

650
00:36:41,100 --> 00:36:43,380
And it won't be so, so concerned.

651
00:36:43,380 --> 00:36:46,460
So like when I look at the different types of customers, you have, we just talked before

652
00:36:46,460 --> 00:36:50,460
you have the black stones, the JP Morgan's, they know what they're doing.

653
00:36:50,460 --> 00:36:54,500
They're hiring people, they're building stuff themselves or they're working with massive

654
00:36:54,500 --> 00:36:57,860
consulting companies that will come in there, do one specific topic and leave.

655
00:36:57,860 --> 00:37:02,700
Then you have the companies that on the other side of it say, I'm scared of this AI

656
00:37:02,700 --> 00:37:03,700
stuff.

657
00:37:03,700 --> 00:37:04,700
We don't need it.

658
00:37:04,700 --> 00:37:05,700
We've been doing this all the time.

659
00:37:05,700 --> 00:37:06,700
Well, they're not my customers.

660
00:37:06,700 --> 00:37:08,940
There'd be no different than somebody saying, we don't need cybersecurity.

661
00:37:08,940 --> 00:37:12,940
So you'd kill yourself trying to convince them to do it.

662
00:37:12,940 --> 00:37:15,140
It's not going to work.

663
00:37:15,140 --> 00:37:19,900
The customers we all love the most are the ones that say, listen, I, I, I, I'm reading about

664
00:37:19,900 --> 00:37:20,900
this.

665
00:37:20,900 --> 00:37:21,900
I know about this.

666
00:37:21,900 --> 00:37:24,980
It's something I really want to get started on, but I don't know where to begin.

667
00:37:24,980 --> 00:37:26,740
What do you guys advise?

668
00:37:26,740 --> 00:37:28,940
And that is a company that is open.

669
00:37:28,940 --> 00:37:30,180
They want to hear what's happening out there.

670
00:37:30,180 --> 00:37:31,180
Again, they're not naive.

671
00:37:31,180 --> 00:37:35,780
They're not just going to pay any, you know, any price that you have, but they'll all

672
00:37:35,780 --> 00:37:40,180
find out and educate themselves on what's out there in order to protect their business and

673
00:37:40,180 --> 00:37:41,860
take the next steps forward.

674
00:37:41,860 --> 00:37:46,980
And I think that is a model that everybody should follow, educate, start teaching your, your

675
00:37:46,980 --> 00:37:49,580
teams to be AI first.

676
00:37:49,580 --> 00:37:51,780
Encourage them to work with chat GPT.

677
00:37:51,780 --> 00:37:54,180
Encourage them to work with these different technologies.

678
00:37:54,180 --> 00:37:57,780
And what you're going to see as well is something to add as well.

679
00:37:57,780 --> 00:38:00,660
I saw a, a poll that came out.

680
00:38:00,660 --> 00:38:06,700
I think it was from PWC or something like that saying that they've looked at companies,

681
00:38:06,700 --> 00:38:09,340
about 43% of employees within a company.

682
00:38:09,340 --> 00:38:13,500
We use an AI without the company's knowledge.

683
00:38:13,500 --> 00:38:16,900
So I really, they're going to do it.

684
00:38:16,900 --> 00:38:19,500
I mean, you know, block them from doing it.

685
00:38:19,500 --> 00:38:21,020
They're probably going to find a way to do it anyway.

686
00:38:21,020 --> 00:38:24,100
You know, blacklisted and say they can't get to chat GPT.

687
00:38:24,100 --> 00:38:26,620
They'll find some way to do it anyway on their phones or whatever.

688
00:38:26,620 --> 00:38:28,620
Yeah, they're going their phones.

689
00:38:28,620 --> 00:38:29,620
Yeah.

690
00:38:29,620 --> 00:38:31,500
So, they're using it.

691
00:38:31,500 --> 00:38:35,500
It's like why not just start educating and get ahead of the curve, start teaching what's

692
00:38:35,500 --> 00:38:37,740
happening out there, start building the teams.

693
00:38:37,740 --> 00:38:41,100
You can even go one step further, start building competition.

694
00:38:41,100 --> 00:38:47,700
So, you know, I'm not a competition against each other, but more of maybe a, a, a, a, a thing

695
00:38:47,700 --> 00:38:51,300
where you say everybody in a company, what you come to us with ideas or what type of use

696
00:38:51,300 --> 00:38:54,420
case we can use to AI that will be beneficial to our company.

697
00:38:54,420 --> 00:38:56,020
And you'll get, again, pie in the sky.

698
00:38:56,020 --> 00:39:00,980
You'll get things that never going to work and whoever comes up with something great,

699
00:39:00,980 --> 00:39:06,740
you reward them in front of either, either social acknowledgement or a prize or a couple

700
00:39:06,740 --> 00:39:08,060
days off or something like that.

701
00:39:08,060 --> 00:39:12,900
We get people in energized to start coming up with ideas since they, they understand your

702
00:39:12,900 --> 00:39:14,140
company best.

703
00:39:14,140 --> 00:39:18,700
And that might help you to really start getting on the AI train and learning.

704
00:39:18,700 --> 00:39:24,660
I think that if you're going to be putting that type of, and I agree about using AI, there's

705
00:39:24,660 --> 00:39:26,180
no reason not to at this point.

706
00:39:26,180 --> 00:39:29,460
But if you don't have a policy in place, what they're allowed to put in those chatbots,

707
00:39:29,460 --> 00:39:35,740
what they're not allowed, which is more important to put inside those, especially in the LLM's,

708
00:39:35,740 --> 00:39:40,380
there's been a lot going on and you would say, buy us, there's hallucinations.

709
00:39:40,380 --> 00:39:44,460
You really have to be careful about what type of information you're getting and putting

710
00:39:44,460 --> 00:39:45,460
out.

711
00:39:45,460 --> 00:39:46,460
Yep.

712
00:39:46,460 --> 00:39:49,780
You should not put your financial statement.

713
00:39:49,780 --> 00:39:51,380
Yeah, I wouldn't do that.

714
00:39:51,380 --> 00:39:53,940
Or put your database in there just because you can.

715
00:39:53,940 --> 00:39:56,020
Yeah, probably a good idea.

716
00:39:56,020 --> 00:39:58,740
Don't hook in your HR, all everything from the HR perspective.

717
00:39:58,740 --> 00:40:04,380
Look up people's salaries and type of sick days and medical records, I mean, it's stuff like

718
00:40:04,380 --> 00:40:05,380
that.

719
00:40:05,380 --> 00:40:06,380
So you're right.

720
00:40:06,380 --> 00:40:10,700
Again, that's just another concern for a leader of an organization saying, oh my God, now

721
00:40:10,700 --> 00:40:12,700
I have to worry about all that as well.

722
00:40:12,700 --> 00:40:13,700
Well, guess what?

723
00:40:13,700 --> 00:40:15,060
You have to worry about it anyway.

724
00:40:15,060 --> 00:40:18,580
Because like we just said, the bad guys can use AI in order to attack you and get that

725
00:40:18,580 --> 00:40:19,580
information anyway.

726
00:40:19,580 --> 00:40:26,420
So you have no choice but to understand what it is and start working with it yourself.

727
00:40:26,420 --> 00:40:27,420
Absolutely.

728
00:40:27,420 --> 00:40:33,700
So guys, as we wrap up this conversation, let's indulge in a little creative thinking.

729
00:40:33,700 --> 00:40:40,180
So, um, current with your extensive technology background, if you could imagine, you could

730
00:40:40,180 --> 00:40:47,780
snap your fingers and have an AI powered business assistant tailored to your needs.

731
00:40:47,780 --> 00:40:51,940
What features do you think you'd add to it and how do you think it would benefit others?

732
00:40:51,940 --> 00:40:57,620
I think, I think something that everybody, absolutely everybody can use is from the email

733
00:40:57,620 --> 00:40:59,140
perspective.

734
00:40:59,140 --> 00:41:01,500
And it's, it's coming on Microsoft co-pilot.

735
00:41:01,500 --> 00:41:06,540
They've already said it's, it's coming where the emails will come in.

736
00:41:06,540 --> 00:41:08,780
It'll read the email.

737
00:41:08,780 --> 00:41:13,100
It will actually either go back to your database and refer to something if it's a product

738
00:41:13,100 --> 00:41:17,540
question or it'll look at other emails that you've sent in the past.

739
00:41:17,540 --> 00:41:26,140
It will then generate the email response for you and send it if you wanted to.

740
00:41:26,140 --> 00:41:30,500
So that doesn't mean you get one pending, maybe an again, a pending folder so you could

741
00:41:30,500 --> 00:41:33,700
prove for me that and okay, yep, yep.

742
00:41:33,700 --> 00:41:37,380
So, so that is everybody's trying to manage email.

743
00:41:37,380 --> 00:41:38,860
Everybody's always challenged the email.

744
00:41:38,860 --> 00:41:45,580
I wanted to people, I give up on, on, moving everything out of my, out of my inbox, everybody,

745
00:41:45,580 --> 00:41:51,460
I have folders, but I can't keep up with every single email that's coming in.

746
00:41:51,460 --> 00:41:53,300
I'll just spend the entire day just going through emails.

747
00:41:53,300 --> 00:41:57,660
So, so I've given up from that perspective, but there are a lot of email management tools

748
00:41:57,660 --> 00:41:59,900
and no co-pilot has that within it.

749
00:41:59,900 --> 00:42:03,300
And with me even saying that, they are certain concerns around it.

750
00:42:03,300 --> 00:42:05,860
You don't want to say the wrong thing or send it out.

751
00:42:05,860 --> 00:42:09,340
But it's, it's coming real fast is about to release.

752
00:42:09,340 --> 00:42:12,460
And once it does, it's going to be a game changer for businesses as well.

753
00:42:12,460 --> 00:42:17,180
And I think that is something that that people can get a lot of use from.

754
00:42:17,180 --> 00:42:19,940
That will be beneficial if used correctly.

755
00:42:19,940 --> 00:42:21,420
>> That's going to be interesting.

756
00:42:21,420 --> 00:42:22,620
It's going to be very interesting.

757
00:42:22,620 --> 00:42:26,900
Like, I don't know if it looks at how you responded in in the past and all that, yeah, that's

758
00:42:26,900 --> 00:42:27,900
okay, cool.

759
00:42:27,900 --> 00:42:28,900
>> It does.

760
00:42:28,900 --> 00:42:29,900
>> It does.

761
00:42:29,900 --> 00:42:30,900
But then there's other sides to it.

762
00:42:30,900 --> 00:42:34,300
Microsoft co-pilot says that it's going to, the, the, the generator, VI within Microsoft

763
00:42:34,300 --> 00:42:38,900
co-pilot is going to start taking snapshots of your system and your everything is going

764
00:42:38,900 --> 00:42:47,380
on there and start building a profile for you that's only within your, you know, your area

765
00:42:47,380 --> 00:42:49,700
and not be shared with anybody else.

766
00:42:49,700 --> 00:42:53,740
And you know, Satya was talking about that and I was like, he's a, but we can always turn

767
00:42:53,740 --> 00:42:55,220
that off if you want to.

768
00:42:55,220 --> 00:42:58,060
And I'm like, wow, that's, that's going to be a little concerning.

769
00:42:58,060 --> 00:43:01,740
And then you have all the generator of AI agents that are coming next.

770
00:43:01,740 --> 00:43:05,540
And the agents just going to be like your little AI bots that go out there and do multiple

771
00:43:05,540 --> 00:43:08,220
tasks at the same time and then come back to you.

772
00:43:08,220 --> 00:43:11,500
And that's most likely where that, that email is coming from as well.

773
00:43:11,500 --> 00:43:15,700
You have AI agents going out looking at past emails, past responses, how you've written

774
00:43:15,700 --> 00:43:18,260
things in the past, or write your emails and send it out.

775
00:43:18,260 --> 00:43:22,820
With all that said, some people might be concerned that, that, you know, that's going to reduce

776
00:43:22,820 --> 00:43:26,500
the amount of productivity in their work and they get to sit around and do nothing.

777
00:43:26,500 --> 00:43:27,500
That's not the answer, right?

778
00:43:27,500 --> 00:43:29,500
You, I don't want to see what you're saying.

779
00:43:29,500 --> 00:43:30,500
>> Yeah.

780
00:43:30,500 --> 00:43:36,300
>> I can see like, you know, when I'm doing research, you know, I'm googling, I'm chat GBT, I'm,

781
00:43:36,300 --> 00:43:38,060
I'm doing all kinds of stuff, right?

782
00:43:38,060 --> 00:43:42,980
To get that, that research done, I can see just sending out agents and going, hey, I want

783
00:43:42,980 --> 00:43:45,060
to know more about blank.

784
00:43:45,060 --> 00:43:50,700
And then it goes and comes back and says, here's what I found, you know, so that, that's,

785
00:43:50,700 --> 00:43:51,700
I just made that up.

786
00:43:51,700 --> 00:43:52,700
>> You're both, right, real.

787
00:43:52,700 --> 00:43:56,660
>> Yeah, and you're both scaring me because I know, like, I'm just all from the other side,

788
00:43:56,660 --> 00:44:03,660
my mind's going privacy and when they get, when, when they get in, and what is Microsoft

789
00:44:03,660 --> 00:44:06,060
doing with this data or Apple?

790
00:44:06,060 --> 00:44:10,500
They say they're not monitoring it, but they know people are using it for the wrong purposes,

791
00:44:10,500 --> 00:44:12,620
which means they are monitoring it.

792
00:44:12,620 --> 00:44:13,620
I don't know.

793
00:44:13,620 --> 00:44:14,620
>> Yeah.

794
00:44:14,620 --> 00:44:15,620
>> Yeah.

795
00:44:15,620 --> 00:44:18,460
>> Where is, you're 100% right, Tim.

796
00:44:18,460 --> 00:44:22,900
And I understand that that from a security aspect, it does have companies saying, whoa,

797
00:44:22,900 --> 00:44:27,220
hold on a minute, and you have to have that push and shove.

798
00:44:27,220 --> 00:44:30,460
You can't, you can't pull it all the way back and say you can't do anything, but you also

799
00:44:30,460 --> 00:44:32,900
can't, like, run, go.

800
00:44:32,900 --> 00:44:37,820
You have to find that bounce, but you're 100% right, the AI agents are coming fast.

801
00:44:37,820 --> 00:44:39,620
And then you're like, two facts.

802
00:44:39,620 --> 00:44:40,620
>> Two facts, yeah.

803
00:44:40,620 --> 00:44:41,620
>> Yeah.

804
00:44:41,620 --> 00:44:45,140
>> All right, guys, well, that's, that's all the time we have on today's episode.

805
00:44:45,140 --> 00:44:50,380
So I want to extend my sincere gratitude to you, Kurt, for sharing your extra decent insights

806
00:44:50,380 --> 00:44:51,620
with us today.

807
00:44:51,620 --> 00:44:58,820
I know I've gained some valuable perspective on the AI, and that undoubtedly will inspire

808
00:44:58,820 --> 00:45:00,380
our listeners.

809
00:45:00,380 --> 00:45:03,100
So thanks for tuning in today's episode.

810
00:45:03,100 --> 00:45:07,060
And if you've found today's conversation engaging, I'm going to suggest you check out

811
00:45:07,060 --> 00:45:09,940
last week's episode as well.

812
00:45:09,940 --> 00:45:14,700
We've featured April Yurby, discussing risk management and cyber liability insurance.

813
00:45:14,700 --> 00:45:19,580
So be sure to subscribe, stay vigilant, and stay safe.

814
00:45:19,580 --> 00:45:29,580
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