October 23, 2025 • 43 mins
What if AI could help you think more clearly, lead more effectively, and scale faster—without replacing your human touch?
In this episode of the Business Roundtable Podcast, David W. Carr speaks with Kyle Becker, Founder of Qualia AI, about the evolving relationship between AI and human leadership. Kyle shares his journey in startup innovation and why he believes AI should serve as a thinking partner rather than a replacement for leaders. This is not hype—it’s a grounded, strategic conversation about where AI meets emotional intelligence, decision-making, and growth.
You’ll learn:
Connect with Kyle Becker:
Website: https://www.qualiaai.com
LinkedIn: https://www.linkedin.com/in/kylejbecker
Become a supporter of this podcast: https://www.spreaker.com/podcast/business-roundtable--6049255/support.
Watch more episodes on YouTube and subscribe here:
https://www.youtube.com/@steward_your_business
Connect with Steward Your Business:
Website: https://stewardyourbusiness.com
LinkedIn: https://www.linkedin.com/in/davidwcarr
In this episode of the Business Roundtable Podcast, David W. Carr speaks with Kyle Becker, Founder of Qualia AI, about the evolving relationship between AI and human leadership. Kyle shares his journey in startup innovation and why he believes AI should serve as a thinking partner rather than a replacement for leaders. This is not hype—it’s a grounded, strategic conversation about where AI meets emotional intelligence, decision-making, and growth.
You’ll learn:
- What leaders get wrong about using AI
- Why AI should assist, not replace, human thinking
- How Kyle built Qualia AI to enhance real-world productivity
- The importance of systems thinking and decision structure
- How to balance technology with timeless leadership values
- The ethical challenges and blind spots leaders must confront
- Why authenticity still beats automation in client relationships
Connect with Kyle Becker:
Website: https://www.qualiaai.com
LinkedIn: https://www.linkedin.com/in/kylejbecker
Become a supporter of this podcast: https://www.spreaker.com/podcast/business-roundtable--6049255/support.
Watch more episodes on YouTube and subscribe here:
https://www.youtube.com/@steward_your_business
Connect with Steward Your Business:
Website: https://stewardyourbusiness.com
LinkedIn: https://www.linkedin.com/in/davidwcarr
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:31):
Hello, and welcome back to the Business round Table podcast.
I am your host, David Carr, founder of Steward your
Business bringing people together to accomplish great things. And of
course this week we have another fantastic guest, Kyle Becker.
Super excited to have him here on the podcast. We're
going to talk all things AI, strategy and more. So
Welcome to the podcast, Kyle.
Speaker 2 (00:53):
Thank you. David can see you.
Speaker 1 (00:55):
Absolutely glad to have you here. I wanted to bring
Kyle on the podcast today because Kyle has just a
diverse background. I'm going to get let him share a
little bit about his background and what he got him
to creating quality AI. We're hearing a lot about AI
in the in the marketplace and whatnot. But what I
found that Kyle brings this unique perspective on strategy and
(01:16):
how he's helping companies organizations use this tool today. And
so Kyle, again, welcome to the podcast. I would love
for you to share a little bit with you about
your journey and before we recorded this podcast. You're sharing
a little bit about this from your military background and whatnot,
But what got you to create quality AI? Why is
your focus on strategy and if you wouldn't mind just
take us a little take us back a little bit
(01:37):
to your journey as a business owner and leader.
Speaker 2 (01:41):
Yeah, okay, So so Quality AI. The reason we started
it is we wanted to help companies put a holistic
framework around their AI strategy. Now how I got there was,
you know, we saw a gap sort of the in
the market place, a gap in sort of traditional strategic planning,
(02:04):
and we sought to fill it. You know, we thought
we could we were the right people to position ourselves,
you know, uh in such a way to where, uh
we could help our our clients, our partners understand how
to how to guide the ship right, because with AI,
there's so much uncertainty around AI, so much ambiguity, and
(02:26):
there's a lot of thoughts in people's minds. We'll say
that our influenced from you know, sci fi. Uh they're
both you know, both good but mostly bad, you know,
and no one knows how it's going to work out.
Is it going to be you know, a terminator thing
or is it going to be an eye robot? It
will help humanity or will we be enslaved by it?
(02:46):
So what we kind of decided at Quality AI is
it's it's hard to predict the future, right, it's even
harder to control the future. Right. So I think the
the you know, we're like a river going down stream.
You know, you can either try to control the flow
of the river or you can guide the ship. Right,
(03:09):
So we believe that trying to control the way. You know,
there's a lot of things that are being done with
you know, regulatory uh, you know, measures that are being
done with you like you see in the news every
day with Sam Alton and Elon Musk, you know, and
and a lot of a lot of tech behemoths going
before Congress, you know, talking about you know, where AI
(03:30):
is going. But we believe it's already so AI, you know,
it's already proliferated throughout every industry, you know, throughout every sector.
Already a lot of the stuff is open source. That
putting you know, putting regulations around it. Not that that's
a bad thing, but it's almost like putting a stick
and a river, you know, to try to control the flow.
(03:51):
The waters just go around it. So instead of trying
to dam up the river or redivert it, you know,
we we help our companies the ship. So whichever way
the future goes it's as smooth selling as possible, and
we're as adaptable.
Speaker 3 (04:07):
As we can be, you know, to the to So
can I ask you, Kyle, look what I like this
strategy you're talking about?
Speaker 1 (04:17):
What led you to kind of coming up of the
strategy because we know you're talking before we recorded, Like,
what led you to kind of coming this? Because I
know you've been in the Marine Corps in your background,
I would love to hear like kind of because it's
a different strategy. Like you said, some people are trying
to put a stick in the in the river. You're
you're proposing a different strategy. What what God brought you
to this kind of place? Yeah?
Speaker 2 (04:37):
Absolutely? Yeah, Sorry, David, I you're a goodding. I was
gonna manager so much. Uh uh. So. My background is
so I grew up in West Virginia kind of out
in the sticks, and I joined the Marine Corps from
a really young age. As soon as I turned eighteen,
I was in I was in boot camp ten days later,
and I spent you know, my the like the majority
(05:00):
of my twenties, well all of my twenties an active
duty in the Marine Corps and predominantly in a field
called reconnaissances, ground and recon Yeah, and our mension was
to you know, without getting caught. We were to insert
into the area of operations in which the main Marine Corps,
(05:22):
the main element we called it, is maneuvering into and
so there's a lot of uncertainty, the fog of war,
a lot of ambiguity about this battle space. Even with
you know, satellite imagery and other forms of intelligence is
SR imagery, surveillance, reconnaissance, you know, drones, and even with reconnaissance.
(05:45):
Ground reconnaissance is essential because you know, you've got guys
like me and my team out there. You know, actually
you know, looking at firsthand what the environment's like. So
we were to court information about rivers, streams, roads, the beach,
you know, wherever the battalion is going to make entry,
(06:07):
right their avenues, that approach. We would you know, get
all that data together into reports and send that up
to the commanders so they could make the best informed
decisions possible for their troop movements.
Speaker 1 (06:24):
Right.
Speaker 2 (06:25):
Yeah, we would collect information about the objective as well,
you know, where the enemy's at, their size, their disposition,
their uniforms, their weapons, if there's any high value targets
things like that, and we would also as well, when
the rainforse came, we would position ourselves to do what's
(06:45):
called a sniper initiated raid, right, which is right before
and then we usually would do this in tandem with
a unit like Force Recon, whereas there's more of a
limited scale raid right before they blow open the door,
you know, we would initiate raid with a sniper shot,
you know, taking up a century or an HBI or
something like that. So that was so anyways, that's all
(07:08):
to say. You asked me, like, what the hell does
this have to do with AI or data. Yeah, so
I think it's critical. I grew up, you know, gathering information,
getting it in the hands of people who have the
sort of control over you know, it's very high stakes game, right,
(07:33):
Lives are in the hands of the people who are
going to make decisions based off of this information. Right,
It's this critical that we're gathering the right sort of
right sort of stuff, right because our brothers and sisters
that were about to, you know, get into a fight,
are going to need to know everything about the environment
they're getting into. So I take it seriously. Right, So, now,
(07:56):
what I've been doing for the past few years. Is
I've been in data and AI, right, so I still
collect data, right, just in the Marine Corps, only the
environment is a little more comfortable. Now yeah, maybe it's.
Speaker 1 (08:12):
Still critical, still critical. I mean we need this information,
this critical making business decisions and how are you planning? Absolutely,
that's right.
Speaker 2 (08:20):
Yeah, making business decisions, you need the right sort of information, right,
And then AI needs the right sort of data as
well too to generate information that that is accurate, you know,
and uh, and so that's that's that's for a rat quality.
AI is, as I mentioned in the beginning of this call,
(08:41):
is about uh, you know, helping our clients develop strategy
uh in which they can guide their ship and make
the best decisions uh possible. So there's a lot that
goes into our framework.
Speaker 1 (08:54):
But yeah, well well well I want to break into that.
So so what I'm hearing is, you know, you're going
from uh to the re recon if you will, and
reinvention of like you're taking these things and focusing on
what's the most important and making decisions and I and
I love that, and I know you know that is
(09:14):
so powerful because we want to make powerful decisions. And
one of the things you shared to me, what I
really liked having you on the podcast was this pivot
of you know, you're in the military. You made have
been to prioritize you know, you're both dads and focusing
on what's most important. How do we make the decisions
that are most important our life making this taking all
the state of this information and then to actually you know,
(09:34):
make solid plans priorities, right, because there's lots of information,
but how do we actually make sense of all of
that and make the right decision? And so there's a
lot of type out there. I feel like Kyle in
the in the AI space, and I think everybody's selling
you AI this, AI that, and you know, but what's
the strategy over that? Like and so i'd like, you know,
(09:57):
I know you have a specific framework that we've you
developed and maybe you know the break us down, like
you know, moving us away from the hype. You know,
AI is a tool. It's great. You know, you could
have lots of information, like you said, but what do
you do with all that information? How do you prioritize it?
How do you make sense that. It's just like when
you were doing your RecA and you're looking at different things,
You're evaluating all of these elements. Well, yeah, these are
(10:18):
not all equal, Okay, they have different weight. But how
do you how do you break that down? Maybe walk
us through your framework.
Speaker 2 (10:24):
Kyle, how to distinguish between you know, hype and things
with true value? Yeah right, yeah, I mean, I don't
know if there is an easy answer for it. But
the fact that you know we're answering, we're asking that
question begin with, it means we're on the right track.
I think I back up just a little bit and yeah,
it's you know, to your point, why is it important,
(10:46):
you know, to distinguish between the hype and and tools
that add real value. And AI, as we all know,
is a big disruptor across about every industry and when
companies don't adapt, you know, technologies that come out like this,
you know, you can easily go the way of Blockbuster,
(11:06):
Blockbuster or Kodak or BlackBerry. You know, when you take
your pick of all these companies that used to be
behemists leaders in the industry that no longer exist, right,
So no one wants that to happen. And I think
most most leaders, you know, most business leaders know that.
But the flip side of that is the hype, right,
you don't want to be chasing after every uh, every
(11:29):
shiny ball, you know, every bit of marketing you see
about the promises that AI is going to transform your
company or transform your personal life or whatever. If you
end up subscribing everything subscription based. Now, if you end up,
you know, subscribing to everything, you can quickly run up
expenses that you can't afford, right, So you'll end up
(11:49):
just with a whole repository of licenses that aren't getting used.
Speaker 1 (11:54):
Right.
Speaker 2 (11:54):
So it's it's being able to find the right balance
between those between those two things. And and so how
do you do that. There's probably a bunch of different methods,
but you just have to ask, you know, the right questions.
Speaker 1 (12:06):
You know, you.
Speaker 2 (12:07):
Have to ask, well, is this really does this really
align with our company's objectives? Will this really be useful?
Will it be adopted? You know, who's going to be
in charge of its adoption after we after we purchase it?
You know, it's kind of a change management question. And
then I think it's always useful to do a business
(12:28):
case on things in which you have someone an analyst
or a team that's in charge of really understanding the
both the direct and the indirect value you know of
this AI tool, right, and then compare that against how
much it costs. You know, from that you can derive
derive the r o I and the payback period, right,
And so if those numbers add up, you know, go
(12:49):
for it. But if after that analysis it doesn't, you know,
it doesn't really align. You're not sure about the you're
not sure about the value. You know, move on to
the next thing.
Speaker 1 (13:01):
So, yeah, no, I think that's important. I mean, you're right,
because there's there's a lot of things. It's like, I
think there's a lot of people that just think I
can plug and play get the description turns off, and
they're chasing trends. You know, maybe well this is a
new one. This is the new one. There is no
clear roadmap, if you will, Kyle of like, why do
(13:21):
we why do we have this tool? What's what's this
problem is solving? Is that, you know, is there something
more that we need to be thinking about? Right? And
so you know that that that's where I feel. I
seeing that, Kyle, and I think you know, there's a
lot of different things out there and depending on what
industry are what makes sense to be using How do
(13:42):
you want to use that? Who should have access? But
when do we want to use it? There's a whole
I come up with a whole lot of questions. So,
I mean, this is where I feel like having you
on the podcast, Kyle is is having somebody come along
in your business and asking helping you build a strategy.
Yeah you aren't you wasting time or spending on this
sary you know, money or effort looking after something that
(14:03):
and it doesn't really serve you, not at least not
going to get you as much of the results that
you're hoping for.
Speaker 2 (14:11):
I mean, I I would I would first of all,
have someone who's responsible for that, you know, within your organization.
Uh that has some you know, political influence in your
organization as well. Who's in charge of those sorts of
acquisitions of different tools? Right? And you want to you
want to ask like, okay, what's your framework for assessing
(14:34):
these things? What what you don't want to do though,
David is I see? Uh, this is this is one
area I believe where a lot of software developers also
get tripped up. Is there they're quick to be dismissive
of new tools as well. You know, they're they'll highlight
the things that jenerative AI screws up, you know, the
(14:56):
the bugs that are within the software, you know, with
the code that recommends and and so forth. They'll point
to those mistakes and say, you know, see we don't
you know, we don't need a humans, it's going to
be better. There's all sorts of faults with the code,
so you don't. Uh. And I think that may come
from sometimes sometimes software developers or the experts, they have
(15:21):
a point right that you know, you should approach things
with this AI, with new technology, with all these sense
of caution and skepticism, right. I think that's very important.
But also you don't want to throw the baby out
with the bathwater. If these tools can give you and
your team your company competitive edge, look into it. I
guess a metaphor from reconnaissance as well, from the Marine Corps,
(15:44):
because I was in a unit that got like all
this high speed equipment, right, you know, the newest goggles
and scopes and in different firearms and things like that.
But it was you know, you had to learn it.
You had to absolutely get training on it right, and
it was kind of another thing you had to add
to your already busy schedule. But do it, train with it.
(16:08):
If you don't need the tool, throw it out. But
a lot of times it gives you a serious competitive advantage,
you know, with the night vision devices we had, we
own the night right, but you have to train with that.
You got to, you know, make sure that you're the
laser on your rifle. You know, it actually like shows
up and it's styled in and uh, anyways, I don't
want to go down.
Speaker 1 (16:28):
Yeah, I know you're right, but you have to think
about if you the tool. I hear what you're saying, Kyle,
whatever tool, whatever it is, AI otherwise it can absolutely
give you a committed manager, but you have to take
the time to learn it, apply it, stay on top
of it. Either may be upgrades or changes, you know.
So it's it's you have to we only have so
much time and energy. So it's like, what are you
(16:49):
going to focus on. What's the tool or the resource
or what's going to make the most impact. Like you said,
maybe there was one that was working but that's now
obsolete or doesn't do the job as well well. But
it will take you time, just like AI to learn
something new. I think some people are hesitanting Kyle a
little bit about what's going to do. Is this going
to really help me? Right, They're like, Oh, I don't know.
I've got this tool. It's like, could this help me? Well,
(17:12):
it does take time, and the tool that you're doing
currently maybe does. It may be quicker in the short term,
but it's not going to give you the long committed
advantage in the long term, but it does take time.
Like how to shift and focus Like again strategy, Right,
it's Kyle like like they have to like think about
like planning for this.
Speaker 2 (17:31):
It's changed, right, and there's always there's always a lot
of friction when it comes to change. That's why there's
all these books and consultant consultant agencies that are established
because of you know how, even though you know you
may have the best tool in the world, getting folks
in your enterprise to adopt it, there's a lot of
friction that comes with that. And there's a whole life
(17:53):
cycle to tool adoption or strategic development that needs to
be shepherd every every step of the way.
Speaker 1 (18:02):
Right.
Speaker 2 (18:03):
So that's why you know, I delegating delegating this sort
of thing, delegating AI development or advancement to a competent
leader in your company. I recommend is the is the
place to start, right, and then you map out the
life cycle or the phases of which you adopt this technology,
(18:23):
and you make sure you make sure it's trapped right. So,
as we were saying at the beginning, you know, you
need to figure out, you know, assess what sort of
AI application you want to adopt first, and how are
you doing that? I think a good way to do
that is, you know, you just score based on impact
and feasibility that quadrant right or that matrix you know,
where selected ones in the top right that have the
(18:45):
highest impact, high highest feasibility, and you prioritize those right
now when you need to incorporate it or after you
purchase it, folks are going to need to get trained
on it, right, They're going to need to be made
aware of it, right. So that's that's both a communication plan, right,
and that's a training plan that you'd have to work
out with you know, your HR or who's ever the
(19:08):
most fit you know, most fit person to be involved
with that. And then and then afterwards you want to
track its effectiveness. Like let's say you get this tool implemented,
you have a vanguard that's trained on it, right, Okay,
is it really doing what the tool promised it to do?
And I think there's all sorts of ways you can
capture you know, different kprs, sorry, KPIs and OKRs. But
(19:33):
to put it broadly, I like one method. I need
to remember who I got this from.
Speaker 1 (19:39):
But we'll put it in the show notes, Kyle. So
anything we have, we'll make sure it's in the in
the show notes too.
Speaker 2 (19:45):
Right. So the book, the book is a Business Case
for AI. And this actually came out before twenty twenty
two and chat ChiPT came out in junior tobay AI
got real popular. But the Business Case for AI is
still a really good book on how to uh sort
of govern and provide oversight and really capture the value
(20:08):
of AI because it can be somewhat nebulous. And what
she what she recommends this author is that you assess
the business impact, the model accuracy, and the and the
user impact. Right. So, so it is a business impact, right,
is it really promising to deliver? Are we really capturing
the value or or lower the costs or retaining more customers? Right?
(20:33):
Or we uh, you know, is our employee satisfaction going up?
Whatever promise? You know, is that needle really moving? Post
implementation user success, that's what she calls a business success
user success. Model success. So user success is, you know,
how often are people spinning up this tool. You can
usually track this sort of thing, so a Microsoft pasture,
(20:56):
you know, I will show you the ping the ping
rate of how often a tool is getting use within
your within your company, right, so our user is actually
using it. If not right, let's say you have a
low engagement rate with your users. Maybe it's just not visible, right.
Maybe it's a quick fix, right, and it needs to
be put at the top of the web page ers
(21:16):
and some sort of in some random place. So that's
user success and then models success. We want to make
sure whatever the AI is outputting right, if it's if
it's forecasting you know, sells right, or if it's generative
AI that's providing insights about your company's standard operating procedures.
(21:38):
I want to make sure that the model is accurate.
And that's that's somewhat hard to gauge with generative AI.
Usually you know it's it's done through survey based you know,
and you have to differ a lot to your subject
matter experts. Right, if the model is accurate or not.
If it's more traditional artificial intelligence, we're doing machine learning
(22:00):
right to forecast certain things. And then there's all sorts
of metrics you can track from model success like accuracy, precision, recall,
F one score. But those those three broad categories a
business success success and model success is how you It's
how you gauge how uh effective your your purchase was,
(22:22):
your your acquisition of this new AI tool is I
think a starting point.
Speaker 1 (22:28):
So so from the from so from the quality of
AI perspective, Kyle, you know this. I think this is
great because I think what I'm hearing you is, Okay,
there's these these different areas we're looking at, and I
hear exactly what you're talking about the generative AI versus.
I just had another one of my podcasts who had
an amazing database information that he person assessments and things
(22:49):
like that which they could actually do and they could
verify that this was accurate or not right. And depends
on where you're pulling your data and all that stuff.
Like you're saying, so what so so now you have
this breakdown, So tell me a little bit more about
like how do you come alongside, how do you come
alongside businesses in this, Like you said, you might find
(23:09):
the leader. You might person's like, hey, I'm willing to
take this on. But where do you come alongside with
quality I and really help them in their in their
strategy with the Yeah, like, where do you come in
and in search themselves? Like where's the point where it's like, hey,
this is more than enough. I need help here to
make sure that I'm this effectively.
Speaker 2 (23:28):
Well, we try to ask you questions and listen real.
Speaker 1 (23:30):
Well, yes, that's so important.
Speaker 2 (23:34):
Absolutely, But we uh, we have a framework that we use.
It's called the Lyceum, the Lyceum Framework in it it uh,
you know, we we start there and it's a we
have eight different dimensions which we assess our clients AI strategy,
(23:54):
right or lack thereof?
Speaker 1 (23:56):
Yep?
Speaker 2 (23:57):
And does there's eight dimensions is are you know, the
first thing you want to assess us their planning? How
are they planning for AI? You know? Is it? Are
they doing it incrementally you know? Or are they planning
too far out? You know? Are they adaptable enough to
take advantage of new technologies as they emerge? But we
start we start with planning. Okay, that's a good point.
(24:19):
Are we even planning at all? Like, are we just
about this?
Speaker 1 (24:22):
So you're looking at you're asking me the question, are
you planning short term? Long term? Okay?
Speaker 2 (24:26):
We would you know you're planning.
Speaker 1 (24:29):
They're planning.
Speaker 2 (24:31):
Yeah, you're planning. Trickle down to the operational right, and
then the tacticals you know, agile level right. And then
so if the planning, you know what, we have a
series of questions there, you know, we score them from
one to five, right, and try to identify where their
gaps are, and they're planning, and we help them fill
those gaps and improve those gaps. Right. A lot of
(24:53):
backing up a little bit, David. We you know, we
a design thinking design thinking sessions. You know, we have
we have a lot of whiteboards, a lot of templates
we put together in which we but I mean it
all kind of follows the same, uh, the same agenda
in which you know, we we first, uh, identify the problem, right,
(25:15):
everyone lists up the problem to get everyone into the room, right,
and they they put on sticky notes whately the biggest
issue is they're facing in their department, right, and then
you know, we we identify gaps, let's see, and then
you know, we we idate on potential solutions, right, the
same thing, and then we prioritize those solutions, you know,
(25:36):
based on fuze back, feasibility and impact. Right, we figure
out which ones are more important than we kind of
list out and prioritize them and then put them on
a timeline. Right. That's that's sort of the gist of it.
I mean, that's maybe a little bit of an oversimplification,
but that's normally the course we take when we're doing
(25:57):
design thinking sessions. After the Lyceum framework. Maybe I'll just
cover these roles real quickly. Uh, there's planning right then,
the Scarbreels is safeguards, you know, it's the second the VSS.
You know, are they developing AI safely right across several
different dimensions securely? And then rapid prototyping? How do they prototype?
(26:20):
And quick thing on prototyping is you know, I'm sure
you've read certain headlineser statistics saying you know, x amount
of prototypes don't make it into production. So how do
you address that? Like, well, I think, well, you can
either make your prototyping process better, right, or you can
prototype more right both right, So right, and I'm totally
(26:45):
fine with prototyping a lot, right, and let's say only
ten percent of those make it to production. Like, well,
that's okay. We got a lot of experience, you know,
trying felling learning, trying felling learning, then finally trying and succeeding.
Speaker 1 (27:01):
Right.
Speaker 2 (27:01):
So but you know, you just probably need to identify
which course you want to take first. You want to
refine your prototyping process or do you want to make
h encourage citizen development right, in which we can prototype
more and we can enable people who don't even come
from a computer science background or a developer background right
(27:21):
to develop their own AI I can I can talk
about that later, but AI development has is starting to
become starting to become easy, right, and that's both a
good and a bad thing.
Speaker 1 (27:35):
Yeah, definitely. Well maybe we may have to have another
whole another podcast episode and that have you come back, Kyle.
Speaker 2 (27:40):
But that's why we that's why we talk about safeguards
and planning.
Speaker 1 (27:44):
Before we talk about prototyping.
Speaker 2 (27:47):
Yeah, and then after that, you know, we assess their
data is their data AI ready? A lot of these
generative AI tools use unstructured data, which the planning and
the the talent around unstructured data isn't in my observation
isn't as common as structured data relational database management. You know,
(28:09):
it's unstructured data. It's kind of a different animal. Right,
So as your data AI ready, and then we get
into tools and technologies, right, we call that the tech
arsenal Right, how do you like you're talking at the
beginning of the podcast, how do you assess which tools
are best to adopt? And what is your implementation plan?
(28:29):
Acquisition and implementation plan? Then after that, I mean, look,
that's the first five things we talked about. You're really
getting set up there to to incorporate AI, right, Well,
how do you how do you then train up your
people and institutionalize both your people and your AI agents
(28:52):
Because we're talking about intelligence, right, We're talking about artificial intelligence,
So there is maybe agency is the wrong. These AIS
have have a certain amount of agency, right, in which
they can take information, synthesize it, and then use that
information to accomplish task. Right. It's somewhat limited in scope. Still,
(29:17):
we haven't a g I, but there is specialized generative
AI that can reason or at least give the illusion
of reasoning, and then take action and perform task right,
based on what they what they reason that information to
be so that AI UH need you need to have
a plan to manage that in a very similar way
(29:37):
that you manage people, right, and and so that's that's
the UH what we're we at now. That's a sixth
part of the Lyceum framework is training and institutionalizing uh.
And then the last two are the AI advantage and
the AI c oe. So the AI advantage is you know,
as we were talking at the beginning of the call, David,
(29:58):
is this technology is a doubt being very very very rapidly.
We all know that. So we need people with their
air to the ground right that are partnering with the
right institutions, with the right you know, other other companies
perhaps right where you're you're staying on top of things,
right and again not chasing every shiny ball. But if
(30:18):
there's something that's going to give you a competitive advantage,
let's say, like there's a quantum breakthrough. I just want
to get a conference recently where we had some quantum
guys there. They were quantum security, brilliant individuals, man Aquin,
I need to get these over credits due, but we'll
put this in the show note as well. Absolutely one
(30:38):
of the key takeaways they had with quantum is that whoever,
whenever there is quantum supremacy, who's ever able to adapt
it to their industry, who's ever able to harness it first,
will command their industry. It's like they say, it's a
mathematical certainty, you know. So that's what's sort of thing
(31:00):
we want people to be listening for, right, look out
for is breakthroughs like that, because you can't just dismiss
everything like, oh, it's you know, it's at the what
do they call it, the peak of inflated expectations? Yeah,
you know, it'll it'll go into the traffic dissolution mitt first,
like are you sure is that a hope more or
or or is that really the reality? So yeah, keep
(31:24):
your ear to the ground. That's the AI. Yeah. And
then finally it's the A I C O E is
the center of excellence. This again is your is your
leadership team?
Speaker 1 (31:36):
Right?
Speaker 2 (31:36):
That makes sure it's all these.
Speaker 1 (31:37):
Noises me, I'm sorry, you're just get You're just popular, Kyle.
Speaker 2 (31:41):
Popular guy. Yeah for all of our listeners out there,
okay talking.
Speaker 1 (31:47):
Uh, but yeah, you need so.
Speaker 2 (31:50):
I come from a military background, as I mentioned at
the beginning of this call, and I just in the
in the in the I T industry will say is
they do not like hierarchy. They do not like any
anything where they feel like things are being bureaucratic or
they're being micromanaged. Flat the flat organizational structure manager is
(32:13):
almost a dirty word. And to be honest with you,
it all kind of sounds like I get it, you know,
bureaucracy will really throw slow things down. Let builders build
that sort of thing. But also some of it sounds
a bit communist to me too, like they have the
agile manifesto, you know, and anyways, there's the communist thing.
(32:37):
Maybe we'll get into later.
Speaker 1 (32:38):
But that'd be a whole other episode that we got.
We got multiple episodes. We'll have to come back to you, Kyle.
But what you were saying is that that yes, so
what I hear you saying, and this I get this
from the manager, like, hey, we don't want to have
somebody above us. We want to just have be able
to you know, there's they're not they're paying lip service
to the really the leadership that needs to be there.
There's a purpose for the leadership and and it's helping
(33:01):
build trust and structure that were like you said, just
like the AI, I think that we have to have
people there that they're looking after each other. It's not
a matter of I'm trying to serve power or control
over you. It's because I'm actually wanted to help you
be more successful.
Speaker 2 (33:17):
My that's exactly right. Yeah, So we have really good
project managers right that, they get it right. They're efficient,
they understand agile right there, they're SCRUMP certified and we
do daily stand ups. But yeah, the pms, they're keeping
everything on track and they're invaluable and just like you said,
they're enabling people to do their to do their job right.
Speaker 1 (33:42):
Yeah. It's like General.
Speaker 2 (33:44):
McCrystal came out with this book called Team of Teams,
and I don't I think he gives a perfect metaphor
for a leader, a good leader at least one that
really resonates with me. And he calls it the humble gardener.
And I think that metaphor is perfect because just like
a gardener is in charge of all the plants and
crops he or she is growing, they all need different
(34:05):
things right to grow. To grow, Yeah, some need more sunlight,
some mean more nitrogen, others need more phosphorus. You know, drainage.
Some of them are overcrowded. Some of them just need
to get prune and thrown out because they're taking up
resources that other plants need.
Speaker 1 (34:24):
Right.
Speaker 2 (34:25):
So, just like people, everyone's a little bit different. Everyone
needs different moles and you know, emotional support, things of
that nature to be the best version of themselves. Right.
So that's what I think. That is the sort of
leadership we have a quality of AI. That's the sort
of leadership principles we try our best to espouse and
(34:45):
live mine. But when you don't have that, when you
don't have any sort of hierarchy or any sort of
I guess we'll say bureaucracy or rigidity to your to
your organization, then you get things like that's not good either.
Speaker 1 (35:02):
No, no, it's not good either. We don't. We want
to healthy, like you said, healthy. That's why you and
I connected, I feel, Kyle, because we have similar passion.
I'm I'm more on the people side and the strategy
of your people versus necessary which you do integrate. What
I hear you telling me in your listener I mean
is people are part of it, but it's also using
this overall technology. How do we do that with the
(35:23):
people you know, make that successful integration.
Speaker 2 (35:27):
That's right. Yeah, yeah, yeah, I mean duplication of effort. Right,
You're gonna have people doing the same job, so just
be wasted effort. There's there's also folks that will play
the gray man right and fly under the radar, right,
and that's not cool because there's your team's relying on you,
people who will take advantage of that. So yeah, just
(35:50):
like you said, David, it's a little a little bit
of leadership in the right place. Is is essential, It's critical.
So that's why the last thing in our in our
framework is the A I c OE. But that could
be like your project management office or whoever your spirit
committee or leadership team is that is in charge of
(36:12):
the acquisition making sure everything you're doing with the AI
is managed throughout its entire life cycle, right from provisioning
it right to training up your people to measuring its
its success rate. Right. You need it. You need a
group of people that are in charge of that in
order for your AI strategy to really uh manifest and
(36:37):
permanent throughout throughout your company.
Speaker 1 (36:39):
Yeah. And I've seen that, Cayle, what you're saying. I've
seen this in other inities non AI initiatives, if nobody's
what I call it championing over seeing it, it comes
and it goes, and then it's like, well this was
left over to the side. It was just kind of like, oh,
where's where is this happening? So I know we're getting
the end of the podcast because and when we have
to come back and have a lot of good conversations here, Kyle.
(37:00):
But you know, you hit a number of different things
here in the Lyceum principle, and I hopefully I want
to hear people say because I feel like a lot
of people aren't even at stage one that you're talking
about planning. They're not planning among little let alone the
other components. And so you know, hopefully as they're hearing this,
you know, we're going to make sure that they can
connect with you, because we're connected on LinkedIn. We're gonna
(37:23):
put that in the show notes too, about how they
can get to quality AI, how they can you know,
maybe get you know, ask getting with you and asking
some of these questions and kind of getting clearer on hey,
what is your ROADBAP, what is your what is your plan?
And to walk them through this because what I see
is this is an ongoing need for companies that you
(37:44):
know are doing this in a very thoughtful way. And
I think it's really I'm from a leading way, a
leadership way, like you said. I like how you said
this is quantum way of like how they can really
leap forward if they do this well, they're really planning
and going forward. So you covered so many different things today.
I know a lot on the podcast, but you guys
are gonna have to go back and listen to it again.
(38:04):
But if I'm a business owner, I'm a leader, even
if I'm the but I'm I'm I'm seeing where there
is no strategy, there is no planning or roadmaple what
do you you know, what is your kind of takeaway
or what would be your you know, you know, your
call out there to folks in this space right now
leadership here in this age of AI and whatnot? What
(38:27):
to that I can be considering thinking about, of course,
in addition to calling and reaching out to you directly
pile but quality AI. But what should I be? What
should I what was your your takeaway? Call the action
here at the end of the podcast.
Speaker 2 (38:42):
Call the action for the for the companies that happened.
Speaker 1 (38:46):
Yeah, they have not had that just you know, they
haven't planned, they don't have a roadmap, you know what
what what what? You know that's me because I'm seeing
that a lot of one of the businesses and the
folks that I'm talking with, they don't have a click
plane where they go.
Speaker 2 (39:02):
Well, there there is a sense of urgency here, you know,
and not panic, but for the sake of you know,
your your company and the employees you know, and customers
and all the stakeholders involved with whatever product or service
you're offering. Considered. Yeah, our species you know, adapts and
(39:30):
changes absolutely after generation, and it just seems to be
happening more and more quickly. But you know, I guess
people say, we start out as hunter gatherers, right, and
then someone figured out seeds and agriculture started.
Speaker 1 (39:42):
Right.
Speaker 2 (39:43):
Those hunter gatherers didn't die off, right, that they found
other things to do, right, And then you think about
the transition into the industrial revolution, Right, the farmers didn't
die off. They became you know, factory workers or the
horse stables or or something thing like that. They found
other stuff to do, things to do and become productive.
(40:03):
And it's happening over and over again, you know, like
real war, we start to transition, uh, you know, from
manufacturing into into a service economy. Right, well, now we're
doing we're there's another epoch that we're transitioning into that
we're it's kind of uncertain, right, but but you know,
(40:25):
people aren't going to run out of things to do.
But people aren't going to whatever this happens. Whenever a
big transition like this happens, there's always a bit of disruption,
and it's it's hard on a lot of people. People
do lose their job.
Speaker 1 (40:40):
Right.
Speaker 2 (40:42):
What I think, uh, what a what a good leader
should do, and in this sort of transition transitory period
is equip their people and their workforce with the right
rules and the right training they need to not only strive,
but thrive, you know, and come out on the better
(41:05):
on the other end, better than what they were before.
Guide your ship, right, captain your go to these streams.
Speaker 1 (41:11):
Yeah, yeah, yeah, I love that. I love that, Kyle, No,
I think that's so important. Here's an opportunity. You can
either stick your head in the sand, kind of try
to ignore it, think that it's going to go over you,
or you can in this this or you can be
a leader that's going to step forward and say, hey, look,
I need to take care of my company, care care
(41:31):
of my people, take care of my clients. How can
you do it in a better thoughtful way? Kyle and
I appreciate you bringing that to the podcast today and
encouraging people to kind of look hold them you're up
and look at yourself. Are you doing that with AI
and all other areas of your of your life and business?
And you know, here's an opportunity so to come up
and connect with Kyle and his team at Quality AI
(41:52):
if you're like struggling in this area specifically of AI,
and how do we how do we go forward with this?
How do we leave more effectively? How I just want
to say thank you for coming on the podcast and
being a resource to our listeners. We will make sure
that they can connect with you, provide the talk a
number of different resources reference. We'll make sure that those
are on the show notes. Connect with you of course
on LinkedIn I'm there as well, or look to look
(42:16):
up Quality AI online. Thank you again so much for
being with us, Kyle.
Speaker 2 (42:21):
Yeah, thank you, David. It's a real pleasure being here.
But yeah, I last thing I would say is have
courage take heart and lead, get in front of it,
right because the sooner you do that, the sooner you'll
learn and be equipped to h to guide your company
through this thing. So yeah, David, it was a real pleasure.
Look forward to the speaking again. And if anybody wants
(42:41):
to find me or quality AI, you know, just go
to our website engage quality dot com. You can go
to LinkedIn and find us there as well. So we
also have an e learning course right if you If
you want to understand what the li seem is all about,
you can go to our website and find our e
learning course as well.
Speaker 1 (43:00):
Fantastic framework.
Speaker 2 (43:02):
Yeah, thank you, that's your pleasure being here. Thanks again, dude.
Speaker 1 (43:05):
All right, thanks everybody for listening. Being a part of
the business around Table Podcasts. Of course, we want you
to leave any comments feedback, so we'll make sure Kyle
get the subscribe and share this podcast if you found
it was helpful. If you're interested in being a guest,
let me know. We are always having a new guests
on the podcast. And until next time, be well. Thanks everybody,
take care,
Hello, and welcome back to the Business round Table podcast.
I am your host, David Carr, founder of Steward your
Business bringing people together to accomplish great things. And of
course this week we have another fantastic guest, Kyle Becker.
Super excited to have him here on the podcast. We're
going to talk all things AI, strategy and more. So
Welcome to the podcast, Kyle.
Speaker 2 (00:53):
Thank you. David can see you.
Speaker 1 (00:55):
Absolutely glad to have you here. I wanted to bring
Kyle on the podcast today because Kyle has just a
diverse background. I'm going to get let him share a
little bit about his background and what he got him
to creating quality AI. We're hearing a lot about AI
in the in the marketplace and whatnot. But what I
found that Kyle brings this unique perspective on strategy and
(01:16):
how he's helping companies organizations use this tool today. And
so Kyle, again, welcome to the podcast. I would love
for you to share a little bit with you about
your journey and before we recorded this podcast. You're sharing
a little bit about this from your military background and whatnot,
But what got you to create quality AI? Why is
your focus on strategy and if you wouldn't mind just
take us a little take us back a little bit
(01:37):
to your journey as a business owner and leader.
Speaker 2 (01:41):
Yeah, okay, So so Quality AI. The reason we started
it is we wanted to help companies put a holistic
framework around their AI strategy. Now how I got there was,
you know, we saw a gap sort of the in
the market place, a gap in sort of traditional strategic planning,
(02:04):
and we sought to fill it. You know, we thought
we could we were the right people to position ourselves,
you know, uh in such a way to where, uh
we could help our our clients, our partners understand how
to how to guide the ship right, because with AI,
there's so much uncertainty around AI, so much ambiguity, and
(02:26):
there's a lot of thoughts in people's minds. We'll say
that our influenced from you know, sci fi. Uh they're
both you know, both good but mostly bad, you know,
and no one knows how it's going to work out.
Is it going to be you know, a terminator thing
or is it going to be an eye robot? It
will help humanity or will we be enslaved by it?
(02:46):
So what we kind of decided at Quality AI is
it's it's hard to predict the future, right, it's even
harder to control the future. Right. So I think the
the you know, we're like a river going down stream.
You know, you can either try to control the flow
of the river or you can guide the ship. Right,
(03:09):
So we believe that trying to control the way. You know,
there's a lot of things that are being done with
you know, regulatory uh, you know, measures that are being
done with you like you see in the news every
day with Sam Alton and Elon Musk, you know, and
and a lot of a lot of tech behemoths going
before Congress, you know, talking about you know, where AI
(03:30):
is going. But we believe it's already so AI, you know,
it's already proliferated throughout every industry, you know, throughout every sector.
Already a lot of the stuff is open source. That
putting you know, putting regulations around it. Not that that's
a bad thing, but it's almost like putting a stick
and a river, you know, to try to control the flow.
(03:51):
The waters just go around it. So instead of trying
to dam up the river or redivert it, you know,
we we help our companies the ship. So whichever way
the future goes it's as smooth selling as possible, and
we're as adaptable.
Speaker 3 (04:07):
As we can be, you know, to the to So
can I ask you, Kyle, look what I like this
strategy you're talking about?
Speaker 1 (04:17):
What led you to kind of coming up of the
strategy because we know you're talking before we recorded, Like,
what led you to kind of coming this? Because I
know you've been in the Marine Corps in your background,
I would love to hear like kind of because it's
a different strategy. Like you said, some people are trying
to put a stick in the in the river. You're
you're proposing a different strategy. What what God brought you
to this kind of place? Yeah?
Speaker 2 (04:37):
Absolutely? Yeah, Sorry, David, I you're a goodding. I was
gonna manager so much. Uh uh. So. My background is
so I grew up in West Virginia kind of out
in the sticks, and I joined the Marine Corps from
a really young age. As soon as I turned eighteen,
I was in I was in boot camp ten days later,
and I spent you know, my the like the majority
(05:00):
of my twenties, well all of my twenties an active
duty in the Marine Corps and predominantly in a field
called reconnaissances, ground and recon Yeah, and our mension was
to you know, without getting caught. We were to insert
into the area of operations in which the main Marine Corps,
(05:22):
the main element we called it, is maneuvering into and
so there's a lot of uncertainty, the fog of war,
a lot of ambiguity about this battle space. Even with
you know, satellite imagery and other forms of intelligence is
SR imagery, surveillance, reconnaissance, you know, drones, and even with reconnaissance.
(05:45):
Ground reconnaissance is essential because you know, you've got guys
like me and my team out there. You know, actually
you know, looking at firsthand what the environment's like. So
we were to court information about rivers, streams, roads, the beach,
you know, wherever the battalion is going to make entry,
(06:07):
right their avenues, that approach. We would you know, get
all that data together into reports and send that up
to the commanders so they could make the best informed
decisions possible for their troop movements.
Speaker 1 (06:24):
Right.
Speaker 2 (06:25):
Yeah, we would collect information about the objective as well,
you know, where the enemy's at, their size, their disposition,
their uniforms, their weapons, if there's any high value targets
things like that, and we would also as well, when
the rainforse came, we would position ourselves to do what's
(06:45):
called a sniper initiated raid, right, which is right before
and then we usually would do this in tandem with
a unit like Force Recon, whereas there's more of a
limited scale raid right before they blow open the door,
you know, we would initiate raid with a sniper shot,
you know, taking up a century or an HBI or
something like that. So that was so anyways, that's all
(07:08):
to say. You asked me, like, what the hell does
this have to do with AI or data. Yeah, so
I think it's critical. I grew up, you know, gathering information,
getting it in the hands of people who have the
sort of control over you know, it's very high stakes game, right,
(07:33):
Lives are in the hands of the people who are
going to make decisions based off of this information. Right,
It's this critical that we're gathering the right sort of
right sort of stuff, right because our brothers and sisters
that were about to, you know, get into a fight,
are going to need to know everything about the environment
they're getting into. So I take it seriously. Right, So, now,
(07:56):
what I've been doing for the past few years. Is
I've been in data and AI, right, so I still
collect data, right, just in the Marine Corps, only the
environment is a little more comfortable. Now yeah, maybe it's.
Speaker 1 (08:12):
Still critical, still critical. I mean we need this information,
this critical making business decisions and how are you planning? Absolutely,
that's right.
Speaker 2 (08:20):
Yeah, making business decisions, you need the right sort of information, right,
And then AI needs the right sort of data as
well too to generate information that that is accurate, you know,
and uh, and so that's that's that's for a rat quality.
AI is, as I mentioned in the beginning of this call,
(08:41):
is about uh, you know, helping our clients develop strategy
uh in which they can guide their ship and make
the best decisions uh possible. So there's a lot that
goes into our framework.
Speaker 1 (08:54):
But yeah, well well well I want to break into that.
So so what I'm hearing is, you know, you're going
from uh to the re recon if you will, and
reinvention of like you're taking these things and focusing on
what's the most important and making decisions and I and
I love that, and I know you know that is
(09:14):
so powerful because we want to make powerful decisions. And
one of the things you shared to me, what I
really liked having you on the podcast was this pivot
of you know, you're in the military. You made have
been to prioritize you know, you're both dads and focusing
on what's most important. How do we make the decisions
that are most important our life making this taking all
the state of this information and then to actually you know,
(09:34):
make solid plans priorities, right, because there's lots of information,
but how do we actually make sense of all of
that and make the right decision? And so there's a
lot of type out there. I feel like Kyle in
the in the AI space, and I think everybody's selling
you AI this, AI that, and you know, but what's
the strategy over that? Like and so i'd like, you know,
(09:57):
I know you have a specific framework that we've you
developed and maybe you know the break us down, like
you know, moving us away from the hype. You know,
AI is a tool. It's great. You know, you could
have lots of information, like you said, but what do
you do with all that information? How do you prioritize it?
How do you make sense that. It's just like when
you were doing your RecA and you're looking at different things,
You're evaluating all of these elements. Well, yeah, these are
(10:18):
not all equal, Okay, they have different weight. But how
do you how do you break that down? Maybe walk
us through your framework.
Speaker 2 (10:24):
Kyle, how to distinguish between you know, hype and things
with true value? Yeah right, yeah, I mean, I don't
know if there is an easy answer for it. But
the fact that you know we're answering, we're asking that
question begin with, it means we're on the right track.
I think I back up just a little bit and yeah,
it's you know, to your point, why is it important,
(10:46):
you know, to distinguish between the hype and and tools
that add real value. And AI, as we all know,
is a big disruptor across about every industry and when
companies don't adapt, you know, technologies that come out like this,
you know, you can easily go the way of Blockbuster,
(11:06):
Blockbuster or Kodak or BlackBerry. You know, when you take
your pick of all these companies that used to be
behemists leaders in the industry that no longer exist, right,
So no one wants that to happen. And I think
most most leaders, you know, most business leaders know that.
But the flip side of that is the hype, right,
you don't want to be chasing after every uh, every
(11:29):
shiny ball, you know, every bit of marketing you see
about the promises that AI is going to transform your
company or transform your personal life or whatever. If you
end up subscribing everything subscription based. Now, if you end up,
you know, subscribing to everything, you can quickly run up
expenses that you can't afford, right, So you'll end up
(11:49):
just with a whole repository of licenses that aren't getting used.
Speaker 1 (11:54):
Right.
Speaker 2 (11:54):
So it's it's being able to find the right balance
between those between those two things. And and so how
do you do that. There's probably a bunch of different methods,
but you just have to ask, you know, the right questions.
Speaker 1 (12:06):
You know, you.
Speaker 2 (12:07):
Have to ask, well, is this really does this really
align with our company's objectives? Will this really be useful?
Will it be adopted? You know, who's going to be
in charge of its adoption after we after we purchase it?
You know, it's kind of a change management question. And
then I think it's always useful to do a business
(12:28):
case on things in which you have someone an analyst
or a team that's in charge of really understanding the
both the direct and the indirect value you know of
this AI tool, right, and then compare that against how
much it costs. You know, from that you can derive
derive the r o I and the payback period, right,
And so if those numbers add up, you know, go
(12:49):
for it. But if after that analysis it doesn't, you know,
it doesn't really align. You're not sure about the you're
not sure about the value. You know, move on to
the next thing.
Speaker 1 (13:01):
So, yeah, no, I think that's important. I mean, you're right,
because there's there's a lot of things. It's like, I
think there's a lot of people that just think I
can plug and play get the description turns off, and
they're chasing trends. You know, maybe well this is a
new one. This is the new one. There is no
clear roadmap, if you will, Kyle of like, why do
(13:21):
we why do we have this tool? What's what's this
problem is solving? Is that, you know, is there something
more that we need to be thinking about? Right? And
so you know that that that's where I feel. I
seeing that, Kyle, and I think you know, there's a
lot of different things out there and depending on what
industry are what makes sense to be using How do
(13:42):
you want to use that? Who should have access? But
when do we want to use it? There's a whole
I come up with a whole lot of questions. So,
I mean, this is where I feel like having you
on the podcast, Kyle is is having somebody come along
in your business and asking helping you build a strategy.
Yeah you aren't you wasting time or spending on this
sary you know, money or effort looking after something that
(14:03):
and it doesn't really serve you, not at least not
going to get you as much of the results that
you're hoping for.
Speaker 2 (14:11):
I mean, I I would I would first of all,
have someone who's responsible for that, you know, within your organization.
Uh that has some you know, political influence in your
organization as well. Who's in charge of those sorts of
acquisitions of different tools? Right? And you want to you
want to ask like, okay, what's your framework for assessing
(14:34):
these things? What what you don't want to do though,
David is I see? Uh, this is this is one
area I believe where a lot of software developers also
get tripped up. Is there they're quick to be dismissive
of new tools as well. You know, they're they'll highlight
the things that jenerative AI screws up, you know, the
(14:56):
the bugs that are within the software, you know, with
the code that recommends and and so forth. They'll point
to those mistakes and say, you know, see we don't
you know, we don't need a humans, it's going to
be better. There's all sorts of faults with the code,
so you don't. Uh. And I think that may come
from sometimes sometimes software developers or the experts, they have
(15:21):
a point right that you know, you should approach things
with this AI, with new technology, with all these sense
of caution and skepticism, right. I think that's very important.
But also you don't want to throw the baby out
with the bathwater. If these tools can give you and
your team your company competitive edge, look into it. I
guess a metaphor from reconnaissance as well, from the Marine Corps,
(15:44):
because I was in a unit that got like all
this high speed equipment, right, you know, the newest goggles
and scopes and in different firearms and things like that.
But it was you know, you had to learn it.
You had to absolutely get training on it right, and
it was kind of another thing you had to add
to your already busy schedule. But do it, train with it.
(16:08):
If you don't need the tool, throw it out. But
a lot of times it gives you a serious competitive advantage,
you know, with the night vision devices we had, we
own the night right, but you have to train with that.
You got to, you know, make sure that you're the
laser on your rifle. You know, it actually like shows
up and it's styled in and uh, anyways, I don't
want to go down.
Speaker 1 (16:28):
Yeah, I know you're right, but you have to think
about if you the tool. I hear what you're saying, Kyle,
whatever tool, whatever it is, AI otherwise it can absolutely
give you a committed manager, but you have to take
the time to learn it, apply it, stay on top
of it. Either may be upgrades or changes, you know.
So it's it's you have to we only have so
much time and energy. So it's like, what are you
(16:49):
going to focus on. What's the tool or the resource
or what's going to make the most impact. Like you said,
maybe there was one that was working but that's now
obsolete or doesn't do the job as well well. But
it will take you time, just like AI to learn
something new. I think some people are hesitanting Kyle a
little bit about what's going to do. Is this going
to really help me? Right, They're like, Oh, I don't know.
I've got this tool. It's like, could this help me? Well,
(17:12):
it does take time, and the tool that you're doing
currently maybe does. It may be quicker in the short term,
but it's not going to give you the long committed
advantage in the long term, but it does take time.
Like how to shift and focus Like again strategy, Right,
it's Kyle like like they have to like think about
like planning for this.
Speaker 2 (17:31):
It's changed, right, and there's always there's always a lot
of friction when it comes to change. That's why there's
all these books and consultant consultant agencies that are established
because of you know how, even though you know you
may have the best tool in the world, getting folks
in your enterprise to adopt it, there's a lot of
friction that comes with that. And there's a whole life
(17:53):
cycle to tool adoption or strategic development that needs to
be shepherd every every step of the way.
Speaker 1 (18:02):
Right.
Speaker 2 (18:03):
So that's why you know, I delegating delegating this sort
of thing, delegating AI development or advancement to a competent
leader in your company. I recommend is the is the
place to start, right, and then you map out the
life cycle or the phases of which you adopt this technology,
(18:23):
and you make sure you make sure it's trapped right. So,
as we were saying at the beginning, you know, you
need to figure out, you know, assess what sort of
AI application you want to adopt first, and how are
you doing that? I think a good way to do
that is, you know, you just score based on impact
and feasibility that quadrant right or that matrix you know,
where selected ones in the top right that have the
(18:45):
highest impact, high highest feasibility, and you prioritize those right
now when you need to incorporate it or after you
purchase it, folks are going to need to get trained
on it, right, They're going to need to be made
aware of it, right. So that's that's both a communication plan, right,
and that's a training plan that you'd have to work
out with you know, your HR or who's ever the
(19:08):
most fit you know, most fit person to be involved
with that. And then and then afterwards you want to
track its effectiveness. Like let's say you get this tool implemented,
you have a vanguard that's trained on it, right, Okay,
is it really doing what the tool promised it to do?
And I think there's all sorts of ways you can
capture you know, different kprs, sorry, KPIs and OKRs. But
(19:33):
to put it broadly, I like one method. I need
to remember who I got this from.
Speaker 1 (19:39):
But we'll put it in the show notes, Kyle. So
anything we have, we'll make sure it's in the in
the show notes too.
Speaker 2 (19:45):
Right. So the book, the book is a Business Case
for AI. And this actually came out before twenty twenty
two and chat ChiPT came out in junior tobay AI
got real popular. But the Business Case for AI is
still a really good book on how to uh sort
of govern and provide oversight and really capture the value
(20:08):
of AI because it can be somewhat nebulous. And what
she what she recommends this author is that you assess
the business impact, the model accuracy, and the and the
user impact. Right. So, so it is a business impact, right,
is it really promising to deliver? Are we really capturing
the value or or lower the costs or retaining more customers? Right?
(20:33):
Or we uh, you know, is our employee satisfaction going up?
Whatever promise? You know, is that needle really moving? Post
implementation user success, that's what she calls a business success
user success. Model success. So user success is, you know,
how often are people spinning up this tool. You can
usually track this sort of thing, so a Microsoft pasture,
(20:56):
you know, I will show you the ping the ping
rate of how often a tool is getting use within
your within your company, right, so our user is actually
using it. If not right, let's say you have a
low engagement rate with your users. Maybe it's just not visible, right.
Maybe it's a quick fix, right, and it needs to
be put at the top of the web page ers
(21:16):
and some sort of in some random place. So that's
user success and then models success. We want to make
sure whatever the AI is outputting right, if it's if
it's forecasting you know, sells right, or if it's generative
AI that's providing insights about your company's standard operating procedures.
(21:38):
I want to make sure that the model is accurate.
And that's that's somewhat hard to gauge with generative AI.
Usually you know it's it's done through survey based you know,
and you have to differ a lot to your subject
matter experts. Right, if the model is accurate or not.
If it's more traditional artificial intelligence, we're doing machine learning
(22:00):
right to forecast certain things. And then there's all sorts
of metrics you can track from model success like accuracy, precision, recall,
F one score. But those those three broad categories a
business success success and model success is how you It's
how you gauge how uh effective your your purchase was,
(22:22):
your your acquisition of this new AI tool is I
think a starting point.
Speaker 1 (22:28):
So so from the from so from the quality of
AI perspective, Kyle, you know this. I think this is
great because I think what I'm hearing you is, Okay,
there's these these different areas we're looking at, and I
hear exactly what you're talking about the generative AI versus.
I just had another one of my podcasts who had
an amazing database information that he person assessments and things
(22:49):
like that which they could actually do and they could
verify that this was accurate or not right. And depends
on where you're pulling your data and all that stuff.
Like you're saying, so what so so now you have
this breakdown, So tell me a little bit more about
like how do you come alongside, how do you come
alongside businesses in this, Like you said, you might find
(23:09):
the leader. You might person's like, hey, I'm willing to
take this on. But where do you come alongside with
quality I and really help them in their in their
strategy with the Yeah, like, where do you come in
and in search themselves? Like where's the point where it's like, hey,
this is more than enough. I need help here to
make sure that I'm this effectively.
Speaker 2 (23:28):
Well, we try to ask you questions and listen real.
Speaker 1 (23:30):
Well, yes, that's so important.
Speaker 2 (23:34):
Absolutely, But we uh, we have a framework that we use.
It's called the Lyceum, the Lyceum Framework in it it uh,
you know, we we start there and it's a we
have eight different dimensions which we assess our clients AI strategy,
(23:54):
right or lack thereof?
Speaker 1 (23:56):
Yep?
Speaker 2 (23:57):
And does there's eight dimensions is are you know, the
first thing you want to assess us their planning? How
are they planning for AI? You know? Is it? Are
they doing it incrementally you know? Or are they planning
too far out? You know? Are they adaptable enough to
take advantage of new technologies as they emerge? But we
start we start with planning. Okay, that's a good point.
(24:19):
Are we even planning at all? Like, are we just
about this?
Speaker 1 (24:22):
So you're looking at you're asking me the question, are
you planning short term? Long term? Okay?
Speaker 2 (24:26):
We would you know you're planning.
Speaker 1 (24:29):
They're planning.
Speaker 2 (24:31):
Yeah, you're planning. Trickle down to the operational right, and
then the tacticals you know, agile level right. And then
so if the planning, you know what, we have a
series of questions there, you know, we score them from
one to five, right, and try to identify where their
gaps are, and they're planning, and we help them fill
those gaps and improve those gaps. Right. A lot of
(24:53):
backing up a little bit, David. We you know, we
a design thinking design thinking sessions. You know, we have
we have a lot of whiteboards, a lot of templates
we put together in which we but I mean it
all kind of follows the same, uh, the same agenda
in which you know, we we first, uh, identify the problem, right,
(25:15):
everyone lists up the problem to get everyone into the room, right,
and they they put on sticky notes whately the biggest
issue is they're facing in their department, right, and then
you know, we we identify gaps, let's see, and then
you know, we we idate on potential solutions, right, the
same thing, and then we prioritize those solutions, you know,
(25:36):
based on fuze back, feasibility and impact. Right, we figure
out which ones are more important than we kind of
list out and prioritize them and then put them on
a timeline. Right. That's that's sort of the gist of it.
I mean, that's maybe a little bit of an oversimplification,
but that's normally the course we take when we're doing
(25:57):
design thinking sessions. After the Lyceum framework. Maybe I'll just
cover these roles real quickly. Uh, there's planning right then,
the Scarbreels is safeguards, you know, it's the second the VSS.
You know, are they developing AI safely right across several
different dimensions securely? And then rapid prototyping? How do they prototype?
(26:20):
And quick thing on prototyping is you know, I'm sure
you've read certain headlineser statistics saying you know, x amount
of prototypes don't make it into production. So how do
you address that? Like, well, I think, well, you can
either make your prototyping process better, right, or you can
prototype more right both right, So right, and I'm totally
(26:45):
fine with prototyping a lot, right, and let's say only
ten percent of those make it to production. Like, well,
that's okay. We got a lot of experience, you know,
trying felling learning, trying felling learning, then finally trying and succeeding.
Speaker 1 (27:01):
Right.
Speaker 2 (27:01):
So but you know, you just probably need to identify
which course you want to take first. You want to
refine your prototyping process or do you want to make
h encourage citizen development right, in which we can prototype
more and we can enable people who don't even come
from a computer science background or a developer background right
(27:21):
to develop their own AI I can I can talk
about that later, but AI development has is starting to
become starting to become easy, right, and that's both a
good and a bad thing.
Speaker 1 (27:35):
Yeah, definitely. Well maybe we may have to have another
whole another podcast episode and that have you come back, Kyle.
Speaker 2 (27:40):
But that's why we that's why we talk about safeguards
and planning.
Speaker 1 (27:44):
Before we talk about prototyping.
Speaker 2 (27:47):
Yeah, and then after that, you know, we assess their
data is their data AI ready? A lot of these
generative AI tools use unstructured data, which the planning and
the the talent around unstructured data isn't in my observation
isn't as common as structured data relational database management. You know,
(28:09):
it's unstructured data. It's kind of a different animal. Right,
So as your data AI ready, and then we get
into tools and technologies, right, we call that the tech
arsenal Right, how do you like you're talking at the
beginning of the podcast, how do you assess which tools
are best to adopt? And what is your implementation plan?
(28:29):
Acquisition and implementation plan? Then after that, I mean, look,
that's the first five things we talked about. You're really
getting set up there to to incorporate AI, right, Well,
how do you how do you then train up your
people and institutionalize both your people and your AI agents
(28:52):
Because we're talking about intelligence, right, We're talking about artificial intelligence,
So there is maybe agency is the wrong. These AIS
have have a certain amount of agency, right, in which
they can take information, synthesize it, and then use that
information to accomplish task. Right. It's somewhat limited in scope. Still,
(29:17):
we haven't a g I, but there is specialized generative
AI that can reason or at least give the illusion
of reasoning, and then take action and perform task right,
based on what they what they reason that information to
be so that AI UH need you need to have
a plan to manage that in a very similar way
(29:37):
that you manage people, right, and and so that's that's
the UH what we're we at now. That's a sixth
part of the Lyceum framework is training and institutionalizing uh.
And then the last two are the AI advantage and
the AI c oe. So the AI advantage is you know,
as we were talking at the beginning of the call, David,
(29:58):
is this technology is a doubt being very very very rapidly.
We all know that. So we need people with their
air to the ground right that are partnering with the
right institutions, with the right you know, other other companies
perhaps right where you're you're staying on top of things,
right and again not chasing every shiny ball. But if
(30:18):
there's something that's going to give you a competitive advantage,
let's say, like there's a quantum breakthrough. I just want
to get a conference recently where we had some quantum
guys there. They were quantum security, brilliant individuals, man Aquin,
I need to get these over credits due, but we'll
put this in the show note as well. Absolutely one
(30:38):
of the key takeaways they had with quantum is that whoever,
whenever there is quantum supremacy, who's ever able to adapt
it to their industry, who's ever able to harness it first,
will command their industry. It's like they say, it's a
mathematical certainty, you know. So that's what's sort of thing
(31:00):
we want people to be listening for, right, look out
for is breakthroughs like that, because you can't just dismiss
everything like, oh, it's you know, it's at the what
do they call it, the peak of inflated expectations? Yeah,
you know, it'll it'll go into the traffic dissolution mitt first,
like are you sure is that a hope more or
or or is that really the reality? So yeah, keep
(31:24):
your ear to the ground. That's the AI. Yeah. And
then finally it's the A I C O E is
the center of excellence. This again is your is your
leadership team?
Speaker 1 (31:36):
Right?
Speaker 2 (31:36):
That makes sure it's all these.
Speaker 1 (31:37):
Noises me, I'm sorry, you're just get You're just popular, Kyle.
Speaker 2 (31:41):
Popular guy. Yeah for all of our listeners out there,
okay talking.
Speaker 1 (31:47):
Uh, but yeah, you need so.
Speaker 2 (31:50):
I come from a military background, as I mentioned at
the beginning of this call, and I just in the
in the in the I T industry will say is
they do not like hierarchy. They do not like any
anything where they feel like things are being bureaucratic or
they're being micromanaged. Flat the flat organizational structure manager is
(32:13):
almost a dirty word. And to be honest with you,
it all kind of sounds like I get it, you know,
bureaucracy will really throw slow things down. Let builders build
that sort of thing. But also some of it sounds
a bit communist to me too, like they have the
agile manifesto, you know, and anyways, there's the communist thing.
(32:37):
Maybe we'll get into later.
Speaker 1 (32:38):
But that'd be a whole other episode that we got.
We got multiple episodes. We'll have to come back to you, Kyle.
But what you were saying is that that yes, so
what I hear you saying, and this I get this
from the manager, like, hey, we don't want to have
somebody above us. We want to just have be able
to you know, there's they're not they're paying lip service
to the really the leadership that needs to be there.
There's a purpose for the leadership and and it's helping
(33:01):
build trust and structure that were like you said, just
like the AI, I think that we have to have
people there that they're looking after each other. It's not
a matter of I'm trying to serve power or control
over you. It's because I'm actually wanted to help you
be more successful.
Speaker 2 (33:17):
My that's exactly right. Yeah, So we have really good
project managers right that, they get it right. They're efficient,
they understand agile right there, they're SCRUMP certified and we
do daily stand ups. But yeah, the pms, they're keeping
everything on track and they're invaluable and just like you said,
they're enabling people to do their to do their job right.
Speaker 1 (33:42):
Yeah. It's like General.
Speaker 2 (33:44):
McCrystal came out with this book called Team of Teams,
and I don't I think he gives a perfect metaphor
for a leader, a good leader at least one that
really resonates with me. And he calls it the humble gardener.
And I think that metaphor is perfect because just like
a gardener is in charge of all the plants and
crops he or she is growing, they all need different
(34:05):
things right to grow. To grow, Yeah, some need more sunlight,
some mean more nitrogen, others need more phosphorus. You know, drainage.
Some of them are overcrowded. Some of them just need
to get prune and thrown out because they're taking up
resources that other plants need.
Speaker 1 (34:24):
Right.
Speaker 2 (34:25):
So, just like people, everyone's a little bit different. Everyone
needs different moles and you know, emotional support, things of
that nature to be the best version of themselves. Right.
So that's what I think. That is the sort of
leadership we have a quality of AI. That's the sort
of leadership principles we try our best to espouse and
(34:45):
live mine. But when you don't have that, when you
don't have any sort of hierarchy or any sort of
I guess we'll say bureaucracy or rigidity to your to
your organization, then you get things like that's not good either.
Speaker 1 (35:02):
No, no, it's not good either. We don't. We want
to healthy, like you said, healthy. That's why you and
I connected, I feel, Kyle, because we have similar passion.
I'm I'm more on the people side and the strategy
of your people versus necessary which you do integrate. What
I hear you telling me in your listener I mean
is people are part of it, but it's also using
this overall technology. How do we do that with the
(35:23):
people you know, make that successful integration.
Speaker 2 (35:27):
That's right. Yeah, yeah, yeah, I mean duplication of effort. Right,
You're gonna have people doing the same job, so just
be wasted effort. There's there's also folks that will play
the gray man right and fly under the radar, right,
and that's not cool because there's your team's relying on you,
people who will take advantage of that. So yeah, just
(35:50):
like you said, David, it's a little a little bit
of leadership in the right place. Is is essential, It's critical.
So that's why the last thing in our in our
framework is the A I c OE. But that could
be like your project management office or whoever your spirit
committee or leadership team is that is in charge of
(36:12):
the acquisition making sure everything you're doing with the AI
is managed throughout its entire life cycle, right from provisioning
it right to training up your people to measuring its
its success rate. Right. You need it. You need a
group of people that are in charge of that in
order for your AI strategy to really uh manifest and
(36:37):
permanent throughout throughout your company.
Speaker 1 (36:39):
Yeah. And I've seen that, Cayle, what you're saying. I've
seen this in other inities non AI initiatives, if nobody's
what I call it championing over seeing it, it comes
and it goes, and then it's like, well this was
left over to the side. It was just kind of like, oh,
where's where is this happening? So I know we're getting
the end of the podcast because and when we have
to come back and have a lot of good conversations here, Kyle.
(37:00):
But you know, you hit a number of different things
here in the Lyceum principle, and I hopefully I want
to hear people say because I feel like a lot
of people aren't even at stage one that you're talking
about planning. They're not planning among little let alone the
other components. And so you know, hopefully as they're hearing this,
you know, we're going to make sure that they can
connect with you, because we're connected on LinkedIn. We're gonna
(37:23):
put that in the show notes too, about how they
can get to quality AI, how they can you know,
maybe get you know, ask getting with you and asking
some of these questions and kind of getting clearer on hey,
what is your ROADBAP, what is your what is your plan?
And to walk them through this because what I see
is this is an ongoing need for companies that you
(37:44):
know are doing this in a very thoughtful way. And
I think it's really I'm from a leading way, a
leadership way, like you said. I like how you said
this is quantum way of like how they can really
leap forward if they do this well, they're really planning
and going forward. So you covered so many different things today.
I know a lot on the podcast, but you guys
are gonna have to go back and listen to it again.
(38:04):
But if I'm a business owner, I'm a leader, even
if I'm the but I'm I'm I'm seeing where there
is no strategy, there is no planning or roadmaple what
do you you know, what is your kind of takeaway
or what would be your you know, you know, your
call out there to folks in this space right now
leadership here in this age of AI and whatnot? What
(38:27):
to that I can be considering thinking about, of course,
in addition to calling and reaching out to you directly
pile but quality AI. But what should I be? What
should I what was your your takeaway? Call the action
here at the end of the podcast.
Speaker 2 (38:42):
Call the action for the for the companies that happened.
Speaker 1 (38:46):
Yeah, they have not had that just you know, they
haven't planned, they don't have a roadmap, you know what
what what what? You know that's me because I'm seeing
that a lot of one of the businesses and the
folks that I'm talking with, they don't have a click
plane where they go.
Speaker 2 (39:02):
Well, there there is a sense of urgency here, you know,
and not panic, but for the sake of you know,
your your company and the employees you know, and customers
and all the stakeholders involved with whatever product or service
you're offering. Considered. Yeah, our species you know, adapts and
(39:30):
changes absolutely after generation, and it just seems to be
happening more and more quickly. But you know, I guess
people say, we start out as hunter gatherers, right, and
then someone figured out seeds and agriculture started.
Speaker 1 (39:42):
Right.
Speaker 2 (39:43):
Those hunter gatherers didn't die off, right, that they found
other things to do, right, And then you think about
the transition into the industrial revolution, Right, the farmers didn't
die off. They became you know, factory workers or the
horse stables or or something thing like that. They found
other stuff to do, things to do and become productive.
(40:03):
And it's happening over and over again, you know, like
real war, we start to transition, uh, you know, from
manufacturing into into a service economy. Right, well, now we're
doing we're there's another epoch that we're transitioning into that
we're it's kind of uncertain, right, but but you know,
(40:25):
people aren't going to run out of things to do.
But people aren't going to whatever this happens. Whenever a
big transition like this happens, there's always a bit of disruption,
and it's it's hard on a lot of people. People
do lose their job.
Speaker 1 (40:40):
Right.
Speaker 2 (40:42):
What I think, uh, what a what a good leader
should do, and in this sort of transition transitory period
is equip their people and their workforce with the right
rules and the right training they need to not only strive,
but thrive, you know, and come out on the better
(41:05):
on the other end, better than what they were before.
Guide your ship, right, captain your go to these streams.
Speaker 1 (41:11):
Yeah, yeah, yeah, I love that. I love that, Kyle, No,
I think that's so important. Here's an opportunity. You can
either stick your head in the sand, kind of try
to ignore it, think that it's going to go over you,
or you can in this this or you can be
a leader that's going to step forward and say, hey, look,
I need to take care of my company, care care
(41:31):
of my people, take care of my clients. How can
you do it in a better thoughtful way? Kyle and
I appreciate you bringing that to the podcast today and
encouraging people to kind of look hold them you're up
and look at yourself. Are you doing that with AI
and all other areas of your of your life and business?
And you know, here's an opportunity so to come up
and connect with Kyle and his team at Quality AI
(41:52):
if you're like struggling in this area specifically of AI,
and how do we how do we go forward with this?
How do we leave more effectively? How I just want
to say thank you for coming on the podcast and
being a resource to our listeners. We will make sure
that they can connect with you, provide the talk a
number of different resources reference. We'll make sure that those
are on the show notes. Connect with you of course
on LinkedIn I'm there as well, or look to look
(42:16):
up Quality AI online. Thank you again so much for
being with us, Kyle.
Speaker 2 (42:21):
Yeah, thank you, David. It's a real pleasure being here.
But yeah, I last thing I would say is have
courage take heart and lead, get in front of it,
right because the sooner you do that, the sooner you'll
learn and be equipped to h to guide your company
through this thing. So yeah, David, it was a real pleasure.
Look forward to the speaking again. And if anybody wants
(42:41):
to find me or quality AI, you know, just go
to our website engage quality dot com. You can go
to LinkedIn and find us there as well. So we
also have an e learning course right if you If
you want to understand what the li seem is all about,
you can go to our website and find our e
learning course as well.
Speaker 1 (43:00):
Fantastic framework.
Speaker 2 (43:02):
Yeah, thank you, that's your pleasure being here. Thanks again, dude.
Speaker 1 (43:05):
All right, thanks everybody for listening. Being a part of
the business around Table Podcasts. Of course, we want you
to leave any comments feedback, so we'll make sure Kyle
get the subscribe and share this podcast if you found
it was helpful. If you're interested in being a guest,
let me know. We are always having a new guests
on the podcast. And until next time, be well. Thanks everybody,
take care,
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