April 13, 2026 • 38 mins
Join Inside the Vault host Dave Miller as he talks with Dan Simkins and Doogie Levine from ATiiD. Dan and Doogie bring a wealth of experience in helping small businesses navigate the evolving landscape of artificial intelligence (AI).
In this episode, Dan, Doogie, and Dave explore the intersection of technology and human productivity, focusing on how small business owners can effectively integrate AI into their operations. Doogie and Dan discuss the challenges faced by small businesses and emphasize the importance of understanding both the technical and human aspects of AI implementation. They also provide actionable insights on the importance of documenting processes and organizing data to prepare for an AI-driven future. To learn more and to connect with ATiiD, visit their website at www.atiid.com.
Thank you for listening to this episode of Inside the Vault. Subscribe today and follow us for updates. If you have any questions or topics you would like to hear about, please email us at insidethevault@enterprisebankpgh.com!
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Episode Transcript
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(00:05):
Welcome to Inside the Vault, Enterprise Bank's podcast series where we talk
about items of interest to the small business community. Today,
we're going to dig into the emergence of
artificial intelligence, AI, and how it applies to businesses of
all size with a particular focus on our viewers
and listeners that are small business owners or involved in small privately
(00:26):
held companies. With me today are Dan Simkins and
Doogie Levine of ATiiD, which is
a business that is focused on local business
here in the Pittsburgh area that is focused on helping businesses engage
efficiently and effectively with AI. Dan, Doogie, welcome
(00:49):
Doogie's a repeat guest. It's a pleasure to be back. Dan's
new to us, but before we
start talking about ATiiD and how small
business owners can embrace this evolving AI landscape, get
a little background from you guys. So, Dan, let's start with
(01:09):
you. A little bit of your personal professional background,
OK, so my background, oddly enough,
starts in the creative, the arts. I have an arts
background and went to school for design, but
I graduated in the 90s. And that's when the internet
(01:30):
was that new technology that was becoming more graphical. And
to learn the internet, you had to learn HTML. And
so, I ended up going down the rabbit hole. Next thing I know, I wake up,
I'm a full-blown .NET developer designing and building databases. And
so, working shoulder to shoulder with computer science
majors, and I did that for about seven and a half years. But,
(01:53):
and then from there, I ended up in Healthcare, I
went to McKesson, I was in their implementations, I got promoted, led
several teams at McKesson, and went through their Six Sigma
Green Belt training program. And that was
great. And then from there, I went to another healthcare company
where I thought, oh, here's my dream job, I'm going to be an art director. So
(02:16):
I was an art director. And we did a lot of things in
marketing and e-learning. And so I had creative
people. I had web developers. I had a videographer. We
had a whole studio podcast, the whole nine yards. And
then they got acquired by Premier Health,
which is a, they do data analytics, and that's a great company out
(02:37):
of Charlotte, North Carolina. And so after that is
where I broke out on my own. I ended up deciding, hey,
let's, you know, take my try at business. And
because that was the frontier I hadn't reached yet. So to start
my own business, I started a marketing agency. And so that's the blend of
the creative and the technical, which is why marketing was just a
good fit. And so after,
(03:00):
and I got a business coach. So I have a business coach. And after about
a year or two, he says, hey, I have a business idea for you. And this is after chat
Yeah, and everyone's playing with it. And we would talk about it. And
he says, you should do AI consulting. And at first, I was very hesitant. I
thought, nah, it's chaos. Why would I wade into that mess? I
(03:21):
get it, but no one's figured it out yet. And he says, no, businesses need
someone like you to help make sense of that technology. And you seem
to be good at that. And so I said, OK,
here, we'll try it. I said, I'll analyze two businesses
as a case study because I don't know, you know, what I have to
offer or what needs to be done. But so after doing
(03:41):
two, analyzing two businesses, the light bulbs went
off and I thought, okay, now I get, you know, the challenge and
the importance. that businesses need to be, you know, understand
what this technology is going to offer and how to prepare
So, kind of your second go-around with an emerging technology started
(04:02):
with the proliferation of the internet and now
the proliferation of AI. Correct. So, you mentioned a business coach, which
is a good segue to Doogie, who the
bank has had a relationship with from a management consulting perspective.
Yeah, so I also have, I guess, a non-traditional background to getting to
doing what I'm doing, right? My background's in
(04:24):
youth work, mental health, behavioral health. You know, I
have a 12-year career of working with
kids and developing that. And then I started my first business,
which was a summer camp. So in
2019, I segue, I moved back to Pittsburgh, and I was looking for something to do. And
a light bulb went off when I started meeting business owners who were struggling with
(04:47):
how. How do I do the things that people are telling me to
do? How do I implement a plan? How do I build a system?
How do I help my team to actually achieve? So I started my
first business in Pittsburgh called IAS, Business Coaching Consulting,
to help people around operations, SOPs. And
that's what's actually evolved into what we do with
(05:08):
ATiiD. Because to be successful in
an AI future, you really have to have your operations dialed
in. You have to understand your workflows and how
you want people to actually do the job that you want them to do. Not
just from a functional standpoint, but from an emotional and behavioral standpoint to
get the most out of what AI is capable of doing. And that's
(05:29):
going back to even old school, taking data analytics, which
is like the first touch point that most people have with AI is,
you know, a Google analytics account or seeing on the website, the
traffic, whatever it was like you've been interacting with some form of
AI for a fairly long time. But it's
like being able to actually apply this and know how, that's where
(05:50):
our superpower attitude has become, you know, to really help
This is more than just technology. It's about process. It's about
Yeah. I mean, because without it, you know, if
you just try to implement AI without taking into account the human
components of it, it's not going to go anywhere. It's like trying to,
you know. or it's gonna be very painful, you
(06:12):
won't see results. So I think that's like a huge thing about
kind of how our backgrounds come together to really help and assist businesses
in a space. with this transition that other
Gotcha. So how did you guys get
together in forming and operating a
(06:34):
So, you know, we run in the same circles and
I knew Doogie and just even talking to
him, I was obviously became impressed with him early on.
And he knew me in the marketing sphere, and I shared with
him, hey, I'm doing these case studies, and I've decided this
is a good direction to move into. And basically,
(06:55):
he says, hey, let's talk. And what's interesting
from my background is, given that I have that creative and the technical, I
also have a lot of that leadership and process improvement right
through the Six Sigma. And I have an appreciation with
the human behavior process aspect
of it, which is a strength that Doogie really brings. And it
(07:16):
just made just complete sense because I knew technology
is only half the story and it's just our skill
And I thought we locked ourselves like we literally met for
a year before we decided to like launch. So this was
like in what, 2023? Yeah, something
like that. And in 2022, 2023, we locked ourselves in a room one day a week for
(07:38):
like two or three hours just to- For about two months. Yeah,
for months to go and say like, how is this
really going to impact businesses? What are they going to need? And at the same time, Dan's
starting to do these case studies. to see
where these businesses are starting to look at this. And I
think that's when a lot of light bulbs went off, because Dan's technical knowledge
(08:01):
of the foundation of AI, because the foundation of
AI is in .NET development. It's in database development.
It all comes down to data anyways. It
was like, oh, hold on. There's something special
here that really can you know, make positive
(08:22):
So you kind of focused yourselves as people
Yeah. So we wanted to, we knew just like
every other technology that's come out, there's going to be plenty of people building widgets,
right? Building something they think people want. and you
(08:42):
see tons of those on the market. And then you also have people that
are rushing to buy these things from small business all
the way up to large enterprise companies throwing billions and
trillions of dollars really at this thing without really analyzing
their business and understanding where should this fit. And
yeah, the biggest guys, they don't mind. They've got billions
(09:04):
of dollars in R&D money to throw around. But small business,
like you don't have that same money to be throwing and
making a mistake. A $2,000 investment. in
something might be a lot to a small business. You know,
a $10,000 investment is a huge thing. And,
you know, a $600,000 to build something custom, that's
(09:25):
like an impossible thing. But to get certain results,
that's the different levels we're talking about of what businesses need. So
we were saying like, okay, we need to look at your business use
case. Right? We have to look at your workflow, like how
you actually want to run your business before you go and just start wasting
money and throwing it around, hoping. This isn't, you
(09:50):
Gotcha. Gotcha. So, you know, talking with business owners
myself and what I do here for the bank, and I'm sure you guys,
I kind of see it as a, as kind of a continuum on
one end of the spectrum. You know, there's certain people
out there with the mindset that this is going, this is
going to be the end all be all. This is the greatest thing to happen to
(10:12):
data analytics and business efficiency and business
growth. And then you have the other end of the spectrum where,
oh my god, this is going to replace all my employees and all
the people and human touch of businesses. So
Well, I think a big part of our
(10:34):
sort of mission is to address that question. Is AI
going to replace our jobs? And just from my background or
my experience, and I know Dougie's as well, is from leading teams,
what you realize is the power of people. And what I see
in this technology is that people are still going to
be extremely crucial, right? So it's the idea of people
(10:56):
are going to be your ultimate resource because AI alone isn't
enough. And so what does that look like? And so I think a big motivation is
to say, let's help businesses design
the human role to account for this technology so
that they're getting the greatest impact. And so people, I
mean, that's the other thing. No one's, I mean, jobs are obviously going to change and
(11:18):
evolve and there's going to be some pain involved and it's
going to be scary. And that's just like all change, but you
know, with the right analysis and approach, you can help people see the
value of the shift. Because if you do that, they'll shift more
naturally, organically. And I think ultimately, AI is
going to help people's work be more fulfilling, to
(11:40):
Yeah. I mean, one of the things that we've noticed in our early implementations are
that people are getting to the harder parts of their
job. more you know faster more
often right so like you know instead of having
to spend hours doing research or hours writing documentation which
may be might feel good in the moment because you're checking a box
(12:02):
kind of thing but it's kind of wasteful and it's not where you get the
win right like you don't get the win in the research you don't get the win
in the writing of the the offer letter or the production
of the report or the you know maintenance log
or whatever you're providing your client like you don't get the win from that
you get the win from the interaction with the client and
(12:24):
the delivery of it and we're seeing that You
know, with AI, you're getting more time to do those and to
do them more successfully, more, you know, personally versus
like transactionally. So I
have a very positive outlook for AI. I think
for the most part, it's not going to replace jobs. It's going to make up more abundance
(12:45):
of jobs. However, there
are probably some positions that will be eliminated, but there's gonna be so many
Yeah, the Bob problem. Well, that's a slight different problem.
It's like every company has a Bob, you know, the guy that just knows how
to do all the things, right? Like, and
(13:05):
he's probably older, been there for a long time. He or she has been
there for a long time. And that's like AI
gives you the opportunity to capture that person's knowledge for
the first time. where it doesn't leave the door, right?
Like so many people are like, oh, I need to hold on to these people. Cause they're the only person
that knows how to run my machine. When it breaks, they're the only
(13:27):
one that knows how to fix it. Cause we've Jerry rigged this thing a million times. Yeah.
And we look at our business owner demographic, not just business
owners, but key employees, you know, we have an
aging business population here. A lot of that intelligence,
a lot of that skill, knowledge, experience, that's all capturable.
(13:48):
Yeah, and that's the nice thing. I know Dan has
a lot of, like this is what we consider the holy grail
of what this version of AI is going to be able to do. So I'll let Dan
talk more about like the Bob problems and how businesses can think about
Well, I think what's interesting is that This
technology, the power is now expanding beyond
(14:11):
what we've traditionally thought of how data is stored. It's
allowing you to store broader aspects of
information because AI and machine learning can
understand it. A lot of businesses aren't
thinking that way. This is a completely new approach,
but it's possible because it's just data. As long as you're storing data,
(14:33):
you can do something with it. The key is
what's good data versus bad data. That's why it's important
to have an analysis done or to create a
process by which you're capturing that
data. And so the ideas of the Bob, see, I know there's a
lot of fear around, well, I have my Bob and he's been here
(14:54):
25 years, he's not going to be here much longer. Well, the day Bob retires is
the day that knowledge is gone, right? He walks out the
door and or, you know, or if something happened, right, God forbid,
he gets hit by a bus. There's all that risk, right? So
It's going to take time to fully capture Bob's experience. So
what we're trying to encourage businesses now is you have to create
(15:16):
those processes now to capture that, because you also
not only do you want to capture Bob's experience, but you want Bob to validate
it, right? Because we're training models. So Bob can say, yes, the
model's giving you the result I would give you. Now you're confident that
you've captured Bob. But the other thing, which is with that blog
we just released, is the idea of apprenticeship, right? The idea that
(15:38):
Kids coming out of school don't have the knowledge that businesses need.
And so the concept is basically in the future with AI,
onboarding will be easier. Why? Because you're basically going
to pair your new employee with an AI model. and the AI
model will become their trainer. But once that human
gets to the point of a Bob-type knowledge, now
(16:02):
the AI shifts from being their trainer to their assistant, right?
And that's where work's going, and we can see it. And what we're saying to businesses is,
even if you can't fully implement it today or tomorrow,
let's say, still lay the groundwork to
capture Bob's knowledge today, because when you
do have the resources or when the technology comes
(16:25):
down in price enough where you can afford it, you want that data waiting for that moment
so that you can basically resurrect Bob as
Yeah. So dealing with, you know, small business, which is
the focus of the bank, the other thing I hear from
our clients is, I'm too small to worry about AI. This
is just for big companies and big data. And I'm
(16:47):
sure you guys, you know, with case studies and your
work, see that that is not necessarily a
limiting factor for use of AI, the size of the business. You
Yeah. So, you know, big companies,
of course, are going to be able to do bigger things with AI. but
(17:08):
they're also doing it at higher cost, right?
Like even just augmenting workflows
right now, just tacking on AI into certain parts of
it, you know, a basic LLM like ChatGBT or Claude
or Gemini or Copilot into your workflow,
either through human action, use this sequence and
(17:30):
do it or building agents or going full agentic tools.
Those are all accessible to small business. You know, what I just
talked about varies from $50 a month to
$1,000 total. You know, that's an accessible thing, minus
the build cost. Like, you know, the cost to do it, but
(17:50):
the benefits to a small business, like a 10 person employee company,
All right. You know what I mean? Like what's, what's one more employee, the
one you always wanted to add work to your company. So
we're at 30,000, 40,000, $50,000 a year for
a $12,000 investment. That's what's accessible still to small business.
(18:14):
And AI aside, the other thing I hear from, you
know, small privately held companies, mom and pop shops, small
employee count is I can't really
focus on strategy. I can't really focus on sales because
I'm so mired in my day-to-day operations. And
there's a real place for AI in, let's
(18:37):
say, making the more mundane day-to-day operations
Yeah, I mean, you know, that's a problem that I deal with in my previous business quite
a bit. I mean, first of all, it starts with their own belief system, right?
Like AI is not going to solve that problem if you don't actually want to
solve that problem. A lot of business owners want
to own the idea of being busy in their business and
(19:01):
they're like attached to it emotionally. This, I can't
focus on strategy, right? It's an emotional feeling of
like, oh, I have to be the guy doing it
or whatever. And it's like, unless you're willing to move on from that and move to,
okay, I want something more for my business than owning it as
a job, which is totally fine to be like, I want to own it as a job. That's
(19:21):
great. But if you want something more, that's when you'll
really be able to do it, because that's when you actually start documenting your processes and
you start actually saying, hold on, how can I make this faster, more
efficient? When you start asking yourself, how do I make this faster, more efficient, less
time consuming on me? That's when you'll be like, oh, let me see what AI
Yeah. So when we're talking
(19:43):
about AI in
the small or in the general business world. I mean, every
business owner, every key employee, they're getting hit in all directions from
the media. You know, talking about it
is this kind of nebulous thing. What
are the biggest mistakes you see business owners making
(20:05):
in this still relatively early stage of innovation in
terms of you know, trying to adopt something without really thinking it
In terms of mistakes, you know, the number one one is
not actually understanding their business, right? It's hard to
add in something brand new that isn't really understood, like,
as a market. Like, we actually don't know how we're
(20:28):
going to do AI at scale yet. Like, as a country, we don't
know how to do it. Like, it will cost over $8 trillion a year to
maintain the infrastructure for AI at scale. No
one knows how to do this. So like the cost of how to operate, it has to be dropped quite
a bit for it to become realistic as this widely
implemented thing. So the business use case is
(20:51):
the number one mistake that I see
with AI is what is my actual use cases for AI?
How should I be using it versus what I'm hearing or
seeing? So that's the number one thing that I would say.
Yeah, another might be that they're locking into
a specific technology without looking at it holistically, right?
(21:13):
So everyone's going to their preferred LLM, large language model,
for those who don't know what that is. You know, like a chat GPT, a Gemini. And
they're really hyper-focused on that, where when
you look at the process of the business that needs to
be accomplished right by a system it
might not AI might not be the answer that's a big problem as well
(21:35):
people assume well AI can do this yeah not as accurately
as you think and perhaps AI is
not what you need to solve that. It's more of an automated system.
Yeah, I was going to say the next mistake is thinking AI is the solution when
you need either. I was actually just talking with someone yesterday and
I was like, actually, a virtual assistant would do that a heck of a lot better than trying to force AI.
(21:57):
Hiring a VA would solve that problem, which
is a human being that works remote for your company. Would it
solve that problem 10 times more effectively? than
AI would right now, from a cost basis. And that's
something that I see all the time is like, well, when we do this analysis work
for companies to be like, actually, you know what, your problem can be solved more
(22:19):
cost effectively doing it this way than trying to fit AI. However,
when it gets to this point, or the cost to do it with AI comes
down to this point, switch to AI. You
know, but that's another, I would say that's probably the third
biggest mistake is forcing it into places where it doesn't apply
(22:40):
And one other point is that I feel that it's not, or
I think it's not orchestrated well, meaning, okay, they have X
number of employees and every employee is using AI to
do their role, but are they creating consistent results across?
Right. So that's part of it, I think. And also the idea of orchestrating But
getting into governance, well, even the governance, but even as OK,
(23:02):
if we've if you look at someone's role and they have
now gained efficiency with A.I. Are
they taking longer lunch breaks? Are they leaving home early? Have they
gained hours that the company could benefit from and the
company's missing out? Yeah. I mean, because that's really a big part of our analysis is
to say, and that's why when we look at the next iteration of what the job is,
(23:25):
is when we go into a business and say, well, here, you can automate all these things with
AI or machine learning. you know, a lot of, and they're hearing it in
the bigger companies, they're just laying off people. And what we're saying is, hey, before
you go and lay people off, people who've been in your industry, who
know your business, who know your customer, don't let them just walk
out the door. Yeah. So that's another thing. I think people aren't capturing those
(23:46):
extra hours that their employees have gained by using LLMs
Yeah. So interesting, interested in you guys take
on kind of open AI versus closed AI. And what I'm
getting at is, One of the things that scares me in my world,
we do a lot of startup businesses. And I
(24:07):
can, not that I'm a genius, but I've been doing this a long
time, I can tell an AI generated business plan. And
it's a little scary because, you know, part of
getting into a business and a startup scenario is doing your
own research and really understanding your market and
you know, just plugging in what you want to do into an open AI
(24:30):
model, how good is the intelligence that
you're getting? And is that really an appropriate way
to basically vet your risks, which
Well, here, that goes back to what I was saying, the importance
of the human aspect of the business, right? Because what
(24:52):
AI is good at is ideation, right? It'll create all these plans and
ideas. And ideas are a dime a dozen. The
hard part is executing on idea, right? Everyone can come up
with a business idea, but it's the person who execute and accomplishes it
and makes it profitable. Those are the ones that are
(25:13):
Blanket ideation, but it's going to take the human
to capture and make it happen and actually like it's actually on the flip
side I would say it's on the bank would have to
change its processes of how it's actually evaluating it like whereas
traditionally you would take You know I would assume you would take the business plan
you would review and be like oh, this is good Let's move on to the next step You
(25:33):
actually probably need to put in more questioning of the items in this
like okay great I saw in this that you your ideal ICP is
X. How did you verify that? You
know, what methodology did you use to verify this? Or
Right? Like, by adding in more questioning, first of all, you're going to
get a higher quality investment from the bank standpoint,
(25:56):
because they're either going to know the answer, they're not going to know the answer, and
they're going to have to go get it. And that's not something that AI is
going to be able to do, because they can go back and say, how did you verify? And the AI is going to be like, well, I
guessed. I mean, that's most likely what it will say. And
then they're going to have to actually do some sort of verification exercise, which is
going to be like, well, how can I verify this? They might ask the AI that
(26:17):
and the AI is going to be like, well, here's a few ideas, you know, go
survey this type of client or schedule me,
you know, you're ultimately going to get a better startup
company than even the previous way. Gotcha. You
know, even though they're auto generating the minutiae and the formatting, you
But can you guys talk a little bit about that concept of, you
(26:38):
know, open AI versus closed AI? A lot of what we were talking
about from an efficiency perspective is capturing internal company
data for training purposes for growth versus
Yeah. So you're talking more about protecting your data versus like
using an open source model like an LM, right? So,
(27:02):
Yeah. So, a couple things is, one, the one
crucial thing for small businesses that they have to understand is that
they are at the mercy of someone
creating a tool for them to use, right? So, for instance, these
larger companies are building them in-house, right? But
the good news is, like any other technology, it's becoming cheaper. And
(27:24):
right now, like, say, for instance, Microsoft. Microsoft's creating easier environments
Yeah, so it's not that unaffordable. So it's there for
the people. But also what the small businesses have
to understand is that their tools that they're using
(27:45):
are getting smarter. And that's another aspect of advice for small
businesses is rather than focus on AI broadly
of all the confusion of what's out there, try to focus on
the tools you're using and make sure you're keeping up with how they're advancing. And
sometimes maybe a competing version of their CRM or
ERP or some tool they're using is implement an
(28:06):
AI that would help them. Maybe they shift or whatever. That's
just things they'll have to navigate going forward is
the idea of reading through their
And from a functional standpoint, we talk about like governance, the rules that
a company makes for what is and is not being put into different
(28:29):
types of sources. So that could be even like,
okay, we do allow AI to be used for planning,
ideation, this, this, this x, w, but we don't allow
it for this, you know, And that's fine, right?
Cause that will still protect. I just couldn't imagine that companies are
actually putting in too much actual sensitive data, right?
(28:52):
Like, cause all the stuff you might want to do in your workflow, you
can either just not put that information in from the beginning and say, leave it blank, I'll
fill it in. Right? It's not a necessary
thing. Or it's probably not
I couldn't imagine that there's that much secret data work
(29:18):
Gotcha. So, process. How
does a small business eat this elephant? What
are, at a very high level, what are
the best steps in the process to
So, I like to tell people, when I talk to people about
(29:39):
AI, I'm like, have you dabbled yet? So
there's like, I put my toe in the water is I use chat
to UBT to help me write an email. Right.
That's like step one for most people right now is that's their
story. Um, then I go. have
you dabbled? Which is, have you started asking this
(30:00):
LLM, if it's ChatGVT or any of the other ones, how you can
help my business? Have you asked it that question versus just
feeding it for a result? When you start asking that
question, that's when you're starting to figure out how AI actually works
and how it can help you. So those are
the first two steps is tone the water, just start using it. Two,
(30:21):
start asking questions about you. So you have to give it some information about
you. This is who we are, this is how we work, blah, blah, blah, blah, blah. This
is what I'm trying to accomplish. And then ask
it, how can I help you? And then start trying. Once
you do that, then you're ready to start engaging and talking about, okay, I
need to talk to people about how to make AI really work for my business. But
(30:43):
after those two stages, that's when you're really ready to start diving
Yeah. And from a fear factor perspective, another
thing I think business owners, you guys speak to this from your
experience, your competitors are doing this. Or
it may, Maybe not. But
(31:05):
you don't want to be catching
up, so to speak. Timing-wise,
what scale of business, what stage of business makes
I would say as soon as possible. The one term I like to
(31:26):
use is I tell people, AI is not going to
be a light switch that you can just flick on and it's going to work. To
really leverage it most fully in
your business, you have to make sure that your data is
Sometimes that could be... And by data, we
(31:50):
correct. But there's also the idea, as we touched upon earlier,
is because of AI's advancement,
are there other data points that you've never thought to
capture just because you've been in that traditional mindset of, OK, here,
client name, address, phone number, contact, what they ordered, whatever.
There's all kinds of data outside of that that you can
(32:12):
actually start capturing. And so it's really about just
You know analyzing your business and preparing it now so when
I tell people is if your competitor is
Fully leveraging AI to where it's now caused them
has given them a capacity beyond you Again, you're not
gonna be able just flick on a light switch. You're now probably six months to a year behind
(32:35):
So that's why we're telling businesses start now and that's kind of what the service
we do is say look We're gonna analyze your business and
we're gonna determine where it makes sense to implement now But we also give
them as part of the roadmap Here's an ultimate vision
for where you can be with AI. So we're not telling them,
oh, you have to get there today. But that
(32:55):
needs to be your new bullseye as far as on the horizon line.
And start implementing this technology and improving your processes and
your data gradually so that you're moving in the right direction. So
that once that technology fully becomes available and
effective at achieving that, you'll
(33:17):
Gotcha. Well, great segue. So how
do business owners of all sizes, how
do they engage with ATiiD? What resources?
So there are, yeah, the best ways to engage with us are one,
connect with us on LinkedIn. So, you know, we have our ATiiD page,
we have our personal pages. We put out tons of content that
(33:39):
can help businesses just around AI. how
to think about it, how to strategize around it, so that's a great way to just collect
information. To contact us, I would say, you know, fill
out our thing on our website, you know, come to our website, fill out a contact form, we'll
connect with you. You can also email us, I'm doogie,
at a T, D-O-G-I-E, at a T, A-T-I-I-D.com, super
(34:02):
easy. The other thing I wanna put out there for everybody is we run
a community for the Pittsburgh Tech Council, called
Steel City AI Innovators. We have a monthly meetup every
second Wednesday of the month. And this is a great place for
if you are a complete novice in AI to, I'm an
expert in AI, to come meet. We do live workshops there
(34:24):
on AI tools. We do theoretical discussions. We have
speakers. And I really encourage people that are like,
I'm nervous, I'm scared, or I'm avid, like
I am an evangelist. This is the place to be. Because the
reason we started this group was we wanted to bridge
the gap. between these
people who are building these high-tech tools and the implementations at the
(34:47):
high level to the people that want to use it every day. Because so
much technology is developed in these silos of what people think and then it's forced
on them. This doesn't have to be that way. Come
to the room, be a part of the discussion, and shape what the future of AI is
And I'm assuming, you know, your initial engagement with a
business business, potential business client is kind
(35:10):
Exactly. Yeah. I mean, just one conversation with us will give
you a good idea of what your potential is. And
then, from there, if they want to engage with us
to do a roadmap, in that first conversation, we
determine, okay, where is a good place to start and focus this analysis? And
then, if they want to engage with us, we'll do a roadmap analysis on
(35:32):
that given process. And
in our roadmap, we're giving them a layout of what their tech
is today, what it will look like in the AI implementation. But
we also include the human behavioral. Here's what your people or
you are doing as a process, and here's what they should
(35:55):
As I always do in concluding our podcast episodes,
nuggets of advice for entrepreneur small
business owners in this realm parting words well i would
say you have to start the analysis now
on your business because like i said it's going to take some preparation,
(36:16):
and it's going to be, there's a lot of complete
dynamic shifts in how businesses are going to be run,
how they work and function, and
again, what data they capture and what data they leverage. And the earlier
you get on, get into the idea
of capturing that, what would be a good approach to an AI
(36:39):
Yeah, I would say organize your business, right? Like if
you don't have documented process right now, documented
workflows, just start there. Like
you can start with the man. First of all, AI can help you with that. Be like, Hey, I need
to document my prop workflows. I'm a landscaper. Yeah. Okay.
Help me do this. Let's start with a list of all the things. Um,
(37:03):
Start there, because that's gonna tell you what information is important
to capture, which is the next thing I would say is organize your
data. Once you understand your workflows, now you understand what
information's important. Once you do that, now you're starting to get
So again, for our viewers and listeners, Emerging
technology, still in the early stages, but we have some local
(37:25):
resources here that can help even the smallest of
businesses kind of embrace this change in the
business landscape and this new technology. Dan Doogie.
Thanks for the info. For those of you that have
any questions or ideas for future episodes, you can
email us at InsideTheVault at EnterpriseBankPGH.com. You
(37:48):
can check us out in audio format on all the major podcast platforms
and in video format on YouTube. Once again, guys, thanks
for the info. And for our viewers and listeners, thanks for
Welcome to Inside the Vault, Enterprise Bank's podcast series where we talk
about items of interest to the small business community. Today,
we're going to dig into the emergence of
artificial intelligence, AI, and how it applies to businesses of
all size with a particular focus on our viewers
and listeners that are small business owners or involved in small privately
(00:26):
held companies. With me today are Dan Simkins and
Doogie Levine of ATiiD, which is
a business that is focused on local business
here in the Pittsburgh area that is focused on helping businesses engage
efficiently and effectively with AI. Dan, Doogie, welcome
(00:49):
Doogie's a repeat guest. It's a pleasure to be back. Dan's
new to us, but before we
start talking about ATiiD and how small
business owners can embrace this evolving AI landscape, get
a little background from you guys. So, Dan, let's start with
(01:09):
you. A little bit of your personal professional background,
OK, so my background, oddly enough,
starts in the creative, the arts. I have an arts
background and went to school for design, but
I graduated in the 90s. And that's when the internet
(01:30):
was that new technology that was becoming more graphical. And
to learn the internet, you had to learn HTML. And
so, I ended up going down the rabbit hole. Next thing I know, I wake up,
I'm a full-blown .NET developer designing and building databases. And
so, working shoulder to shoulder with computer science
majors, and I did that for about seven and a half years. But,
(01:53):
and then from there, I ended up in Healthcare, I
went to McKesson, I was in their implementations, I got promoted, led
several teams at McKesson, and went through their Six Sigma
Green Belt training program. And that was
great. And then from there, I went to another healthcare company
where I thought, oh, here's my dream job, I'm going to be an art director. So
(02:16):
I was an art director. And we did a lot of things in
marketing and e-learning. And so I had creative
people. I had web developers. I had a videographer. We
had a whole studio podcast, the whole nine yards. And
then they got acquired by Premier Health,
which is a, they do data analytics, and that's a great company out
(02:37):
of Charlotte, North Carolina. And so after that is
where I broke out on my own. I ended up deciding, hey,
let's, you know, take my try at business. And
because that was the frontier I hadn't reached yet. So to start
my own business, I started a marketing agency. And so that's the blend of
the creative and the technical, which is why marketing was just a
good fit. And so after,
(03:00):
and I got a business coach. So I have a business coach. And after about
a year or two, he says, hey, I have a business idea for you. And this is after chat
Yeah, and everyone's playing with it. And we would talk about it. And
he says, you should do AI consulting. And at first, I was very hesitant. I
thought, nah, it's chaos. Why would I wade into that mess? I
(03:21):
get it, but no one's figured it out yet. And he says, no, businesses need
someone like you to help make sense of that technology. And you seem
to be good at that. And so I said, OK,
here, we'll try it. I said, I'll analyze two businesses
as a case study because I don't know, you know, what I have to
offer or what needs to be done. But so after doing
(03:41):
two, analyzing two businesses, the light bulbs went
off and I thought, okay, now I get, you know, the challenge and
the importance. that businesses need to be, you know, understand
what this technology is going to offer and how to prepare
So, kind of your second go-around with an emerging technology started
(04:02):
with the proliferation of the internet and now
the proliferation of AI. Correct. So, you mentioned a business coach, which
is a good segue to Doogie, who the
bank has had a relationship with from a management consulting perspective.
Yeah, so I also have, I guess, a non-traditional background to getting to
doing what I'm doing, right? My background's in
(04:24):
youth work, mental health, behavioral health. You know, I
have a 12-year career of working with
kids and developing that. And then I started my first business,
which was a summer camp. So in
2019, I segue, I moved back to Pittsburgh, and I was looking for something to do. And
a light bulb went off when I started meeting business owners who were struggling with
(04:47):
how. How do I do the things that people are telling me to
do? How do I implement a plan? How do I build a system?
How do I help my team to actually achieve? So I started my
first business in Pittsburgh called IAS, Business Coaching Consulting,
to help people around operations, SOPs. And
that's what's actually evolved into what we do with
(05:08):
ATiiD. Because to be successful in
an AI future, you really have to have your operations dialed
in. You have to understand your workflows and how
you want people to actually do the job that you want them to do. Not
just from a functional standpoint, but from an emotional and behavioral standpoint to
get the most out of what AI is capable of doing. And that's
(05:29):
going back to even old school, taking data analytics, which
is like the first touch point that most people have with AI is,
you know, a Google analytics account or seeing on the website, the
traffic, whatever it was like you've been interacting with some form of
AI for a fairly long time. But it's
like being able to actually apply this and know how, that's where
(05:50):
our superpower attitude has become, you know, to really help
This is more than just technology. It's about process. It's about
Yeah. I mean, because without it, you know, if
you just try to implement AI without taking into account the human
components of it, it's not going to go anywhere. It's like trying to,
you know. or it's gonna be very painful, you
(06:12):
won't see results. So I think that's like a huge thing about
kind of how our backgrounds come together to really help and assist businesses
in a space. with this transition that other
Gotcha. So how did you guys get
together in forming and operating a
(06:34):
So, you know, we run in the same circles and
I knew Doogie and just even talking to
him, I was obviously became impressed with him early on.
And he knew me in the marketing sphere, and I shared with
him, hey, I'm doing these case studies, and I've decided this
is a good direction to move into. And basically,
(06:55):
he says, hey, let's talk. And what's interesting
from my background is, given that I have that creative and the technical, I
also have a lot of that leadership and process improvement right
through the Six Sigma. And I have an appreciation with
the human behavior process aspect
of it, which is a strength that Doogie really brings. And it
(07:16):
just made just complete sense because I knew technology
is only half the story and it's just our skill
And I thought we locked ourselves like we literally met for
a year before we decided to like launch. So this was
like in what, 2023? Yeah, something
like that. And in 2022, 2023, we locked ourselves in a room one day a week for
(07:38):
like two or three hours just to- For about two months. Yeah,
for months to go and say like, how is this
really going to impact businesses? What are they going to need? And at the same time, Dan's
starting to do these case studies. to see
where these businesses are starting to look at this. And I
think that's when a lot of light bulbs went off, because Dan's technical knowledge
(08:01):
of the foundation of AI, because the foundation of
AI is in .NET development. It's in database development.
It all comes down to data anyways. It
was like, oh, hold on. There's something special
here that really can you know, make positive
(08:22):
So you kind of focused yourselves as people
Yeah. So we wanted to, we knew just like
every other technology that's come out, there's going to be plenty of people building widgets,
right? Building something they think people want. and you
(08:42):
see tons of those on the market. And then you also have people that
are rushing to buy these things from small business all
the way up to large enterprise companies throwing billions and
trillions of dollars really at this thing without really analyzing
their business and understanding where should this fit. And
yeah, the biggest guys, they don't mind. They've got billions
(09:04):
of dollars in R&D money to throw around. But small business,
like you don't have that same money to be throwing and
making a mistake. A $2,000 investment. in
something might be a lot to a small business. You know,
a $10,000 investment is a huge thing. And,
you know, a $600,000 to build something custom, that's
(09:25):
like an impossible thing. But to get certain results,
that's the different levels we're talking about of what businesses need. So
we were saying like, okay, we need to look at your business use
case. Right? We have to look at your workflow, like how
you actually want to run your business before you go and just start wasting
money and throwing it around, hoping. This isn't, you
(09:50):
Gotcha. Gotcha. So, you know, talking with business owners
myself and what I do here for the bank, and I'm sure you guys,
I kind of see it as a, as kind of a continuum on
one end of the spectrum. You know, there's certain people
out there with the mindset that this is going, this is
going to be the end all be all. This is the greatest thing to happen to
(10:12):
data analytics and business efficiency and business
growth. And then you have the other end of the spectrum where,
oh my god, this is going to replace all my employees and all
the people and human touch of businesses. So
Well, I think a big part of our
(10:34):
sort of mission is to address that question. Is AI
going to replace our jobs? And just from my background or
my experience, and I know Dougie's as well, is from leading teams,
what you realize is the power of people. And what I see
in this technology is that people are still going to
be extremely crucial, right? So it's the idea of people
(10:56):
are going to be your ultimate resource because AI alone isn't
enough. And so what does that look like? And so I think a big motivation is
to say, let's help businesses design
the human role to account for this technology so
that they're getting the greatest impact. And so people, I
mean, that's the other thing. No one's, I mean, jobs are obviously going to change and
(11:18):
evolve and there's going to be some pain involved and it's
going to be scary. And that's just like all change, but you
know, with the right analysis and approach, you can help people see the
value of the shift. Because if you do that, they'll shift more
naturally, organically. And I think ultimately, AI is
going to help people's work be more fulfilling, to
(11:40):
Yeah. I mean, one of the things that we've noticed in our early implementations are
that people are getting to the harder parts of their
job. more you know faster more
often right so like you know instead of having
to spend hours doing research or hours writing documentation which
may be might feel good in the moment because you're checking a box
(12:02):
kind of thing but it's kind of wasteful and it's not where you get the
win right like you don't get the win in the research you don't get the win
in the writing of the the offer letter or the production
of the report or the you know maintenance log
or whatever you're providing your client like you don't get the win from that
you get the win from the interaction with the client and
(12:24):
the delivery of it and we're seeing that You
know, with AI, you're getting more time to do those and to
do them more successfully, more, you know, personally versus
like transactionally. So I
have a very positive outlook for AI. I think
for the most part, it's not going to replace jobs. It's going to make up more abundance
(12:45):
of jobs. However, there
are probably some positions that will be eliminated, but there's gonna be so many
Yeah, the Bob problem. Well, that's a slight different problem.
It's like every company has a Bob, you know, the guy that just knows how
to do all the things, right? Like, and
(13:05):
he's probably older, been there for a long time. He or she has been
there for a long time. And that's like AI
gives you the opportunity to capture that person's knowledge for
the first time. where it doesn't leave the door, right?
Like so many people are like, oh, I need to hold on to these people. Cause they're the only person
that knows how to run my machine. When it breaks, they're the only
(13:27):
one that knows how to fix it. Cause we've Jerry rigged this thing a million times. Yeah.
And we look at our business owner demographic, not just business
owners, but key employees, you know, we have an
aging business population here. A lot of that intelligence,
a lot of that skill, knowledge, experience, that's all capturable.
(13:48):
Yeah, and that's the nice thing. I know Dan has
a lot of, like this is what we consider the holy grail
of what this version of AI is going to be able to do. So I'll let Dan
talk more about like the Bob problems and how businesses can think about
Well, I think what's interesting is that This
technology, the power is now expanding beyond
(14:11):
what we've traditionally thought of how data is stored. It's
allowing you to store broader aspects of
information because AI and machine learning can
understand it. A lot of businesses aren't
thinking that way. This is a completely new approach,
but it's possible because it's just data. As long as you're storing data,
(14:33):
you can do something with it. The key is
what's good data versus bad data. That's why it's important
to have an analysis done or to create a
process by which you're capturing that
data. And so the ideas of the Bob, see, I know there's a
lot of fear around, well, I have my Bob and he's been here
(14:54):
25 years, he's not going to be here much longer. Well, the day Bob retires is
the day that knowledge is gone, right? He walks out the
door and or, you know, or if something happened, right, God forbid,
he gets hit by a bus. There's all that risk, right? So
It's going to take time to fully capture Bob's experience. So
what we're trying to encourage businesses now is you have to create
(15:16):
those processes now to capture that, because you also
not only do you want to capture Bob's experience, but you want Bob to validate
it, right? Because we're training models. So Bob can say, yes, the
model's giving you the result I would give you. Now you're confident that
you've captured Bob. But the other thing, which is with that blog
we just released, is the idea of apprenticeship, right? The idea that
(15:38):
Kids coming out of school don't have the knowledge that businesses need.
And so the concept is basically in the future with AI,
onboarding will be easier. Why? Because you're basically going
to pair your new employee with an AI model. and the AI
model will become their trainer. But once that human
gets to the point of a Bob-type knowledge, now
(16:02):
the AI shifts from being their trainer to their assistant, right?
And that's where work's going, and we can see it. And what we're saying to businesses is,
even if you can't fully implement it today or tomorrow,
let's say, still lay the groundwork to
capture Bob's knowledge today, because when you
do have the resources or when the technology comes
(16:25):
down in price enough where you can afford it, you want that data waiting for that moment
so that you can basically resurrect Bob as
Yeah. So dealing with, you know, small business, which is
the focus of the bank, the other thing I hear from
our clients is, I'm too small to worry about AI. This
is just for big companies and big data. And I'm
(16:47):
sure you guys, you know, with case studies and your
work, see that that is not necessarily a
limiting factor for use of AI, the size of the business. You
Yeah. So, you know, big companies,
of course, are going to be able to do bigger things with AI. but
(17:08):
they're also doing it at higher cost, right?
Like even just augmenting workflows
right now, just tacking on AI into certain parts of
it, you know, a basic LLM like ChatGBT or Claude
or Gemini or Copilot into your workflow,
either through human action, use this sequence and
(17:30):
do it or building agents or going full agentic tools.
Those are all accessible to small business. You know, what I just
talked about varies from $50 a month to
$1,000 total. You know, that's an accessible thing, minus
the build cost. Like, you know, the cost to do it, but
(17:50):
the benefits to a small business, like a 10 person employee company,
All right. You know what I mean? Like what's, what's one more employee, the
one you always wanted to add work to your company. So
we're at 30,000, 40,000, $50,000 a year for
a $12,000 investment. That's what's accessible still to small business.
(18:14):
And AI aside, the other thing I hear from, you
know, small privately held companies, mom and pop shops, small
employee count is I can't really
focus on strategy. I can't really focus on sales because
I'm so mired in my day-to-day operations. And
there's a real place for AI in, let's
(18:37):
say, making the more mundane day-to-day operations
Yeah, I mean, you know, that's a problem that I deal with in my previous business quite
a bit. I mean, first of all, it starts with their own belief system, right?
Like AI is not going to solve that problem if you don't actually want to
solve that problem. A lot of business owners want
to own the idea of being busy in their business and
(19:01):
they're like attached to it emotionally. This, I can't
focus on strategy, right? It's an emotional feeling of
like, oh, I have to be the guy doing it
or whatever. And it's like, unless you're willing to move on from that and move to,
okay, I want something more for my business than owning it as
a job, which is totally fine to be like, I want to own it as a job. That's
(19:21):
great. But if you want something more, that's when you'll
really be able to do it, because that's when you actually start documenting your processes and
you start actually saying, hold on, how can I make this faster, more
efficient? When you start asking yourself, how do I make this faster, more efficient, less
time consuming on me? That's when you'll be like, oh, let me see what AI
Yeah. So when we're talking
(19:43):
about AI in
the small or in the general business world. I mean, every
business owner, every key employee, they're getting hit in all directions from
the media. You know, talking about it
is this kind of nebulous thing. What
are the biggest mistakes you see business owners making
(20:05):
in this still relatively early stage of innovation in
terms of you know, trying to adopt something without really thinking it
In terms of mistakes, you know, the number one one is
not actually understanding their business, right? It's hard to
add in something brand new that isn't really understood, like,
as a market. Like, we actually don't know how we're
(20:28):
going to do AI at scale yet. Like, as a country, we don't
know how to do it. Like, it will cost over $8 trillion a year to
maintain the infrastructure for AI at scale. No
one knows how to do this. So like the cost of how to operate, it has to be dropped quite
a bit for it to become realistic as this widely
implemented thing. So the business use case is
(20:51):
the number one mistake that I see
with AI is what is my actual use cases for AI?
How should I be using it versus what I'm hearing or
seeing? So that's the number one thing that I would say.
Yeah, another might be that they're locking into
a specific technology without looking at it holistically, right?
(21:13):
So everyone's going to their preferred LLM, large language model,
for those who don't know what that is. You know, like a chat GPT, a Gemini. And
they're really hyper-focused on that, where when
you look at the process of the business that needs to
be accomplished right by a system it
might not AI might not be the answer that's a big problem as well
(21:35):
people assume well AI can do this yeah not as accurately
as you think and perhaps AI is
not what you need to solve that. It's more of an automated system.
Yeah, I was going to say the next mistake is thinking AI is the solution when
you need either. I was actually just talking with someone yesterday and
I was like, actually, a virtual assistant would do that a heck of a lot better than trying to force AI.
(21:57):
Hiring a VA would solve that problem, which
is a human being that works remote for your company. Would it
solve that problem 10 times more effectively? than
AI would right now, from a cost basis. And that's
something that I see all the time is like, well, when we do this analysis work
for companies to be like, actually, you know what, your problem can be solved more
(22:19):
cost effectively doing it this way than trying to fit AI. However,
when it gets to this point, or the cost to do it with AI comes
down to this point, switch to AI. You
know, but that's another, I would say that's probably the third
biggest mistake is forcing it into places where it doesn't apply
(22:40):
And one other point is that I feel that it's not, or
I think it's not orchestrated well, meaning, okay, they have X
number of employees and every employee is using AI to
do their role, but are they creating consistent results across?
Right. So that's part of it, I think. And also the idea of orchestrating But
getting into governance, well, even the governance, but even as OK,
(23:02):
if we've if you look at someone's role and they have
now gained efficiency with A.I. Are
they taking longer lunch breaks? Are they leaving home early? Have they
gained hours that the company could benefit from and the
company's missing out? Yeah. I mean, because that's really a big part of our analysis is
to say, and that's why when we look at the next iteration of what the job is,
(23:25):
is when we go into a business and say, well, here, you can automate all these things with
AI or machine learning. you know, a lot of, and they're hearing it in
the bigger companies, they're just laying off people. And what we're saying is, hey, before
you go and lay people off, people who've been in your industry, who
know your business, who know your customer, don't let them just walk
out the door. Yeah. So that's another thing. I think people aren't capturing those
(23:46):
extra hours that their employees have gained by using LLMs
Yeah. So interesting, interested in you guys take
on kind of open AI versus closed AI. And what I'm
getting at is, One of the things that scares me in my world,
we do a lot of startup businesses. And I
(24:07):
can, not that I'm a genius, but I've been doing this a long
time, I can tell an AI generated business plan. And
it's a little scary because, you know, part of
getting into a business and a startup scenario is doing your
own research and really understanding your market and
you know, just plugging in what you want to do into an open AI
(24:30):
model, how good is the intelligence that
you're getting? And is that really an appropriate way
to basically vet your risks, which
Well, here, that goes back to what I was saying, the importance
of the human aspect of the business, right? Because what
(24:52):
AI is good at is ideation, right? It'll create all these plans and
ideas. And ideas are a dime a dozen. The
hard part is executing on idea, right? Everyone can come up
with a business idea, but it's the person who execute and accomplishes it
and makes it profitable. Those are the ones that are
(25:13):
Blanket ideation, but it's going to take the human
to capture and make it happen and actually like it's actually on the flip
side I would say it's on the bank would have to
change its processes of how it's actually evaluating it like whereas
traditionally you would take You know I would assume you would take the business plan
you would review and be like oh, this is good Let's move on to the next step You
(25:33):
actually probably need to put in more questioning of the items in this
like okay great I saw in this that you your ideal ICP is
X. How did you verify that? You
know, what methodology did you use to verify this? Or
Right? Like, by adding in more questioning, first of all, you're going to
get a higher quality investment from the bank standpoint,
(25:56):
because they're either going to know the answer, they're not going to know the answer, and
they're going to have to go get it. And that's not something that AI is
going to be able to do, because they can go back and say, how did you verify? And the AI is going to be like, well, I
guessed. I mean, that's most likely what it will say. And
then they're going to have to actually do some sort of verification exercise, which is
going to be like, well, how can I verify this? They might ask the AI that
(26:17):
and the AI is going to be like, well, here's a few ideas, you know, go
survey this type of client or schedule me,
you know, you're ultimately going to get a better startup
company than even the previous way. Gotcha. You
know, even though they're auto generating the minutiae and the formatting, you
But can you guys talk a little bit about that concept of, you
(26:38):
know, open AI versus closed AI? A lot of what we were talking
about from an efficiency perspective is capturing internal company
data for training purposes for growth versus
Yeah. So you're talking more about protecting your data versus like
using an open source model like an LM, right? So,
(27:02):
Yeah. So, a couple things is, one, the one
crucial thing for small businesses that they have to understand is that
they are at the mercy of someone
creating a tool for them to use, right? So, for instance, these
larger companies are building them in-house, right? But
the good news is, like any other technology, it's becoming cheaper. And
(27:24):
right now, like, say, for instance, Microsoft. Microsoft's creating easier environments
Yeah, so it's not that unaffordable. So it's there for
the people. But also what the small businesses have
to understand is that their tools that they're using
(27:45):
are getting smarter. And that's another aspect of advice for small
businesses is rather than focus on AI broadly
of all the confusion of what's out there, try to focus on
the tools you're using and make sure you're keeping up with how they're advancing. And
sometimes maybe a competing version of their CRM or
ERP or some tool they're using is implement an
(28:06):
AI that would help them. Maybe they shift or whatever. That's
just things they'll have to navigate going forward is
the idea of reading through their
And from a functional standpoint, we talk about like governance, the rules that
a company makes for what is and is not being put into different
(28:29):
types of sources. So that could be even like,
okay, we do allow AI to be used for planning,
ideation, this, this, this x, w, but we don't allow
it for this, you know, And that's fine, right?
Cause that will still protect. I just couldn't imagine that companies are
actually putting in too much actual sensitive data, right?
(28:52):
Like, cause all the stuff you might want to do in your workflow, you
can either just not put that information in from the beginning and say, leave it blank, I'll
fill it in. Right? It's not a necessary
thing. Or it's probably not
I couldn't imagine that there's that much secret data work
(29:18):
Gotcha. So, process. How
does a small business eat this elephant? What
are, at a very high level, what are
the best steps in the process to
So, I like to tell people, when I talk to people about
(29:39):
AI, I'm like, have you dabbled yet? So
there's like, I put my toe in the water is I use chat
to UBT to help me write an email. Right.
That's like step one for most people right now is that's their
story. Um, then I go. have
you dabbled? Which is, have you started asking this
(30:00):
LLM, if it's ChatGVT or any of the other ones, how you can
help my business? Have you asked it that question versus just
feeding it for a result? When you start asking that
question, that's when you're starting to figure out how AI actually works
and how it can help you. So those are
the first two steps is tone the water, just start using it. Two,
(30:21):
start asking questions about you. So you have to give it some information about
you. This is who we are, this is how we work, blah, blah, blah, blah, blah. This
is what I'm trying to accomplish. And then ask
it, how can I help you? And then start trying. Once
you do that, then you're ready to start engaging and talking about, okay, I
need to talk to people about how to make AI really work for my business. But
(30:43):
after those two stages, that's when you're really ready to start diving
Yeah. And from a fear factor perspective, another
thing I think business owners, you guys speak to this from your
experience, your competitors are doing this. Or
it may, Maybe not. But
(31:05):
you don't want to be catching
up, so to speak. Timing-wise,
what scale of business, what stage of business makes
I would say as soon as possible. The one term I like to
(31:26):
use is I tell people, AI is not going to
be a light switch that you can just flick on and it's going to work. To
really leverage it most fully in
your business, you have to make sure that your data is
Sometimes that could be... And by data, we
(31:50):
correct. But there's also the idea, as we touched upon earlier,
is because of AI's advancement,
are there other data points that you've never thought to
capture just because you've been in that traditional mindset of, OK, here,
client name, address, phone number, contact, what they ordered, whatever.
There's all kinds of data outside of that that you can
(32:12):
actually start capturing. And so it's really about just
You know analyzing your business and preparing it now so when
I tell people is if your competitor is
Fully leveraging AI to where it's now caused them
has given them a capacity beyond you Again, you're not
gonna be able just flick on a light switch. You're now probably six months to a year behind
(32:35):
So that's why we're telling businesses start now and that's kind of what the service
we do is say look We're gonna analyze your business and
we're gonna determine where it makes sense to implement now But we also give
them as part of the roadmap Here's an ultimate vision
for where you can be with AI. So we're not telling them,
oh, you have to get there today. But that
(32:55):
needs to be your new bullseye as far as on the horizon line.
And start implementing this technology and improving your processes and
your data gradually so that you're moving in the right direction. So
that once that technology fully becomes available and
effective at achieving that, you'll
(33:17):
Gotcha. Well, great segue. So how
do business owners of all sizes, how
do they engage with ATiiD? What resources?
So there are, yeah, the best ways to engage with us are one,
connect with us on LinkedIn. So, you know, we have our ATiiD page,
we have our personal pages. We put out tons of content that
(33:39):
can help businesses just around AI. how
to think about it, how to strategize around it, so that's a great way to just collect
information. To contact us, I would say, you know, fill
out our thing on our website, you know, come to our website, fill out a contact form, we'll
connect with you. You can also email us, I'm doogie,
at a T, D-O-G-I-E, at a T, A-T-I-I-D.com, super
(34:02):
easy. The other thing I wanna put out there for everybody is we run
a community for the Pittsburgh Tech Council, called
Steel City AI Innovators. We have a monthly meetup every
second Wednesday of the month. And this is a great place for
if you are a complete novice in AI to, I'm an
expert in AI, to come meet. We do live workshops there
(34:24):
on AI tools. We do theoretical discussions. We have
speakers. And I really encourage people that are like,
I'm nervous, I'm scared, or I'm avid, like
I am an evangelist. This is the place to be. Because the
reason we started this group was we wanted to bridge
the gap. between these
people who are building these high-tech tools and the implementations at the
(34:47):
high level to the people that want to use it every day. Because so
much technology is developed in these silos of what people think and then it's forced
on them. This doesn't have to be that way. Come
to the room, be a part of the discussion, and shape what the future of AI is
And I'm assuming, you know, your initial engagement with a
business business, potential business client is kind
(35:10):
Exactly. Yeah. I mean, just one conversation with us will give
you a good idea of what your potential is. And
then, from there, if they want to engage with us
to do a roadmap, in that first conversation, we
determine, okay, where is a good place to start and focus this analysis? And
then, if they want to engage with us, we'll do a roadmap analysis on
(35:32):
that given process. And
in our roadmap, we're giving them a layout of what their tech
is today, what it will look like in the AI implementation. But
we also include the human behavioral. Here's what your people or
you are doing as a process, and here's what they should
(35:55):
As I always do in concluding our podcast episodes,
nuggets of advice for entrepreneur small
business owners in this realm parting words well i would
say you have to start the analysis now
on your business because like i said it's going to take some preparation,
(36:16):
and it's going to be, there's a lot of complete
dynamic shifts in how businesses are going to be run,
how they work and function, and
again, what data they capture and what data they leverage. And the earlier
you get on, get into the idea
of capturing that, what would be a good approach to an AI
(36:39):
Yeah, I would say organize your business, right? Like if
you don't have documented process right now, documented
workflows, just start there. Like
you can start with the man. First of all, AI can help you with that. Be like, Hey, I need
to document my prop workflows. I'm a landscaper. Yeah. Okay.
Help me do this. Let's start with a list of all the things. Um,
(37:03):
Start there, because that's gonna tell you what information is important
to capture, which is the next thing I would say is organize your
data. Once you understand your workflows, now you understand what
information's important. Once you do that, now you're starting to get
So again, for our viewers and listeners, Emerging
technology, still in the early stages, but we have some local
(37:25):
resources here that can help even the smallest of
businesses kind of embrace this change in the
business landscape and this new technology. Dan Doogie.
Thanks for the info. For those of you that have
any questions or ideas for future episodes, you can
email us at InsideTheVault at EnterpriseBankPGH.com. You
(37:48):
can check us out in audio format on all the major podcast platforms
and in video format on YouTube. Once again, guys, thanks
for the info. And for our viewers and listeners, thanks for
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