November 5, 2025 • 27 mins
Forget the sci‑fi headlines. We zero in on the kind of AI that actually ships value today and unpack how to choose it, pilot it, and prove ROI without blowing up your workflow. With Ken Johnson from USIT Systems, we sort hype from reality, cut through vendor noise, and focus on targeted wins that save time, reduce errors, and move the bottom line.
We start by clarifying the landscape: narrow AI that powers predictive text, chatbots, and smart thermostats is the workhorse of modern automation. Strong or self‑aware systems remain theory, while early “theory of mind” experiments are emerging in eldercare robotics. From there, we get practical. Ken walks through a simple framework: define the pain point, quantify cost versus value, choose whether your goal is direct monetization or better predictions, and run a small pilot before scaling. You’ll hear real cases, like a clinic enabling secure after‑hours bill pay and a dealership forecasting inventory and buyer segments to tune marketing and stocking.
We also tackle the pitfalls. Predictive systems can trap you in your past choices, narrowing research for tools and even healthcare providers. Vendor ecosystems push their own models, so we talk about comparing outputs, maintaining optionality, and avoiding lock‑in. Then we look at where AI meets robotics to make work safer and more consistent: fryer automation that reduces burns, robots handling hazardous tasks, and near‑term hospital helpers that free nurses to focus on human care. Through it all, the theme holds: AI augments people and process, but human judgment sets the guardrails.
If you’re ready to turn AI from a buzzword into a line on your P&L, this conversation gives you the blueprint. Subscribe for more practical tech strategy, share this with a teammate planning an automation pilot, and leave a review telling us the first task you’d automate.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Intro/Close (00:00):
Welcome to Tech Talk, your go-to guide for
making technology work for you.
Whether you're running agrowing business or just trying
to keep things running smoothlyat home, we've got IT covered.
US IT Systems brings theknowledge, experience, and
solutions you need to stayconnected, protected, and
productive.
It's Tech Talk Time.
Here's your host, Cabo Jim.
Cabo Jim (00:18):
Welcome to Tech Talk again.
We've got Ken Johnson from USIT Systems with us once again.
And today we're going to talk alittle bit about AI, right?
Ken Johnson (00:29):
Well, AI is the big buzzword.
And after the last podcast, Iput it out there, and that was
the number one comment I gotback was talk to us about AI and
what a what AI is all about.
Cabo Jim (00:46):
So and there's there's a lot that AI can do, right?
Ken Johnson (00:49):
There's there's a lot it can do, and there's a lot
that it can't do.
And and so I want to clarifysome of that, you know, uh as
far as a lot of themisinformation out there.
Yeah, so so that that's where Iwant to start.
Cabo Jim (01:06):
Okay, well, let's start off by I guess first
addressing the types of AI thatare out there, because there are
a lot of different types of AI.
Ken Johnson (01:14):
Well, and and there's types by function, but
let's talk about type bycapability first.
You've got you've got narrowAI, which is the the parts and
pieces that um uh are there forspecific functions, and then
(01:36):
you've got uh much moreintelligent AI or strong AI.
And and currently that's stilltheoretical because because
strong AI is is not implementedin in any way, shape, or form.
The strong AI is where whereyou've got a machine making
(01:58):
decisions, and and right nowthose decisions are still in
human hands.
The humans come along and theythey say, all right, if this
happens, then this happens.
So basically, AI is nothing buta bunch of if-then-else
statements.
So if if you if this is true,then do this, or else go on to
(02:25):
the next question.
And so so that is what narrowAI is, and and narrow AI is is
what we have today.
And you see that withpredictive text when you try to
text somebody with your cellphone, and when you're you're
doing that, the the narrow AIcomes along and it it suggests
(02:46):
what the next next thing isgonna be.
Hey, every day at at uh youknow two o'clock in the
afternoon, you turn thetemperature down two degrees.
Would you like me to make thatautomatic for you?
And so so that's that's narrowAI, and that's that's what we
have right now.
And then the the the next stepis super intelligent AI, and
(03:13):
superintelligent AI is is whateverybody's afraid of, and and
there's a lot of ethical andmoral questions out there, but
we don't have super intelligentAI out there.
I I haven't uh I haven't seenArnold Schwarzenegger walking
down the street and going, I'dbe back.
But you know, it's it's thedifferent levels there.
(03:35):
So now if you'll humor me,we'll go on to to functionality
and and let me grab my glassesso that I make sure that I talk
intelligently.
The by function, if we're justtalking within narrow AI, which
we have today, by function wehave reactive AI, it responds to
(03:57):
specific input, but lacksmemory and learning capability.
So uh a game that you have onyour phone that you're playing
against a computer, that's areactive AI.
Um uh words with friends whenyou when you do a a solo um game
(04:21):
with with it, you're you'redealing with reactive AI because
the AI is actually respondingto your input and playing a game
against you.
Okay, limited memory AI learnsfrom historical data.
This is this is in pastexperience.
This is your thermostat.
(04:42):
This is self-driving cars,these are the chatbots that are
on there, and and you can youcan implement these chatbots in
a business environment, you canimplement these chatbots in in
all kinds of environment, andand that limited memory AI,
again, is a narrow AI, it's taskspecific.
(05:05):
And then the next level it getsup is what's called theory of
mind.
Um, and and that's future AImodels are expected to
understand human emotions andintentions and interactions, but
at this point, that's all stillstill very experimental.
(05:27):
Um, a number of the Asiancountries are out there and and
doing that and implementing itbecause of the aging population,
they're looking at AI robotsbasically that can understand
the needs of the agingpopulation and provide services
(05:49):
for that aging population.
So that that activity is iscoming along quickly and and
being implemented.
And then the last piece of thepuzzle is the self-aware AI, and
that's still totally, totallytheoretical.
Cabo Jim (06:06):
So as an individual, as a business owner, how do I
decide where and how or whattype of AI to use?
Ken Johnson (06:16):
Well, if you listen to the last podcast, I'm gonna
tell you that I am not an expertin all these fields.
Nobody is, but I've got accessto uh little over 400 experts
out there.
So what you're gonna do isyou're gonna decide what you're
(06:37):
trying to achieve.
You've got to define your painpoint, you know, what it is in
your business that you want toimplement and automate, and and
what those points are.
Oh, I mean, everybody wants tocall in at seven o'clock at
night to to pay their billbecause they got home from work
(07:00):
and I've got a small medicaloffice, and and I don't want to
staff at at uh eight o'clock atnight.
I was talking to a doctoryesterday that I'm I'm working
with, and and the the doctorstold me that in in town there
are five independent medicaloffices left.
All the rest of them have beenbought up and bought out and are
(07:26):
part of a major hospital group,and that hospital group
implements all the technology.
And he says, How do I implementsome of this technology to
compete and stay independent?
And and so that's that's what Idid is I set a meeting with him
to sit down and identify whathe wants to automate, and that's
(07:47):
that's the first piece you'vegot to do is decide what you
want to automate.
Okay, second piece of thepuzzle is to quantify the cost
versus the value, and that thatvalue can be a complete return
(08:07):
on investment where you you turnaround, you say it's gonna cost
X number of dollars toimplement it, it's gonna save me
X number of man hours a monthor a year or a week or whatever,
and that is gonna be a laborsavings of such and such, or
it's gonna reduce errors in dataentry or errors in in
(08:28):
implementation.
So, what are you trying to fix?
And then what's the cost versusthe value?
The next piece of it is is thehard piece, and that's that's to
choose your model.
Are you trying to directlymonetize whatever you're
(08:51):
implementing, or are you tryingto just collect data for
independent activity, like youknow, sales information and
predictive sales information?
And AI is excellent at doingthe predictive sales.
Uh, I've got a car dealershipthat I've been working with over
the last uh 18 months or so,and and that car dealership is
(09:16):
looking at what cars are sellingin new and used.
They are also looking at who'sbuying in new and used, and
they're looking at thosedemographics, and they're making
predictions based on thedemographics, so who they're
(09:36):
gonna market and advertise to.
They're also making predictionson what vehicles they need in
both the new and used markets tohave on the lot in order to get
people to sell, and car buyinghas has changed.
I mean, uh when you and I werekids, we went out and and we
went to a car lot and we walkedaround and looked at what cars
(10:00):
were there.
Well, that's not the gameanymore.
Now everybody goes online andthey look at what cars are
available at what dealership,and then they decide what
dealership to go to and puttheir hands on it.
So the entire experience hastotally changed, and AI can
predict that experience andpredict what people are doing
(10:23):
and predict what you need tohave as a retailer to get the
job done.
Cabo Jim (10:29):
Interesting.
So so now, as a you know, as asmaller business, for uh one of
your examples, you can now moreor less compete with some of the
bigger people because you'vegot some of that technology,
you've got some of thatknowledge without having to go
out and spend money on a wholenew department, right?
Ken Johnson (10:45):
Correct.
And and uh I'm gonna I'm gonnasay anything, anything that
you're implementing with AI, I'mgonna tell you start small, do
a pilot operation and startvery, very small.
Do not try to implement thisbroad sweeping change throughout
(11:08):
your operation.
Start small.
I want to process, I want Iwant to change my phone system
up, I want to have it set up sothat when people call in, that
they can pay their bill directlyover the phone.
Boom, that's it.
I don't want to do anythingelse, I just want to do that.
(11:30):
Next step.
Okay, what time of day dopeople pay their bill?
Well, they pay their bill at 742 p.m.
Um, 80% of the people pay theirbill then.
Okay, that's great.
Now I want to send out myinvoices at 6 45 at night to
(11:53):
remind them that they got to paytheir bill, and they'll go pay
their bill in an hour.
So you can start off with, Iwant to do one thing, then I
want to implement another thing,and then I want to step up and
step up.
And and it is start small andmove up very slowly.
(12:14):
Do not try to throw everythingto the walls.
Cabo Jim (12:19):
That's an that's great advice because, like you said,
you know, with anything, youwant to make sure it's working,
you want to make sure it's doingwhat you want it to be doing,
and then you know, you want tomake sure it's helping your
business at the end of the day.
Ken Johnson (12:31):
Absolutely, absolutely.
So that that's the parts andpieces to to implementing it.
So now, what questions have yougot for me?
Cabo Jim (12:42):
Well, I I mean, I guess you know, there's a lot of
different AI out there, youknow.
It seems like every program Ihave right now has an AI element
attached to it, you know.
Absolutely.
Do I need to be using all that,or do I again do I'm picking
and choosing where I'm using it?
Ken Johnson (13:02):
I I'm gonna tell you to pick and choose because
yeah, everybody, every searchengine has got some AI.
Well, what is that AI doing?
It's predictive AI.
So that predictive AI is isdirecting you to where they want
you to go, not necessarilywhere you want to go.
(13:24):
So as you go through and youyou engage that AI, understand
that that engagement ispredicting based on past
experience.
Now, I know you, and I know youvery well.
You and I have been interactingfor what 15, 20 years now, and
(13:46):
and so I know that you do notkeep doing the same thing over
and over, expecting differentresults.
You constantly are changing,you're constantly looking at new
ways to implement things,you're constantly looking to
grow as a person and intechnology.
(14:08):
You've never been stagnant, andand that's that's really key.
And a lot of this AI andpredictive AI is pushing people
to be stagnant and doing thesame thing over and over again,
expecting different results,which is the definition of
insanity.
So I don't like all thepredictive AI.
(14:31):
Is it good for my thermostat?
Yeah, okay.
I kind of like it predicting mythermostat.
Is it good for me doingresearch on particular
information and technologies?
Not necessarily.
Uh the AI model may know thatI've looked at a particular
(14:53):
phone system in the past.
So when I ask the next questionof uh which phone system uh
that I sell uh does uh callcenter implementation, it's
going to come back and recommendthe specific one that I've
looked at in the past instead ofgiving me all of my options.
(15:16):
I don't like having optionsrestricted.
Uh the other piece that that uhis out there with the AI is is
healthcare prediction.
And I'm I I really, you know,when I'm looking for a doctor,
um, I don't want to have thedoctor recommended as only the
(15:37):
doctor that I've seen in thepast.
I may be looking for adifferent situation, a different
product, uh a differentspecialty.
Uh, same with a dentist.
I may be at my age, I'm lookingfor a dentist that specializes
in implants instead of justdoing standard fillings.
But the AI knows that I talkedto a doctor.
(15:59):
Um I'm trying to think of thedoctor's name from Little Shop
of Horse.
But uh I'm um I'm looked atthat doctor in the past, it's
going to recommend that doctoronly.
And that's those are the thingsthat that bother me about about
AI and and what you'reimplementing.
So as you engage it, it can behelpful and useful, but it can
(16:22):
also be restrictive.
Cabo Jim (16:24):
And it's only as smart as, you know, it's it's a
learning tool.
It's only as smart as theinformation somebody is putting
into it and interacting with,you know, can it help uh you
know come up with differentideas in certain situations, but
it's only gonna it's limited inthe fact that it's only the
information that's uh been outthere already or that they've
(16:45):
found or limited memory AIlearns from historical data and
past experiences to informdecisions, and that's that's the
key.
Ken Johnson (17:01):
That's what we've got right now.
Theory of mind, it's stillexperimental and not there yet.
Um, you know, I'm I'm I'mreally glad that uh if I go in
for surgery, that there's ahuman making the decision of
whether that part needs to beremoved or not, right?
Cabo Jim (17:21):
Yeah, yeah, I'll leave it up to a computer.
Yeah, I don't want to leave itup to the computer.
So it's and there's there's alot of different AI in the fact
that you know a lot of peopleoffer it, but on the other hand,
like you mentioned, it's uhthere's competition, people want
you to use their platform andtheir version of AI.
They don't talk to each other,right?
Ken Johnson (17:43):
Uh they really don't.
Um, it's it's called marketdifferentiation, and uh, we've
all experienced it for for many,many years.
So um, yeah, it's not it, it'sit's not uh universal where
everybody's talking toeverybody.
You got perplexity, you gotchat GBT, you got Groke, uh,
(18:06):
that there's all these differentpieces out there, and each of
these companies want to sell uhtheir backbone, their program,
their tools, their their machinelearning.
They want to sell that to umXYZ phone company, uh ABC, uh,
(18:27):
data analytical company, um, allthe rest of it.
Now, I'm gonna I'm gonna tellyou everybody knows Salesforce.
Salesforce is the big monsterin the room.
There's a company uh in Europethat used um an AI set of tools.
I'm not gonna promote one oranother, to write a competitive
(18:54):
program specific for theircompany and replaced their
Salesforce program with thisvery targeted uh uh management
system for managing their leadsand and all of their technology.
So that that is you know ahuge, huge disruption to the
(19:20):
industry being able to dosomething like that.
Uh in Orlando, there's agentleman I know who has written
a marketing program in order totake and in used AI to write
this program in order to takeand do direct mail marketing,
(19:44):
exceptionally targeted for somevery specific industries, so
that that industry can turnaround and look at their
database of past customers,predict what customers they
should be selling to, go out onthe internet, find those
customers, find those contacts,find those email addresses, and
(20:09):
turn around and send a directmail campaign out to those
existing customers, and anotherdirect mail campaign to the
prospective customers, and athird direct mail campaign to
customers that haven't boughtfrom them for 90 days, 180 days,
365 days.
(20:29):
And so this was all done andwritten with AI with a very,
very minimal uh financial costto get it implemented.
And and they just rolled it upoh about a month, six weeks ago.
unknown (20:44):
Yeah.
Cabo Jim (20:45):
So I mean, there's there's some good things that AI
is doing, but you know, again,you know, I I guess I warn you,
much like the media, they'regonna filter and they're gonna
push people in the direction ofwhat benefits them as a company,
um, providing that AI, right?
Ken Johnson (21:00):
Absolutely, absolutely.
So you've you've got to pickand choose, and you've gotta be
aware.
And uh I don't remember who thequote was, but uh of the many
truths, if you pick one andfollow it blindly, um, it will
become a falsehood and you willbecome a fanatic.
(21:23):
So there's a lot of truths outthere.
Look at all of them.
Cabo Jim (21:28):
Yep, look at all of them.
And make your own decision.
End of the day.
There we go.
Well, very good.
Any last words for ourlisteners today?
Ken Johnson (21:37):
Um, yeah, if if you see Arnold Schwarzenegger
walking down the street, uh, youknow, with uh, you know, uh
saying, I'll be Bach, uh, beafraid.
But so far, we're we're not outthere.
Uh, we haven't got self-awareuh AI.
Um everything out there is isstill uh limited memory AI and
(22:03):
and predictive AI.
So it's uh theory of mind is iscoming.
Um the the uh Asian countriesare way ahead of the US in
implementing that, but it isit's coming, and I think that
that's uh uh an area that isgoing to to absolutely mushroom
(22:27):
in the future.
Um when I I I I think nursing.
Uh think nursing.
Wouldn't you how would you feelabout having a robot be able to
deliver the food trays?
Um, how would you feel aboutthe robot being able to uh solve
(22:49):
minor problems?
Like uh I drop the call buttonfrom the side of the bed and
have a robot come in and pick upthe call button and hand it to
you.
Uh, I think that that's gonnabe theory of mind uh
implementation.
Uh I think medical is huge inthat area.
Um but it's not there yet.
(23:10):
Uh limited memory AI.
Uh we've got um uh there's acompany out there called Miso
that in my experience as a youngman, uh running the fryer is is
the absolute worst job in anyfast food restaurant.
And Miso has come up with a AImachine that that cooks the
(23:37):
French fries or or whatever elseis in the deep fryer and
removes the human element fromthat, which increases safety
from burns, which increasesefficiency and consistency of
the product coming out, and andthere's uh that that whole area
is absolutely exploding.
Cabo Jim (23:59):
Wow, absolutely AI fry guy.
There we go.
We got a little bit of an AIfry guy that's called the jobs,
does the jobs you don't want todo, right?
Ken Johnson (24:08):
That's the job you don't want to do, and there's a
lot of jobs that that you don'twant to do or that are
dangerous, and and I I mean I Ilook at oil fields and and I
look at the the the dangerinvolved in that.
Um I I I worked uh on uh airbaguh explosives, and and I I saw
(24:34):
a guy in the powder room when aflash happened in the powder
room and and the guy got burned.
I mean putting uh a robot inthe powder room that if the if
the flash happens and and uh andand the robot gets hurt, you
you put another one in there andsend that one out for repair.
(24:56):
So yeah, I think there's somany areas that are dangerous
that AI can be implemented andand it would be great.
I I just think that that wouldbe huge.
Cabo Jim (25:10):
Very good.
Ken Johnson (25:11):
We can only hope, right?
It's not even hope anymore,Jim.
It's they're coming.
Uh the it's out there now.
Are they gonna be able to to umyou know lay bricks?
Maybe, but are they gonna beable to make human decisions?
(25:32):
Uh maybe.
So the the people out therethat are are the ones that have
to make decisions to make surethat the structure is complete,
to make sure that everything isintact.
Uh, those are all things thatthat those are jobs that are not
gonna go to AI.
Cabo Jim (25:52):
Very good.
Very good.
Well, Ken, again, I appreciateyour time today and your
knowledge.
It's been a pleasure getting toknow a little bit more about AI
as we continue to move forward.
But uh, I guess we'll see younext time.
Ken Johnson (26:05):
Uh, I don't know if we have a topic pick for next
time, but uh I'm sure and uh I'mgonna I'm gonna ask people to
comment and and send in therewhat do you want to hear about?
Uh and and we can pull inexperts from other fields too,
uh, you know in order to addresssome of this, but uh but I've
I've had a couple of requests uhfor another topic, but uh well
(26:29):
let's let's see what the whatthe response is when I post up
this video.
Cabo Jim (26:34):
Very good, very good.
Well, Ken, again, uh pleasure.
Thank you for your time today,and uh, we will see you out
there soon.
Always a pleasure, You.
Take care now.
unknown (26:44):
Yeah.
Intro/Close (26:44):
That's it for this episode of Tech Talk, where
we've got IT covered so you cankeep life and business running
smoothly.
Remember, whether it'scybersecurity, cloud solutions,
or just keeping your techtrouble free, USIT Systems is
here to help.
Visit us online atusitsystems.com or give us a
call at 407-753-4499.
Stay safe, stay connected, andwe'll catch you on the next tech
(27:05):
talk.
Welcome to Tech Talk, your go-to guide for
making technology work for you.
Whether you're running agrowing business or just trying
to keep things running smoothlyat home, we've got IT covered.
US IT Systems brings theknowledge, experience, and
solutions you need to stayconnected, protected, and
productive.
It's Tech Talk Time.
Here's your host, Cabo Jim.
Cabo Jim (00:18):
Welcome to Tech Talk again.
We've got Ken Johnson from USIT Systems with us once again.
And today we're going to talk alittle bit about AI, right?
Ken Johnson (00:29):
Well, AI is the big buzzword.
And after the last podcast, Iput it out there, and that was
the number one comment I gotback was talk to us about AI and
what a what AI is all about.
Cabo Jim (00:46):
So and there's there's a lot that AI can do, right?
Ken Johnson (00:49):
There's there's a lot it can do, and there's a lot
that it can't do.
And and so I want to clarifysome of that, you know, uh as
far as a lot of themisinformation out there.
Yeah, so so that that's where Iwant to start.
Cabo Jim (01:06):
Okay, well, let's start off by I guess first
addressing the types of AI thatare out there, because there are
a lot of different types of AI.
Ken Johnson (01:14):
Well, and and there's types by function, but
let's talk about type bycapability first.
You've got you've got narrowAI, which is the the parts and
pieces that um uh are there forspecific functions, and then
(01:36):
you've got uh much moreintelligent AI or strong AI.
And and currently that's stilltheoretical because because
strong AI is is not implementedin in any way, shape, or form.
The strong AI is where whereyou've got a machine making
(01:58):
decisions, and and right nowthose decisions are still in
human hands.
The humans come along and theythey say, all right, if this
happens, then this happens.
So basically, AI is nothing buta bunch of if-then-else
statements.
So if if you if this is true,then do this, or else go on to
(02:25):
the next question.
And so so that is what narrowAI is, and and narrow AI is is
what we have today.
And you see that withpredictive text when you try to
text somebody with your cellphone, and when you're you're
doing that, the the narrow AIcomes along and it it suggests
(02:46):
what the next next thing isgonna be.
Hey, every day at at uh youknow two o'clock in the
afternoon, you turn thetemperature down two degrees.
Would you like me to make thatautomatic for you?
And so so that's that's narrowAI, and that's that's what we
have right now.
And then the the the next stepis super intelligent AI, and
(03:13):
superintelligent AI is is whateverybody's afraid of, and and
there's a lot of ethical andmoral questions out there, but
we don't have super intelligentAI out there.
I I haven't uh I haven't seenArnold Schwarzenegger walking
down the street and going, I'dbe back.
But you know, it's it's thedifferent levels there.
(03:35):
So now if you'll humor me,we'll go on to to functionality
and and let me grab my glassesso that I make sure that I talk
intelligently.
The by function, if we're justtalking within narrow AI, which
we have today, by function wehave reactive AI, it responds to
(03:57):
specific input, but lacksmemory and learning capability.
So uh a game that you have onyour phone that you're playing
against a computer, that's areactive AI.
Um uh words with friends whenyou when you do a a solo um game
(04:21):
with with it, you're you'redealing with reactive AI because
the AI is actually respondingto your input and playing a game
against you.
Okay, limited memory AI learnsfrom historical data.
This is this is in pastexperience.
This is your thermostat.
(04:42):
This is self-driving cars,these are the chatbots that are
on there, and and you can youcan implement these chatbots in
a business environment, you canimplement these chatbots in in
all kinds of environment, andand that limited memory AI,
again, is a narrow AI, it's taskspecific.
(05:05):
And then the next level it getsup is what's called theory of
mind.
Um, and and that's future AImodels are expected to
understand human emotions andintentions and interactions, but
at this point, that's all stillstill very experimental.
(05:27):
Um, a number of the Asiancountries are out there and and
doing that and implementing itbecause of the aging population,
they're looking at AI robotsbasically that can understand
the needs of the agingpopulation and provide services
(05:49):
for that aging population.
So that that activity is iscoming along quickly and and
being implemented.
And then the last piece of thepuzzle is the self-aware AI, and
that's still totally, totallytheoretical.
Cabo Jim (06:06):
So as an individual, as a business owner, how do I
decide where and how or whattype of AI to use?
Ken Johnson (06:16):
Well, if you listen to the last podcast, I'm gonna
tell you that I am not an expertin all these fields.
Nobody is, but I've got accessto uh little over 400 experts
out there.
So what you're gonna do isyou're gonna decide what you're
(06:37):
trying to achieve.
You've got to define your painpoint, you know, what it is in
your business that you want toimplement and automate, and and
what those points are.
Oh, I mean, everybody wants tocall in at seven o'clock at
night to to pay their billbecause they got home from work
(07:00):
and I've got a small medicaloffice, and and I don't want to
staff at at uh eight o'clock atnight.
I was talking to a doctoryesterday that I'm I'm working
with, and and the the doctorstold me that in in town there
are five independent medicaloffices left.
All the rest of them have beenbought up and bought out and are
(07:26):
part of a major hospital group,and that hospital group
implements all the technology.
And he says, How do I implementsome of this technology to
compete and stay independent?
And and so that's that's what Idid is I set a meeting with him
to sit down and identify whathe wants to automate, and that's
(07:47):
that's the first piece you'vegot to do is decide what you
want to automate.
Okay, second piece of thepuzzle is to quantify the cost
versus the value, and that thatvalue can be a complete return
(08:07):
on investment where you you turnaround, you say it's gonna cost
X number of dollars toimplement it, it's gonna save me
X number of man hours a monthor a year or a week or whatever,
and that is gonna be a laborsavings of such and such, or
it's gonna reduce errors in dataentry or errors in in
(08:28):
implementation.
So, what are you trying to fix?
And then what's the cost versusthe value?
The next piece of it is is thehard piece, and that's that's to
choose your model.
Are you trying to directlymonetize whatever you're
(08:51):
implementing, or are you tryingto just collect data for
independent activity, like youknow, sales information and
predictive sales information?
And AI is excellent at doingthe predictive sales.
Uh, I've got a car dealershipthat I've been working with over
the last uh 18 months or so,and and that car dealership is
(09:16):
looking at what cars are sellingin new and used.
They are also looking at who'sbuying in new and used, and
they're looking at thosedemographics, and they're making
predictions based on thedemographics, so who they're
(09:36):
gonna market and advertise to.
They're also making predictionson what vehicles they need in
both the new and used markets tohave on the lot in order to get
people to sell, and car buyinghas has changed.
I mean, uh when you and I werekids, we went out and and we
went to a car lot and we walkedaround and looked at what cars
(10:00):
were there.
Well, that's not the gameanymore.
Now everybody goes online andthey look at what cars are
available at what dealership,and then they decide what
dealership to go to and puttheir hands on it.
So the entire experience hastotally changed, and AI can
predict that experience andpredict what people are doing
(10:23):
and predict what you need tohave as a retailer to get the
job done.
Cabo Jim (10:29):
Interesting.
So so now, as a you know, as asmaller business, for uh one of
your examples, you can now moreor less compete with some of the
bigger people because you'vegot some of that technology,
you've got some of thatknowledge without having to go
out and spend money on a wholenew department, right?
Ken Johnson (10:45):
Correct.
And and uh I'm gonna I'm gonnasay anything, anything that
you're implementing with AI, I'mgonna tell you start small, do
a pilot operation and startvery, very small.
Do not try to implement thisbroad sweeping change throughout
(11:08):
your operation.
Start small.
I want to process, I want Iwant to change my phone system
up, I want to have it set up sothat when people call in, that
they can pay their bill directlyover the phone.
Boom, that's it.
I don't want to do anythingelse, I just want to do that.
(11:30):
Next step.
Okay, what time of day dopeople pay their bill?
Well, they pay their bill at 742 p.m.
Um, 80% of the people pay theirbill then.
Okay, that's great.
Now I want to send out myinvoices at 6 45 at night to
(11:53):
remind them that they got to paytheir bill, and they'll go pay
their bill in an hour.
So you can start off with, Iwant to do one thing, then I
want to implement another thing,and then I want to step up and
step up.
And and it is start small andmove up very slowly.
(12:14):
Do not try to throw everythingto the walls.
Cabo Jim (12:19):
That's an that's great advice because, like you said,
you know, with anything, youwant to make sure it's working,
you want to make sure it's doingwhat you want it to be doing,
and then you know, you want tomake sure it's helping your
business at the end of the day.
Ken Johnson (12:31):
Absolutely, absolutely.
So that that's the parts andpieces to to implementing it.
So now, what questions have yougot for me?
Cabo Jim (12:42):
Well, I I mean, I guess you know, there's a lot of
different AI out there, youknow.
It seems like every program Ihave right now has an AI element
attached to it, you know.
Absolutely.
Do I need to be using all that,or do I again do I'm picking
and choosing where I'm using it?
Ken Johnson (13:02):
I I'm gonna tell you to pick and choose because
yeah, everybody, every searchengine has got some AI.
Well, what is that AI doing?
It's predictive AI.
So that predictive AI is isdirecting you to where they want
you to go, not necessarilywhere you want to go.
(13:24):
So as you go through and youyou engage that AI, understand
that that engagement ispredicting based on past
experience.
Now, I know you, and I know youvery well.
You and I have been interactingfor what 15, 20 years now, and
(13:46):
and so I know that you do notkeep doing the same thing over
and over, expecting differentresults.
You constantly are changing,you're constantly looking at new
ways to implement things,you're constantly looking to
grow as a person and intechnology.
(14:08):
You've never been stagnant, andand that's that's really key.
And a lot of this AI andpredictive AI is pushing people
to be stagnant and doing thesame thing over and over again,
expecting different results,which is the definition of
insanity.
So I don't like all thepredictive AI.
(14:31):
Is it good for my thermostat?
Yeah, okay.
I kind of like it predicting mythermostat.
Is it good for me doingresearch on particular
information and technologies?
Not necessarily.
Uh the AI model may know thatI've looked at a particular
(14:53):
phone system in the past.
So when I ask the next questionof uh which phone system uh
that I sell uh does uh callcenter implementation, it's
going to come back and recommendthe specific one that I've
looked at in the past instead ofgiving me all of my options.
(15:16):
I don't like having optionsrestricted.
Uh the other piece that that uhis out there with the AI is is
healthcare prediction.
And I'm I I really, you know,when I'm looking for a doctor,
um, I don't want to have thedoctor recommended as only the
(15:37):
doctor that I've seen in thepast.
I may be looking for adifferent situation, a different
product, uh a differentspecialty.
Uh, same with a dentist.
I may be at my age, I'm lookingfor a dentist that specializes
in implants instead of justdoing standard fillings.
But the AI knows that I talkedto a doctor.
(15:59):
Um I'm trying to think of thedoctor's name from Little Shop
of Horse.
But uh I'm um I'm looked atthat doctor in the past, it's
going to recommend that doctoronly.
And that's those are the thingsthat that bother me about about
AI and and what you'reimplementing.
So as you engage it, it can behelpful and useful, but it can
(16:22):
also be restrictive.
Cabo Jim (16:24):
And it's only as smart as, you know, it's it's a
learning tool.
It's only as smart as theinformation somebody is putting
into it and interacting with,you know, can it help uh you
know come up with differentideas in certain situations, but
it's only gonna it's limited inthe fact that it's only the
information that's uh been outthere already or that they've
(16:45):
found or limited memory AIlearns from historical data and
past experiences to informdecisions, and that's that's the
key.
Ken Johnson (17:01):
That's what we've got right now.
Theory of mind, it's stillexperimental and not there yet.
Um, you know, I'm I'm I'mreally glad that uh if I go in
for surgery, that there's ahuman making the decision of
whether that part needs to beremoved or not, right?
Cabo Jim (17:21):
Yeah, yeah, I'll leave it up to a computer.
Yeah, I don't want to leave itup to the computer.
So it's and there's there's alot of different AI in the fact
that you know a lot of peopleoffer it, but on the other hand,
like you mentioned, it's uhthere's competition, people want
you to use their platform andtheir version of AI.
They don't talk to each other,right?
Ken Johnson (17:43):
Uh they really don't.
Um, it's it's called marketdifferentiation, and uh, we've
all experienced it for for many,many years.
So um, yeah, it's not it, it'sit's not uh universal where
everybody's talking toeverybody.
You got perplexity, you gotchat GBT, you got Groke, uh,
(18:06):
that there's all these differentpieces out there, and each of
these companies want to sell uhtheir backbone, their program,
their tools, their their machinelearning.
They want to sell that to umXYZ phone company, uh ABC, uh,
(18:27):
data analytical company, um, allthe rest of it.
Now, I'm gonna I'm gonna tellyou everybody knows Salesforce.
Salesforce is the big monsterin the room.
There's a company uh in Europethat used um an AI set of tools.
I'm not gonna promote one oranother, to write a competitive
(18:54):
program specific for theircompany and replaced their
Salesforce program with thisvery targeted uh uh management
system for managing their leadsand and all of their technology.
So that that is you know ahuge, huge disruption to the
(19:20):
industry being able to dosomething like that.
Uh in Orlando, there's agentleman I know who has written
a marketing program in order totake and in used AI to write
this program in order to takeand do direct mail marketing,
(19:44):
exceptionally targeted for somevery specific industries, so
that that industry can turnaround and look at their
database of past customers,predict what customers they
should be selling to, go out onthe internet, find those
customers, find those contacts,find those email addresses, and
(20:09):
turn around and send a directmail campaign out to those
existing customers, and anotherdirect mail campaign to the
prospective customers, and athird direct mail campaign to
customers that haven't boughtfrom them for 90 days, 180 days,
365 days.
(20:29):
And so this was all done andwritten with AI with a very,
very minimal uh financial costto get it implemented.
And and they just rolled it upoh about a month, six weeks ago.
unknown (20:44):
Yeah.
Cabo Jim (20:45):
So I mean, there's there's some good things that AI
is doing, but you know, again,you know, I I guess I warn you,
much like the media, they'regonna filter and they're gonna
push people in the direction ofwhat benefits them as a company,
um, providing that AI, right?
Ken Johnson (21:00):
Absolutely, absolutely.
So you've you've got to pickand choose, and you've gotta be
aware.
And uh I don't remember who thequote was, but uh of the many
truths, if you pick one andfollow it blindly, um, it will
become a falsehood and you willbecome a fanatic.
(21:23):
So there's a lot of truths outthere.
Look at all of them.
Cabo Jim (21:28):
Yep, look at all of them.
And make your own decision.
End of the day.
There we go.
Well, very good.
Any last words for ourlisteners today?
Ken Johnson (21:37):
Um, yeah, if if you see Arnold Schwarzenegger
walking down the street, uh, youknow, with uh, you know, uh
saying, I'll be Bach, uh, beafraid.
But so far, we're we're not outthere.
Uh, we haven't got self-awareuh AI.
Um everything out there is isstill uh limited memory AI and
(22:03):
and predictive AI.
So it's uh theory of mind is iscoming.
Um the the uh Asian countriesare way ahead of the US in
implementing that, but it isit's coming, and I think that
that's uh uh an area that isgoing to to absolutely mushroom
(22:27):
in the future.
Um when I I I I think nursing.
Uh think nursing.
Wouldn't you how would you feelabout having a robot be able to
deliver the food trays?
Um, how would you feel aboutthe robot being able to uh solve
(22:49):
minor problems?
Like uh I drop the call buttonfrom the side of the bed and
have a robot come in and pick upthe call button and hand it to
you.
Uh, I think that that's gonnabe theory of mind uh
implementation.
Uh I think medical is huge inthat area.
Um but it's not there yet.
(23:10):
Uh limited memory AI.
Uh we've got um uh there's acompany out there called Miso
that in my experience as a youngman, uh running the fryer is is
the absolute worst job in anyfast food restaurant.
And Miso has come up with a AImachine that that cooks the
(23:37):
French fries or or whatever elseis in the deep fryer and
removes the human element fromthat, which increases safety
from burns, which increasesefficiency and consistency of
the product coming out, and andthere's uh that that whole area
is absolutely exploding.
Cabo Jim (23:59):
Wow, absolutely AI fry guy.
There we go.
We got a little bit of an AIfry guy that's called the jobs,
does the jobs you don't want todo, right?
Ken Johnson (24:08):
That's the job you don't want to do, and there's a
lot of jobs that that you don'twant to do or that are
dangerous, and and I I mean I Ilook at oil fields and and I
look at the the the dangerinvolved in that.
Um I I I worked uh on uh airbaguh explosives, and and I I saw
(24:34):
a guy in the powder room when aflash happened in the powder
room and and the guy got burned.
I mean putting uh a robot inthe powder room that if the if
the flash happens and and uh andand the robot gets hurt, you
you put another one in there andsend that one out for repair.
(24:56):
So yeah, I think there's somany areas that are dangerous
that AI can be implemented andand it would be great.
I I just think that that wouldbe huge.
Cabo Jim (25:10):
Very good.
Ken Johnson (25:11):
We can only hope, right?
It's not even hope anymore,Jim.
It's they're coming.
Uh the it's out there now.
Are they gonna be able to to umyou know lay bricks?
Maybe, but are they gonna beable to make human decisions?
(25:32):
Uh maybe.
So the the people out therethat are are the ones that have
to make decisions to make surethat the structure is complete,
to make sure that everything isintact.
Uh, those are all things thatthat those are jobs that are not
gonna go to AI.
Cabo Jim (25:52):
Very good.
Very good.
Well, Ken, again, I appreciateyour time today and your
knowledge.
It's been a pleasure getting toknow a little bit more about AI
as we continue to move forward.
But uh, I guess we'll see younext time.
Ken Johnson (26:05):
Uh, I don't know if we have a topic pick for next
time, but uh I'm sure and uh I'mgonna I'm gonna ask people to
comment and and send in therewhat do you want to hear about?
Uh and and we can pull inexperts from other fields too,
uh, you know in order to addresssome of this, but uh but I've
I've had a couple of requests uhfor another topic, but uh well
(26:29):
let's let's see what the whatthe response is when I post up
this video.
Cabo Jim (26:34):
Very good, very good.
Well, Ken, again, uh pleasure.
Thank you for your time today,and uh, we will see you out
there soon.
Always a pleasure, You.
Take care now.
unknown (26:44):
Yeah.
Intro/Close (26:44):
That's it for this episode of Tech Talk, where
we've got IT covered so you cankeep life and business running
smoothly.
Remember, whether it'scybersecurity, cloud solutions,
or just keeping your techtrouble free, USIT Systems is
here to help.
Visit us online atusitsystems.com or give us a
call at 407-753-4499.
Stay safe, stay connected, andwe'll catch you on the next tech
(27:05):
talk.
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