A Baby Boomers Advantage with AI

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Join Tom Wheelwright as he explores the skills Baby Boomers need to not only be successful with AI, but also transform their small businesses with his guest and AI specialist, Tal Galon.


As the founder of AI Outfitters, Tal Galon is on a mission to help small business owners experience transformation through AI. He focuses on the value AI can bring to improve revenue, the quality of output, and reclaiming entrepreneurs’ time to help them focus on strategy. With his 20 years of consulting, strategy, and business intelligence experience, he specializes in:

🔹 Identifying key areas for AI integration and improvement
🔹 Facilitating workshops on AI-driven efficiency
🔹 Developing tailored strategies for 50-70% productivity boosts
🔹 Cross-cultural collaboration and C-suite level problem-solving.


In this episode, discover the ways AI can be immensely helpful for Baby Boomers and their small businesses, and how this differs from previous technological advances that has often left Baby Boomers behind.


Order Tom’s book, “The Win-Win Wealth Strategy: 7 Investments the Government Will Pay You to Make” at: https://winwinwealthstrategy.com/


00:00 - Intro.
03:14 - Advantage #1: Questioning - Intelligence & Experience with Asking the Right Question
09:28 - The One Tech Baby Boomers are Not Left Behind On
10:47 - Tal’s Steps of AI Implementation in Small Business
16:37 - Advantage #2: Training AI - Boomers Knowledge & Ability to Train People
20:30 - AI Agents can build your workflow.
24:20 - AI Integration Focus #1: Goal Setting Leads to Customization and Automation
26:45 - AI Integration Focus #2: Mapping what you are doing currently.
27:08 - AI Integration Focus #3: Alignment & Optimization
27:40 - AI Integration Focus #4: Strategizing based on what is most important to you.
33:56 - Closing Statements


Looking for more on Tal Galon?
LinkedIn: www.linkedin.com/in/ai4u/

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Episode Transcript

Speaker 1 (00:00):
Do baby boomers have an advantage when it comes to
working with AI that is completely different than all the
disadvantages we had as a group when it was coming
with working with all the other technology of the last
twenty to thirty years. Today, we're going to discover just

(00:21):
what skill sets are necessary to best take advantage of
AI and white baby boomers might have an advantage over
the Gen xers, millennials and Gen zers even though we're
not tech savvy. And with us today we have Tal Galon,
and Tal is an expert in AI integration and Tal

(00:43):
if you would, first of all, welcome to the Wealthability Show,
and if you would give us a little of your background.

Speaker 2 (00:50):
So thanks, thanks for having me Tom. As you mentioned,
my name is Calgalon. I spent over twenty years as
business development executives, researcher and consultant before pivoting fully into
AIR implementation early twenty twenty or late twenty twenty two.

(01:10):
Basically the moment chet ChiPT was released, I recognized this
wasn't just another tech advanced right, it was a complete
part time shift completely as far as I saw it
then and was very much verified now. It could level
the playing fields for small businesses. And just two days

(01:31):
after chetchipt went out, I phone my brother who works
for Google, and I told him, how come you guys
are not in the game yet? And we had the
discussion and we see the results you know of what's
happening with AI these days and what really drove my
decision to focus on AI. And currently I drive thirty

(01:55):
day AI sprints with small businesses. I call it a
sprint because it brings us from zero to eighty or
from thirty to ninety, but it really brings you a
long way in this thirty day window. And I saw
a financial broker I was consulting how to transform his

(02:16):
analyst workflow and basically used to spend five six hours
preparing for each client's research report. And with the right
AIR implementation, cut the time to under an hour even
half an hour, while actually improving the depth and quality
of the analysis. And then I knew and to kind

(02:37):
of go with more businesses, help more businesses capture this
opportunity because it's immense today. My company Outfitters, we work
directly with business owners to implement the practical AIR solutions,
less theory, more practice, and deliver immediate results. Clients typically
see fifty to seventy percent time saving in key are

(03:00):
yes and also significantly improving the output quality. So maybe
to start with your question, So let's.

Speaker 3 (03:12):
Start with this question.

Speaker 1 (03:14):
I started this with baby roomers have an advantage and
one of the things you talk about, and here's really
the question, what skills do humans need to have to
be successful with AI?

Speaker 2 (03:30):
So first of all questioning, but you need to know
to ask the right questions. And this is a much
more significant way of showing intelligence than providing answers. Because
chet GIPT can give you great answers, it can also
give you good questions if you know how to question it.

(03:50):
But to question something is beyond the scope of the
jet GIPT right to question how I do things? To
question what are the goals of my business? Because you
can have a very fancy, flashy warship going somewhere, but
if you don't know where it's going, it's going to

(04:12):
do that very efficiently, maybe, but it's going to get
to the wrong destination if you don't know where you're going.
And this is where people who have experienced, like baby boomers,
who know how a business works. It's really interesting that
you mentioned this because it relates to a very like

(04:34):
very viral post I saw today about a prompt like
having a McKinsey advisor in your pocket, and it gives
you like a very you know, the output is like
ten pages of output of how to you know, create
your business strategy, et cetera, et cetera. But it's not

(04:55):
going to work for nineteen nine percent of the businesses
because they it's not based on the real business, it's
not based on the grind, on the experience. So this
is where I think, and I know I see that
people tackle the things that are very on surface without

(05:17):
that and then you'll have like very flashy outputs, but
without the actual implementation, it's going it's going to cause
a lot of friction.

Speaker 1 (05:27):
Yeah, So so I want to delve into the just
this idea of questioning because I first of all, I
love hearing you say that it's it's a much greater
sign of intelligence, much more difficult to ask a good
question then get a good answer chat JPT. It's like
a massive it's like the world's biggest library rights. It's

(05:47):
a library of everything, and and all you have to
do is ask the right question. You can find it well.
So as baby boomers. I was talking to my wife,
also a baby boomer, last night about this, and I said, look,
think about when we were young.

Speaker 3 (06:04):
So we didn't have.

Speaker 1 (06:05):
Google, so it wasn't easy to type in a question
and get an answer. We had to go to the library.
We had to go to encyclopedia's. We had to find
out where in the encyclopedia was. We had to use
an index at the library, we had to use the
card catalogs with the archaic structure of how do you
find the right book in the right place.

Speaker 3 (06:28):
And then even when I started.

Speaker 1 (06:30):
When we first had our first technology, when it came
to legal research, and you know, my field is tax
and it was called Lexus Nexus and we had to
use bullying connectors. Now you probably know what boolean connectors are,
but most people don't know what a bullying connector is.

Speaker 3 (06:46):
Where you have to.

Speaker 1 (06:47):
Say, okay, I want tax within five words of tariffs,
or I want tax and tariffs versus tax or tariffs.
You know, how do you actually formulate that question in
such a way that you find the precise answer.

Speaker 3 (07:05):
Because we were charged by the minute.

Speaker 1 (07:07):
On that Lexus Nexus terminal, and the partner charge of
my department was pretty unhappy if I spent too much
time on that terminal. So I had to make sure
that I was asking really good questions. So it seems
like with AI that if you ask a typical, an

(07:28):
average question, you'll really get an average answer, and if
you ask a really good question. It's like when I
give research. So I give research to my staff, who
are all millennials. Okay, my staff's millennials and gen zers,
and I'll give a research issue to my staff, but
I'll also do the research at the same time because
I want them to learn. Right, they'll come back, it'll

(07:50):
take them an hour and a half and I can
go and do it in three minutes. And the difference
is just because I'm asking better questions.

Speaker 2 (08:00):
Right. It's being precise, right, It's knowing what you're doing
because you can you can, you know, pretend because you'll
have the output, the right output. You can pretend, but
you cannot fool the experts, right, and you have to

(08:21):
know what you're doing when dealing with the AI. And
eventually this is where this is going to go right
to niche practices. If you're a designer, you're going to
be an amplified designer when you use AI. If you're
a broker, you're going to be an amplified broker, and
everything's going to be this way because eventually you'll have
the tools. Now there's like a huge gap, but eventually

(08:45):
the gap is going to close and then you'll have
again the niches, right you have or you have today
even you know an accountant before Excel, Right, if you
could use Excel really well and then someone else couldn't,
then you'll have a gap. Right. So again, now we're
having the tools and we have this exponential curve because

(09:09):
it's really fast. The changes are really fast. We're not
prepared as a society and governments are not prepared and
things are shifting really fast. But this is happening and
we have to deal with it and we have to
do the shift.

Speaker 1 (09:23):
So well, here's what I love about the hotel is
that so Internet, iPhone, all the technology has been challenging
for baby boomers. I mean, we are just not Our
minds don't work like that. But when it comes to AI,
our minds do work like that. And I think that's

(09:44):
the big difference with this technology from all predecessor technologies
that we've had to deal with because and baby boomers.
Let's face it, we're I mean, most a lot of
companies are still run by baby boomers. They're being passed
on to Gen xers and money, et cetera. They're being
passed on there, but in large part a lot of

(10:04):
them are still being run by babymers, and baby boomers sometimes.

Speaker 3 (10:08):
Feel left out. They feel left out.

Speaker 1 (10:10):
Well, wait a minute, this technology is too hard. And
what I'm suggesting is, and I'd like you to kind
of walk through what you do with small businesses because
I'm suggesting that I think when it comes to AI,
baby members have an advantage and it's not that hard
because really just all we're doing is asking the right questions.
We're just coming up with a series of questions. You

(10:30):
can can continue asking the questions and AI can actually
generates its own bot to look at your stuff and
so that you're continually refining what you're doing there. So
it seems like this is the one technology that baby
members may not be so far behind on. So if
you could walk us through kind of the steps you

(10:50):
take a small business through in using AI in one
of your sprints.

Speaker 2 (10:57):
So, first of all, what I do is send a
questionnaire to the relevant people. I always start from the top, right,
and these are usually baby boomers, as you mentioned, and
they have to be convinced in what we're going through
because they are the ones who are telling the staff
and the managers. You know, take two hours off this week,

(11:20):
just focus on AI implementation. Right, build this custom GPT,
create this project on cloud, create a hub, a knowledge
hub on notebook and whatever. The tools right tools can change,
but the attitude, the strategy must come from people understand
where the business is going. Right If I'm managing an

(11:41):
international conference vendor business and I want more attendees and
I want more sponsorships, right, I know my goals, but
my staff they're focused on on their thing, and so
it has to come from there. And then when the
importance because eventually know it's it's research based. Seventy to

(12:03):
eighty percent of the failure or success rate is the
human factor of integrating AI into the business. And what
is this human factor is change management and adoption of technology?
And where does change management happen with the baby boomers
who say, do I want AI here? Do I want

(12:23):
to change the existing processes? Do I want to amplify
the existing more cloths? And this is exactly where we start.
We start with mapping the existing workflow, the processes, the goals, right,
what do I want to achieve the sprint. I usually
focus on one to two use cases, right, and then
in thirty days we can create a very significant change.

(12:45):
And then after that, for each session we create quickments.
We start, you know with after I met the questionnaire,
We do some research on the company. We understand how
they work, we understand the after the discovery call, what
the founder is like, what they're looking at. Also, of
course the level of acquaintance with the existing technology. Are
they using it, are they not using it? You know,

(13:07):
it might be might just be that people are using
checkipt to five percent or three percent of the capabilities,
they are not eighteen ninety percent. So we might not
even introduce a single new tool just knowing how to
work with the existing tools. So this is one thing.
And then a lot of a lot of the problem

(13:32):
with adopting AI is the POMO right, Faro missing out
and everyone are experiencing POMO. And what this causes is
many people to just you know, to get the new tech,
new tech, new tech, and because they're so overwhelmed, they
do nothing. I see it a lot. They just do
nothing because this is one thing and the other thing

(13:55):
that happens a lot that people tried. You know, I
tried GPT once. The was not good and they left it.
But the most basic understanding has to be that AI
is like an intern you just took to the company
and you have to teach them. Now, you wouldn't expect
an intern on their first day to give you one

(14:17):
hundred percent perfect output, right, This should be the exact
same approach. You have a new intern, you teach them,
You give them the knowledge they need to understand how
the company works. You need to have access to the data. Right.
The data is the basic foundation of everything AI. Because
data is like if you refer to the question right,

(14:40):
if I'm asking the right question, and if I have
the right data, the output can be good. Like there
is gigle right, the garbage in, garbage out, there is
also gigle gold in, gold out. If it's gold in,
it's going to go gold out. And this is the
questioning and this is the data. And if the data
is bad, the output is necessarily going to be bad.

(15:00):
This is why I also went to when I decided
to focus on this, I took a certification in data
engineering because I wanted to understand how the data work. Now,
in terms of complexity, again, maybe the setup, the initial
setup that we do for example in the sprint, this

(15:21):
is a little bit technical. Again, it's not too much.
There are things that require more technical, but again it's
mostly the setup after it's using. It shouldn't be too
complicated for people who run a business, right or the
agentic work and stuff like that. Eventually you're creating a.

Speaker 4 (15:42):
Helper in whatever field you're choosing to help you get
things done faster. Beat inventory or beat customer support, or
beat content creation, whatever you're doing.

Speaker 2 (15:57):
It's going to help you make it consistently better and faster.
But you have to know it's an iterative process. It's
not going to be the first time, and this is
what breaks a lot of people because they start and
then they don't get perfect. Talk with it and say,
you know, it's easiest to get back to what I
do every time, right if I if I'm used to

(16:18):
doing it, whatever time it takes me, whatever the output,
I know how to do it my way. So the
shift has to be first of all a mindset.

Speaker 1 (16:30):
But so I think that it comes back though to
this question, and you bring out a couple of things here.
First of all, so the good news is baby boomers
all have millennials working in their office. Okay, that's that's
our primary That's who our managers are.

Speaker 3 (16:47):
Our millennials and millennials are.

Speaker 1 (16:49):
Tech savvy just as a as a as a group,
they're tech savay not everyone individually, but as a group
they are. So there's chances are we've got people in
our company who are tech savvy. So when you're talking
about building and the tech stuff like that, the owners
don't need to be don't need to know how to
do that, right that they that that's something that is
that Look, we'll delegate whoever wants to be the champion,

(17:12):
be the champion, work with somebody like you and develop
the tool. But when it comes to training it, you know,
here's the advantage that the baby boomer has, or the
you know, the person with the more experienced has is
that we're, first of all, we're good at training.

Speaker 3 (17:30):
You know, we've spent years and years training.

Speaker 1 (17:33):
People, right, I mean, every every business owner has spent
years training people. Otherwise we would still be in business, right,
And and so we're just training AI instead of training
a person like you say, it's an intern. So we're
training AI and we're refining our questions.

Speaker 3 (17:49):
But it still comes back to me.

Speaker 1 (17:51):
It seems like that it comes back to being ask
the good questions. And if it takes longer, it's maybe
because we're not asking the right question in the first place.

Speaker 2 (18:02):
That's right. And again it's not necessarily longer. It's being
able to shift the mindset to iterations, not having the
perfect answer the first time. And again it's not It
might not be a shift from one hour to one month.
It's just one hour to two hours, three hours or

(18:23):
four hours, but it's going to happen and eventually, like
for example, now when we train a custom GPT, which
is basically a type of an agent, right, AGENTIC is
a spectrum right from from nothing to one hundred percent,
no human in the loop, there's a spectrum, and the
custom jipity is basically type of an agent. Right. Also,

(18:48):
the new models of j JIPT are our agents basically
all three and the stuff. So you need to know
what you're doing because you want to see that the
agent is actually doing what you want to do. And
again this goes back to asking the right question and
knowing what type of knowledge will be necessary to get
the right type of bans. And obviously the knowledge is

(19:11):
in your core business, right you know how operations work,
you know what clients like or dislike like. All of
this knowledge has to be integrated somehow to your agent, custom,
GPT project, whatever it is, in order to get the
output that you want to get.

Speaker 3 (19:29):
Yeah, let me ask you a question.

Speaker 1 (19:30):
So let's talk about agents, just for saying, because I
think most people don't know what an agent is. Business
owners have spent we've spent years and years that's creating systems,
which a lot of those systems there really are policies
and procedures.

Speaker 3 (19:47):
But if I'm kind of.

Speaker 1 (19:48):
The way I look at that agent is really AI
can be all of those policy and procedures without having
to write them all down. You're just training AI to
have those built into the system, so you don't have
to spend all that time. I mean I've had times

(20:09):
years where we've spent literally thousands of man hours developing
processes and procedures, which was always very frustrating to me.
It seems like with AI, we're talking about doing this
in a matter of a few weeks, you know, in
a sprint with you or.

Speaker 3 (20:28):
You know, we can actually put all of this knowledge.

Speaker 1 (20:31):
One of the other issues is we lose so much
knowledge when somebody leaves. Right, There's so much knowledge that leaves.
So can you kind of address that in terms of
that agent and how you're setting up the AI.

Speaker 2 (20:46):
Right, I'll just give you an example of a workflow
that you can use. For example, now you have a
conversation with your engineer about the process that you want
to create in the company, and then you like we
have now you use a transcriber, an AI agent to
transcribe the call, and then you prompt it to create

(21:08):
a process from your call. Right, So instead of someone
spending now five six hours documenting, which everyone hates, you
just take the call and you have a structure of
a prompt, right you can use For example, just let's
use a specific tool by Google. It's called notebook Lamp,
and you take the sources. For example, one source would

(21:31):
be the transcription of the call or ten transcriptions of
ten calls we had about this topic, and then I
prompt it with an example of an existing process documentation
for example, right, because I have those and then I
wanted to take the ten transcripts that I just had

(21:51):
and turn it into a new process documentation based on
the old one. This is a workflow that can save
tons of hours and will give you a very good
output because a you gave it an example of how
good looks like and this only you can know as
a person who has the experience, right, and also you

(22:12):
give it these specifics of the output or the discussions
you had. And this this is the main advantages of llms,
even before the new models is identifying patterns, right, they
do it very efficiently and quickly, much better than humans.
So let's use it for that, right, and then I

(22:34):
create process to temptation in a much shorter time and lee.

Speaker 3 (22:40):
And then on top of that, it's searchable.

Speaker 1 (22:42):
Yes right now, now I don't have to I mean,
it's all in the AI system, so you don't have
to go, Okay, i'm gonna put it over here, I'm
gonna put it over here. I'm gonna put it over here,
because you're just gonna search it.

Speaker 2 (22:55):
Yeah, yeah, and you'll have a project for that way.
If you want to onboard someone you have all questions
that everyone asks or the knowledge that you want to transfer,
you have a hub, let's say again on notebook LM,
because it's just very you know, it's typical knowledge hub, right,

(23:18):
and you would upload the all the documents and you
would create on that hub the FAQ file, a mind
map of how the business looks like UH, an audio
overview which is very interactive of the company and people
can just type in their questions about the company before

(23:40):
coming to anyone else. So this can be a full
workflow of employee on boarding for a new company. Creating
one hub and you know, the setup would take one, two, three,
four hours if you know where the data is, if
you know what to ask, but then you have it
and anyone you in the company will have this knowledge

(24:03):
hub to question. Right.

Speaker 1 (24:06):
Yeah, I love it, So if you will, as we
wrap up, would you just give us maybe two or
three steps that you would have a business owner take
to start integrating AI.

Speaker 2 (24:19):
Yeah. So the first step, and we mentioned it, is
to understand the goals or maybe more specifically one goal.
Start small, start with a pilot project with a real
pain point that you're having, and just focus on this
one and also focus on something that people can visually

(24:41):
see how it improves their lives. Basically, right their work,
but their lives. Because if now, let's say I just
did a project for project managers in a company that
does a lot of outreach before you know, conferences and
stuff like that, and they are the COO of the

(25:04):
company told, you know, our employees are not happy before
the conferences. They're really they're working in their ass off
until twelve pm, one am, two am, and we want
happier employees. So we started with this for a small
pilot conference and then we created a custom GPT for

(25:29):
them that turned a two week process into half an
hour creating all the outreach in their brand, in their language,
with their right people, with the right templates, and then
the people can focus on building relationship with the clients

(25:51):
instead of frantically writing all the communications and all these
specifics of the conference, the conference room, the hours. These
things can be automated and then the actual relationship building
and nurturing new relationship. You have more time for that.
So this is one thing you will find this you

(26:13):
have your goal, You have this specific pilot project that
you know is going to bring people value, and also
make sure everyone knows it's an iterative process and give
time to people expand this you know, even make AI
time for people during the week, and I see this

(26:33):
is really a pity. I see business owners that think
like the old way and know they should do it
on their own time at home. Whatever, This is not
going to work. Just give them time during the week,
even you know, I don't want to say make it mandatory,
but you can have a meeting around that and you
can share prompts and you can. So this is the

(26:54):
workflow I would suggest. It's mapping what you're doing currently.
Find one small pilot program. Once it's successful, everyone are
going to want to implement that. And also obviously align
everyone right because nowadays I see also two things I'm
doing for businesses. One is optimizing the cost because people

(27:17):
are kind of spending on tools they're not using, not optimizing,
not sure why they're paying for so we optimize that.
So that's one thing that's important for us. And this
because it can scale up the cost of AI tools
once you have five, ten, twenty tools, so maybe you
just need too right, but you're paying for many and
you're paying for the wrong tiers and et cetera. So

(27:39):
that's one thing. And another thing obviously is to kind
of strategize around what's important to you and show like
real specific value to the people. And then again everyone
would want to implement, everyone would want to use that.

(28:00):
So this is a good starting point.

Speaker 3 (28:03):
I love it.

Speaker 1 (28:04):
Show them, show them the win, give them the win,
show them, shall them, show them how this actually helps
not hurts them, doesn't take more of their time.

Speaker 3 (28:13):
And that's how we use AI.

Speaker 1 (28:15):
And of course when we when we're when when we
actually learned how to use AI the right way, we're
gonna end up always making more money and payless tax.
And uh, tell, if you would give us where can
people find you so that we can reach you?

Speaker 2 (28:31):
Sure? So, so you have my LinkedIn talgalon on LinkedIn.
I do share a lot of AI implementation knowledge over there,
so I invite everyone to follow and connect and if
you want to, I can share also the email the
other details on the podcast or wherever.

Speaker 1 (28:51):
Great, we'll put that in the show notes. Appreciate that,
h TL, thank you so much for joining us, and
uh if we've done a number of podcasts on AI
and the different aspects of AI, think this has been terrific.
Tale and so go to those others on the wealth
Ability Show and remember again the more knowledge we get

(29:14):
in this, the more money we make, and this is
actually a place where it's coming down the road quickly,
but we're going to end up paying way less tax
at the same time.

Speaker 3 (29:22):
We'll see y'all next time.

Speaker 2 (29:24):
This podcast is a presentation of rich Dad Media Network.