September 4, 2025 • 41 mins
Artificial Intelligence is no longer just hype—it’s here, reshaping how companies think about pricing. In this episode of Let’s Talk Pricing, George Boretos, CEO of FutureUP and recognized Top 50 Thought Leader in AI, joins us to explore how predictive AI is already transforming pricing decisions and why now is the time for first movers to act.
We cover:
The “AI in Pricing Paradox” and why timing matters
Where predictive AI is making the biggest impact today
Quick wins to start your AI-powered pricing journey
How pricing professionals can stay relevant and confident as AI becomes more integrated
If you’re curious about how to put AI into practice—not someday, but today—this episode is for you.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
You're listening to Let's Talk Pricing, your connection to the
voices, stories, and strategies shaping the pricing world.
Each episode, we go beyond theory into the practical,
timely conversations that help you lead with confidence and
drive results. Let's start the show.
Very good day, everyone, and welcome back to the Let's Talk
(00:23):
Pricing podcast, where we explore the ideas, the
strategies and the new innovations that shape pricing,
revenue management, sales enablement and related fields.
So I'm very excited about today's conversation.
We're going to be talking about a new frontier in pricing and
that is artificial intelligence.AI is still largely
(00:47):
misunderstood by a lot of our members worldwide, but we have
some great information coming today.
I'm very happy that we are joined by Mr. George Barrettos.
George is the founder and CEO ofFuture Up.
He has been at the forefront of applying predictive AI to
pricing and optimization. George has worked with Fortune
(01:10):
500 companies from across the globe.
He's raised millions in AI funding, and he has been
recognized as a top 50 thought leader in AI and a top voice in
predictive analytics. George is also a very great
partner with Professional Pricing Society, of course, and
he has a very new, very excitingnew online pricing course with
(01:34):
us that's called the AI in pricing Paradox and opportunity
for first Movers O. We're going to talk about the
paradox. We're going to talk about
timing. We're going to talk about how
pricing professionals and revenue managers can take
practical steps to get ahead. But first of all, a very nice
welcome to our guest for today'sLet's Talk Pricing podcast, Mr.
(01:55):
George Barretos. George, how are you today, Sir?
I'm great. And Kevin, to everyone, thanks
for the invitation. Really excited.
To be here today and discuss, all right.
Wonderful. Thank you so much.
So we have a few questions for you.
And of course, for me personally, when I see people at
our events and they ask me aboutAI, I have to admit that I'm a
(02:15):
student as well and I have a lotto learn.
So we've got a lot of questions and I'm looking forward to some
great insights here. But first of all, can you tell
us a little bit about your journey?
How did you come to focus on this great intersection or great
Venn diagram overlap between artificial intelligence and
(02:37):
pricing? And what has inspired your
teaching around this and your work in these areas?
OK, How much time do you have? Because it's a long journey.
Because. It's 30 years.
Ago and I had two parallel journeys, one for AI and one for
pricing and invergency. Eventually they converged.
(02:59):
So with AI I've started in the university.
Where I studied AI, some ancientprogramming languages back then.
They're not used anymore, unfortunately.
And. Nobody was talking about AI.
It wasn't popular but I loved itand I've seen it growing.
And eventually becoming what it's now.
It's been mainstream and so on. So forth.
(03:20):
I've used it continuously as a business executive initially,
but successfully in several initiatives.
And then I became a startupper. The past almost 10 years now,
I've launched, as you said, the three startup companies and I've
used. AIA lot in all these companies,
they were AI based companies. So that was my AI.
(03:41):
Part of the journey. And then there is the pricing
part, which started almost at the same time actually with my.
MBA. So I've just.
Finished my software engineeringdiploma.
And then I've decided that I needed to open up my horizons.
I didn't know a lot. About business, but I thought
that would be. A nice direction to follow.
(04:03):
So I did my. MBA in.
Imperial Collins in London and we had the marketing professor.
They are a great guy and he saidmany great things, but one of
the cases case studies that he said remember it.
Even now it. Had to do with pricing.
It was a story about the price. War even before the time that
(04:25):
I've studied and. It was a price war between cell
and other petrol. Companies.
And what happened is what usually happens in price wars,
prices declined, margins declined and everybody was
following each other, decreasingprices again and again.
And nobody was happy about that.And there was a product manager
back then in sale and she decided to check a bit to do
(04:50):
some number granting and check price elasticity, sell against
competitors. And eventually he found that
they had less. Elastic prices and demand
against their. Competitors, so he suggested,
and they did, that they stopped increasing, decreasing prices
and actually they started. Slightly increasing them
(05:10):
instead. And what happens afterwards?
They stopped the. Price war, everybody followed.
Eventually, and even they won the price war, they had better
profitability and they retained their market share.
For me that was. A great lesson.
By the way, rumors said that ourprofessor was that.
Product manager I never. Confirmed that, but it was.
(05:31):
Something that was being said. Possibly.
It's true. I don't know.
But for me it was a great lessonbecause that day I really
understood the power of pricing and also the power of numbers,
and this LED afterwards my entrepreneurial endeavours, my
three start-ups. All involved in pricing as.
(05:51):
Well, and eventually this led tothe creation of Future which is
a dedicated company in. AI based price optimization so.
This is the journey. Excellent.
That's quite a journey. And I love the story that you
mentioned from your Imperial College, from your professor
there. And I think that's a great
example of how there was one person with the insights
(06:15):
necessary, with the business acumen, using game theory and
using the analytics and using all of the skills there.
And when he stopped that price war, he probably saved his
company and also his competitors.
He probably saved a lot of jobs in that industry as well.
Because as we know, price wars can really depress an entire
(06:36):
industry and cause a lot of people their jobs.
So if it was your professor, then he or she is a hero or a
heroine for probably saving a lot of jobs, whoever that
individual was. Of course, that's a that's a
great lesson and I love your background.
When you talked about your software background, and I
(06:56):
probably go back a few languagesas well.
I think I remember being a basicprogrammer when I was in high
school, believe it or not. Of course, that's not used
anymore, at least I hope it's not.
But I love the background of pricing people sometimes where
we come from different fields and we take all of these
knowledge experiences that we have and combine them in order
(07:16):
to move forward there. So I think that that's great.
Thanks for the explanation of the background there.
So another question for you here.
You refer to a paradox a lot. Your course with us has the word
paradox in the, in the title, wetalked about the paradox in AI,
artificial intelligence and pricing.
So please tell us a little bit more about that paradox and why
(07:41):
it is important for pricing professionals to understand
everything that's going on rightnow.
Well, it is a paradox and recently confused me as well
when I've discovered it it. Has to do with the following if
you search. Around and find studies about
the value of AI based price optimization for instance,
(08:03):
you'll find great things. And a lot of.
Evidence to support. It.
For instance, Gardner says that among.
All the other AI applications inbusiness, the commercial.
Part of business price optimization is the best one,
the most valuable and the most feasible 1.
So it's there, you can use it, and it's very, very valuable.
(08:24):
So I thought that most companieswould have done something about
it and we did the survey with highly acclaim, value based
selling and pricing. Expert Steve Laborde and his
company Value Based Booster. This survey last year to
identify several things. Among these things was also the
adoption of different AI technologies in companies.
(08:48):
And we're surprised because AI price optimization had the
small. Adoption rate and not the
largest one. And that's the paradox, because.
You see a a reversed relationship between the.
Value of these. Technologies and the adoption
and. For me this is a big red light
(09:09):
or red flag that there is something wrong out there and
most likely people don't understand.
They are not aware. They need to be educated about
the huge benefits of using AI all in almost everything, but
especially in pricing and the need to prioritize it more.
Than they have right now. And This is why I wanted to do
(09:32):
this course. And again, thanks.
To the PBS and you Kevin for this.
Opportunity to identify this problem, issue, paradox and to
help. Fix it to some extent.
Obviously, but I think that awareness is at least the first
step. Towards fixing it.
Understood. And thank you for the
(09:52):
description of that paradox there.
And you're absolutely right, pricing people are often under
trained, under appreciated, under compensated in spite of
the fact of the great influence that we as professionals can
have on our organization's strength and profitability and
margins and the good things to come there.
(10:13):
So you're correct, that is quitea paradox.
That's something that PPS members, of course, are very
familiar with on a very close basis, of course, because that's
their jobs day-to-day where theyhave this outsized importance on
the company's success. But also they are often under
(10:34):
appreciated, under compensated, under trained.
They don't have the tools. And so that's what our
organization and others in our field, of course, try to do as
we try to get them the tools there, which is of course, why
we're very happy about your course and about the information
that you're giving us there. So thank you so much for that.
And George, another thing that you mentioned is AI is shifting
(10:57):
from hype to practical applications.
So where are you seeing the biggest breakthroughs When we
talk about AI being used in pricing?
Who is taking advantage of it? Well, as Garner said, AI price
optimization is not just valuable but also feasible.
So they know better and they have seen, as we all have seen,
(11:20):
practical examples of AI applications in pricing.
There are numerous of success stories from companies.
Like mine for instance and othervendors out.
There, but I will mention a couple of examples that are
highly visible and we have all used.
Them and or seen them so. Price optimization, I think it's
(11:41):
the. Most common sense example of AI
in pricing and IT. Could be price optimizing
prices. To reach a better.
Revenue to maximize your revenueor profits, profitability, or.
Any other indicator? That matters for the compound.
The second thing that. Again, it's very, very visible.
(12:03):
We've seen it all of the time when we try to book our airplane
tickets or we buy something fromAmazon.
So it's dynamic pricing. And this is when.
We have. Varying suggestions or in.
Prices based on market indicators supply.
Demand dynamics and several other.
Things. I think that's an emerging.
(12:24):
Field imagine although it. Started from the previous
century to be honest, but now it's highly popular because of.
AI and because of the use of these highly visible.
Tools like from Amazon. And other entire line tickets
and all these things. But there are other areas also
(12:45):
that perhaps are not so popular but are extremely important.
And they are arising in interestand we have evidence about how
value and there are and their benefits like a price
predictions or creating what if scenarios based on price and
other market factors. Product.
Bundling AI can help on that a lot.
(13:08):
Sometimes people use conjoint analysis for that and they don't
understand. That beneath that there is a
simplistic but there is an AI. Layer that helps analyse the.
Information. There are other AI systems that
are even more sophisticated. And they can do that.
For a product bundling. And the the last.
Thing that I wanted to. Mention because.
This is a side. Benefit of price.
(13:30):
Optimization, but it's extremelyhelpful, is segmentation,
because in order to do price optimization, we need to
identify. Many cases, not no cases.
Groups of customers or countriesor anything segments that behave
in the same way price wise, theyhave the same price sensitivity.
So, so you segment based on price sensitivity, which by
(13:53):
definition is the most importantway that you can segment your
market and you can. Get that with the AI tools.
Again, it's not as visible as other.
Things like dynamic pricing or standard price.
Optimization, but I think it's here to stay.
And very, very important. Excellent.
Thank you, George. And segmentation, of course, as
(14:14):
you mentioned, is very key to pricing professionals, to
revenue managers. That's something that
essentially we have to do in order to perform the best for
ourselves, for our careers and for our companies as well.
And of course, as you mentioned also AI can be very good at
recognizing the patterns at grouping things together and can
(14:35):
be a very big bonus in segmentation in addition to the
other things that you mentioned there such as optimization and
doing what if analysis as well. So there are a lot of different
applications. So thank you for the information
there. And I one more question here.
I know that predictive AI is 1 area that you are essentially
(14:57):
knowledgeable in, and predictiveAI seems to be playing more of a
leading role when we talk about some of the applications that
we're seeing right now. Can you explain the value of
predictive AI to someone who is just starting out in pricing or
someone who is just starting to use it in their work?
(15:19):
Yeah, I will do that with an example because I think it's
easier this way. So let's imagine a case where
you have a product, it sells good and nicely, you have a good
market share and so on, so. Forth, but you're not happy with
its profitability, you would like to.
Have a bit better price. So what you do?
Sometimes you experiment, so youstart increasing slightly your
(15:42):
price. And you see if this has an
effect. On your profits if your profits.
Increase you continuously increase your.
Price until it doesn't anymore. When you reach a maximum point,
when after that your profits start declining, practically
what you have done is manually optimizing your pricing to
(16:02):
maximize your profit. It could have been your revenue
and so on so forth, but you needto experiment manually in order
to do. That.
With predictive AI, you don't have to experiment yourself,
because predictive AI does. Exactly.
The same thing. And it analyzes existing sales
data, so you don't have to do toexpose yourself.
With the experimentation you canuse your existing.
(16:25):
Sales data with varying prices and so on and so forth.
And the system will identify thepatterns, the dynamics, pricing,
sales dynamics, and in the end, create a system, an AI model
that can predict your sales performance based on your
pricing. And based on that it can
optimise prices and so on and soforth.
And even more, it can do something better.
(16:48):
It can factor in additional factors, additional drivers.
So imagine the previous example with your experimentation.
If you change your price but at the same time your competitors
change their prices, or you had tariffs, or you had inflation or
you had macro. Things changing in the market.
So this is even more. Complex for the human brain to.
(17:10):
Process. Usually it will have more than
two or three dimensions. It's almost impossible to
process it manually, but predictive AI is specifically
designed for this, so it can factor.
In 10s of different indicators. And understand which indicator
is the most important and their.Weight into defining sales
(17:31):
performance in the end so predictively.
I can do all these things that we do instinctively and
manually, but can do it faster, quicker, better in a more
sophisticated way and factor in all the important factors and
not just. A couple.
Excellent. So predictive AI sounds like
it's a great tool given the macroeconomic environment that
(17:54):
we are in now in various parts of the globe.
So it sounds like a great usefulthing for us to consider for
right now with all of the extra dimensions and all of the extra
things that are coming into playfor pricing people and for
revenue managers. So thank you for the information
there. That was great.
And what we're going to do rightnow, we are enjoying our
(18:17):
conversation with Mr. George Barretos.
We're going to take a short break to hear from our sponsors,
but please stay with us, the Let's Talk Pricing podcast with
Mr. George Barretos. We'll be right back.
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All right, everyone. Welcome back to Let's Talk
Pricing. We are talking about the AI in
Pricing Paradox and opportunity for first movers with our guest,
Mr. George Barretos, CEO of Future Up and a top 50 thought
(19:23):
leader in AI and a top voice in predictive analytics as well.
So, George, we're going to continue with a couple good
questions. And this has been great because
I'm learning a lot, but I've heard a lot of our members, PPS
members from around the world talk about AGI and about
futuristic AI. And your course, I believe for
(19:47):
focuses on what's already available.
But can you give us an example of how AI is being applied
successfully in pricing today? Yeah, and it's important to keep
our feet on the ground because ATI may come or not.
But this is not important. The important.
Thing is how we can. Create value today based on
(20:11):
practically AI. Tools that exist as we.
Speak and are used all over the world.
There are a few examples that are highly visible, so I will
start with this. First of all, with airlines,
because this is something that we are using every.
Day to book. Our flights and what perhaps we
don't. Understand, but we pricing
(20:32):
people and AI people know is that there is an AI.
System for price optimization dynamic.
Price optimization that is running under the hood.
It takes into consideration various factors.
It could be competitors prices, it could be the profile of the
customer or the country of origin, the IP address or things
(20:53):
like that, or market conditions or anything else.
And in the end, dynamically it changes prices and we see that
if you check for a specific. Flight today, and then tomorrow
and the day after. Tomorrow and so on so forth.
You see prices continuously changing as if you were.
The Stock Exchange or something like that?
Then you have Amazon. Which is a great example again
(21:16):
of dynamic pricing. With Amazon it's perhaps even
worse because even if you're thesame person at the same time,
checking for the same book or any other product, and if you
check through your laptop, desktop, mobile device, you
might. Find a different price so they
take into. Consideration every tiny.
Detail of your. Profile in order to process it
(21:38):
and dynamically adjust their prices.
And of course this is. AI based and.
So these are tools that we use them.
All of the. Time and something which is
newer. But it's out there and used
extensively it's. Uber.
So Uber used obviously and AI dynamic pricing, but it's.
Famous for its service pricing. Service pricing means that if
(21:59):
you have a traffic jam, for instance, and there are not so
many. Taxis available and you want to
go from point A to point B. Then in full transparency, Uber
will inform you that the price has increased by X times or X
percent or whatever because of that if you choose to.
(22:20):
To get this right. Then you will pay more, but at
least you will. Find a taxi.
It has been highly successful for Uber.
These are all very. Visible examples.
Because we are using them because these are B to.
C Business to consumer examples.That doesn't.
Mean that we don't have examplesin the B to B world.
But they're less visible becauseit's for the smaller business
(22:44):
community, not for. Everyone to see.
You have great price optimization.
Deployments in companies like BAS, for instance Rio Tinto,
UPSDH. L and there are.
Many, many, many, many successful.
Examples. Some of these examples are
known, and some of these examples are not known because
(23:06):
the customers just do it. They enjoy the benefits of AI in
pricing, but they don't. Speak about it because they want
to retain the competitive advantage for.
Them so This is why B2B success.Is not so visible.
But believe me, it's there and it's great.
I definitely believe you. And I know that that's one of
the, I would say basic, basic cultural things amongst pricing
(23:31):
people, particularly in B to B, is they want to be very, very
good at their job. But often that entails not
saying to everyone that they arevery, very good at their job
because your customers, your competitors, and your
marketplace are always out thereas well.
So it's an interesting, I think cultural part of our part of the
business world where we want to be very, very good, but we don't
(23:52):
necessarily want to have a trumpet or a large instrument or
a large megaphone and announce that to the world.
But from your experience, what are the biggest hurdles that
companies face when they try to implement AI in their pricing
functions? Well, I would say that for.
AI in pricing the most. Important problem and the issue
(24:15):
that has been documented in several studies is data or lack
of. Data or lack of data?
The required form in order to beused by AI, the.
Second most important issue. And again, this is documented
by. Studies is fear of being.
Replaced with a. Pricing person or someone else
(24:36):
or being replaced by. AI.
In my mind, these are both myths.
To some extent, they're true. Yes, we might have problems with
data and we might be replaced ifwe don't do certain things.
And so on so forth. But this is.
Not the main issue. The main issue and so stopper
for most companies. For implementing AI and pricing
(24:59):
is that they don't. Know where to start from.
They don't know how to begin. They think of all the issues.
Involved. We need data, we need processes,
we need people alignment, we need we need the world.
And obviously if you try to. Fix everything, including.
Some of the problems that you had regardless of.
AI deployments. And so on, so forth.
(25:19):
Obviously it's a huge exercise you will never start.
Instead, they should do. Something different they should
start. Small find the first target.
That's the most important thing to find the first quick win, the
first target that it's easily feasible.
So don't start from a complex product, but use a smaller 1A
(25:40):
simpler 1. Where you do have some data.
And if you don't have for all countries, then limit your
initiative in some countries where you have something.
But start. It's important to start, do the
first step, and then continuously learn, adapt
because it's a learning process.This process never ends, it will
mature. Eventually, when you have.
(26:01):
Learned a lot, but you need to learn.
First of all, and. For that, you need to
experiment. I like to use Nike's motto for
that. Because I love it.
Just do it. I mean, don't offer engineer
things, but just do. It and eventually you will find
the right path that. Will lead you into bigger
deployments and to perfect everything.
(26:22):
But you can do it from day one. That's the biggest problem for
most companies. Understood and thank you.
And it kind of comes back to human nature where with a lot of
big projects, sometimes the first step is the hardest.
Sometimes we have to overcome that initial fear of change and
the initial inertia of the way that things are going.
(26:43):
And basically, you have to take that first leap.
It will not be perfect, but you can build upon that and continue
to iterate and improve with every change and continue to do
better there. So thank you for the explanation
there. And one more question for you
here, please. So George, you make the case
that right now is a key movement, a key moment.
(27:05):
I'm sorry for first movers. So what makes the timing of
right now so important? And what advantage can companies
gain by acting quickly? Well, there are a couple of
things. It's like a perfect storm, but a
positive perfect storm for a pricing and AI in pricing.
(27:27):
First of all, because pricing right now is in the.
Spotlight. Why is that?
You have tariffs, you have. Inflation you have, fluctuating
cost of materials you have. Supply chains disrupted, you
have all these things that affect pricing and are.
Affected by pricing. So this puts a lot of focus on
(27:47):
pricing for the first time. After many, many years.
So that's a great. Moment and a great opportunity
to leverage. Pricing.
The second thing is AI, obviously.
AI is in the spotlight. For at least a couple.
Of years 2:00 to 3:00. Years, especially after the
launch of. Chat CBT became mainstream so
everybody is talking about that.Now, why all these are important
(28:09):
and interesting? Because people in companies, top
management, CEOs, directors, allthese guys they're trying to
figure out with. AI.
They understand that it's important and they try to figure
out where and how to apply. It could be pricing, but it
could be a number of other. Different directions or
initiatives. So I think it's a great
(28:31):
opportunity to leverage. Why?
Because pricing people should first of all generate the first
initiative. For AI in pricing.
Price optimization or anything else, First of all to.
Gain a competitive advantage against their competitors,
exactly as the paradox that we explain.
AI based pressure optimization is extremely valuable, but it's
(28:53):
not used by many. Out there, but many covenants.
Out there. So if you start first then you
have the first movers advantage.If you don't do it, then
someone. Else gets this first mover
advantage. So it's great for the company
and a great opportunity for pricing in the company to start
an initiative with. AI, but that's the external
(29:17):
competition. There is also an internal
competition within the companiesand this happens.
Why? Because pricing doesn't have a
big set of. Voice within companies.
It's still an emerging function.An emerging department and
field. So that means that if.
Not. If pricing people don't do
something about. AI because AI is disrupting
(29:39):
things and it's an opportunity to change.
Relative. Relationships and power within
the. Company if you don't do.
Something about AI and marketingtakes a lead or.
Sales or? I don't know any other
department. You lose a great opportunity.
You should instead lead the. Change of your company into the
AI era. And this way you will gain more
(30:00):
attention yourself obviously to your department, you will
increase your share of voice andat the same time you will do
good for your company. It will be great for your
company. I think it's all about pricing
leadership and this is a great opportunity to leverage both
pricing and AI to lead your way into the AI era and establish
(30:20):
yourself and pricing within the organization.
All right, so we heard it here. So for pricing leaders and
future pricing leaders and pricing managers to come, this
is your great opportunity to take advantage of a great new
tool that's going to help your company out.
So with that, we are going to take another short break for our
(30:42):
sponsors. But everyone please stay with
us. We'll be back with more.
Let's talk pricing with Mr. George Barretos.
And George, thank you so much. We'll be right back.
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LV25 to register. Welcome back to the Let's Talk
Pricing podcast, everyone. We are learning a lot about AI
from Mr. George Barretos. And George, I have a few more
questions for you here. But first of all, we've talked a
(31:45):
lot about how AI can be a great opportunity for pricing
organizations, for revenue management and related fields.
But let me ask you this, are there particular types of
organizations and we can think of their size, their industry,
their vertical, their structure?Are there types of organizations
that are best positioned to gainthe benefits from AI,
(32:09):
specifically in pricing? Well, that's another myth that
pricing is just for a few sectors, let's say for the
retail. Sector or it's for just?
The big companies who have the budget or the experience or
anything else, but that's me thethe answer.
Is yes, Sir, and no. And and why is that the yes part
first, if the the question is ifany company could benefit by
(32:33):
introducing an AI initiative in.Pricing.
The answer is definitely yes. All companies can benefit from
either improving their pricing or using.
AI to improve their pricing. They will see different
benefits. In type and magnitude depending
on their structure, the industryand their size, for instance.
(32:54):
If you are a smaller. Company or a smaller product?
Obviously there is more potential.
To increase X fold so you could double for instance your
revenue. But if you are a bigger company,
obviously you cannot double yourrevenue, but you can increase by
a few percentage points, which is more than enough because this
worth. Hundreds of millions possibly,
(33:16):
if you are a big company. So you have different things to
gain, but definitely you have. Substantial things to gain.
Usually in profitability, in growth and everything that
matters in. Companies.
Let me ask you a little bit about the human being and AI
collaboration. This is a theme in a lot of your
work, and also it is a section of your course with us as well.
(33:41):
So what does a human AI collaboration look like in a
practical pricing setting? I get this question a lot to.
Be honest. It comes from two types of.
People, sometimes it's from people who are afraid that they
will be replaced by AI and. To the other end is some people
(34:02):
that feel that AI can go to autopilot.
It can take over the pricing function or something else and
it doesn't need to be attended or monitored or anything else.
Both cases are extremes and. Wrong.
The right way is. Collaboration, Human AI
collaboration and. Think of AI in humans like a
(34:26):
Formula One drivers in cars. So the car is the AI, obviously
it's the technology is the best technology.
Out there, But would you trust aFormula One car, need to drive
it or a naval driver out there? You're laughing because
obviously. You wouldn't and you shouldn't.
Or the other way around, if you had a great formula driver,
(34:47):
let's say Hamilton or someone like that, driving a.
Small car, obviously. You need both to win and this is
some of the Formula One knows itvery very well.
We in the AI. Space and the pricing space, we
haven't. Discovered it yet or realise it
yet? But we do need both.
(35:09):
AI is great in what is a great in number crunching, in
analysing past. Amounts of data.
This is what it does. Best.
Doesn't have any common sense, it doesn't have any instincts.
People do. And people understand even
without all the necessary data would be limited or sometimes
with no data at all. With their instincts they
(35:32):
realise what's the right direction.
So in order to even start training your model, you need
direction from people. And afterwards, when you start
deploying the system and gettingprice adjustments and you see
the results, you need people to monitor continuously for strange
behaviour. We have many, many.
Cases where strange. Things happen that common sense
(35:54):
would have immediately spotted that this is.
Problematic from a person. And there is one final thing
that. In the end.
Regardless of how the AI. Performs and what it does, how
it's trained and so on and so forth in the end.
A person is accountable for the.Outcome so someone is to blame
if. Someone goes South or someone
(36:16):
needs to get the credit if something goes great with AI.
System. It's not the AI system.
So definitely within this equation you have humans and AI
at the same time, so it's not one.
Against the other, or one or theother.
It's definitely both, otherwise you will see disaster.
Absolutely, a great explanation and thank you for that.
(36:37):
So it's a combination of the human being, common sense, all
of the inner workings in our brain in combination with the
tool that can do better at number crunching and do better
at some facets of the issue at hand better than a human brain
can. So that makes perfect sense.
So thank you for the explanationthere.
And George, we'll end with one final question here, since AI is
(37:01):
here to say, what do you see as the next evolution in artificial
intelligence when we think aboutit as a pricing tool?
So how can everyone who's joining us today for the Let's
Talk Pricing podcast, how can westay ahead of what's coming down
the road as well? Well, there are a couple of
(37:24):
areas that will see them emerging that will dominate the
market, at least in my mind, thefollowing years.
The the obvious thing is to say that predictive.
AI, which is mostly responsible for pricing initiatives.
AI pricing. Initiatives will evolve and be
better as time passes. Better models, better pricing.
(37:48):
Information and so on and so forth.
But that's the. The obvious thing?
The most obvious thing is that there is a trend of using domain
intelligent. AI systems.
People. Most people have heard about
the. Black boxes, AI black boxes.
So AI is. Powerful, but it's also.
Something that you cannot explain.
You cannot understand what is happening under the whole.
(38:11):
Why is that? Because these are general
purpose AI tools. They can be.
Used in pricing. But it is more difficult if you
use instead an econometric model.
In combination with some general.
Purpose AI components. That's better because the
econometric. Part is based on economic.
Theory. And why not use economic theory,
(38:31):
which has been proven right all these years and you have vast
amount of knowledge out? There, that's been used.
Even before AI was invaded and quite successfully.
So we will see this combination of econometric intelligence with
AI together forming a better model which can be explained and
it's more business friendly. The other thing that we will see
(38:55):
and we have. Already seen it in.
Practice is dynamic adjustment, so there is price optimization.
That may be static. Well, we optimize prices and
that's it. And then it's a dynamic pricing
that optimizes continuously prices based on varying market
macro or other. Indicators.
And that's important why? Because we live in times where
(39:17):
volatility is the norm and it's not something that.
Happens every now and then. So.
We need to be able to continuously adjust to
continuously generate predictivescenarios based on future
trends. And what is going to happen?
It's not a static. World.
At least not anymore. It's a continuously evolving and
(39:38):
sometimes violently, sometimes more smoothly, but it's
continuously evolving, so pricing should evolve as well.
All right, terrific. So Mr. George Varetos.
George, thank you so much for joining us today for this issue
of the Let's Talk Pricing podcast.
You've given us a lot to think about about AI and how it is a
tool that seems to be very well suited for the macroeconomic
(40:01):
challenges that a lot of us are facing now.
It is these times and as you mentioned B to B companies some
of us have gone from. One price increase per year to
once per quarter, couple times per year and some even once
every month now. So with the change that we are
showing, certainly we all have to take advantage of the tools
that are out there in order to help us do that as well as we
(40:25):
can. So thank you very much for the
insights there. And for those of us listening
today who want to learn more about George, his work with PPS,
his online pricing course with us, of course, you can check out
George. Look for future up.
You can also, of course, check out pricing society.com for
Georgio's course. And also we'll have a lot of
(40:46):
other information for our members worldwide.
You can also check out our events coming up in a few
months. We will be in Las Vegas for our
North American PPS Profitable Conference October 21st or 24th.
We will be in Barcelona for our EMEA PPS Profitable conference
from the 2nd to the 5th of December.
(41:07):
And we will have lots more information and things coming
for you and for your team as well.
So thanks everyone for tuning in.
You're listening to Let's Talk Pricing, your connection to the
voices, stories, and strategies shaping the pricing world.
Each episode, we go beyond theory into the practical,
timely conversations that help you lead with confidence and
drive results. Let's start the show.
Very good day, everyone, and welcome back to the Let's Talk
(00:23):
Pricing podcast, where we explore the ideas, the
strategies and the new innovations that shape pricing,
revenue management, sales enablement and related fields.
So I'm very excited about today's conversation.
We're going to be talking about a new frontier in pricing and
that is artificial intelligence.AI is still largely
(00:47):
misunderstood by a lot of our members worldwide, but we have
some great information coming today.
I'm very happy that we are joined by Mr. George Barrettos.
George is the founder and CEO ofFuture Up.
He has been at the forefront of applying predictive AI to
pricing and optimization. George has worked with Fortune
(01:10):
500 companies from across the globe.
He's raised millions in AI funding, and he has been
recognized as a top 50 thought leader in AI and a top voice in
predictive analytics. George is also a very great
partner with Professional Pricing Society, of course, and
he has a very new, very excitingnew online pricing course with
(01:34):
us that's called the AI in pricing Paradox and opportunity
for first Movers O. We're going to talk about the
paradox. We're going to talk about
timing. We're going to talk about how
pricing professionals and revenue managers can take
practical steps to get ahead. But first of all, a very nice
welcome to our guest for today'sLet's Talk Pricing podcast, Mr.
(01:55):
George Barretos. George, how are you today, Sir?
I'm great. And Kevin, to everyone, thanks
for the invitation. Really excited.
To be here today and discuss, all right.
Wonderful. Thank you so much.
So we have a few questions for you.
And of course, for me personally, when I see people at
our events and they ask me aboutAI, I have to admit that I'm a
(02:15):
student as well and I have a lotto learn.
So we've got a lot of questions and I'm looking forward to some
great insights here. But first of all, can you tell
us a little bit about your journey?
How did you come to focus on this great intersection or great
Venn diagram overlap between artificial intelligence and
(02:37):
pricing? And what has inspired your
teaching around this and your work in these areas?
OK, How much time do you have? Because it's a long journey.
Because. It's 30 years.
Ago and I had two parallel journeys, one for AI and one for
pricing and invergency. Eventually they converged.
(02:59):
So with AI I've started in the university.
Where I studied AI, some ancientprogramming languages back then.
They're not used anymore, unfortunately.
And. Nobody was talking about AI.
It wasn't popular but I loved itand I've seen it growing.
And eventually becoming what it's now.
It's been mainstream and so on. So forth.
(03:20):
I've used it continuously as a business executive initially,
but successfully in several initiatives.
And then I became a startupper. The past almost 10 years now,
I've launched, as you said, the three startup companies and I've
used. AIA lot in all these companies,
they were AI based companies. So that was my AI.
(03:41):
Part of the journey. And then there is the pricing
part, which started almost at the same time actually with my.
MBA. So I've just.
Finished my software engineeringdiploma.
And then I've decided that I needed to open up my horizons.
I didn't know a lot. About business, but I thought
that would be. A nice direction to follow.
(04:03):
So I did my. MBA in.
Imperial Collins in London and we had the marketing professor.
They are a great guy and he saidmany great things, but one of
the cases case studies that he said remember it.
Even now it. Had to do with pricing.
It was a story about the price. War even before the time that
(04:25):
I've studied and. It was a price war between cell
and other petrol. Companies.
And what happened is what usually happens in price wars,
prices declined, margins declined and everybody was
following each other, decreasingprices again and again.
And nobody was happy about that.And there was a product manager
back then in sale and she decided to check a bit to do
(04:50):
some number granting and check price elasticity, sell against
competitors. And eventually he found that
they had less. Elastic prices and demand
against their. Competitors, so he suggested,
and they did, that they stopped increasing, decreasing prices
and actually they started. Slightly increasing them
(05:10):
instead. And what happens afterwards?
They stopped the. Price war, everybody followed.
Eventually, and even they won the price war, they had better
profitability and they retained their market share.
For me that was. A great lesson.
By the way, rumors said that ourprofessor was that.
Product manager I never. Confirmed that, but it was.
(05:31):
Something that was being said. Possibly.
It's true. I don't know.
But for me it was a great lessonbecause that day I really
understood the power of pricing and also the power of numbers,
and this LED afterwards my entrepreneurial endeavours, my
three start-ups. All involved in pricing as.
(05:51):
Well, and eventually this led tothe creation of Future which is
a dedicated company in. AI based price optimization so.
This is the journey. Excellent.
That's quite a journey. And I love the story that you
mentioned from your Imperial College, from your professor
there. And I think that's a great
example of how there was one person with the insights
(06:15):
necessary, with the business acumen, using game theory and
using the analytics and using all of the skills there.
And when he stopped that price war, he probably saved his
company and also his competitors.
He probably saved a lot of jobs in that industry as well.
Because as we know, price wars can really depress an entire
(06:36):
industry and cause a lot of people their jobs.
So if it was your professor, then he or she is a hero or a
heroine for probably saving a lot of jobs, whoever that
individual was. Of course, that's a that's a
great lesson and I love your background.
When you talked about your software background, and I
(06:56):
probably go back a few languagesas well.
I think I remember being a basicprogrammer when I was in high
school, believe it or not. Of course, that's not used
anymore, at least I hope it's not.
But I love the background of pricing people sometimes where
we come from different fields and we take all of these
knowledge experiences that we have and combine them in order
(07:16):
to move forward there. So I think that that's great.
Thanks for the explanation of the background there.
So another question for you here.
You refer to a paradox a lot. Your course with us has the word
paradox in the, in the title, wetalked about the paradox in AI,
artificial intelligence and pricing.
So please tell us a little bit more about that paradox and why
(07:41):
it is important for pricing professionals to understand
everything that's going on rightnow.
Well, it is a paradox and recently confused me as well
when I've discovered it it. Has to do with the following if
you search. Around and find studies about
the value of AI based price optimization for instance,
(08:03):
you'll find great things. And a lot of.
Evidence to support. It.
For instance, Gardner says that among.
All the other AI applications inbusiness, the commercial.
Part of business price optimization is the best one,
the most valuable and the most feasible 1.
So it's there, you can use it, and it's very, very valuable.
(08:24):
So I thought that most companieswould have done something about
it and we did the survey with highly acclaim, value based
selling and pricing. Expert Steve Laborde and his
company Value Based Booster. This survey last year to
identify several things. Among these things was also the
adoption of different AI technologies in companies.
(08:48):
And we're surprised because AI price optimization had the
small. Adoption rate and not the
largest one. And that's the paradox, because.
You see a a reversed relationship between the.
Value of these. Technologies and the adoption
and. For me this is a big red light
(09:09):
or red flag that there is something wrong out there and
most likely people don't understand.
They are not aware. They need to be educated about
the huge benefits of using AI all in almost everything, but
especially in pricing and the need to prioritize it more.
Than they have right now. And This is why I wanted to do
(09:32):
this course. And again, thanks.
To the PBS and you Kevin for this.
Opportunity to identify this problem, issue, paradox and to
help. Fix it to some extent.
Obviously, but I think that awareness is at least the first
step. Towards fixing it.
Understood. And thank you for the
(09:52):
description of that paradox there.
And you're absolutely right, pricing people are often under
trained, under appreciated, under compensated in spite of
the fact of the great influence that we as professionals can
have on our organization's strength and profitability and
margins and the good things to come there.
(10:13):
So you're correct, that is quitea paradox.
That's something that PPS members, of course, are very
familiar with on a very close basis, of course, because that's
their jobs day-to-day where theyhave this outsized importance on
the company's success. But also they are often under
(10:34):
appreciated, under compensated, under trained.
They don't have the tools. And so that's what our
organization and others in our field, of course, try to do as
we try to get them the tools there, which is of course, why
we're very happy about your course and about the information
that you're giving us there. So thank you so much for that.
And George, another thing that you mentioned is AI is shifting
(10:57):
from hype to practical applications.
So where are you seeing the biggest breakthroughs When we
talk about AI being used in pricing?
Who is taking advantage of it? Well, as Garner said, AI price
optimization is not just valuable but also feasible.
So they know better and they have seen, as we all have seen,
(11:20):
practical examples of AI applications in pricing.
There are numerous of success stories from companies.
Like mine for instance and othervendors out.
There, but I will mention a couple of examples that are
highly visible and we have all used.
Them and or seen them so. Price optimization, I think it's
(11:41):
the. Most common sense example of AI
in pricing and IT. Could be price optimizing
prices. To reach a better.
Revenue to maximize your revenueor profits, profitability, or.
Any other indicator? That matters for the compound.
The second thing that. Again, it's very, very visible.
(12:03):
We've seen it all of the time when we try to book our airplane
tickets or we buy something fromAmazon.
So it's dynamic pricing. And this is when.
We have. Varying suggestions or in.
Prices based on market indicators supply.
Demand dynamics and several other.
Things. I think that's an emerging.
(12:24):
Field imagine although it. Started from the previous
century to be honest, but now it's highly popular because of.
AI and because of the use of these highly visible.
Tools like from Amazon. And other entire line tickets
and all these things. But there are other areas also
(12:45):
that perhaps are not so popular but are extremely important.
And they are arising in interestand we have evidence about how
value and there are and their benefits like a price
predictions or creating what if scenarios based on price and
other market factors. Product.
Bundling AI can help on that a lot.
(13:08):
Sometimes people use conjoint analysis for that and they don't
understand. That beneath that there is a
simplistic but there is an AI. Layer that helps analyse the.
Information. There are other AI systems that
are even more sophisticated. And they can do that.
For a product bundling. And the the last.
Thing that I wanted to. Mention because.
This is a side. Benefit of price.
(13:30):
Optimization, but it's extremelyhelpful, is segmentation,
because in order to do price optimization, we need to
identify. Many cases, not no cases.
Groups of customers or countriesor anything segments that behave
in the same way price wise, theyhave the same price sensitivity.
So, so you segment based on price sensitivity, which by
(13:53):
definition is the most importantway that you can segment your
market and you can. Get that with the AI tools.
Again, it's not as visible as other.
Things like dynamic pricing or standard price.
Optimization, but I think it's here to stay.
And very, very important. Excellent.
Thank you, George. And segmentation, of course, as
(14:14):
you mentioned, is very key to pricing professionals, to
revenue managers. That's something that
essentially we have to do in order to perform the best for
ourselves, for our careers and for our companies as well.
And of course, as you mentioned also AI can be very good at
recognizing the patterns at grouping things together and can
(14:35):
be a very big bonus in segmentation in addition to the
other things that you mentioned there such as optimization and
doing what if analysis as well. So there are a lot of different
applications. So thank you for the information
there. And I one more question here.
I know that predictive AI is 1 area that you are essentially
(14:57):
knowledgeable in, and predictiveAI seems to be playing more of a
leading role when we talk about some of the applications that
we're seeing right now. Can you explain the value of
predictive AI to someone who is just starting out in pricing or
someone who is just starting to use it in their work?
(15:19):
Yeah, I will do that with an example because I think it's
easier this way. So let's imagine a case where
you have a product, it sells good and nicely, you have a good
market share and so on, so. Forth, but you're not happy with
its profitability, you would like to.
Have a bit better price. So what you do?
Sometimes you experiment, so youstart increasing slightly your
(15:42):
price. And you see if this has an
effect. On your profits if your profits.
Increase you continuously increase your.
Price until it doesn't anymore. When you reach a maximum point,
when after that your profits start declining, practically
what you have done is manually optimizing your pricing to
(16:02):
maximize your profit. It could have been your revenue
and so on so forth, but you needto experiment manually in order
to do. That.
With predictive AI, you don't have to experiment yourself,
because predictive AI does. Exactly.
The same thing. And it analyzes existing sales
data, so you don't have to do toexpose yourself.
With the experimentation you canuse your existing.
(16:25):
Sales data with varying prices and so on and so forth.
And the system will identify thepatterns, the dynamics, pricing,
sales dynamics, and in the end, create a system, an AI model
that can predict your sales performance based on your
pricing. And based on that it can
optimise prices and so on and soforth.
And even more, it can do something better.
(16:48):
It can factor in additional factors, additional drivers.
So imagine the previous example with your experimentation.
If you change your price but at the same time your competitors
change their prices, or you had tariffs, or you had inflation or
you had macro. Things changing in the market.
So this is even more. Complex for the human brain to.
(17:10):
Process. Usually it will have more than
two or three dimensions. It's almost impossible to
process it manually, but predictive AI is specifically
designed for this, so it can factor.
In 10s of different indicators. And understand which indicator
is the most important and their.Weight into defining sales
(17:31):
performance in the end so predictively.
I can do all these things that we do instinctively and
manually, but can do it faster, quicker, better in a more
sophisticated way and factor in all the important factors and
not just. A couple.
Excellent. So predictive AI sounds like
it's a great tool given the macroeconomic environment that
(17:54):
we are in now in various parts of the globe.
So it sounds like a great usefulthing for us to consider for
right now with all of the extra dimensions and all of the extra
things that are coming into playfor pricing people and for
revenue managers. So thank you for the information
there. That was great.
And what we're going to do rightnow, we are enjoying our
(18:17):
conversation with Mr. George Barretos.
We're going to take a short break to hear from our sponsors,
but please stay with us, the Let's Talk Pricing podcast with
Mr. George Barretos. We'll be right back.
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Four days of bold strategies, practical tools, and real world
(18:40):
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All right, everyone. Welcome back to Let's Talk
Pricing. We are talking about the AI in
Pricing Paradox and opportunity for first movers with our guest,
Mr. George Barretos, CEO of Future Up and a top 50 thought
(19:23):
leader in AI and a top voice in predictive analytics as well.
So, George, we're going to continue with a couple good
questions. And this has been great because
I'm learning a lot, but I've heard a lot of our members, PPS
members from around the world talk about AGI and about
futuristic AI. And your course, I believe for
(19:47):
focuses on what's already available.
But can you give us an example of how AI is being applied
successfully in pricing today? Yeah, and it's important to keep
our feet on the ground because ATI may come or not.
But this is not important. The important.
Thing is how we can. Create value today based on
(20:11):
practically AI. Tools that exist as we.
Speak and are used all over the world.
There are a few examples that are highly visible, so I will
start with this. First of all, with airlines,
because this is something that we are using every.
Day to book. Our flights and what perhaps we
don't. Understand, but we pricing
(20:32):
people and AI people know is that there is an AI.
System for price optimization dynamic.
Price optimization that is running under the hood.
It takes into consideration various factors.
It could be competitors prices, it could be the profile of the
customer or the country of origin, the IP address or things
(20:53):
like that, or market conditions or anything else.
And in the end, dynamically it changes prices and we see that
if you check for a specific. Flight today, and then tomorrow
and the day after. Tomorrow and so on so forth.
You see prices continuously changing as if you were.
The Stock Exchange or something like that?
Then you have Amazon. Which is a great example again
(21:16):
of dynamic pricing. With Amazon it's perhaps even
worse because even if you're thesame person at the same time,
checking for the same book or any other product, and if you
check through your laptop, desktop, mobile device, you
might. Find a different price so they
take into. Consideration every tiny.
Detail of your. Profile in order to process it
(21:38):
and dynamically adjust their prices.
And of course this is. AI based and.
So these are tools that we use them.
All of the. Time and something which is
newer. But it's out there and used
extensively it's. Uber.
So Uber used obviously and AI dynamic pricing, but it's.
Famous for its service pricing. Service pricing means that if
(21:59):
you have a traffic jam, for instance, and there are not so
many. Taxis available and you want to
go from point A to point B. Then in full transparency, Uber
will inform you that the price has increased by X times or X
percent or whatever because of that if you choose to.
(22:20):
To get this right. Then you will pay more, but at
least you will. Find a taxi.
It has been highly successful for Uber.
These are all very. Visible examples.
Because we are using them because these are B to.
C Business to consumer examples.That doesn't.
Mean that we don't have examplesin the B to B world.
But they're less visible becauseit's for the smaller business
(22:44):
community, not for. Everyone to see.
You have great price optimization.
Deployments in companies like BAS, for instance Rio Tinto,
UPSDH. L and there are.
Many, many, many, many successful.
Examples. Some of these examples are
known, and some of these examples are not known because
(23:06):
the customers just do it. They enjoy the benefits of AI in
pricing, but they don't. Speak about it because they want
to retain the competitive advantage for.
Them so This is why B2B success.Is not so visible.
But believe me, it's there and it's great.
I definitely believe you. And I know that that's one of
the, I would say basic, basic cultural things amongst pricing
(23:31):
people, particularly in B to B, is they want to be very, very
good at their job. But often that entails not
saying to everyone that they arevery, very good at their job
because your customers, your competitors, and your
marketplace are always out thereas well.
So it's an interesting, I think cultural part of our part of the
business world where we want to be very, very good, but we don't
(23:52):
necessarily want to have a trumpet or a large instrument or
a large megaphone and announce that to the world.
But from your experience, what are the biggest hurdles that
companies face when they try to implement AI in their pricing
functions? Well, I would say that for.
AI in pricing the most. Important problem and the issue
(24:15):
that has been documented in several studies is data or lack
of. Data or lack of data?
The required form in order to beused by AI, the.
Second most important issue. And again, this is documented
by. Studies is fear of being.
Replaced with a. Pricing person or someone else
(24:36):
or being replaced by. AI.
In my mind, these are both myths.
To some extent, they're true. Yes, we might have problems with
data and we might be replaced ifwe don't do certain things.
And so on so forth. But this is.
Not the main issue. The main issue and so stopper
for most companies. For implementing AI and pricing
(24:59):
is that they don't. Know where to start from.
They don't know how to begin. They think of all the issues.
Involved. We need data, we need processes,
we need people alignment, we need we need the world.
And obviously if you try to. Fix everything, including.
Some of the problems that you had regardless of.
AI deployments. And so on, so forth.
(25:19):
Obviously it's a huge exercise you will never start.
Instead, they should do. Something different they should
start. Small find the first target.
That's the most important thing to find the first quick win, the
first target that it's easily feasible.
So don't start from a complex product, but use a smaller 1A
(25:40):
simpler 1. Where you do have some data.
And if you don't have for all countries, then limit your
initiative in some countries where you have something.
But start. It's important to start, do the
first step, and then continuously learn, adapt
because it's a learning process.This process never ends, it will
mature. Eventually, when you have.
(26:01):
Learned a lot, but you need to learn.
First of all, and. For that, you need to
experiment. I like to use Nike's motto for
that. Because I love it.
Just do it. I mean, don't offer engineer
things, but just do. It and eventually you will find
the right path that. Will lead you into bigger
deployments and to perfect everything.
(26:22):
But you can do it from day one. That's the biggest problem for
most companies. Understood and thank you.
And it kind of comes back to human nature where with a lot of
big projects, sometimes the first step is the hardest.
Sometimes we have to overcome that initial fear of change and
the initial inertia of the way that things are going.
(26:43):
And basically, you have to take that first leap.
It will not be perfect, but you can build upon that and continue
to iterate and improve with every change and continue to do
better there. So thank you for the explanation
there. And one more question for you
here, please. So George, you make the case
that right now is a key movement, a key moment.
(27:05):
I'm sorry for first movers. So what makes the timing of
right now so important? And what advantage can companies
gain by acting quickly? Well, there are a couple of
things. It's like a perfect storm, but a
positive perfect storm for a pricing and AI in pricing.
(27:27):
First of all, because pricing right now is in the.
Spotlight. Why is that?
You have tariffs, you have. Inflation you have, fluctuating
cost of materials you have. Supply chains disrupted, you
have all these things that affect pricing and are.
Affected by pricing. So this puts a lot of focus on
(27:47):
pricing for the first time. After many, many years.
So that's a great. Moment and a great opportunity
to leverage. Pricing.
The second thing is AI, obviously.
AI is in the spotlight. For at least a couple.
Of years 2:00 to 3:00. Years, especially after the
launch of. Chat CBT became mainstream so
everybody is talking about that.Now, why all these are important
(28:09):
and interesting? Because people in companies, top
management, CEOs, directors, allthese guys they're trying to
figure out with. AI.
They understand that it's important and they try to figure
out where and how to apply. It could be pricing, but it
could be a number of other. Different directions or
initiatives. So I think it's a great
(28:31):
opportunity to leverage. Why?
Because pricing people should first of all generate the first
initiative. For AI in pricing.
Price optimization or anything else, First of all to.
Gain a competitive advantage against their competitors,
exactly as the paradox that we explain.
AI based pressure optimization is extremely valuable, but it's
(28:53):
not used by many. Out there, but many covenants.
Out there. So if you start first then you
have the first movers advantage.If you don't do it, then
someone. Else gets this first mover
advantage. So it's great for the company
and a great opportunity for pricing in the company to start
an initiative with. AI, but that's the external
(29:17):
competition. There is also an internal
competition within the companiesand this happens.
Why? Because pricing doesn't have a
big set of. Voice within companies.
It's still an emerging function.An emerging department and
field. So that means that if.
Not. If pricing people don't do
something about. AI because AI is disrupting
(29:39):
things and it's an opportunity to change.
Relative. Relationships and power within
the. Company if you don't do.
Something about AI and marketingtakes a lead or.
Sales or? I don't know any other
department. You lose a great opportunity.
You should instead lead the. Change of your company into the
AI era. And this way you will gain more
(30:00):
attention yourself obviously to your department, you will
increase your share of voice andat the same time you will do
good for your company. It will be great for your
company. I think it's all about pricing
leadership and this is a great opportunity to leverage both
pricing and AI to lead your way into the AI era and establish
(30:20):
yourself and pricing within the organization.
All right, so we heard it here. So for pricing leaders and
future pricing leaders and pricing managers to come, this
is your great opportunity to take advantage of a great new
tool that's going to help your company out.
So with that, we are going to take another short break for our
(30:42):
sponsors. But everyone please stay with
us. We'll be back with more.
Let's talk pricing with Mr. George Barretos.
And George, thank you so much. We'll be right back.
This October 21st through 24th, PPS Profitable in Las Vegas is
all about you, the pricing professional ready to navigate
today's challenges and lead withconfidence.
(31:02):
In just four days, you'll gain the strategies, tools and
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Early Bird pricing ends September 19th and our group
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Make the investment in yourself.Visit pricingsociety.com/P PS:
(31:25):
LV25 to register. Welcome back to the Let's Talk
Pricing podcast, everyone. We are learning a lot about AI
from Mr. George Barretos. And George, I have a few more
questions for you here. But first of all, we've talked a
(31:45):
lot about how AI can be a great opportunity for pricing
organizations, for revenue management and related fields.
But let me ask you this, are there particular types of
organizations and we can think of their size, their industry,
their vertical, their structure?Are there types of organizations
that are best positioned to gainthe benefits from AI,
(32:09):
specifically in pricing? Well, that's another myth that
pricing is just for a few sectors, let's say for the
retail. Sector or it's for just?
The big companies who have the budget or the experience or
anything else, but that's me thethe answer.
Is yes, Sir, and no. And and why is that the yes part
first, if the the question is ifany company could benefit by
(32:33):
introducing an AI initiative in.Pricing.
The answer is definitely yes. All companies can benefit from
either improving their pricing or using.
AI to improve their pricing. They will see different
benefits. In type and magnitude depending
on their structure, the industryand their size, for instance.
(32:54):
If you are a smaller. Company or a smaller product?
Obviously there is more potential.
To increase X fold so you could double for instance your
revenue. But if you are a bigger company,
obviously you cannot double yourrevenue, but you can increase by
a few percentage points, which is more than enough because this
worth. Hundreds of millions possibly,
(33:16):
if you are a big company. So you have different things to
gain, but definitely you have. Substantial things to gain.
Usually in profitability, in growth and everything that
matters in. Companies.
Let me ask you a little bit about the human being and AI
collaboration. This is a theme in a lot of your
work, and also it is a section of your course with us as well.
(33:41):
So what does a human AI collaboration look like in a
practical pricing setting? I get this question a lot to.
Be honest. It comes from two types of.
People, sometimes it's from people who are afraid that they
will be replaced by AI and. To the other end is some people
(34:02):
that feel that AI can go to autopilot.
It can take over the pricing function or something else and
it doesn't need to be attended or monitored or anything else.
Both cases are extremes and. Wrong.
The right way is. Collaboration, Human AI
collaboration and. Think of AI in humans like a
(34:26):
Formula One drivers in cars. So the car is the AI, obviously
it's the technology is the best technology.
Out there, But would you trust aFormula One car, need to drive
it or a naval driver out there? You're laughing because
obviously. You wouldn't and you shouldn't.
Or the other way around, if you had a great formula driver,
(34:47):
let's say Hamilton or someone like that, driving a.
Small car, obviously. You need both to win and this is
some of the Formula One knows itvery very well.
We in the AI. Space and the pricing space, we
haven't. Discovered it yet or realise it
yet? But we do need both.
(35:09):
AI is great in what is a great in number crunching, in
analysing past. Amounts of data.
This is what it does. Best.
Doesn't have any common sense, it doesn't have any instincts.
People do. And people understand even
without all the necessary data would be limited or sometimes
with no data at all. With their instincts they
(35:32):
realise what's the right direction.
So in order to even start training your model, you need
direction from people. And afterwards, when you start
deploying the system and gettingprice adjustments and you see
the results, you need people to monitor continuously for strange
behaviour. We have many, many.
Cases where strange. Things happen that common sense
(35:54):
would have immediately spotted that this is.
Problematic from a person. And there is one final thing
that. In the end.
Regardless of how the AI. Performs and what it does, how
it's trained and so on and so forth in the end.
A person is accountable for the.Outcome so someone is to blame
if. Someone goes South or someone
(36:16):
needs to get the credit if something goes great with AI.
System. It's not the AI system.
So definitely within this equation you have humans and AI
at the same time, so it's not one.
Against the other, or one or theother.
It's definitely both, otherwise you will see disaster.
Absolutely, a great explanation and thank you for that.
(36:37):
So it's a combination of the human being, common sense, all
of the inner workings in our brain in combination with the
tool that can do better at number crunching and do better
at some facets of the issue at hand better than a human brain
can. So that makes perfect sense.
So thank you for the explanationthere.
And George, we'll end with one final question here, since AI is
(37:01):
here to say, what do you see as the next evolution in artificial
intelligence when we think aboutit as a pricing tool?
So how can everyone who's joining us today for the Let's
Talk Pricing podcast, how can westay ahead of what's coming down
the road as well? Well, there are a couple of
(37:24):
areas that will see them emerging that will dominate the
market, at least in my mind, thefollowing years.
The the obvious thing is to say that predictive.
AI, which is mostly responsible for pricing initiatives.
AI pricing. Initiatives will evolve and be
better as time passes. Better models, better pricing.
(37:48):
Information and so on and so forth.
But that's the. The obvious thing?
The most obvious thing is that there is a trend of using domain
intelligent. AI systems.
People. Most people have heard about
the. Black boxes, AI black boxes.
So AI is. Powerful, but it's also.
Something that you cannot explain.
You cannot understand what is happening under the whole.
(38:11):
Why is that? Because these are general
purpose AI tools. They can be.
Used in pricing. But it is more difficult if you
use instead an econometric model.
In combination with some general.
Purpose AI components. That's better because the
econometric. Part is based on economic.
Theory. And why not use economic theory,
(38:31):
which has been proven right all these years and you have vast
amount of knowledge out? There, that's been used.
Even before AI was invaded and quite successfully.
So we will see this combination of econometric intelligence with
AI together forming a better model which can be explained and
it's more business friendly. The other thing that we will see
(38:55):
and we have. Already seen it in.
Practice is dynamic adjustment, so there is price optimization.
That may be static. Well, we optimize prices and
that's it. And then it's a dynamic pricing
that optimizes continuously prices based on varying market
macro or other. Indicators.
And that's important why? Because we live in times where
(39:17):
volatility is the norm and it's not something that.
Happens every now and then. So.
We need to be able to continuously adjust to
continuously generate predictivescenarios based on future
trends. And what is going to happen?
It's not a static. World.
At least not anymore. It's a continuously evolving and
(39:38):
sometimes violently, sometimes more smoothly, but it's
continuously evolving, so pricing should evolve as well.
All right, terrific. So Mr. George Varetos.
George, thank you so much for joining us today for this issue
of the Let's Talk Pricing podcast.
You've given us a lot to think about about AI and how it is a
tool that seems to be very well suited for the macroeconomic
(40:01):
challenges that a lot of us are facing now.
It is these times and as you mentioned B to B companies some
of us have gone from. One price increase per year to
once per quarter, couple times per year and some even once
every month now. So with the change that we are
showing, certainly we all have to take advantage of the tools
that are out there in order to help us do that as well as we
(40:25):
can. So thank you very much for the
insights there. And for those of us listening
today who want to learn more about George, his work with PPS,
his online pricing course with us, of course, you can check out
George. Look for future up.
You can also, of course, check out pricing society.com for
Georgio's course. And also we'll have a lot of
(40:46):
other information for our members worldwide.
You can also check out our events coming up in a few
months. We will be in Las Vegas for our
North American PPS Profitable Conference October 21st or 24th.
We will be in Barcelona for our EMEA PPS Profitable conference
from the 2nd to the 5th of December.
(41:07):
And we will have lots more information and things coming
for you and for your team as well.
So thanks everyone for tuning in.
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