May 15, 2025 • 20 mins
What happens when AI stops asking for instructions and starts acting on its own? In this episode, we explore the rise of Agentic AI with expert Enver Cetin Listen as he and host, Jim Jockle, breaks down what makes Agentic AI different from traditional models, why it’s revolutionizing industries, and how businesses can build trust and governance around autonomous decision-making.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Jim Jockle (00:06):
Welcome to Trading Tomorrow Navigating Trends in
Capital Markets the podcastwhere we deep dive into
technologies reshaping the worldof capital markets.
I'm your host, jim Jockle, aveteran of the finance industry
with a passion for thecomplexities of financial
technologies and market trends.
In each episode, we'll explorethe cutting-edge trends, tools
and strategies driving today'sfinancial landscapes and paving
(00:29):
the way for the future.
With the finance industry at apivotal point, influenced by
groundbreaking innovations, it'smore crucial than ever to
understand how thesetechnological advancements
interact with market dynamics.
(00:52):
We're diving into one of themost transformative developments
in artificial intelligenceagentic AI.
Unlike traditional AIassistants that rely on human
prompts, agentic AI is designedto think, plan and act
autonomously towards specificgoals.
These AI-powered agents canoptimize supply chains in real
time, revolutionize customerservice and even drive
(01:15):
scientific discovery, allwithout direct human
intervention.
To explore Agentic AI further,we're joined by Enver Seaton,
senior Manager for Generative AIat ClickLum, a global digital
solutions company With abackground in AI strategy and
automation.
Enver helps businesses harnessAI-driven transformation and has
spoken at industry events anduniversities on the future of AI
(01:38):
, enterprise adoption and theemerging role of AI agents in
business.
Today, he'll help us unpackwhat agentic AI really is, why
it's critical to the future ofwork and how businesses can
prepare for this shift.
Guest (01:53):
Enver welcome.
Thank you for having me today,jim.
It's a pleasure to join andexplore today's fascinating
topic.
Jim Jockle (02:00):
Yeah, so agentic AI.
It's gaining a lot of attention.
Arguably, chat GPT is oldschool and it's all about agents
.
But perhaps you can start byexplaining what it is, how it
differs from traditional AImodels like chatbots or
generative AI.
Guest (02:18):
Of course.
So for me, agentic AI is trulychanging the game, and here's
why and I always try to useexamples just imagine you're
working with a typical chatbotor a generative ai tool.
You have a question or needsomething done and you
explicitly tell it what to do.
It then responds based on yourprompt, and that's traditional
(02:38):
ai.
It's responsive and, of course,helpful, but requires constant
human guidance.
And now let's think of agenticAI as giving AI not just ears to
listen, but also legs to moveforward independently and eyes
to spot opportunities on its own.
So, instead of waiting forinstructions, agentic AI can
(02:59):
think, plan and act more or lessindependently to achieve a
specific goal, and that's wherethe whole proactiveness comes in
place.
Jim Jockle (03:07):
So let's talk about proactive AI.
What does that really mean andhow can this proactiveness be a
game changer?
Guest (03:16):
So when I call agentic AI proactive, I mean that, of
course, traditional AI modelsare like helpful assistants they
respond when asked, butproactive AI agents don't sit
around waiting for instructions.
Instead, they constantlymonitor their environment, your
environment, anticipate what'scoming next and actively take
(03:39):
steps to achieve their or yourgoals, and sometimes even before
humans notice a need.
So think of a proactive AI likea skilled team member who is
always looking out for your bestinterest, and imagine you're
running an investment portfolioand a proactive AI doesn't wait
(04:01):
until you say, penalize the riskin my investment.
Instead, it's constantlyscanning the market trends,
identifying potential risk andadjusting strategists strategies
automatically, even overnightwhen you're sleeping, and it's
sometimes even several stepsahead, continuously adopting to
(04:21):
changing changing trends,changing data, and always tries
to be proactive and not waitingfor your guidance.
Jim Jockle (04:31):
That seems to have implicit within that a
tremendous amount of trust tolet agents work on your behalf.
You know, in setting these upand thinking about it, you know
how are you gaining trust withthat end user?
Guest (04:49):
I mean, of course, autonomy brings up critical
questions around trust,reliability and, of course,
graphics as well, and theseconcerns that can't be taken
lightly.
My advice always is to ensurethat Agile AI remains reliable
(05:09):
and ethical.
It's crucial to build robustguardrails, so organizations
that want to use AI agents youneed to have transparent
mechanism, regularly auditdecision-making processes and
constantly monitor, for example,for bias or unexpected behavior
(05:31):
.
And constantly monitor, forexample, for bias or unexpected
behavior.
So you need to have yourguardrails and governance in
place to make sure you know whythe AI agent is behaving like it
is and it is actively pursuingyour goal and not its own goals.
Jim Jockle (05:47):
So when I think about generative AI, I think
three years ago all we did wastalk about hallucinations, and
that conversation has prettymuch come to an end.
I mean, in terms of agentic AI,how long is this technology?
Guest (06:06):
It probably depends on who you're asking, but for me,
agentic AI for me, isn't somedistant.
It's not a futuristic ideaanymore.
It's already there and it'salready making significant
impacts right now.
To give you a clear picture,let's explore an example from
one of our case studies from thefinancial industry.
Some hedge funds, for example,and trading firms they actively
(06:31):
are deploying AI agents tomanage investment portfolios
autonomously and they arecontinuously analyzing market
data, predicting trends,identifying investment
opportunities and sometimes evenmaking trades independently,
and all in real time.
Real time.
(06:53):
Beyond finance, we also havelogistics and supply chain
management that are alsoexperiencing remarkable changes,
as AI agents, for example,optimize shipping routes,
inventory levels and resourceallocation without human input.
So for me, or what I'm seeingout of the market or from the
industry, it isn't justtheoretical.
There are businesses who arealready witnessing impressive
(07:16):
efficiency gains, costreductions and strategic
advantages by integrating AIagents today.
Jim Jockle (07:24):
So you talk about goals and guardrails, and
guardrails, I would assume, arecritical right In terms of, if
my goal is make money, right, towhat extent?
How are guardrails being builtto ensure things are ethical,
things are not exploiting anyand every opportunity just to
(07:49):
reach a goal, without that kindof human bias?
Guest (07:53):
of course, um, I mean, there are multiple ways to to to
set up guardrails, but what Ialways try to do is to, for,
when I use goals, when I try togive an ai agent a goal to to
pursue for me, I always try touse as much context as possible.
I I make sure I do have theright data in place and I, for
(08:14):
example, just to be veryspecific, I'm using smart goals.
So I'm making sure the goalsI'm giving the model, they are
measurable, they are welldefined.
There are no room for notunderstanding them, and that's
one specific way to make sureyour goals are understood by the
(08:36):
models as well.
Jim Jockle (08:38):
That's really interesting in terms of the
acronym of the SMART goals.
I think there's this huge fearof knowledge work and workers
being replaced, but at the sametime as I speak with you or
speak with others, it's like youreally need your MBA and a good
understanding of fundamentalprinciples and the way of
(09:00):
knowledge and knowledge work toactually engage and get the most
out of these types of tools.
But you know, I mean, someexperts are believing that
agentic AI will fundamentallychange the knowledge work and do
you think this technology couldimpact job and even broader
(09:22):
industries across the board?
Guest (09:23):
Absolutely so.
I mean considering the broaderimpact on jobs and industries.
Agentic AI, for me, is indeedpoised to fundamentally reshape
knowledge work and, just asautomation, for example,
reshaped manufacturing decadesago, for me AI agents will
(09:43):
reshape how we approach tasksthat previously required human
judgment, analysis and decisionmaking.
But, of course, let's betransparent and let's be clear.
While, of course, some certainrepetitive and or analytical
(10:06):
jobs might become fullyautomated by AI agents, I think
we are more likely to see anevolution rather than a
replacement.
I think roles will shifttowards overseeing AI systems,
ensuring quality and strategicalignment and strategic
alignment, and focusing moredeeply on tasks that require
human creativity, empathy andsome nuanced judgments.
(10:27):
So, for me, the real storyisn't about job losses.
It's about transformation.
Once again, it was always abouttransformation and, of course,
always about adoption to afuture where humans and
proactive AI work side by sideand leveraging each other's
strengths.
Jim Jockle (10:47):
Well, I guess any transformation is always scary,
right?
You think about robotics andmanufacturing, and how many
workers were on a floor ascompared to being there today,
as compared to being there today.
So what is the best way, as ahuman, and dealing with this
evolution of transformation thatfor many of us probably many of
(11:10):
our listeners is close tohitting home?
How should they be thinkingabout it and approaching the
introduction of agents?
Is it just run away in a holeand be scared and perhaps get
automated yourself?
Or, from your perspective,what's some best practices that
people should be thinking of?
I mean?
Guest (11:30):
for me, when it comes to agentic AI, it's all about trust
and transparency, and it'sabout responsible and
transparent governance.
Be proactive.
As a human that might beaffected by agentic AI and I
(11:51):
think we are all going to beaffected by AI Be proactive, be
transparent and try to be partof the solution.
And for our leaders, it shouldbe the goal to include as many
people as possible in yourstrategy when it comes to
finding out where an AI agentcan help your organization and
(12:11):
make the people part of thesolution, because you will still
need these people.
You will still need thesepeople to make sure your models
do know what they are going todo and you know what your people
are doing, making sure you arenot teaching wrong things to
(12:32):
your AI model.
So, for me, it's all abouttrust.
It's all about transparentgovernance.
Jim Jockle (12:37):
There was a recent McKinsey report that was talking
about adoption of AI, and thereport itself was really focused
on generative AI, and theinteresting thing was it was
talking about more, let's say,middle management and workers
themselves were more prone to betrying to utilize or figure out
(12:59):
ways to adopt to all of theseAI tools, and it wasn't
necessarily management or theold guard, if you will, in terms
of driving AI initiatives down.
I guess a couple of questions.
Here is number one are youseeing a change now from some of
the companies and organizationsyou work with in terms of of
(13:21):
thinking a little bit more abouthow they're introducing ai
tools, uh, systematically?
And a second is you know, whenit comes to agentic ai, it's
like we haven't even solved thefirst problem in terms of
changing the ways we work, butnow we now we've got a whole new
thing, so so where's theadoption curve?
Guest (13:38):
right now.
I think it really depends onorganization.
I am.
I know organizations that arestill struggling to just use
simple automations in theirprocesses.
I know some organizations thatare dealing with ai agents
already and what I see why someorganizations are far ahead than
than the other ones is thatthey do have one strategy, but
(14:02):
they are still adapting.
They do have a flexiblestrategy.
For example, when, like five orsix years ago, there was no
generative AI strategy or partof generative AI in corporate
strategy, and because of all thehype and explosion through
ChatGPT, it was all spread ontables of all CEOs worldwide and
(14:28):
it was very easy to use themand to use hands-on new AI
technologies they figured out.
Okay, it's affecting me already.
Maybe I should put that into mycorporate strategy as well.
But it's affecting me already.
Maybe I should put that into mycorporate strategy as well.
So the goal for me is to alwaysencourage leaders from our
(14:50):
customers to make sure you dohave a strategy, make sure you
do have an AI strategy, but beflexible.
The changes they aredramatically.
We are seeing that the costsper token are going down and
down.
It's it's not comparable to thecost of tokens two years ago.
(15:10):
So be flexible in your strategy, because what we are seeing in
the industry is that a lot ofthings will change, if you like
it or not.
Be flexible to adapt to themand make sure you are using some
part of it let's talk aboutdisruption.
Jim Jockle (15:26):
Um, you know, obviously, um ai has the ability
to be incredibly disruptive,but yet you know, we still see
pushback.
We saw, um you know, the hugeuh screen actors guild strike uh
in terms of use of AI toolswith any entertainment industry
in the film industry.
You know there was thelongshoreman strikes here in the
(15:47):
United States of keepingautomation and AI off the docks,
if you will.
You know, but from yourperspective, you know, you have
a wide view on the market.
You know, are there anyparticular industries that you
that potentially will see themost disruption from agentic ai
in the next three?
Guest (16:06):
to five years.
I mean I'm I do have mixedfeelings or mixed thoughts about
that.
There are some industries weare seeing that are poised to
experience the most disruptionfrom agentic ai over, let's say,
the next five years, and theyinclude finance, logistics,
healthcare and especiallycustomer service, for example,
(16:27):
logistics and supply chain.
They will becomehyper-efficient as AI
autonomously adjusts operationsin response to real-time
conditions.
Healthcare will for me, it isalready witnessing substantial
shifts of AI managing patientmonitoring, predictive
diagnostics and personalized,hyper personalized treatment
(16:50):
plans.
So, on one hand, theseindustries stand at the
forefront because they involvecomplex decision-making, massive
data flows and criticalreal-time adjustments, precisely
where agentic AI shinesbrightest.
On the other hand, I'm seeingthat we are coming away from the
(17:10):
Pareto principle, so we werealways taught to always think of
a beta 20.
So to see where we can solvebeta percent of work with 20% of
input data or with money.
But what?
I'm seeing?
That with the help of agenticAI or like trends around agentic
(17:32):
AI AI agents, that nowadays youcan build multimillion dollar
businesses just with one or twopeople and you can solve very
niche problems just within someweeks and or even some days and
um.
So, wherever you have a veryniche, a very, very small
problem, but that's costing youmillions and millions of dollars
(17:53):
.
But there is no solution yet,and there or it would be too
expensive or it was tooexpensive some years ago.
Nowadays, you can just hiresome people and they can build
the solution with AI agents insome days.
Jim Jockle (18:07):
That's incredible.
So that's almost good advice toall the CEOs out there is where
are your highest costs withinyour business and to what extent
can AI reduce some of that costburden?
That's an interesting way tolook at it and, I think, a
(18:29):
really good takeaway, but sadlywe made it to the final question
of this podcast and so we callit the trend drop.
It's like a desert islandquestion.
Guest (18:51):
So we call it the trend drop.
It's like a desert islandquestion.
And if you could only watch ortrack one fusion of agentic AI
and hyper personalizationbanking experiences.
Because what I'm already seeingnow is that, with the help of
generative AI, with the help ofagentic AI systems, hyper
personalization is going toaffect everything For me.
(19:12):
I'm sometimes even imagining afuture where my bank doesn't
just respond to my financialneeds, but also anticipates my
life goals proactively, soadjusting my investments,
suggesting strategic financialmoves and even preparing my
financial, health or lifechanges before I even ask.
So it is a blend of proactiveintelligence and
(19:37):
hyper-personalized touch thathas the potential for me to
transform banking from a passiveservice into my trusted
financial ally, and that's atrend I'm incredibly excited
about.
Jim Jockle (19:52):
Well, enver, if I was on a desert island, I'd have
an agent schedule me a rescueship.
I want to thank you so much foryour insights.
I really appreciated theconversation.
You're on the cutting edge ofthe hype cycle, but that reality
is coming absolutely quick.
So thank you so much for yourtime today.
(20:14):
Thank you, jim for having metoday.
Thank you, Jim, for having me.
Thanks so much for listening totoday's episode and if you're
enjoying Trading Tomorrow,navigating trends and capital
markets, be sure to like,subscribe and share, and we'll
see you next time you.
Welcome to Trading Tomorrow Navigating Trends in
Capital Markets the podcastwhere we deep dive into
technologies reshaping the worldof capital markets.
I'm your host, jim Jockle, aveteran of the finance industry
with a passion for thecomplexities of financial
technologies and market trends.
In each episode, we'll explorethe cutting-edge trends, tools
and strategies driving today'sfinancial landscapes and paving
(00:29):
the way for the future.
With the finance industry at apivotal point, influenced by
groundbreaking innovations, it'smore crucial than ever to
understand how thesetechnological advancements
interact with market dynamics.
(00:52):
We're diving into one of themost transformative developments
in artificial intelligenceagentic AI.
Unlike traditional AIassistants that rely on human
prompts, agentic AI is designedto think, plan and act
autonomously towards specificgoals.
These AI-powered agents canoptimize supply chains in real
time, revolutionize customerservice and even drive
(01:15):
scientific discovery, allwithout direct human
intervention.
To explore Agentic AI further,we're joined by Enver Seaton,
senior Manager for Generative AIat ClickLum, a global digital
solutions company With abackground in AI strategy and
automation.
Enver helps businesses harnessAI-driven transformation and has
spoken at industry events anduniversities on the future of AI
(01:38):
, enterprise adoption and theemerging role of AI agents in
business.
Today, he'll help us unpackwhat agentic AI really is, why
it's critical to the future ofwork and how businesses can
prepare for this shift.
Guest (01:53):
Enver welcome.
Thank you for having me today,jim.
It's a pleasure to join andexplore today's fascinating
topic.
Jim Jockle (02:00):
Yeah, so agentic AI.
It's gaining a lot of attention.
Arguably, chat GPT is oldschool and it's all about agents
.
But perhaps you can start byexplaining what it is, how it
differs from traditional AImodels like chatbots or
generative AI.
Guest (02:18):
Of course.
So for me, agentic AI is trulychanging the game, and here's
why and I always try to useexamples just imagine you're
working with a typical chatbotor a generative ai tool.
You have a question or needsomething done and you
explicitly tell it what to do.
It then responds based on yourprompt, and that's traditional
(02:38):
ai.
It's responsive and, of course,helpful, but requires constant
human guidance.
And now let's think of agenticAI as giving AI not just ears to
listen, but also legs to moveforward independently and eyes
to spot opportunities on its own.
So, instead of waiting forinstructions, agentic AI can
(02:59):
think, plan and act more or lessindependently to achieve a
specific goal, and that's wherethe whole proactiveness comes in
place.
Jim Jockle (03:07):
So let's talk about proactive AI.
What does that really mean andhow can this proactiveness be a
game changer?
Guest (03:16):
So when I call agentic AI proactive, I mean that, of
course, traditional AI modelsare like helpful assistants they
respond when asked, butproactive AI agents don't sit
around waiting for instructions.
Instead, they constantlymonitor their environment, your
environment, anticipate what'scoming next and actively take
(03:39):
steps to achieve their or yourgoals, and sometimes even before
humans notice a need.
So think of a proactive AI likea skilled team member who is
always looking out for your bestinterest, and imagine you're
running an investment portfolioand a proactive AI doesn't wait
(04:01):
until you say, penalize the riskin my investment.
Instead, it's constantlyscanning the market trends,
identifying potential risk andadjusting strategists strategies
automatically, even overnightwhen you're sleeping, and it's
sometimes even several stepsahead, continuously adopting to
(04:21):
changing changing trends,changing data, and always tries
to be proactive and not waitingfor your guidance.
Jim Jockle (04:31):
That seems to have implicit within that a
tremendous amount of trust tolet agents work on your behalf.
You know, in setting these upand thinking about it, you know
how are you gaining trust withthat end user?
Guest (04:49):
I mean, of course, autonomy brings up critical
questions around trust,reliability and, of course,
graphics as well, and theseconcerns that can't be taken
lightly.
My advice always is to ensurethat Agile AI remains reliable
(05:09):
and ethical.
It's crucial to build robustguardrails, so organizations
that want to use AI agents youneed to have transparent
mechanism, regularly auditdecision-making processes and
constantly monitor, for example,for bias or unexpected behavior
(05:31):
.
And constantly monitor, forexample, for bias or unexpected
behavior.
So you need to have yourguardrails and governance in
place to make sure you know whythe AI agent is behaving like it
is and it is actively pursuingyour goal and not its own goals.
Jim Jockle (05:47):
So when I think about generative AI, I think
three years ago all we did wastalk about hallucinations, and
that conversation has prettymuch come to an end.
I mean, in terms of agentic AI,how long is this technology?
Guest (06:06):
It probably depends on who you're asking, but for me,
agentic AI for me, isn't somedistant.
It's not a futuristic ideaanymore.
It's already there and it'salready making significant
impacts right now.
To give you a clear picture,let's explore an example from
one of our case studies from thefinancial industry.
Some hedge funds, for example,and trading firms they actively
(06:31):
are deploying AI agents tomanage investment portfolios
autonomously and they arecontinuously analyzing market
data, predicting trends,identifying investment
opportunities and sometimes evenmaking trades independently,
and all in real time.
Real time.
(06:53):
Beyond finance, we also havelogistics and supply chain
management that are alsoexperiencing remarkable changes,
as AI agents, for example,optimize shipping routes,
inventory levels and resourceallocation without human input.
So for me, or what I'm seeingout of the market or from the
industry, it isn't justtheoretical.
There are businesses who arealready witnessing impressive
(07:16):
efficiency gains, costreductions and strategic
advantages by integrating AIagents today.
Jim Jockle (07:24):
So you talk about goals and guardrails, and
guardrails, I would assume, arecritical right In terms of, if
my goal is make money, right, towhat extent?
How are guardrails being builtto ensure things are ethical,
things are not exploiting anyand every opportunity just to
(07:49):
reach a goal, without that kindof human bias?
Guest (07:53):
of course, um, I mean, there are multiple ways to to to
set up guardrails, but what Ialways try to do is to, for,
when I use goals, when I try togive an ai agent a goal to to
pursue for me, I always try touse as much context as possible.
I I make sure I do have theright data in place and I, for
(08:14):
example, just to be veryspecific, I'm using smart goals.
So I'm making sure the goalsI'm giving the model, they are
measurable, they are welldefined.
There are no room for notunderstanding them, and that's
one specific way to make sureyour goals are understood by the
(08:36):
models as well.
Jim Jockle (08:38):
That's really interesting in terms of the
acronym of the SMART goals.
I think there's this huge fearof knowledge work and workers
being replaced, but at the sametime as I speak with you or
speak with others, it's like youreally need your MBA and a good
understanding of fundamentalprinciples and the way of
(09:00):
knowledge and knowledge work toactually engage and get the most
out of these types of tools.
But you know, I mean, someexperts are believing that
agentic AI will fundamentallychange the knowledge work and do
you think this technology couldimpact job and even broader
(09:22):
industries across the board?
Guest (09:23):
Absolutely so.
I mean considering the broaderimpact on jobs and industries.
Agentic AI, for me, is indeedpoised to fundamentally reshape
knowledge work and, just asautomation, for example,
reshaped manufacturing decadesago, for me AI agents will
(09:43):
reshape how we approach tasksthat previously required human
judgment, analysis and decisionmaking.
But, of course, let's betransparent and let's be clear.
While, of course, some certainrepetitive and or analytical
(10:06):
jobs might become fullyautomated by AI agents, I think
we are more likely to see anevolution rather than a
replacement.
I think roles will shifttowards overseeing AI systems,
ensuring quality and strategicalignment and strategic
alignment, and focusing moredeeply on tasks that require
human creativity, empathy andsome nuanced judgments.
(10:27):
So, for me, the real storyisn't about job losses.
It's about transformation.
Once again, it was always abouttransformation and, of course,
always about adoption to afuture where humans and
proactive AI work side by sideand leveraging each other's
strengths.
Jim Jockle (10:47):
Well, I guess any transformation is always scary,
right?
You think about robotics andmanufacturing, and how many
workers were on a floor ascompared to being there today,
as compared to being there today.
So what is the best way, as ahuman, and dealing with this
evolution of transformation thatfor many of us probably many of
(11:10):
our listeners is close tohitting home?
How should they be thinkingabout it and approaching the
introduction of agents?
Is it just run away in a holeand be scared and perhaps get
automated yourself?
Or, from your perspective,what's some best practices that
people should be thinking of?
I mean?
Guest (11:30):
for me, when it comes to agentic AI, it's all about trust
and transparency, and it'sabout responsible and
transparent governance.
Be proactive.
As a human that might beaffected by agentic AI and I
(11:51):
think we are all going to beaffected by AI Be proactive, be
transparent and try to be partof the solution.
And for our leaders, it shouldbe the goal to include as many
people as possible in yourstrategy when it comes to
finding out where an AI agentcan help your organization and
(12:11):
make the people part of thesolution, because you will still
need these people.
You will still need thesepeople to make sure your models
do know what they are going todo and you know what your people
are doing, making sure you arenot teaching wrong things to
(12:32):
your AI model.
So, for me, it's all abouttrust.
It's all about transparentgovernance.
Jim Jockle (12:37):
There was a recent McKinsey report that was talking
about adoption of AI, and thereport itself was really focused
on generative AI, and theinteresting thing was it was
talking about more, let's say,middle management and workers
themselves were more prone to betrying to utilize or figure out
(12:59):
ways to adopt to all of theseAI tools, and it wasn't
necessarily management or theold guard, if you will, in terms
of driving AI initiatives down.
I guess a couple of questions.
Here is number one are youseeing a change now from some of
the companies and organizationsyou work with in terms of of
(13:21):
thinking a little bit more abouthow they're introducing ai
tools, uh, systematically?
And a second is you know, whenit comes to agentic ai, it's
like we haven't even solved thefirst problem in terms of
changing the ways we work, butnow we now we've got a whole new
thing, so so where's theadoption curve?
Guest (13:38):
right now.
I think it really depends onorganization.
I am.
I know organizations that arestill struggling to just use
simple automations in theirprocesses.
I know some organizations thatare dealing with ai agents
already and what I see why someorganizations are far ahead than
than the other ones is thatthey do have one strategy, but
(14:02):
they are still adapting.
They do have a flexiblestrategy.
For example, when, like five orsix years ago, there was no
generative AI strategy or partof generative AI in corporate
strategy, and because of all thehype and explosion through
ChatGPT, it was all spread ontables of all CEOs worldwide and
(14:28):
it was very easy to use themand to use hands-on new AI
technologies they figured out.
Okay, it's affecting me already.
Maybe I should put that into mycorporate strategy as well.
But it's affecting me already.
Maybe I should put that into mycorporate strategy as well.
So the goal for me is to alwaysencourage leaders from our
(14:50):
customers to make sure you dohave a strategy, make sure you
do have an AI strategy, but beflexible.
The changes they aredramatically.
We are seeing that the costsper token are going down and
down.
It's it's not comparable to thecost of tokens two years ago.
(15:10):
So be flexible in your strategy, because what we are seeing in
the industry is that a lot ofthings will change, if you like
it or not.
Be flexible to adapt to themand make sure you are using some
part of it let's talk aboutdisruption.
Jim Jockle (15:26):
Um, you know, obviously, um ai has the ability
to be incredibly disruptive,but yet you know, we still see
pushback.
We saw, um you know, the hugeuh screen actors guild strike uh
in terms of use of AI toolswith any entertainment industry
in the film industry.
You know there was thelongshoreman strikes here in the
(15:47):
United States of keepingautomation and AI off the docks,
if you will.
You know, but from yourperspective, you know, you have
a wide view on the market.
You know, are there anyparticular industries that you
that potentially will see themost disruption from agentic ai
in the next three?
Guest (16:06):
to five years.
I mean I'm I do have mixedfeelings or mixed thoughts about
that.
There are some industries weare seeing that are poised to
experience the most disruptionfrom agentic ai over, let's say,
the next five years, and theyinclude finance, logistics,
healthcare and especiallycustomer service, for example,
(16:27):
logistics and supply chain.
They will becomehyper-efficient as AI
autonomously adjusts operationsin response to real-time
conditions.
Healthcare will for me, it isalready witnessing substantial
shifts of AI managing patientmonitoring, predictive
diagnostics and personalized,hyper personalized treatment
(16:50):
plans.
So, on one hand, theseindustries stand at the
forefront because they involvecomplex decision-making, massive
data flows and criticalreal-time adjustments, precisely
where agentic AI shinesbrightest.
On the other hand, I'm seeingthat we are coming away from the
(17:10):
Pareto principle, so we werealways taught to always think of
a beta 20.
So to see where we can solvebeta percent of work with 20% of
input data or with money.
But what?
I'm seeing?
That with the help of agenticAI or like trends around agentic
(17:32):
AI AI agents, that nowadays youcan build multimillion dollar
businesses just with one or twopeople and you can solve very
niche problems just within someweeks and or even some days and
um.
So, wherever you have a veryniche, a very, very small
problem, but that's costing youmillions and millions of dollars
(17:53):
.
But there is no solution yet,and there or it would be too
expensive or it was tooexpensive some years ago.
Nowadays, you can just hiresome people and they can build
the solution with AI agents insome days.
Jim Jockle (18:07):
That's incredible.
So that's almost good advice toall the CEOs out there is where
are your highest costs withinyour business and to what extent
can AI reduce some of that costburden?
That's an interesting way tolook at it and, I think, a
(18:29):
really good takeaway, but sadlywe made it to the final question
of this podcast and so we callit the trend drop.
It's like a desert islandquestion.
Guest (18:51):
So we call it the trend drop.
It's like a desert islandquestion.
And if you could only watch ortrack one fusion of agentic AI
and hyper personalizationbanking experiences.
Because what I'm already seeingnow is that, with the help of
generative AI, with the help ofagentic AI systems, hyper
personalization is going toaffect everything For me.
(19:12):
I'm sometimes even imagining afuture where my bank doesn't
just respond to my financialneeds, but also anticipates my
life goals proactively, soadjusting my investments,
suggesting strategic financialmoves and even preparing my
financial, health or lifechanges before I even ask.
So it is a blend of proactiveintelligence and
(19:37):
hyper-personalized touch thathas the potential for me to
transform banking from a passiveservice into my trusted
financial ally, and that's atrend I'm incredibly excited
about.
Jim Jockle (19:52):
Well, enver, if I was on a desert island, I'd have
an agent schedule me a rescueship.
I want to thank you so much foryour insights.
I really appreciated theconversation.
You're on the cutting edge ofthe hype cycle, but that reality
is coming absolutely quick.
So thank you so much for yourtime today.
(20:14):
Thank you, jim for having metoday.
Thank you, Jim, for having me.
Thanks so much for listening totoday's episode and if you're
enjoying Trading Tomorrow,navigating trends and capital
markets, be sure to like,subscribe and share, and we'll
see you next time you.
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