April 24, 2025 • 28 mins
Artificial intelligence has evolved from a cutting-edge concept to a vital force in capital markets—reshaping strategies, streamlining decisions, and making prompt engineering a must-have skill for today’s financial professionals.
In this episode of Trading Tomorrow - Navigating Trends in Capital Markets, we revisit key AI trends and bold predictions from our first two seasons. What did we get right? What surprised us? Tune in as we reflect on AI's rapid rise and its real-world impact on the financial landscape.
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Episode Transcript
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Speaker 1 (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.
Hi, I'm Jim Jockle, host ofTrading Tomorrow navigating
(00:53):
trends in capital markets.
Speaker 2 (00:54):
And I'm Emily Drew, the podcast's producer.
Speaker 1 (01:01):
This is our fourth season of Trading Tomorrow.
Over the years, we've hadfascinating conversations with
people from all over the globewho are leading the way in new
technologies and trends withincapital markets.
Now, for the next few episodes,we'd like to take a step back
pause and really reflect on someof the conversations we've had
over the first and secondseasons of our show, alongside
the current state of thetechnologies we've highlighted
over the years.
Speaker 2 (01:21):
And we figured the best way to kick things off was
with artificial intelligence,one of the most powerful forces
redefining capital markets herein 2025.
What's especially interestingis that we launched this podcast
back in 2023, which is reallyright after ChatGPT burst into
the public consciousness.
In many ways, we've had a frontrow seat to the rapid evolution
(01:42):
of this technology as it'sreshaped the industry and our
lives in turn.
Speaker 1 (01:46):
Well, you know, from high frequency trading to AI
driven risk analysis, machinelearning has moved from being a
competitive edge to an absolutenecessity.
But, to quote Spider-Man, withgreat power comes great
responsibility.
And what happens when AI beginsto make decisions faster than
human traders can?
How do we balance automationwith regulation, and what's next
(02:07):
for AI and finance?
And we'll discuss all of thattoday.
Ai has proven to be a majorfocus over the past few years.
In fact, it was the topic ofour very first episode back in
September 2023.
Speaker 2 (02:26):
Wow, jim, that feels like a lifetime ago, and yet
it's amazing to look back andrealize how foundational that
conversation was.
Speaker 1 (02:33):
It really was, and in the evolution of AI it was a
lifetime ago.
But during that episode weheard from Parag Sharma, global
Head of Artificial Intelligenceat Citi's AI Center of
Excellence, and for me there wasa few major takeaways from that
interview.
Let's roll that tape.
How do you keep up with thespeed of growth, adaptation and
(02:59):
innovation in this space?
Speaker 3 (03:01):
Simply put, we do not keep up with it.
There's too much going on tokeep up with everything, but the
idea here is not to know abouteverything, but to focus on the
aspects of artificialintelligence or generative AI,
which is a subcomponent of that.
To focus on the things thatmatter to you specifically for
your job or the industry thatyou work in, and really spend
(03:23):
some quality time getting underthe hood, understanding what the
technology does, but alsounderstanding the use cases.
So a number of ways to keep upto speed with depending where
you are in your life cycle, inyour career life cycles.
Speaker 1 (03:35):
Well, you know, I, for me, Emily, I think one of
the key things was Parag wasabsolutely right there is
absolutely no way to stay on topof the evolution that's coming
out.
You know, we've always madethat old joke it's, you know,
evolution, not revolution.
But in the world of dealingwith AI, it is a revolution
every major release.
But you know, I think one ofthe fascinating things was you
(03:57):
know, while Parag was runningthis center of excellence, Citi
as a whole at that point in timewas still very restrictive of
the use of AI for all of itsemployees.
And now City, in many ways, isa leader among financial
institutions in terms ofembracing AI across the entirety
of the organization somethingthat felt so niche back then has
(04:26):
become really second nature atthis point.
Speaker 2 (04:28):
I love this moment because it really captures how
quickly we've adopted andintegrated AI into our daily
workflows.
As you said, they weren'tallowing employees at Citi to
use AI in their daily lives, butnow it has just overtaken so so
many things that we do, andit's become so important to
understand how to talk to thesesystems effectively.
Speaker 3 (04:48):
Firstly, we need to all have prompt engineering in
our job description.
The sooner the better.
So anybody listening in, pleasedo a course online and get that
prompt engineering going.
Joking apart, the reasonactually you need prompt
engineering is like I wasexplaining.
You have this room-sized model,quote-unquote, and you're
interacting with it.
The clearer you are in yourinteraction, the better results
(05:11):
you're going to get, and promptengineering is simply that.
How clearly can you articulateyour ask so that you get the
right?
Speaker 1 (05:18):
response.
Well, at this point I think Ishould be able to give up my CMO
title and just put promptengineer.
But I think there's a couplethings that have really evolved.
Number one yes, absolutely,people need to be able to have
an understanding of promptingand how to get the most out of
AI, and there's still so manypeople that still think of it as
(05:40):
just a search engine onsteroids.
But the other thing that Ireally think is fascinating is
the innovation of tools thathave come out since 2023 that
are really, let's call it,persona-based, in the sense of
tailoring AI interactions toutilize multiple large language
models, but really begin totailor to a particular job,
(06:03):
function or role.
I can even say, you know, aspart of the marketing team,
we've utilized certain toolsthat are built for marketers,
fit for purpose.
The AI knows how to interactand get the most out of what
we're trying to accomplish withthe tool.
So, while prompt engineeringstill is something that everyone
(06:25):
and I stress everyone should beembracing, and you don't even
have to take online courses atthis point, there's so much
information out there andYouTube videos and whatnot for
free.
But the way we've seen thatevolution evolve over two and a
half years is to make AI evenmore approachable where that
(06:46):
skill isn't necessary.
But I urge, if you're going toget the most out of these tools,
prompt engineer is somethingyou need to be.
Speaker 2 (06:52):
And it's so interesting because I you know,
back when we first had thisconversation with Prague, I
think that prompt engineeringwas something we all were
nervous about.
It seemed really scary.
You felt like you had to takeclasses, like you were saying
Jim.
But now you know, my mom knowshow to talk to ChatGPT.
She looks it up on YouTube andon TikTok and both her and my
(07:13):
dad are comfortable usingChatGPT and I think it shows how
adaptable it's become, thatreally everyone is able to use
it now, and I remember at thetime, prompt engineering it felt
kind of like a new language,but now again it's practically a
core skill set, whether you'rein research, compliance, trading
and knowing how to frame yourquestion and get actionable
(07:34):
insights.
It's critical and we've seen howa slightly better prompt can
drastically improve the outputyou get from a model.
I mean, I personally have seenit and I've found my footing in
that model.
I mean I personally have seenit and I've found my footing in
that too.
I mean it's a lot of trial anda lot of error, but at this
point I think it's crucial.
You need to be trying, you needto be failing, you need to be
looking these things up and youneed to get comfortable because
(07:56):
AI is not going anywhere.
Speaker 1 (07:58):
You know, Emily, we only spoke about AI three other
times during season one.
Speaker 2 (08:02):
That's surprising because I felt like it was
everywhere, even outside of work.
I think it just speaks to howquickly the conversation was
accelerating behind the scenes.
Speaker 1 (08:09):
It really did, but we did speak about it again fairly
early in the series during ourepisode with Neil Chennai,
operating partner at SandhillEast.
He covered four tech trends youneed to be tracking and AI was
one of them, and I think he evenpicked AI for his trend drop.
We now made it to the finalquestion in this podcast and we
(08:29):
call it the trend drop.
It's like a desert islandquestion.
So if you could only track onefuture technology within capital
markets over the next few years, what would it be and why?
Speaker 4 (08:40):
Well, I kind of think it's a combination of the
advanced cloud computing beingthe cloud and generative AI and
how that's going to change howpeople do their job, and a lot
of it's to help driveproductivity.
Research I mean, if you lookacross the whole research in the
(09:14):
medicine field, in the pharmafield, it just seems like that
over the next three years let'spick that number that generative
AI is going to provide really,really great advances in
research.
Speaker 1 (09:29):
I don't know if I would go as far to say, as
Neil's comments were soprescient, but definitely had
his finger on the pulse of wherethe market was going and I
think even when we had thatconversation it was still early
days.
My own personal exploration wasfairly low, but now the things
(09:50):
you're hearing in medicine andlogistics, supply chain and
finance as we talk about all thetime, I mean it's staggering
the advancements that have beenmade in just three short years.
Speaker 2 (10:03):
I think even just in the later episodes of this
podcast that are going to becoming out, we've heard some
things that AI, especiallyangenic AI, is able to do.
That is again, like you said,Jim staggering.
I mean just stuff we couldn'thave even dreamed of back when
we were recording these veryfirst episodes, back in 2023.
(10:25):
And what I appreciated aboutthat conversation is how Neil
framed AI not just as a trend,but as a shift in how people
work.
You know, it wasn't aboutreplacing people, it was about
expanding human capability, andI think he made a great point
about how AI would accelerateproductivity across industries
like medicine and research, likeyou mentioned, which we're
absolutely seeing now, and Imean for me, in communications,
(10:46):
my output has almost doubled,While I still, you know, need to
read through and approveeverything that goes out those
rough first drafts, they can behandled by AI, which cuts my
production time.
Speaker 1 (10:55):
Which makes me happy, exactly so.
We've also had anotherconversation on AI and ML and on
investing with Chauvin Jane ofOkon, but we're going to hold on
to that because she's joiningus again and it's going to be
exciting to speak with her againon a one-on-one basis, but also
(11:16):
just for her perspectives onhow things have changed.
Speaker 2 (11:19):
So that brings us to our conversation with Broadridge
.
Speaker 1 (11:22):
Yes, and so, as you may recall, they sent out a
digital transformation study in2023.
Although digital transformationdoes seem slightly overused,
that's what it was called, butthey really took a hard look
into the cutting-edgetechnologies captivating the
finance industry's investmentsand attention, and you might
remember, one of their findingswas that 71% of their
(11:43):
respondents said AI is changingthe way they work, and here's
what they had to say about it.
And here's what they had to sayabout it.
If you had a crystal ball, howdo you think this number has
either grown or shrunk sincethat?
Speaker 5 (12:01):
I would say it's probably increased.
I think I'd feel prettyconfident saying that it's
increased.
You know to your point.
You're using it every day.
I'm not yet.
I work in a strategy type role,so could I see it potentially
replacing the creation ofstrategic plans and things down
the road?
Yeah, so maybe I'm justavoiding accepting future?
(12:21):
I don't know.
Speaker 2 (12:22):
It's interesting because, again, we really were
at the forefront of Gen AI whenwe started this podcast, and
episodes like this remind me ofthat.
I mean, broadridge's morerecent 2024 study showed that
firms plan to increase AIinvestments by 21%, which is the
highest across all categories,even beyond blockchain and
robotic process automation.
The previous year's study hadcloud and cybersecurity beating.
(12:45):
Ai, and robotic processautomation was tied.
I think it really shows growth.
Companies have seen theimportance of AI and they're
adjusting accordingly, andBroadridge also developed their
own internal AI tool, built onlarge language models, which
they rolled out to employees.
They casually mentioned it inour interview and it's great to
see that it's taken offinternally.
I mean, it really shows howcompanies are not just exploring
(13:08):
AI, they're embedding it.
Speaker 1 (13:09):
Well, I would even say in conversations with
friends and individuals on thestreet.
You know, even those who havebeen laggards are now in the
throes of adoption.
And you know, I recently read aMcKinsey study that I thought
was fascinating, whereby it wassaying AI adoption is really
driven by middle managers andindividual contributors, and
(13:34):
it's actually been executivemanagement that has been a
laggard right.
If you go back to 2023, when wewere having this conversation,
it was something along the linesof 80% 90% of all AI and
machine learning projects failwhich was curtailing
management's investment intothese projects.
(13:54):
But now what we're seeing isthis overarching trend where
people want to use these toolsthey're differentiators for them
in the ways they work which isnow creating this nexus where
management is saying, hmm, Iunderstand, we're getting these
productivity claims internally.
I have external forces, whetherit be investors, whether, you
(14:19):
know, depending on what yourownership is private equity
stockholders.
They want to know what your AIinitiatives are as companies.
So you're seeing these twothings kind of come together at
this point where, iforganizations are not embracing
these tools, you're going tohave unhappy employees.
Right, they want the benefits,they want to explore, they want
(14:41):
to utilize these contributionsdifferent place.
I think Broadridge, in terms ofexploring the way they used AI
internally and embedding it intotheir own ways of working and
processes and in their products,is kind of a way forward that
(15:01):
many companies are at today.
Speaker 2 (15:03):
And I think you hit the nail on the head there, jim.
When we started tradingtomorrow, back in 2023, ai was
something that it was a buzzword, it was exciting, it was in all
the news, it was fun, it wasinteresting, but it wasn't
tangible yet.
And now, in just two shortyears and really a little less
than that, because this wasfilmed near the end of 2023,
(15:26):
it's now embedded, it'simportant, it's crucial and it's
a part of pretty much everysingle company in some way or
another, and AI continued to bea hot topic throughout season
two, which took place in thebeginning of 2024, which was
right after season one.
Speaker 1 (15:40):
Well, at that point we really dove deeper into AI
and we were remiss if we didn't.
You know not that otheremerging technologies are not as
exciting, but AI has beenobviously the most captivating.
You know, so many of thoseconversations explored why AI
rose in popularity so rapidlyand how significant that impact
(16:01):
has already been.
From Kevin McPartland ofCoalition Greenwich to Adam
Hyland, a PhD student at theUniversity of Washington, we got
some incredibly richperspectives.
Let's roll that tape.
Speaker 6 (16:16):
But if we were to compare right now the impact,
the potential impact, say, inthe next five years, of
blockchain, when it sort offirst came on the scene, versus
the conversation about AI now,I'm a lot more excited about AI,
and part of that, perhaps, isbecause you can see it and feel
it.
Once there was a consumerapplication that allowed you to
(16:38):
do these incredible things andhave a machine answer you and
give you results, write code foryou, write press releases for
you, whatever that really, Ithink, opened a lot of people's
eyes as to what this could do.
Now, ai obviously isn't new.
I think I took an intro toartificial intelligence class in
college in the 90s, which Idon't remember any of.
(16:59):
But, all kidding aside, theimmediate impacts feel much more
gigantic.
Speaker 7 (17:09):
Yeah, the adoption and, like you said, I think
integration is a reallyimportant.
Distinguishing feature of howmuch this sort of blew up on the
scene is that not only werepeople adopting it, but people
were linking it into otherprocesses, like connecting the
chat GPT to a text-to-speechgenerator or or the reverse
(17:33):
right, connecting it to to voiceto text and then sending that
to chat GPT.
Like all of these multimodalcomponents coming together is
something that we have not seenat this speed before, just ever.
Speaker 1 (17:44):
I think it's fascinating now in terms of
Adam's thoughts on multimodalToday.
That is the advancement wherewe're seeing some of the most
gains, whether it beincorporating video speech in
(18:04):
addition to text photos, if youhaven't tried this, and now if
you have Apple Intelligence,it's integrated with Siri.
Open up the refrigerator, takea picture and ask ChatGPT three
things that you should make fordinner.
It's absolutely fascinating.
So I think it's getting to thepoint where multimodal is
(18:25):
commonplace and it's reallychanging the way we're
interacting with AI tools, whichis really really became
changeable and just going off ofyour refrigerator comment.
Speaker 2 (18:49):
I recently wanted to redecorate my apartment.
I took a photo in an AI app andI was able to say what needs to
go where, what do we need tobuy, and tell me the background
behind why I need to do this.
So give me a reason, Give me adecorator who's talked about
this and it was able to do that,which is incredible and really
it's just.
These systems are evolving sofast and I think it's something
(19:11):
that we've seen in real life toorecently through the
development of advancedmultimodal AI systems like Alib.
It's compact design.
It can potentially run onsmartphones, which enhances
device capabilities and userinteractions.
(19:32):
And one of my favoriteconversations from season two
was with FinPilot CEO LakshayShuan.
Described as chat GPT forfinancial questions, FinPilot
was using AI to extract insightsfrom unstructured financial
data and at the time that feltso groundbreaking, but now we're
seeing even more companiestrying to build tools just like
that.
Speaker 1 (19:52):
And this kind of brings us back to that prompt
engineering statement.
I think one of the things thatwas really interesting when we
saw what Finpilot was doing wasa lot of the prompting behind
the scenes.
So it allowed the end users toreally interface without being a
prompt engineer to be able tojust ask a simple question.
(20:13):
But behind the scenes thesevery, very elegant prompts were
being designed because it hadthe context of that persona, I
think.
One question I would like to goback to see how FinPilot is
(20:37):
doing, because, as these LMMsare getting stronger and
stronger, they have a lot ofthese capabilities.
Am it's learning from myinteractions?
Even though I'm not trainingmodels, because you know I don't
want my stuff out there in theworld, you know I can give it
the personas that I want andwant to interact with.
(20:58):
So I think we've had some earlyadopters that could have
challenges as general purposetools get even stronger as
general purpose tools.
Speaker 2 (21:07):
Get even stronger.
Have you done that challengeyet that people are suggesting
you do on social media, whereyou go and you ask ChatGPT what
it knows about you?
Speaker 1 (21:15):
I have and it's the whole kind of FBI, cia kind of
thing.
It is a little scary but youknow, for those who are just
passive ChatGPT enthusiasts,some of the Reddit groups are
fantastic, and you know they,those who are just passive chat
GPT enthusiasts some of theReddit groups are fantastic, and
you know they come up with thecraziest things.
Speaker 2 (21:31):
And speaking of what chat GPT does and doesn't know,
perhaps one of the mostimportant conversations we had
during season two was withProfessor Michael Wellman of the
University of Michigan.
Speaker 1 (21:42):
Yeah, the regulatory conversation.
That was an important one.
Let's roll the tape on that.
Speaker 8 (21:50):
But there's also a potential for new AI loopholes.
The current laws and mostregulations are built under the
assumption that it's humanbeings making the decisions, and
when it's computers making thedecisions, it could be that
there's something about the waythe regulations are written that
lets them get around it.
(22:10):
And one example is in the areaof market manipulation, where a
lot of the existing rulespromulgated by the SEC and
through Dodd-Frank in the UnitedStates rely on determining the
intent of a trader when they putin orders to the system.
(22:31):
Are they intended to reallytrade or are they just there to
mislead?
Well, there could be somequestion about how you judge
intent when it comes to acomputer program, and, in
particular, if your computerprogram was generated by machine
learning, or that is, if yourtrading strategy was generated
by computer, through machinelearning.
That might seem to provide onesome kind of deniability as to
(22:53):
intent.
Now, that's a loophole, I think, and actually one of the pieces
of legislation that SenatorWarner and colleagues just filed
, the Financial AI RiskReduction Act, does attempt to
close that particular loophole.
Speaker 1 (23:08):
Basically you're suggesting the AI independently
can learn potentially tomanipulate markets on its own.
Speaker 8 (23:17):
That's right.
We've actually demonstratedthat in our own research and I
wouldn't say it's a hugesurprise.
But we basically set up asystem where we told a trader
that we wanted to maximize itsown profits and made a certain
environment where they had aninterest in a benchmark in some
(23:38):
derivatives.
That depended on some pricingbenchmark and it learned to
manipulate the primary market tomove the benchmark such that
they made additional profit onthe benchmark, even though we
didn't tell it to do thatspecifically.
It basically learned tosacrifice profit in the primary
market in order to make more onthe derivatives and that would
(24:00):
be considered a kind ofmanipulation that was not
directly programmed into thesystem but was rather learned
automatically.
Speaker 1 (24:23):
You know, obviously, regulation is going to be a
guiding principle and this isreally a white space because a
lot of regulators don't evenknow what they're dealingils are
.
And having reward systemswithin these LMMs to ensure that
ethics, and having guardrailsinside of these LMMs that are
(24:48):
very transparent to ensure thatthe activities and outputs are
ethical, I think is thefoundational statement.
I mean, I'm sure if you listento other podcasts there's plenty
of commentary that AI is goingto rule the world and we're you
know, years away from Terminator4, or it might be closer than
(25:10):
we like to think, but you know,clearly the regulatory
environment is something that weall have to watch, especially
now that we're in a newadministration.
Obviously, ai is on theforefront.
You know, obviously, anotherthere's been push to bring
manufacturing and power backinto the United States.
(25:30):
There's been push to bringmanufacturing and power back
into the United States not to gointo all the tariffs and the
politics of it, but AI isplaying hands across the global
community.
Speaker 2 (25:42):
Yeah, that clip still gives me the chills.
I mean, it was really the firsttime I truly could start to
comprehend how AI could learnmarket manipulation, and not
because it was told to, butbecause the incentive structure
allowed it to.
I mean, it's a good reminder ofwhy thoughtful regulation and
ethical design are so criticalin this space, and it's a scary
(26:03):
reminder that it's somethingthat we really need to continue
to push and look into, because Ithink one of the few places
we've seen a lot of evolution inthe past two years since we
started filming this show is inregulation, which is considering
the conversations we've hadover the past half hour about
(26:25):
how much chat, gpt and AI andhow these things have all
changed so much in the past twoyears, I feel like regulation
hasn't, and so I really thinkthat that's somewhere we need to
look moving into 2025.
Speaker 1 (26:39):
Yeah, and especially as we look ahead to this next
season and some of theconversations we've already had,
agentic AI is now on theforefront and if you think of,
it's disturbing that marketmanipulations could happen and
whatnot what happens when youlet the AI work autonomously.
(26:59):
So that's something we're goingto dive into this season
because that is the rage of theyear.
Speaker 2 (27:08):
Agentic AI is one of the most fascinating things
we've spoken about during thisseason.
I can't wait until people getto listen to those episodes.
I mean, it is absolutely whereall the new innovation is going
to be happening, and I thinkpeople don't really understand
that it's happening yet.
So even I thought this was aconversation that we're looking
(27:32):
at technology five, six, sevenyears out, but you know, we're
looking at technology that'shappening right now.
Speaker 1 (27:38):
Well, emily.
Thank you, it's been a fun rideso far.
I can't wait to have more greatconversations and, as we move
forward in season four, pleasemake sure you continue to tune
into the show as we explore AIand other trends and
technologies that are changingand shaping the capital markets.
Speaker 2 (27:56):
Thank you, Jim.
Speaker 1 (28:04):
Thanks so much for listening to today's episode and
if you're enjoying TradingTomorrow, navigating trends and
capital markets, be sure to like, subscribe and share, and we'll
see you next time.
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.
Hi, I'm Jim Jockle, host ofTrading Tomorrow navigating
(00:53):
trends in capital markets.
Speaker 2 (00:54):
And I'm Emily Drew, the podcast's producer.
Speaker 1 (01:01):
This is our fourth season of Trading Tomorrow.
Over the years, we've hadfascinating conversations with
people from all over the globewho are leading the way in new
technologies and trends withincapital markets.
Now, for the next few episodes,we'd like to take a step back
pause and really reflect on someof the conversations we've had
over the first and secondseasons of our show, alongside
the current state of thetechnologies we've highlighted
over the years.
Speaker 2 (01:21):
And we figured the best way to kick things off was
with artificial intelligence,one of the most powerful forces
redefining capital markets herein 2025.
What's especially interestingis that we launched this podcast
back in 2023, which is reallyright after ChatGPT burst into
the public consciousness.
In many ways, we've had a frontrow seat to the rapid evolution
(01:42):
of this technology as it'sreshaped the industry and our
lives in turn.
Speaker 1 (01:46):
Well, you know, from high frequency trading to AI
driven risk analysis, machinelearning has moved from being a
competitive edge to an absolutenecessity.
But, to quote Spider-Man, withgreat power comes great
responsibility.
And what happens when AI beginsto make decisions faster than
human traders can?
How do we balance automationwith regulation, and what's next
(02:07):
for AI and finance?
And we'll discuss all of thattoday.
Ai has proven to be a majorfocus over the past few years.
In fact, it was the topic ofour very first episode back in
September 2023.
Speaker 2 (02:26):
Wow, jim, that feels like a lifetime ago, and yet
it's amazing to look back andrealize how foundational that
conversation was.
Speaker 1 (02:33):
It really was, and in the evolution of AI it was a
lifetime ago.
But during that episode weheard from Parag Sharma, global
Head of Artificial Intelligenceat Citi's AI Center of
Excellence, and for me there wasa few major takeaways from that
interview.
Let's roll that tape.
How do you keep up with thespeed of growth, adaptation and
(02:59):
innovation in this space?
Speaker 3 (03:01):
Simply put, we do not keep up with it.
There's too much going on tokeep up with everything, but the
idea here is not to know abouteverything, but to focus on the
aspects of artificialintelligence or generative AI,
which is a subcomponent of that.
To focus on the things thatmatter to you specifically for
your job or the industry thatyou work in, and really spend
(03:23):
some quality time getting underthe hood, understanding what the
technology does, but alsounderstanding the use cases.
So a number of ways to keep upto speed with depending where
you are in your life cycle, inyour career life cycles.
Speaker 1 (03:35):
Well, you know, I, for me, Emily, I think one of
the key things was Parag wasabsolutely right there is
absolutely no way to stay on topof the evolution that's coming
out.
You know, we've always madethat old joke it's, you know,
evolution, not revolution.
But in the world of dealingwith AI, it is a revolution
every major release.
But you know, I think one ofthe fascinating things was you
(03:57):
know, while Parag was runningthis center of excellence, Citi
as a whole at that point in timewas still very restrictive of
the use of AI for all of itsemployees.
And now City, in many ways, isa leader among financial
institutions in terms ofembracing AI across the entirety
of the organization somethingthat felt so niche back then has
(04:26):
become really second nature atthis point.
Speaker 2 (04:28):
I love this moment because it really captures how
quickly we've adopted andintegrated AI into our daily
workflows.
As you said, they weren'tallowing employees at Citi to
use AI in their daily lives, butnow it has just overtaken so so
many things that we do, andit's become so important to
understand how to talk to thesesystems effectively.
Speaker 3 (04:48):
Firstly, we need to all have prompt engineering in
our job description.
The sooner the better.
So anybody listening in, pleasedo a course online and get that
prompt engineering going.
Joking apart, the reasonactually you need prompt
engineering is like I wasexplaining.
You have this room-sized model,quote-unquote, and you're
interacting with it.
The clearer you are in yourinteraction, the better results
(05:11):
you're going to get, and promptengineering is simply that.
How clearly can you articulateyour ask so that you get the
right?
Speaker 1 (05:18):
response.
Well, at this point I think Ishould be able to give up my CMO
title and just put promptengineer.
But I think there's a couplethings that have really evolved.
Number one yes, absolutely,people need to be able to have
an understanding of promptingand how to get the most out of
AI, and there's still so manypeople that still think of it as
(05:40):
just a search engine onsteroids.
But the other thing that Ireally think is fascinating is
the innovation of tools thathave come out since 2023 that
are really, let's call it,persona-based, in the sense of
tailoring AI interactions toutilize multiple large language
models, but really begin totailor to a particular job,
(06:03):
function or role.
I can even say, you know, aspart of the marketing team,
we've utilized certain toolsthat are built for marketers,
fit for purpose.
The AI knows how to interactand get the most out of what
we're trying to accomplish withthe tool.
So, while prompt engineeringstill is something that everyone
(06:25):
and I stress everyone should beembracing, and you don't even
have to take online courses atthis point, there's so much
information out there andYouTube videos and whatnot for
free.
But the way we've seen thatevolution evolve over two and a
half years is to make AI evenmore approachable where that
(06:46):
skill isn't necessary.
But I urge, if you're going toget the most out of these tools,
prompt engineer is somethingyou need to be.
Speaker 2 (06:52):
And it's so interesting because I you know,
back when we first had thisconversation with Prague, I
think that prompt engineeringwas something we all were
nervous about.
It seemed really scary.
You felt like you had to takeclasses, like you were saying
Jim.
But now you know, my mom knowshow to talk to ChatGPT.
She looks it up on YouTube andon TikTok and both her and my
(07:13):
dad are comfortable usingChatGPT and I think it shows how
adaptable it's become, thatreally everyone is able to use
it now, and I remember at thetime, prompt engineering it felt
kind of like a new language,but now again it's practically a
core skill set, whether you'rein research, compliance, trading
and knowing how to frame yourquestion and get actionable
(07:34):
insights.
It's critical and we've seen howa slightly better prompt can
drastically improve the outputyou get from a model.
I mean, I personally have seenit and I've found my footing in
that model.
I mean I personally have seenit and I've found my footing in
that too.
I mean it's a lot of trial anda lot of error, but at this
point I think it's crucial.
You need to be trying, you needto be failing, you need to be
looking these things up and youneed to get comfortable because
(07:56):
AI is not going anywhere.
Speaker 1 (07:58):
You know, Emily, we only spoke about AI three other
times during season one.
Speaker 2 (08:02):
That's surprising because I felt like it was
everywhere, even outside of work.
I think it just speaks to howquickly the conversation was
accelerating behind the scenes.
Speaker 1 (08:09):
It really did, but we did speak about it again fairly
early in the series during ourepisode with Neil Chennai,
operating partner at SandhillEast.
He covered four tech trends youneed to be tracking and AI was
one of them, and I think he evenpicked AI for his trend drop.
We now made it to the finalquestion in this podcast and we
(08:29):
call it the trend drop.
It's like a desert islandquestion.
So if you could only track onefuture technology within capital
markets over the next few years, what would it be and why?
Speaker 4 (08:40):
Well, I kind of think it's a combination of the
advanced cloud computing beingthe cloud and generative AI and
how that's going to change howpeople do their job, and a lot
of it's to help driveproductivity.
Research I mean, if you lookacross the whole research in the
(09:14):
medicine field, in the pharmafield, it just seems like that
over the next three years let'spick that number that generative
AI is going to provide really,really great advances in
research.
Speaker 1 (09:29):
I don't know if I would go as far to say, as
Neil's comments were soprescient, but definitely had
his finger on the pulse of wherethe market was going and I
think even when we had thatconversation it was still early
days.
My own personal exploration wasfairly low, but now the things
(09:50):
you're hearing in medicine andlogistics, supply chain and
finance as we talk about all thetime, I mean it's staggering
the advancements that have beenmade in just three short years.
Speaker 2 (10:03):
I think even just in the later episodes of this
podcast that are going to becoming out, we've heard some
things that AI, especiallyangenic AI, is able to do.
That is again, like you said,Jim staggering.
I mean just stuff we couldn'thave even dreamed of back when
we were recording these veryfirst episodes, back in 2023.
(10:25):
And what I appreciated aboutthat conversation is how Neil
framed AI not just as a trend,but as a shift in how people
work.
You know, it wasn't aboutreplacing people, it was about
expanding human capability, andI think he made a great point
about how AI would accelerateproductivity across industries
like medicine and research, likeyou mentioned, which we're
absolutely seeing now, and Imean for me, in communications,
(10:46):
my output has almost doubled,While I still, you know, need to
read through and approveeverything that goes out those
rough first drafts, they can behandled by AI, which cuts my
production time.
Speaker 1 (10:55):
Which makes me happy, exactly so.
We've also had anotherconversation on AI and ML and on
investing with Chauvin Jane ofOkon, but we're going to hold on
to that because she's joiningus again and it's going to be
exciting to speak with her againon a one-on-one basis, but also
(11:16):
just for her perspectives onhow things have changed.
Speaker 2 (11:19):
So that brings us to our conversation with Broadridge
.
Speaker 1 (11:22):
Yes, and so, as you may recall, they sent out a
digital transformation study in2023.
Although digital transformationdoes seem slightly overused,
that's what it was called, butthey really took a hard look
into the cutting-edgetechnologies captivating the
finance industry's investmentsand attention, and you might
remember, one of their findingswas that 71% of their
(11:43):
respondents said AI is changingthe way they work, and here's
what they had to say about it.
And here's what they had to sayabout it.
If you had a crystal ball, howdo you think this number has
either grown or shrunk sincethat?
Speaker 5 (12:01):
I would say it's probably increased.
I think I'd feel prettyconfident saying that it's
increased.
You know to your point.
You're using it every day.
I'm not yet.
I work in a strategy type role,so could I see it potentially
replacing the creation ofstrategic plans and things down
the road?
Yeah, so maybe I'm justavoiding accepting future?
(12:21):
I don't know.
Speaker 2 (12:22):
It's interesting because, again, we really were
at the forefront of Gen AI whenwe started this podcast, and
episodes like this remind me ofthat.
I mean, broadridge's morerecent 2024 study showed that
firms plan to increase AIinvestments by 21%, which is the
highest across all categories,even beyond blockchain and
robotic process automation.
The previous year's study hadcloud and cybersecurity beating.
(12:45):
Ai, and robotic processautomation was tied.
I think it really shows growth.
Companies have seen theimportance of AI and they're
adjusting accordingly, andBroadridge also developed their
own internal AI tool, built onlarge language models, which
they rolled out to employees.
They casually mentioned it inour interview and it's great to
see that it's taken offinternally.
I mean, it really shows howcompanies are not just exploring
(13:08):
AI, they're embedding it.
Speaker 1 (13:09):
Well, I would even say in conversations with
friends and individuals on thestreet.
You know, even those who havebeen laggards are now in the
throes of adoption.
And you know, I recently read aMcKinsey study that I thought
was fascinating, whereby it wassaying AI adoption is really
driven by middle managers andindividual contributors, and
(13:34):
it's actually been executivemanagement that has been a
laggard right.
If you go back to 2023, when wewere having this conversation,
it was something along the linesof 80% 90% of all AI and
machine learning projects failwhich was curtailing
management's investment intothese projects.
(13:54):
But now what we're seeing isthis overarching trend where
people want to use these toolsthey're differentiators for them
in the ways they work which isnow creating this nexus where
management is saying, hmm, Iunderstand, we're getting these
productivity claims internally.
I have external forces, whetherit be investors, whether, you
(14:19):
know, depending on what yourownership is private equity
stockholders.
They want to know what your AIinitiatives are as companies.
So you're seeing these twothings kind of come together at
this point where, iforganizations are not embracing
these tools, you're going tohave unhappy employees.
Right, they want the benefits,they want to explore, they want
(14:41):
to utilize these contributionsdifferent place.
I think Broadridge, in terms ofexploring the way they used AI
internally and embedding it intotheir own ways of working and
processes and in their products,is kind of a way forward that
(15:01):
many companies are at today.
Speaker 2 (15:03):
And I think you hit the nail on the head there, jim.
When we started tradingtomorrow, back in 2023, ai was
something that it was a buzzword, it was exciting, it was in all
the news, it was fun, it wasinteresting, but it wasn't
tangible yet.
And now, in just two shortyears and really a little less
than that, because this wasfilmed near the end of 2023,
(15:26):
it's now embedded, it'simportant, it's crucial and it's
a part of pretty much everysingle company in some way or
another, and AI continued to bea hot topic throughout season
two, which took place in thebeginning of 2024, which was
right after season one.
Speaker 1 (15:40):
Well, at that point we really dove deeper into AI
and we were remiss if we didn't.
You know not that otheremerging technologies are not as
exciting, but AI has beenobviously the most captivating.
You know, so many of thoseconversations explored why AI
rose in popularity so rapidlyand how significant that impact
(16:01):
has already been.
From Kevin McPartland ofCoalition Greenwich to Adam
Hyland, a PhD student at theUniversity of Washington, we got
some incredibly richperspectives.
Let's roll that tape.
Speaker 6 (16:16):
But if we were to compare right now the impact,
the potential impact, say, inthe next five years, of
blockchain, when it sort offirst came on the scene, versus
the conversation about AI now,I'm a lot more excited about AI,
and part of that, perhaps, isbecause you can see it and feel
it.
Once there was a consumerapplication that allowed you to
(16:38):
do these incredible things andhave a machine answer you and
give you results, write code foryou, write press releases for
you, whatever that really, Ithink, opened a lot of people's
eyes as to what this could do.
Now, ai obviously isn't new.
I think I took an intro toartificial intelligence class in
college in the 90s, which Idon't remember any of.
(16:59):
But, all kidding aside, theimmediate impacts feel much more
gigantic.
Speaker 7 (17:09):
Yeah, the adoption and, like you said, I think
integration is a reallyimportant.
Distinguishing feature of howmuch this sort of blew up on the
scene is that not only werepeople adopting it, but people
were linking it into otherprocesses, like connecting the
chat GPT to a text-to-speechgenerator or or the reverse
(17:33):
right, connecting it to to voiceto text and then sending that
to chat GPT.
Like all of these multimodalcomponents coming together is
something that we have not seenat this speed before, just ever.
Speaker 1 (17:44):
I think it's fascinating now in terms of
Adam's thoughts on multimodalToday.
That is the advancement wherewe're seeing some of the most
gains, whether it beincorporating video speech in
(18:04):
addition to text photos, if youhaven't tried this, and now if
you have Apple Intelligence,it's integrated with Siri.
Open up the refrigerator, takea picture and ask ChatGPT three
things that you should make fordinner.
It's absolutely fascinating.
So I think it's getting to thepoint where multimodal is
(18:25):
commonplace and it's reallychanging the way we're
interacting with AI tools, whichis really really became
changeable and just going off ofyour refrigerator comment.
Speaker 2 (18:49):
I recently wanted to redecorate my apartment.
I took a photo in an AI app andI was able to say what needs to
go where, what do we need tobuy, and tell me the background
behind why I need to do this.
So give me a reason, Give me adecorator who's talked about
this and it was able to do that,which is incredible and really
it's just.
These systems are evolving sofast and I think it's something
(19:11):
that we've seen in real life toorecently through the
development of advancedmultimodal AI systems like Alib.
It's compact design.
It can potentially run onsmartphones, which enhances
device capabilities and userinteractions.
(19:32):
And one of my favoriteconversations from season two
was with FinPilot CEO LakshayShuan.
Described as chat GPT forfinancial questions, FinPilot
was using AI to extract insightsfrom unstructured financial
data and at the time that feltso groundbreaking, but now we're
seeing even more companiestrying to build tools just like
that.
Speaker 1 (19:52):
And this kind of brings us back to that prompt
engineering statement.
I think one of the things thatwas really interesting when we
saw what Finpilot was doing wasa lot of the prompting behind
the scenes.
So it allowed the end users toreally interface without being a
prompt engineer to be able tojust ask a simple question.
(20:13):
But behind the scenes thesevery, very elegant prompts were
being designed because it hadthe context of that persona, I
think.
One question I would like to goback to see how FinPilot is
(20:37):
doing, because, as these LMMsare getting stronger and
stronger, they have a lot ofthese capabilities.
Am it's learning from myinteractions?
Even though I'm not trainingmodels, because you know I don't
want my stuff out there in theworld, you know I can give it
the personas that I want andwant to interact with.
(20:58):
So I think we've had some earlyadopters that could have
challenges as general purposetools get even stronger as
general purpose tools.
Speaker 2 (21:07):
Get even stronger.
Have you done that challengeyet that people are suggesting
you do on social media, whereyou go and you ask ChatGPT what
it knows about you?
Speaker 1 (21:15):
I have and it's the whole kind of FBI, cia kind of
thing.
It is a little scary but youknow, for those who are just
passive ChatGPT enthusiasts,some of the Reddit groups are
fantastic, and you know they,those who are just passive chat
GPT enthusiasts some of theReddit groups are fantastic, and
you know they come up with thecraziest things.
Speaker 2 (21:31):
And speaking of what chat GPT does and doesn't know,
perhaps one of the mostimportant conversations we had
during season two was withProfessor Michael Wellman of the
University of Michigan.
Speaker 1 (21:42):
Yeah, the regulatory conversation.
That was an important one.
Let's roll the tape on that.
Speaker 8 (21:50):
But there's also a potential for new AI loopholes.
The current laws and mostregulations are built under the
assumption that it's humanbeings making the decisions, and
when it's computers making thedecisions, it could be that
there's something about the waythe regulations are written that
lets them get around it.
(22:10):
And one example is in the areaof market manipulation, where a
lot of the existing rulespromulgated by the SEC and
through Dodd-Frank in the UnitedStates rely on determining the
intent of a trader when they putin orders to the system.
(22:31):
Are they intended to reallytrade or are they just there to
mislead?
Well, there could be somequestion about how you judge
intent when it comes to acomputer program, and, in
particular, if your computerprogram was generated by machine
learning, or that is, if yourtrading strategy was generated
by computer, through machinelearning.
That might seem to provide onesome kind of deniability as to
(22:53):
intent.
Now, that's a loophole, I think, and actually one of the pieces
of legislation that SenatorWarner and colleagues just filed
, the Financial AI RiskReduction Act, does attempt to
close that particular loophole.
Speaker 1 (23:08):
Basically you're suggesting the AI independently
can learn potentially tomanipulate markets on its own.
Speaker 8 (23:17):
That's right.
We've actually demonstratedthat in our own research and I
wouldn't say it's a hugesurprise.
But we basically set up asystem where we told a trader
that we wanted to maximize itsown profits and made a certain
environment where they had aninterest in a benchmark in some
(23:38):
derivatives.
That depended on some pricingbenchmark and it learned to
manipulate the primary market tomove the benchmark such that
they made additional profit onthe benchmark, even though we
didn't tell it to do thatspecifically.
It basically learned tosacrifice profit in the primary
market in order to make more onthe derivatives and that would
(24:00):
be considered a kind ofmanipulation that was not
directly programmed into thesystem but was rather learned
automatically.
Speaker 1 (24:23):
You know, obviously, regulation is going to be a
guiding principle and this isreally a white space because a
lot of regulators don't evenknow what they're dealingils are
.
And having reward systemswithin these LMMs to ensure that
ethics, and having guardrailsinside of these LMMs that are
(24:48):
very transparent to ensure thatthe activities and outputs are
ethical, I think is thefoundational statement.
I mean, I'm sure if you listento other podcasts there's plenty
of commentary that AI is goingto rule the world and we're you
know, years away from Terminator4, or it might be closer than
(25:10):
we like to think, but you know,clearly the regulatory
environment is something that weall have to watch, especially
now that we're in a newadministration.
Obviously, ai is on theforefront.
You know, obviously, anotherthere's been push to bring
manufacturing and power backinto the United States.
(25:30):
There's been push to bringmanufacturing and power back
into the United States not to gointo all the tariffs and the
politics of it, but AI isplaying hands across the global
community.
Speaker 2 (25:42):
Yeah, that clip still gives me the chills.
I mean, it was really the firsttime I truly could start to
comprehend how AI could learnmarket manipulation, and not
because it was told to, butbecause the incentive structure
allowed it to.
I mean, it's a good reminder ofwhy thoughtful regulation and
ethical design are so criticalin this space, and it's a scary
(26:03):
reminder that it's somethingthat we really need to continue
to push and look into, because Ithink one of the few places
we've seen a lot of evolution inthe past two years since we
started filming this show is inregulation, which is considering
the conversations we've hadover the past half hour about
(26:25):
how much chat, gpt and AI andhow these things have all
changed so much in the past twoyears, I feel like regulation
hasn't, and so I really thinkthat that's somewhere we need to
look moving into 2025.
Speaker 1 (26:39):
Yeah, and especially as we look ahead to this next
season and some of theconversations we've already had,
agentic AI is now on theforefront and if you think of,
it's disturbing that marketmanipulations could happen and
whatnot what happens when youlet the AI work autonomously.
(26:59):
So that's something we're goingto dive into this season
because that is the rage of theyear.
Speaker 2 (27:08):
Agentic AI is one of the most fascinating things
we've spoken about during thisseason.
I can't wait until people getto listen to those episodes.
I mean, it is absolutely whereall the new innovation is going
to be happening, and I thinkpeople don't really understand
that it's happening yet.
So even I thought this was aconversation that we're looking
(27:32):
at technology five, six, sevenyears out, but you know, we're
looking at technology that'shappening right now.
Speaker 1 (27:38):
Well, emily.
Thank you, it's been a fun rideso far.
I can't wait to have more greatconversations and, as we move
forward in season four, pleasemake sure you continue to tune
into the show as we explore AIand other trends and
technologies that are changingand shaping the capital markets.
Speaker 2 (27:56):
Thank you, Jim.
Speaker 1 (28:04):
Thanks so much for listening to today's episode and
if you're enjoying TradingTomorrow, navigating trends and
capital markets, be sure to like, subscribe and share, and we'll
see you next time.
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