December 10, 2024 • 29 mins
AI and the Future of Marketing: A Conversation with Dan Evans
In this episode of The Human Code, host Don Finley sits down with Dan Evans, a global marketing leader with over two decades of experience, to explore the transformative potential of AI in marketing. They discuss Dan's pioneering work in digital strategy, from his revolutionary role as the first digital marketing director for the US Marine Corps to leading initiatives at USAA. Dan shares insights on leveraging AI and large language models (LLMs) to enhance efficiency and innovation, touching on practical examples like automated content creation and workflow optimization. The conversation also delves into the implications of AI on jobs, future workforce skills, and maintaining human connection in a tech-driven world. This episode is a deep dive into the evolving intersection of technology, strategy, and human ingenuity.
00:00 Introduction to The Human Code Podcast
00:49 Meet Dan Evans: A Transformative Marketing Leader
01:40 Dan Evans' Journey and Innovations
03:45 The Impact of AI and LLMs in Marketing
06:12 AI in Podcast Production and Beyond
09:07 Future of AI: Opportunities and Challenges
12:57 AI in Everyday Life: Practical Applications
16:05 The Future of AI and Human Interaction
27:09 Preparing for an AI-Driven Future
29:05 Conclusion and Sponsor Message
Sponsored by FINdustries
Hosted by Don Finley
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Don Finley (00:00):
Welcome to The Human Code, the podcast where
technology meets humanity, andthe future is shaped by the
leaders and innovators of today.
I'm your host, Don Finley,inviting you on a journey
through the fascinating world oftech, leadership, and personal
growth.
Here, we delve into the storiesof visionary minds, Who are not
only driving technologicaladvancement, but also embodying
(00:23):
the personal journeys andinsights that inspire us all.
Each episode, we explore theintersections where human
ingenuity meets the cutting edgeof technology, unpacking the
experiences, challenges, andtriumphs that define our era.
So, whether you are a techenthusiast, an inspiring
entrepreneur, or simply curiousabout the human narratives
(00:44):
behind the digital revolution,you're in the right place.
Welcome to The Human Code.
Joining us today is Dan Evans, atransformative global marketing
leader and current globalmarketing officer at end to
growth with over two decades ofexperience, spanning both B2B
and B to C industries.
Dan has redefined digitalstrategy and innovation on a
(01:05):
global scale.
His journey from serving as theU S Marine corpse recruiting
commander's first ever digitalmarketing director.
Where he revolutionizedrecruitment strategies to
leading groundbreakinginitiatives like the USAA
personal brand academy showcaseshis dedication to elevating
brands and talents alike.
Dan is passionate aboutharnessing cutting edge
(01:25):
technologies like AI to driveimpactful results.
Both personally andprofessionally from increasing
inbound leads by 300% to scalingglobal marketing efforts.
Dan's visionary leadershipexemplifies the intersection of
technology strategy and humanconnection.
Today, we dive deep into hisremarkable journey, exploring
the transformative role of AI inmarketing, the evolution of
(01:46):
digital tools and what it meansto lead with innovation in
today's world.
I am here with Dan Evans.
Dan, it's been a pleasuretalking to you pre show, and I
really just want to dive into itto talk about humanity and
technology and what got youinterested in that intersection.
Dan Evans (02:03):
Yeah, so I think for me, technology has always been a
part of my life.
It's, even when I was younger, Igrew up in the days where, we
used LimeWire to download Ourfavorite audio tracks and
convert those into, CDs forthose who don't know what that
is, listening compact discs andmake our favorite jams.
(02:26):
It was long before we werestreaming, music to our phones
over the internet, and videogaming, playing PC.
I did that when I was younger.
And then.
just, I have always embraced,technology and particularly as
social media came out and, the,2000, 10 timeframe, I guess it
(02:48):
was 2008, 2010, somewhere aroundthere.
I was seeing opportunity gettingon LinkedIn.
I remember sitting, having aconversation with my wife, when
we went out on a date and I'mlike, this Facebook thing, Every
single business is going to havea Facebook.
Every single business is goingto use this as a platform to
propel, commercial activity.
(03:11):
And I remember sharing thatinsight with people and it,
seemed like a foreign concept,so it's always just been a part
of, who I am, where I'm going.
And now, of course, with theadvent of artificial
intelligence and these, languagemodels like OpenAI and Clod and,
(03:32):
there's hundreds of different AIpowered platforms that largely
sit on these, popular LLM APIs.
There's just so much opportunitythere, and I'm really excited to
talk about those things.
Don Finley (03:46):
So I'm definitely curious about even taking a step
back.
LLMs really showcased themselvesin the last two years, Like
we've been working with GPT forprobably four or five years
right now, but like the firstGPT 2 that was released was
basically like a glorifiedautocomplete.
GPT 3 had a little bit better,but it was really that use case
(04:06):
of figuring out how to get it tochat with you.
And so ChatGPT showcased us howpowerful LLMs could become, or
not even could become, but thebaseline of this new wave.
And I know two years ago I wouldhave said that the automation
and jobs that would have beenimpacted by AI first were going
(04:28):
to be like entry levelpositions.
Additionally, they were going tobe more of a blue collar type of
work first.
Then, Well, LLMs changed that ontheir head where now you're
talking about like intellectualthought workers and the creative
process can now be impacted bythis.
How has AI and LLMs in the lasttwo years impacted you and your
(04:50):
team?
Dan Evans (04:51):
I would say significantly, the things that
we were, dreaming of, just acouple of years ago are starting
to, grow in maturity today.
things like, just full end toend automations from start to
finish, from, taking, thispodcast, for example, and
turning it into a blog post andpublishing it in an automated
(05:14):
way onto your, website.
Like these types of things startto finish end to end.
It's almost this AI has becomemultiple agents or people, so to
speak, that can do these jobsfor us, or at least create, a 90
percent draft solution from theget go, which is really exciting
(05:37):
because, think of the amount ofeffort and time.
And energy it takes to start anddo some writing from scratch.
So had a podcast around 2014,and, even just creating the show
notes, top to bottom, start tofinish, you'd have to listen to
(05:58):
the podcast, you'd have to jotdown notes, it was very
cumbersome.
having a podcast was a lot ofwork.
Don Finley (06:06):
Yeah.
Dan Evans (06:07):
And, things have since changed.
I'm not sure how you're usingit, but,
Don Finley (06:12):
So here I will tell you 100 percent how we're using
it.
cause my eyes are lighting upthinking about a, how much
different it is from 2015, Likeyou were talking about creating
show notes.
never thought about show notes.
Like we have them, they're inall of our descriptions, but
like they get created by AI andthen they also get reviewed by
(06:35):
our producer.
And so That is a task on ourlist that takes probably a
minute to accomplish.
now, the other side of this isour guests fill out a show form
before coming on.
so when you fill that out, wethen have an AI that pulls like
your LinkedIn profile and putstogether a persona for you, for
(06:56):
me, with some like samplequestions and some possibilities
for what we could go at, Sothat's one area.
Then when it comes to theediting of the podcast, you used
to have to listen to it, makecuts.
and then go through with thatfine tooth comb of did I make
the cut right?
Am I doing this?
And video and audio editing tome has always felt like the same
(07:18):
thing as like the show, the shopfloor of you have the film strip
and you're literally cutting itand then piecing those two
things together.
today we edit on a transcript.
And so like the AI has gonethrough, listened to everything,
labeled the speakers, identifiedwho's speaking when, what
they're saying, and we can gothrough with AI and remove ums,
(07:41):
uhs, filler words as well.
And so that initial process ofediting a 30 minute episode used
to take, I think it, was betweenone to two hours for that
initial cut.
of just removing, like they,just a fast pass kind of thing
in order to do that.
(08:01):
That happens in less than fiveminutes today.
so that's one of those areas.
And then afterwards, Like youwant to do promotional material.
We have an AI that goes throughand takes The 30 minute episode
and then creates between threeto 10 different social media
shares based on the content ofthe episode, as well as the,
(08:25):
what is trending in the worldtoday.
And so since we talk about AI,it's always trending kind of
thing, but, at the same time, italso picks up on other.
And then it writes the post forus as well to describe the
content and what's going on.
Dan Evans (08:39):
I think, that's a great example and I think, it's
not really anoversimplification, but in terms
of like the setup process, I'msure, it took some time to build
out the rules, the style, thetone of your podcast, the types
of.
Clips that, your, AI agent issearching for and trying to find
(09:03):
and curate for your audience.
And, I think that therein is thepiece that we should all be
focusing on is how do we build.
These agents to understand likewe would as people and then
teach them and train them andrefine them.
(09:25):
and that is the skillset Ibelieve of the future is exactly
that.
Don Finley (09:32):
I think you're hitting on something very
positive here because it is a,how do you apply the tools that
we're seeing today?
But then how do you change theway that we look at our work in
association with what we'regetting done?
And that ability to identify theworkflow, the processes, and
effectively more of thatmanagerial, type of work is
going to hit every job.
(09:54):
And knowing that we canessentially automate something
that may have taken.
a couple of hours before into acouple of seconds or to do
something that, like we havelead criteria, like we have
leads that get evaluated, youwant to score them and you want
to see and.
We used to have somebody whowould spend hours of their time
(10:15):
going through scraping data tovalidate, is this person in our
ICP?
Is it not in our ICP?
Do we want to be reaching out tothem?
And now we can have an AI that.
takes a look at the informationand instead of processing a
couple hundred of these an hour,you're doing a couple hundred in
a few seconds.
But at the same time, it isn'twork that people find
fulfilling.
(10:36):
And so they can move on toworking on things that are more
fulfilling.
what has been the impact on thework that you're doing around,
is it more fulfilling now?
Is it less fulfilling?
how does it change?
Dan Evans (10:46):
that's a pretty broad and big question, but.
I would say that, everything haschanged.
I think the most recentdisruptive technology that I can
think of off the top of my headis the internet.
And now it's something that weuse, it's in our homes, it's in
our businesses, it's ubiquitousin every single facet and in
(11:09):
everything that we do.
And it's very difficult to gooff the grid and be off of the
internet and still function as ahuman being today.
I think AI is very similar tothat.
it's going to be embedded,ingrained in every single thing
(11:30):
that we do.
Now, I think that, initially,AI, when it came out, was
focused on Text.
It was very heavy on text.
And, now we've got these toolslike MidJourney.
We have Dolly with OpenAI tocreate images and Meta most
recently announced that they'reLaunching a platform to edit
(11:55):
videos using AI in theirplatforms, which is super
exciting So when we look at justthose things look at the way we
used to do writing Which washighly manual, very difficult
starting from scratch.
Same thing with creating imagesand graphics, creating images
and graphics with a designer, istypically very expensive.
(12:18):
Now, what we're seeing asdesigners, we still need
designers.
We still need the human, butwe're creating some initial
works and graphics that can belayered into, popular editing
tools and refined.
And made, specific to a brand.
And that process is just beenaccelerated.
Don Finley (12:41):
Okay.
So
Dan Evans (12:42):
yeah,
Don Finley (12:43):
in the ideation process of trying to describe to
the designer, Hey, here's whatI'm looking at.
You're using some of these toolsto basically say here's a visual
of what I previously would havedescribed to you.
Dan Evans (12:55):
That's right.
Yeah.
And
Don Finley (12:57):
okay.
Dan Evans (12:57):
yeah, and that's one, one way that, we're using, AI in
our work is we use mid journeyto help create some initial
iterations that are aligned withour brand.
We've defined a very.
Specific style that we use invarious facets of our brand and
(13:18):
we're able to replicate thosethings and make unique imagery
and graphics that really standout, differentiate us from the
competition.
And I don't know about you, Don,but I am absolutely, sick of
stock photography.
And maybe at some point I mayfeel that same way about AI
(13:39):
generated images, graphics,vectors, photographs, etc.
But I'm really struggling toidentify when that's going to be
because it's been a while.
Pretty darn cool.
Don Finley (13:52):
you're 100 percent right.
I resonate at 100 percent withwhat you're saying because it is
so cool to be able to do thingsthat I couldn't do before, and
not to say that I can do them toa level that is professional,
but I can do it to the pointwhere I can convey a thought.
I can convey an idea muchquicker than I could before.
the ideation process happeningfaster.
(14:14):
But I do also recognize thatthere is going to be a point
where I just get tired of it.
Have you heard of the deadinternet theory?
Dan Evans (14:23):
Enlighten me.
Don Finley (14:24):
Okay.
So this is a theory I first raninto around, I want to say
somewhere between 2016, 2018.
And the general premise is thatthe internet that from earlier,
Like our early days in socialmedia, the excitement of being
able to get online, to talk to acommunity, to interact, to do, I
don't know if you were, you aICQ or AOL chat, Like that way,
(14:47):
those were felt exciting.
Cause now you're using a newform of communication to engage
with somebody who's across theworld in some other way.
And now it's pretty standard,there was nothing exciting about
us.
Creating a video chat today inorder to have this podcast.
That wasn't the excitement.
where the dead internet theoryplays in is.
At some point, bot traffic onthe internet will eclipse human
(15:13):
interaction.
And so you see it on like socialmedia platforms today where
you're like, is that a bot or isthat a human?
I'll tell you there's a greaterthan 51 percent chance right now
that it's a bot.
That's where we're at.
We're right at that tippingpoint.
But if you start to get up tothe 80, 90% of interactions are
with bots, you lose thatconnection to a human.
(15:34):
That you can have thosethoughts, you can have those
concepts, and then the worldfeels more and more isolated
because you're not having thatinteraction that you either
previously had, or maybe we justall go out and touch some grass
at that point.
but that's the theory, is thatbasically the internet will end
up getting consumed with bots.
Artificial intelligence.
Dan Evans (15:55):
yeah.
that's not a far fetched theory.
it totally could happen.
At the same time, I think it'simportant to recognize what,
these bots are freeing us from.
And it's the mundane, and we'regoing under the assumption that
the bots will not become smarterand more human like.
I saw an interview with, MarkZuckerberg, the other day, and
(16:18):
he was talking about, the futurelooks like, just a bunch of
agents, AI bot agents thatcommunicate with one another
that they're working together asteams.
They're solving challenges.
They're learning from oneanother.
They're creating qualitativeoutcomes and deliverables that
we as human beings, have ourmortal shortcomings, Like we're
(16:41):
tired.
We miss things.
But you have the precisionaccuracy that comes with a
computer doing the work.
If we've come this far in just ayear, imagine where we're going
to be this time next year,
Don Finley (16:59):
Yeah.
Dan Evans (17:00):
and where are we going to be in five years.
And if we can leverage thesetools for good, and use it as a
means to free up headspace andtime where we can focus on, the
meaningful activities like this,of doing a podcast interview.
People, person to person, theseinterpersonal, relationships, a
(17:25):
beautiful thing in my opinion.
So it is a balance for sure.
How do we protect privacy?
How do we protect people?
How do we make sure that thebots are doing what they should
be doing?
It's almost like we could besupervising teams of agents and
(17:47):
bots in the future and that isan interesting challenge to
solve.
So how do we do thateffectively?
How do we make sure that, thebots don't get deceptive and
start doing things that, they'renot supposed to be doing?
These are all concernsfortunately, there's a lot of
smart people working on theseproblems and ensuring that they
(18:08):
don't become that,
Don Finley (18:10):
you know also, AI alignment, Like that point of,
is the human goal aligned withwhat the AI wants is a
fascinating field of research,but also some of the latest
things that are going on isusing AI to train the AI in
human AI alignment as well,which is, An interesting
(18:31):
scenario.
but I agree with you that ifwe're going to create an
environment that is utilizingthese tools, the place where
those tools will get applied isin the mundane.
it is in the activities that weare not enjoying, and then we
can focus on the activitiesthat, we do enjoy.
how do you see that playing outin your life around the
(18:52):
activities that you find to beeither more worthwhile now that
you weren't able to get to?
And once again, thank you forbeing on this show and creating
these moments with me as well.
Dan Evans (19:03):
I see it, a lot like electricity.
it's just going to be ubiquitousand everything that we do.
And much of the innovationsgoing forward are going to have
various forms of AI in it.
Now, if we look at electricity,entire new markets were stood up
as a result.
of electricity.
We changed business as we knewit.
(19:23):
We changed how we operated inour daily lives.
and even now, like we have theinternet.
That has drastically transformedthe way we do business.
It's transformed our lives.
Gone from, books, hard copybooks to digital copies of books
to being able to use theinternet and AI to scan, and
(19:45):
read a book for us andsynthesize and produce summaries
and, an instant people likethings very fast.
These days we've grown,impatient in a lot of ways.
And I think that impatience isdriving innovation.
And for me, I think my hope isto just be cautiously optimistic
(20:08):
about how that looks.
I'm integrating it where I seefit, where I see that It's safe,
it's been tested, and just beingvery careful about the types of
pieces of information that we'readding to the internet.
because these large languagemodels, they're collecting all
of the pieces of data that areingested into it and forming,
(20:31):
new neural pathways, if youwill.
as those pieces are beingsynthesized,
Don Finley (20:37):
And I think that's an incredibly strong point to
hit on is if you're giving yourdata to these LLMs, you're
training it to do the thing thatyou're asking it about as well,
you're moving the ball forwardin that capacity.
and I know when we work with ourclients around like AI
implementations, that is a bigdiscussion upfront about like,
(21:00):
how comfortable are you aboutputting your data into
somebody's system?
And there's three ways that welook at it.
You're either fully comfortablekind of thing.
Like I know I go to perplexityand I ask it silly questions.
I don't mind about that.
But then there's also datathat's important to my life.
Certain things in the enterprisewill actually move over to open
AI and Microsoft because we havelegal protections that they're
(21:22):
not using it for ourselves.
But then there's sometimes datathat's so sensitive.
And the example that I give isMicrosoft I have trained an AI
to mimic Carl Jung.
I do not want that informationout there.
So I run that locally, In my ownserver, my own space, the data
stays with me.
we're getting the model from,Facebook, from or wherever we're
(21:46):
getting it from and using it,but all the data stays local to
us.
I think it's a good point thatyou're hitting on here around,
you gotta know what you'redoing, how you're handing over
that information.
we look at technology,innovation in businesses and in
our lives as a, Hey, this doesthe thing that solves this task.
And then we bring it in.
(22:07):
Are we going to be looking at AIin different ways?
Or is it still that same sort ofmodel of I'm going to have an AI
that like cleans my house.
I'm going to have an AI that,makes pictures for me.
Dan Evans (22:17):
one recent example that, comes to mind is I was
talking to my wife about,grocery delivery services, we
use Walmart plus, and, here inTexas, we have H E B everybody
loves H E B.
And my wife expressed a littlebit of frustration about like
ordering groceries and, thinkingof meals and all this other
stuff.
(22:37):
well why don't we integrate, ameal planner into, these various
grocery apps going forward andplan our meals for us and do the
ordering for us where everythingjust shows up at our porch,
Amazon is, pioneered thelogistics of getting things to
us between, overnight, between4am and 8am or between, 5 and 10
(22:57):
pm same day delivery type thing.
Why can't we do that withgroceries?
Why can't we take out some ofthese mundane, tasks that just
are dreadful?
Don Finley (23:07):
Please, Dan, I think we're just going to talk to the
audience right now.
And let's hope that somebody islistening who wants to be
creating this, because I'mtelling you that would solve 80
percent of my shopping problemsfor groceries, if you could
create a meal plan, have the AIfigure out what you need and
then place the order that itgets delivered.
(23:27):
Love that.
Like absolutely fantastic
Dan Evans (23:31):
things you don't have to think about.
Yeah,
Don Finley (23:33):
Yeah,
Dan Evans (23:33):
yeah,
Don Finley (23:34):
it's more of a coordination of activities that
go on that are rather.
Not germane, but they feelrepetitive or they feel like
there is something that doesn'trequire my full intelligence.
And then at the same time, goingonline to shop for food requires
that I do that step already, Ican't just go on to the website
(23:54):
for Whole Foods and click a fewbuttons for the pre prepared
meal, not even pre prepared, butlike to get the ingredients for
the meal.
I got to figure out theingredients, what I need, and
then get onto the website.
I love those applications ofthis because it is filling the
gap between why you're doingsomething the way that we used
to do it and saying, you knowwhat, my end purpose here is
(24:17):
actually to make a meal with myfamily.
And so for me to be making thatmeal with my family, what are
the steps that can be taken outof that and go, my family likes
this meal.
All right, AI, go figure outwhat we need to get in order so
I can make that meal at thistime.
Dan Evans (24:32):
yeah.
And that's a beautiful thing.
these things, these little,tasks that are mundane in our
households, there's so many mywife has been, ordering
groceries for our family, goingto the store for, nearly 20
years that we've been together.
And, she's just now, not justnow, but recently getting into
ChatGPT for, planning trips.
(24:54):
ordering groceries, meal plans,like you can plug in the address
of your Airbnb as an example anddo a full outline top to bottom
of, nearby things to do with afamily of five to your Airbnb.
these are things that we'reworking on.
In the, just a couple of yearsago would have taken hours to
(25:14):
do.
Imagine how many Chrome tabs itwould take to plan a, a 10 day
trip.
That's a lot of copying andpasting.
And now we can just, make the AIgo do it.
And then you can plan your triparound, the activities that it's
set forth all the way down from,the distance from where you're
staying to a budget.
Free activities, if you're anoutdoorsy person, if you're a
(25:36):
hike person, or if you're alounge by the pool person, it's
just incredible.
Don Finley (25:41):
We live in a society that basically, we went from
having information scarcity inthis place to going to a place
that was informationallyabundant, if we look back 40
years, there was a generalbenefit to being able to
remember something and to beable to apply it.
And now in an informationabundant society, the value is
in how I can synthesize theinformation and how I can
(26:04):
pattern match against it andfind the relationships.
of the sea of information that'sout there.
Now with LLMs, we have a toolthat can do that.
And it's coming into that space.
And I know with O1 Preview andthe future iterations of where,
ChachiBT is heading, as well asI know others are, that
(26:25):
reasoning step is getting a lotstronger and being able to plan
forward and do the things thatyou're talking about, which is
just an amazing, space that welive in.
But I think you're hitting onthe key activity here of, You
got to interact with it and tryit and see, what it can do to
help you.
Because if you are planning atrip, it's going to help you in
(26:46):
some way to sit down and say,all right, can you at least get
me farther along?
And I know I personally use,chat GPT for exercises where I'm
not the strongest in, Likemarketing and sales.
Isn't my strongest suit.
But I do it and chat GPT hasbeen a nice reflection point for
helping me to advance my skillson there.
(27:07):
A partner in that collaboration.
one thing I would love to knowis what do you think is the
activities that people can focuson to help them like either
adopt this or additionally getprepared for, even more changes
that are coming in the future.
Dan Evans (27:22):
think just using it, I've talked to a lot of
professionals who are stillusing these tools at a very
basic level.
they're going in, asking,ChatGPT to write an article
about this.
And that's the extent of theprompt.
Don Finley (27:41):
Yeah.
Dan Evans (27:42):
And, they always say if you want great answers, you
need to ask better questions.
And if you want great outcomes,you need to ask or tell the AI
be very specific about what itis you're asking it to do, how
you want it to look, what typeof tone, what type of style,
this is just one example, buthaving that kind of, it's like
(28:06):
you're the coach for the AI andthis is where the human really
plays the part in making thesesystems work.
Don Finley (28:15):
Yeah.
Dan Evans (28:16):
I think for your listeners here playing with the
tools, trying different things,getting on YouTube University
doing some studying, going toReddit, do some studying on, how
to get, Prompts that createdesirable outcomes and then
innovating off of that.
I really think that is how youcan position yourself for the
(28:38):
future and maximize.
Don Finley (28:40):
Dan, I gotta say, that's honestly just great
advice on this.
Simple.
And at the same time, like it iswhat's necessary.
You've got to get comfortablewith these tools.
You've got to try them out.
You've got to figure out likewhere it's working for you,
where it isn't working for you.
And that's really helpful foreverybody to understand.
so I really, I just want tothank you again for taking the
time today to talk to us andit's been an absolute blast
(29:01):
having you on.
Dan Evans (29:02):
Yeah.
Thank you for having me.
Don Finley (29:05):
Thank you for tuning into The Human Code, sponsored
by FINdustries, where we harnessAI to elevate your business.
By improving operationalefficiency and accelerating
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(29:26):
co.
Welcome to The Human Code, the podcast where
technology meets humanity, andthe future is shaped by the
leaders and innovators of today.
I'm your host, Don Finley,inviting you on a journey
through the fascinating world oftech, leadership, and personal
growth.
Here, we delve into the storiesof visionary minds, Who are not
only driving technologicaladvancement, but also embodying
(00:23):
the personal journeys andinsights that inspire us all.
Each episode, we explore theintersections where human
ingenuity meets the cutting edgeof technology, unpacking the
experiences, challenges, andtriumphs that define our era.
So, whether you are a techenthusiast, an inspiring
entrepreneur, or simply curiousabout the human narratives
(00:44):
behind the digital revolution,you're in the right place.
Welcome to The Human Code.
Joining us today is Dan Evans, atransformative global marketing
leader and current globalmarketing officer at end to
growth with over two decades ofexperience, spanning both B2B
and B to C industries.
Dan has redefined digitalstrategy and innovation on a
(01:05):
global scale.
His journey from serving as theU S Marine corpse recruiting
commander's first ever digitalmarketing director.
Where he revolutionizedrecruitment strategies to
leading groundbreakinginitiatives like the USAA
personal brand academy showcaseshis dedication to elevating
brands and talents alike.
Dan is passionate aboutharnessing cutting edge
(01:25):
technologies like AI to driveimpactful results.
Both personally andprofessionally from increasing
inbound leads by 300% to scalingglobal marketing efforts.
Dan's visionary leadershipexemplifies the intersection of
technology strategy and humanconnection.
Today, we dive deep into hisremarkable journey, exploring
the transformative role of AI inmarketing, the evolution of
(01:46):
digital tools and what it meansto lead with innovation in
today's world.
I am here with Dan Evans.
Dan, it's been a pleasuretalking to you pre show, and I
really just want to dive into itto talk about humanity and
technology and what got youinterested in that intersection.
Dan Evans (02:03):
Yeah, so I think for me, technology has always been a
part of my life.
It's, even when I was younger, Igrew up in the days where, we
used LimeWire to download Ourfavorite audio tracks and
convert those into, CDs forthose who don't know what that
is, listening compact discs andmake our favorite jams.
(02:26):
It was long before we werestreaming, music to our phones
over the internet, and videogaming, playing PC.
I did that when I was younger.
And then.
just, I have always embraced,technology and particularly as
social media came out and, the,2000, 10 timeframe, I guess it
(02:48):
was 2008, 2010, somewhere aroundthere.
I was seeing opportunity gettingon LinkedIn.
I remember sitting, having aconversation with my wife, when
we went out on a date and I'mlike, this Facebook thing, Every
single business is going to havea Facebook.
Every single business is goingto use this as a platform to
propel, commercial activity.
(03:11):
And I remember sharing thatinsight with people and it,
seemed like a foreign concept,so it's always just been a part
of, who I am, where I'm going.
And now, of course, with theadvent of artificial
intelligence and these, languagemodels like OpenAI and Clod and,
(03:32):
there's hundreds of different AIpowered platforms that largely
sit on these, popular LLM APIs.
There's just so much opportunitythere, and I'm really excited to
talk about those things.
Don Finley (03:46):
So I'm definitely curious about even taking a step
back.
LLMs really showcased themselvesin the last two years, Like
we've been working with GPT forprobably four or five years
right now, but like the firstGPT 2 that was released was
basically like a glorifiedautocomplete.
GPT 3 had a little bit better,but it was really that use case
(04:06):
of figuring out how to get it tochat with you.
And so ChatGPT showcased us howpowerful LLMs could become, or
not even could become, but thebaseline of this new wave.
And I know two years ago I wouldhave said that the automation
and jobs that would have beenimpacted by AI first were going
(04:28):
to be like entry levelpositions.
Additionally, they were going tobe more of a blue collar type of
work first.
Then, Well, LLMs changed that ontheir head where now you're
talking about like intellectualthought workers and the creative
process can now be impacted bythis.
How has AI and LLMs in the lasttwo years impacted you and your
(04:50):
team?
Dan Evans (04:51):
I would say significantly, the things that
we were, dreaming of, just acouple of years ago are starting
to, grow in maturity today.
things like, just full end toend automations from start to
finish, from, taking, thispodcast, for example, and
turning it into a blog post andpublishing it in an automated
(05:14):
way onto your, website.
Like these types of things startto finish end to end.
It's almost this AI has becomemultiple agents or people, so to
speak, that can do these jobsfor us, or at least create, a 90
percent draft solution from theget go, which is really exciting
(05:37):
because, think of the amount ofeffort and time.
And energy it takes to start anddo some writing from scratch.
So had a podcast around 2014,and, even just creating the show
notes, top to bottom, start tofinish, you'd have to listen to
(05:58):
the podcast, you'd have to jotdown notes, it was very
cumbersome.
having a podcast was a lot ofwork.
Don Finley (06:06):
Yeah.
Dan Evans (06:07):
And, things have since changed.
I'm not sure how you're usingit, but,
Don Finley (06:12):
So here I will tell you 100 percent how we're using
it.
cause my eyes are lighting upthinking about a, how much
different it is from 2015, Likeyou were talking about creating
show notes.
never thought about show notes.
Like we have them, they're inall of our descriptions, but
like they get created by AI andthen they also get reviewed by
(06:35):
our producer.
And so That is a task on ourlist that takes probably a
minute to accomplish.
now, the other side of this isour guests fill out a show form
before coming on.
so when you fill that out, wethen have an AI that pulls like
your LinkedIn profile and putstogether a persona for you, for
(06:56):
me, with some like samplequestions and some possibilities
for what we could go at, Sothat's one area.
Then when it comes to theediting of the podcast, you used
to have to listen to it, makecuts.
and then go through with thatfine tooth comb of did I make
the cut right?
Am I doing this?
And video and audio editing tome has always felt like the same
(07:18):
thing as like the show, the shopfloor of you have the film strip
and you're literally cutting itand then piecing those two
things together.
today we edit on a transcript.
And so like the AI has gonethrough, listened to everything,
labeled the speakers, identifiedwho's speaking when, what
they're saying, and we can gothrough with AI and remove ums,
(07:41):
uhs, filler words as well.
And so that initial process ofediting a 30 minute episode used
to take, I think it, was betweenone to two hours for that
initial cut.
of just removing, like they,just a fast pass kind of thing
in order to do that.
(08:01):
That happens in less than fiveminutes today.
so that's one of those areas.
And then afterwards, Like youwant to do promotional material.
We have an AI that goes throughand takes The 30 minute episode
and then creates between threeto 10 different social media
shares based on the content ofthe episode, as well as the,
(08:25):
what is trending in the worldtoday.
And so since we talk about AI,it's always trending kind of
thing, but, at the same time, italso picks up on other.
And then it writes the post forus as well to describe the
content and what's going on.
Dan Evans (08:39):
I think, that's a great example and I think, it's
not really anoversimplification, but in terms
of like the setup process, I'msure, it took some time to build
out the rules, the style, thetone of your podcast, the types
of.
Clips that, your, AI agent issearching for and trying to find
(09:03):
and curate for your audience.
And, I think that therein is thepiece that we should all be
focusing on is how do we build.
These agents to understand likewe would as people and then
teach them and train them andrefine them.
(09:25):
and that is the skillset Ibelieve of the future is exactly
that.
Don Finley (09:32):
I think you're hitting on something very
positive here because it is a,how do you apply the tools that
we're seeing today?
But then how do you change theway that we look at our work in
association with what we'regetting done?
And that ability to identify theworkflow, the processes, and
effectively more of thatmanagerial, type of work is
going to hit every job.
(09:54):
And knowing that we canessentially automate something
that may have taken.
a couple of hours before into acouple of seconds or to do
something that, like we havelead criteria, like we have
leads that get evaluated, youwant to score them and you want
to see and.
We used to have somebody whowould spend hours of their time
(10:15):
going through scraping data tovalidate, is this person in our
ICP?
Is it not in our ICP?
Do we want to be reaching out tothem?
And now we can have an AI that.
takes a look at the informationand instead of processing a
couple hundred of these an hour,you're doing a couple hundred in
a few seconds.
But at the same time, it isn'twork that people find
fulfilling.
(10:36):
And so they can move on toworking on things that are more
fulfilling.
what has been the impact on thework that you're doing around,
is it more fulfilling now?
Is it less fulfilling?
how does it change?
Dan Evans (10:46):
that's a pretty broad and big question, but.
I would say that, everything haschanged.
I think the most recentdisruptive technology that I can
think of off the top of my headis the internet.
And now it's something that weuse, it's in our homes, it's in
our businesses, it's ubiquitousin every single facet and in
(11:09):
everything that we do.
And it's very difficult to gooff the grid and be off of the
internet and still function as ahuman being today.
I think AI is very similar tothat.
it's going to be embedded,ingrained in every single thing
(11:30):
that we do.
Now, I think that, initially,AI, when it came out, was
focused on Text.
It was very heavy on text.
And, now we've got these toolslike MidJourney.
We have Dolly with OpenAI tocreate images and Meta most
recently announced that they'reLaunching a platform to edit
(11:55):
videos using AI in theirplatforms, which is super
exciting So when we look at justthose things look at the way we
used to do writing Which washighly manual, very difficult
starting from scratch.
Same thing with creating imagesand graphics, creating images
and graphics with a designer, istypically very expensive.
(12:18):
Now, what we're seeing asdesigners, we still need
designers.
We still need the human, butwe're creating some initial
works and graphics that can belayered into, popular editing
tools and refined.
And made, specific to a brand.
And that process is just beenaccelerated.
Don Finley (12:41):
Okay.
So
Dan Evans (12:42):
yeah,
Don Finley (12:43):
in the ideation process of trying to describe to
the designer, Hey, here's whatI'm looking at.
You're using some of these toolsto basically say here's a visual
of what I previously would havedescribed to you.
Dan Evans (12:55):
That's right.
Yeah.
And
Don Finley (12:57):
okay.
Dan Evans (12:57):
yeah, and that's one, one way that, we're using, AI in
our work is we use mid journeyto help create some initial
iterations that are aligned withour brand.
We've defined a very.
Specific style that we use invarious facets of our brand and
(13:18):
we're able to replicate thosethings and make unique imagery
and graphics that really standout, differentiate us from the
competition.
And I don't know about you, Don,but I am absolutely, sick of
stock photography.
And maybe at some point I mayfeel that same way about AI
(13:39):
generated images, graphics,vectors, photographs, etc.
But I'm really struggling toidentify when that's going to be
because it's been a while.
Pretty darn cool.
Don Finley (13:52):
you're 100 percent right.
I resonate at 100 percent withwhat you're saying because it is
so cool to be able to do thingsthat I couldn't do before, and
not to say that I can do them toa level that is professional,
but I can do it to the pointwhere I can convey a thought.
I can convey an idea muchquicker than I could before.
the ideation process happeningfaster.
(14:14):
But I do also recognize thatthere is going to be a point
where I just get tired of it.
Have you heard of the deadinternet theory?
Dan Evans (14:23):
Enlighten me.
Don Finley (14:24):
Okay.
So this is a theory I first raninto around, I want to say
somewhere between 2016, 2018.
And the general premise is thatthe internet that from earlier,
Like our early days in socialmedia, the excitement of being
able to get online, to talk to acommunity, to interact, to do, I
don't know if you were, you aICQ or AOL chat, Like that way,
(14:47):
those were felt exciting.
Cause now you're using a newform of communication to engage
with somebody who's across theworld in some other way.
And now it's pretty standard,there was nothing exciting about
us.
Creating a video chat today inorder to have this podcast.
That wasn't the excitement.
where the dead internet theoryplays in is.
At some point, bot traffic onthe internet will eclipse human
(15:13):
interaction.
And so you see it on like socialmedia platforms today where
you're like, is that a bot or isthat a human?
I'll tell you there's a greaterthan 51 percent chance right now
that it's a bot.
That's where we're at.
We're right at that tippingpoint.
But if you start to get up tothe 80, 90% of interactions are
with bots, you lose thatconnection to a human.
(15:34):
That you can have thosethoughts, you can have those
concepts, and then the worldfeels more and more isolated
because you're not having thatinteraction that you either
previously had, or maybe we justall go out and touch some grass
at that point.
but that's the theory, is thatbasically the internet will end
up getting consumed with bots.
Artificial intelligence.
Dan Evans (15:55):
yeah.
that's not a far fetched theory.
it totally could happen.
At the same time, I think it'simportant to recognize what,
these bots are freeing us from.
And it's the mundane, and we'regoing under the assumption that
the bots will not become smarterand more human like.
I saw an interview with, MarkZuckerberg, the other day, and
(16:18):
he was talking about, the futurelooks like, just a bunch of
agents, AI bot agents thatcommunicate with one another
that they're working together asteams.
They're solving challenges.
They're learning from oneanother.
They're creating qualitativeoutcomes and deliverables that
we as human beings, have ourmortal shortcomings, Like we're
(16:41):
tired.
We miss things.
But you have the precisionaccuracy that comes with a
computer doing the work.
If we've come this far in just ayear, imagine where we're going
to be this time next year,
Don Finley (16:59):
Yeah.
Dan Evans (17:00):
and where are we going to be in five years.
And if we can leverage thesetools for good, and use it as a
means to free up headspace andtime where we can focus on, the
meaningful activities like this,of doing a podcast interview.
People, person to person, theseinterpersonal, relationships, a
(17:25):
beautiful thing in my opinion.
So it is a balance for sure.
How do we protect privacy?
How do we protect people?
How do we make sure that thebots are doing what they should
be doing?
It's almost like we could besupervising teams of agents and
(17:47):
bots in the future and that isan interesting challenge to
solve.
So how do we do thateffectively?
How do we make sure that, thebots don't get deceptive and
start doing things that, they'renot supposed to be doing?
These are all concernsfortunately, there's a lot of
smart people working on theseproblems and ensuring that they
(18:08):
don't become that,
Don Finley (18:10):
you know also, AI alignment, Like that point of,
is the human goal aligned withwhat the AI wants is a
fascinating field of research,but also some of the latest
things that are going on isusing AI to train the AI in
human AI alignment as well,which is, An interesting
(18:31):
scenario.
but I agree with you that ifwe're going to create an
environment that is utilizingthese tools, the place where
those tools will get applied isin the mundane.
it is in the activities that weare not enjoying, and then we
can focus on the activitiesthat, we do enjoy.
how do you see that playing outin your life around the
(18:52):
activities that you find to beeither more worthwhile now that
you weren't able to get to?
And once again, thank you forbeing on this show and creating
these moments with me as well.
Dan Evans (19:03):
I see it, a lot like electricity.
it's just going to be ubiquitousand everything that we do.
And much of the innovationsgoing forward are going to have
various forms of AI in it.
Now, if we look at electricity,entire new markets were stood up
as a result.
of electricity.
We changed business as we knewit.
(19:23):
We changed how we operated inour daily lives.
and even now, like we have theinternet.
That has drastically transformedthe way we do business.
It's transformed our lives.
Gone from, books, hard copybooks to digital copies of books
to being able to use theinternet and AI to scan, and
(19:45):
read a book for us andsynthesize and produce summaries
and, an instant people likethings very fast.
These days we've grown,impatient in a lot of ways.
And I think that impatience isdriving innovation.
And for me, I think my hope isto just be cautiously optimistic
(20:08):
about how that looks.
I'm integrating it where I seefit, where I see that It's safe,
it's been tested, and just beingvery careful about the types of
pieces of information that we'readding to the internet.
because these large languagemodels, they're collecting all
of the pieces of data that areingested into it and forming,
(20:31):
new neural pathways, if youwill.
as those pieces are beingsynthesized,
Don Finley (20:37):
And I think that's an incredibly strong point to
hit on is if you're giving yourdata to these LLMs, you're
training it to do the thing thatyou're asking it about as well,
you're moving the ball forwardin that capacity.
and I know when we work with ourclients around like AI
implementations, that is a bigdiscussion upfront about like,
(21:00):
how comfortable are you aboutputting your data into
somebody's system?
And there's three ways that welook at it.
You're either fully comfortablekind of thing.
Like I know I go to perplexityand I ask it silly questions.
I don't mind about that.
But then there's also datathat's important to my life.
Certain things in the enterprisewill actually move over to open
AI and Microsoft because we havelegal protections that they're
(21:22):
not using it for ourselves.
But then there's sometimes datathat's so sensitive.
And the example that I give isMicrosoft I have trained an AI
to mimic Carl Jung.
I do not want that informationout there.
So I run that locally, In my ownserver, my own space, the data
stays with me.
we're getting the model from,Facebook, from or wherever we're
(21:46):
getting it from and using it,but all the data stays local to
us.
I think it's a good point thatyou're hitting on here around,
you gotta know what you'redoing, how you're handing over
that information.
we look at technology,innovation in businesses and in
our lives as a, Hey, this doesthe thing that solves this task.
And then we bring it in.
(22:07):
Are we going to be looking at AIin different ways?
Or is it still that same sort ofmodel of I'm going to have an AI
that like cleans my house.
I'm going to have an AI that,makes pictures for me.
Dan Evans (22:17):
one recent example that, comes to mind is I was
talking to my wife about,grocery delivery services, we
use Walmart plus, and, here inTexas, we have H E B everybody
loves H E B.
And my wife expressed a littlebit of frustration about like
ordering groceries and, thinkingof meals and all this other
stuff.
(22:37):
well why don't we integrate, ameal planner into, these various
grocery apps going forward andplan our meals for us and do the
ordering for us where everythingjust shows up at our porch,
Amazon is, pioneered thelogistics of getting things to
us between, overnight, between4am and 8am or between, 5 and 10
(22:57):
pm same day delivery type thing.
Why can't we do that withgroceries?
Why can't we take out some ofthese mundane, tasks that just
are dreadful?
Don Finley (23:07):
Please, Dan, I think we're just going to talk to the
audience right now.
And let's hope that somebody islistening who wants to be
creating this, because I'mtelling you that would solve 80
percent of my shopping problemsfor groceries, if you could
create a meal plan, have the AIfigure out what you need and
then place the order that itgets delivered.
(23:27):
Love that.
Like absolutely fantastic
Dan Evans (23:31):
things you don't have to think about.
Yeah,
Don Finley (23:33):
Yeah,
Dan Evans (23:33):
yeah,
Don Finley (23:34):
it's more of a coordination of activities that
go on that are rather.
Not germane, but they feelrepetitive or they feel like
there is something that doesn'trequire my full intelligence.
And then at the same time, goingonline to shop for food requires
that I do that step already, Ican't just go on to the website
(23:54):
for Whole Foods and click a fewbuttons for the pre prepared
meal, not even pre prepared, butlike to get the ingredients for
the meal.
I got to figure out theingredients, what I need, and
then get onto the website.
I love those applications ofthis because it is filling the
gap between why you're doingsomething the way that we used
to do it and saying, you knowwhat, my end purpose here is
(24:17):
actually to make a meal with myfamily.
And so for me to be making thatmeal with my family, what are
the steps that can be taken outof that and go, my family likes
this meal.
All right, AI, go figure outwhat we need to get in order so
I can make that meal at thistime.
Dan Evans (24:32):
yeah.
And that's a beautiful thing.
these things, these little,tasks that are mundane in our
households, there's so many mywife has been, ordering
groceries for our family, goingto the store for, nearly 20
years that we've been together.
And, she's just now, not justnow, but recently getting into
ChatGPT for, planning trips.
(24:54):
ordering groceries, meal plans,like you can plug in the address
of your Airbnb as an example anddo a full outline top to bottom
of, nearby things to do with afamily of five to your Airbnb.
these are things that we'reworking on.
In the, just a couple of yearsago would have taken hours to
(25:14):
do.
Imagine how many Chrome tabs itwould take to plan a, a 10 day
trip.
That's a lot of copying andpasting.
And now we can just, make the AIgo do it.
And then you can plan your triparound, the activities that it's
set forth all the way down from,the distance from where you're
staying to a budget.
Free activities, if you're anoutdoorsy person, if you're a
(25:36):
hike person, or if you're alounge by the pool person, it's
just incredible.
Don Finley (25:41):
We live in a society that basically, we went from
having information scarcity inthis place to going to a place
that was informationallyabundant, if we look back 40
years, there was a generalbenefit to being able to
remember something and to beable to apply it.
And now in an informationabundant society, the value is
in how I can synthesize theinformation and how I can
(26:04):
pattern match against it andfind the relationships.
of the sea of information that'sout there.
Now with LLMs, we have a toolthat can do that.
And it's coming into that space.
And I know with O1 Preview andthe future iterations of where,
ChachiBT is heading, as well asI know others are, that
(26:25):
reasoning step is getting a lotstronger and being able to plan
forward and do the things thatyou're talking about, which is
just an amazing, space that welive in.
But I think you're hitting onthe key activity here of, You
got to interact with it and tryit and see, what it can do to
help you.
Because if you are planning atrip, it's going to help you in
(26:46):
some way to sit down and say,all right, can you at least get
me farther along?
And I know I personally use,chat GPT for exercises where I'm
not the strongest in, Likemarketing and sales.
Isn't my strongest suit.
But I do it and chat GPT hasbeen a nice reflection point for
helping me to advance my skillson there.
(27:07):
A partner in that collaboration.
one thing I would love to knowis what do you think is the
activities that people can focuson to help them like either
adopt this or additionally getprepared for, even more changes
that are coming in the future.
Dan Evans (27:22):
think just using it, I've talked to a lot of
professionals who are stillusing these tools at a very
basic level.
they're going in, asking,ChatGPT to write an article
about this.
And that's the extent of theprompt.
Don Finley (27:41):
Yeah.
Dan Evans (27:42):
And, they always say if you want great answers, you
need to ask better questions.
And if you want great outcomes,you need to ask or tell the AI
be very specific about what itis you're asking it to do, how
you want it to look, what typeof tone, what type of style,
this is just one example, buthaving that kind of, it's like
(28:06):
you're the coach for the AI andthis is where the human really
plays the part in making thesesystems work.
Don Finley (28:15):
Yeah.
Dan Evans (28:16):
I think for your listeners here playing with the
tools, trying different things,getting on YouTube University
doing some studying, going toReddit, do some studying on, how
to get, Prompts that createdesirable outcomes and then
innovating off of that.
I really think that is how youcan position yourself for the
(28:38):
future and maximize.
Don Finley (28:40):
Dan, I gotta say, that's honestly just great
advice on this.
Simple.
And at the same time, like it iswhat's necessary.
You've got to get comfortablewith these tools.
You've got to try them out.
You've got to figure out likewhere it's working for you,
where it isn't working for you.
And that's really helpful foreverybody to understand.
so I really, I just want tothank you again for taking the
time today to talk to us andit's been an absolute blast
(29:01):
having you on.
Dan Evans (29:02):
Yeah.
Thank you for having me.
Don Finley (29:05):
Thank you for tuning into The Human Code, sponsored
by FINdustries, where we harnessAI to elevate your business.
By improving operationalefficiency and accelerating
growth, we turn opportunitiesinto reality.
Let FINdustries be your guide toAI mastery, making success
inevitable.
Explore how at FINdustries.
(29:26):
co.
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Amy Robach & T.J. Holmes present: Aubrey O’Day, Covering the Diddy Trial
Introducing… Aubrey O’Day Diddy’s former protege, television personality, platinum selling music artist, Danity Kane alum Aubrey O’Day joins veteran journalists Amy Robach and TJ Holmes to provide a unique perspective on the trial that has captivated the attention of the nation. Join them throughout the trial as they discuss, debate, and dissect every detail, every aspect of the proceedings. Aubrey will offer her opinions and expertise, as only she is qualified to do given her first-hand knowledge. From her days on Making the Band, as she emerged as the breakout star, the truth of the situation would be the opposite of the glitz and glamour. Listen throughout every minute of the trial, for this exclusive coverage. Amy Robach and TJ Holmes present Aubrey O’Day, Covering the Diddy Trial, an iHeartRadio podcast.
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