August 12, 2025 • 45 mins
I am always looking for ways to improve. Send me a text and let me know your thoughts! - Kevin
"I'm having more fun now at work than I can ever remember." When Ryan Bearden shared this feedback from a client who had gone through his AI training program, I knew we were onto something special in this conversation.
The noise around AI implementation is deafening, but what's often missing is practical guidance on how to actually get your team using these tools effectively. Ryan cuts through the hype with refreshing clarity, drawing on his 25+ years of B2B marketing leadership at companies like AT&T to offer a pathway that works.
What makes Ryan's approach unique is his insistence on applying AI directly to your team's current workload. "Work on your work" is his mantra – no theoretical use cases, no abstract concepts. The transformation happens when people see AI improving their actual deliverables, often within days of starting training.
The "transformation journal" concept he introduces is brilliantly simple yet powerful: documenting exactly how AI impacts each task, from time saved to quality improvements. One client discovered they were saving three full days per month per person – but more importantly, they were redirecting that time to strategic work that had previously been impossible due to bandwidth constraints.
For executives feeling pressure to accelerate AI adoption, Ryan offers valuable perspective on setting realistic expectations while still driving meaningful change. "Start small, see what could be possible" provides a framework that builds confidence rather than creating resistance.
What struck me most was Ryan's observation about human connection in the AI implementation process. Creating space for teams to share their experiences – both successes and failures – accelerates learning in ways no structured curriculum can match. The serendipitous conversations that emerge when teams discuss their AI experiments often reveal the most valuable insights.
Whether you're just beginning your AI journey or looking to scale existing initiatives, this episode offers a roadmap for implementation that balances ambition with practicality. Subscribe now and join the conversation about how to make AI work for your marketing team without the overwhelm.
🎧 Tech Marketing Rewired is hosted by Kevin Kerner, founder of Mighty & True.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Kevin Kerner (00:00):
Hey everyone.
This is Kevin Kerner with TechMarketing Rewired.
I'm right in the middle ofbuilding out AI training for my
own team, and when I talked toRyan Bearden, my next podcast
guest, last week, I knew I hadto get him on the podcast.
Ryan spent over 25 years in B2Bmarketing and now helps teams
actually implement AI in a waythat's practical, not
overwhelming, which is one ofthe mistakes I was making with
(00:21):
my team earlier.
In this episode we talked aboutwhat adoption maturity really
looks like right now, how to getstarted without getting stuck,
and why journaling yourexperiments might be the most
underrated AI tactic out there.
We also got into how agenticworkflows are changing, what
collaboration looks like andwhat most executives still get
wrong when they try to scale AIacross the organization.
(00:44):
So this is really fantastic,especially if you're an
executive like me that's tryingto figure out some AI training
for your team.
So I'm really excited for youto hear it.
Let's get to it.
This is Tech Marketing Rewired.
All right, hello everyone, andwelcome back to Tech Marketing
Rewired.
(01:04):
I'm your host, kevin Kerner,and today's guest is Ryan
Bearden, founder of BeardenMarketing and AI Solutions.
Ryan's got over 25 years ofleading B2B marketing at
companies like AT&T and someother top, very large SaaS
brands really innovative SaaSbrands.
Ryan now helps businessesimplement real-world AI
strategies that actually work,and what I know him for is
(01:26):
bridging the gap betweentechnical innovation and really
practical human-centricmarketing and really making AI
feel approachable along the way.
So it's great to have you here,ryan.
This is a great topic.
I'm really excited to have youon the show.
Ryan Bearden (01:40):
Hey, kevin, thank you so much.
It's great to be back with you.
Kevin Kerner (01:42):
Yeah, yeah, it's been a while since we've talked.
I wonder if you could well.
First of all, why don't youjust give us a little
introduction on who you are anda little bit about the company?
Ryan Bearden (02:03):
Yeah, so I, as you mentioned, I've got over 25
years of marketing experience,predominantly B2B marketing.
I did a little couple ofdetours over on the consumer
restaurant side we won't go intothat, though and a couple of
years ago I really noticed thisAI thing, and in my previous
role, I actually was looking athow could we start implementing
with this, testing this, andwhen I left that role, I really
immersed myself in it and wentall in on it and went and did
some certifications training andtransformation certifications
(02:24):
and have really kind of built mybusiness all around this, and
so what I do is I work withcompanies small to mid-sized
businesses and really help themto gain practical skills on
applying AI to their jobs, totheir work, in a very, what I
believe, easy to understand,easy to implement in very
practical ways, and I'm enjoyingthe heck out of it, to be
honest.
Kevin Kerner (02:43):
Yeah, that's awesome.
So this AI thing is not a fad.
It's actually something that'sgoing to stick around.
Ryan Bearden (02:49):
I believe so.
Yes, I certainly hope so,because I need to find another
gig, but no, I really trulybelieve.
You know, all the hyperboleyou're going to read out there,
aside, it is really.
It is a very real, verytangible thing that I think is
only going to become more so inthe coming years.
Kevin Kerner (03:10):
Yeah, I'm super excited to talk about this stuff
because it's been six months orso since we've talked and, of
course, the whole world haschanged over the six months.
Ryan Bearden (03:14):
It's a lifetime ago.
Kevin Kerner (03:14):
Yeah, it's unbelievable.
My first question is just tryto maturity.
Like are people more, how muchmore mature are they from where
we were at six months ago?
Like, what are they good at andwhat's missing in terms of,
like, their understanding?
I wonder just, are peoplegetting better at this stuff at
this point?
Ryan Bearden (03:32):
You know I mature is an interesting word I will
use aware.
Are people more aware of whatit is, what it can do, what
could be Absolutely?
Is the confidence there?
No, not in my experiences, andI don't say that as a negative,
I'm not knocking people,obviously but I think that it is
adoption, maturity andcompetence around it.
(03:55):
I think is nowhere near whatyou might read in the trade
publications on LinkedIn andother social channels, but we're
getting there.
It's just, you know, I think,human beings, we move much
slower than technology.
Right, we have to getcomfortable with it, we have to
learn how to use it, we have tobe unafraid of it, and we do
that through knowledge, throughunderstanding, through education
.
So I think we're moving towardsthere.
(04:15):
I would say maybe a slightincrease in maturity, but it's
really.
I still say we're still in theinfancy of this in terms of
mainstream adoption, to beperfectly honest.
Kevin Kerner (04:23):
Yeah, do you think the hype is kind of it kind of
drives a lot of urgency to tryto learn, but it's it's actually
catching up to the height isdifficult because it changes
everybody and we just had agentslast week and it's like it just
changes so quickly.
Ryan Bearden (04:36):
Yeah, it's really something else.
But you know, again, the peoplethat I'm working with and I'm
speaking with it's.
You know, hey, I've openedChatGPT.
I've used Cloud a little bithere and there, but they really
don't know how or.
And there's experimentation'sgreat.
I'm a big believer in it.
I tell people all the time justopen it up, like, stop reading
Grox, better than Gemini, betterthan Chat.
(04:57):
Just open it up and startexperimenting with it.
Start playing with it andyou're going to get comfortable
moving from experimenting andplaying with it at an individual
level to more.
We're having a real impact onhow we work and the outcomes
that we're driving with ourbusiness.
I still think we have a goodways to go.
Kevin Kerner (05:12):
Yeah, and six months ago too, I was thinking
like the discussion withleadership was probably don't,
maybe even don't use it or useit.
You know, people might havebeen scared to use it.
Now it's probably.
Well, I heard in the we did adinner last week where I had
some executives speaking aroundthis stuff and they were getting
(05:33):
pressure now from theirexecutive teams to use it and
use it fast Are you seeing thatsame thing.
Is that what's driving thaturgency?
If you're seeing the same thing?
Ryan Bearden (05:41):
Yeah, Just pressure it's.
It is the you know in this dayand age, right?
If you look at the businesslandscape, there's always
pressure to perform, right, anda lot of this is how do I say
this?
Fabricated pressure, right,Like, well, our goals are we
need to grow by 25% next year?
Well, is that very realistic,right?
I mean, you and I have workedwith companies.
I've worked, you've worked withcompanies.
(06:02):
I've worked for companies thatare very hyper growth focused,
private equity funded, and theyreally want to grow fast and
they private equity groups andother investors want a return on
that investment.
We all get that, we allunderstand that.
And AI, I believe, and in somepeople's eyes, is that next
darling that's going to help usget there, going to help us
double down and get there, andso I do think a lot of the
pressure is coming there.
(06:24):
But I think there's also on theflip side is I don't even know
where to start.
And if I start researching, Istart searching, I start digging
into where to start, I'm evenmore overwhelmed because it's so
easy to get overwhelmed withwhat's out there, and so I think
that is driving what I'll callsome sense of paralysis.
It's just not knowing where tostart and you know, do I just
(06:47):
get a blank check to go do this?
Or how do I do this smartly?
How do I do this effectively?
That's not easy to navigate Ifyou haven't dug into it this has
been my whole life for twoyears and if you haven't done
that, it's not super simple togo and find your starting point
to go and it's going to lookthree different companies.
Kevin Kerner (07:04):
It's going to look three different ways.
So in the companies that you'recoaching the leaders, I'm in
the same boat.
You know we're all trying tofigure out as business owners,
like, how do you get your teamor team managers?
Or, you know, departmentmanagers, how do you get your
teams around this stuff?
Is it that they don't knowwhere to start when they come to
you, or do they have an ideaabout doing it a certain way?
Like are you having to coachthem from day one, Like here's
(07:27):
how you do this, or do they cometo you?
Ryan Bearden (07:30):
and say hey, I want these things implemented.
Yes, a little bit of both, andthere's definitely an eagerness,
an interest there and a senseof urgency there, but it is.
You know, how I help to frameit with them is let's start
small.
Let's do a pilot.
I'm not asking you to come jumpin bed with me with your entire
organization, your entire team,whatever.
Let's start small and let's seewhat could be.
Now I tell them here's what youshould expect, and I'm very
(07:53):
upfront about that, here's whatyou should expect.
And I do not shy away fromthings like ROI and the actual
results and impact.
I want to put that front andcenter.
What I want to do is I want tohelp you realize these benefits,
these outcomes, these results.
But this is uncharted watersfor a lot of them and a little
scary.
So let's start small and let'ssee what could be possible.
And that really resonatesbecause it gives them a little
(08:16):
bit of flavor, gives them ataste of what could be.
And, knock on wood, kevin,every time I've done it, it's
worked out.
There's been an expansion ofwork.
We want to continue on this.
Hey, with this, pilot's workedgreat.
This current client I'm workingwith halfway through that first
pilot, he was already signing upthe next two cohorts, so
they're definitely seeing thevalue there, and there's a lot
of low hanging fruit, and that'sanother thing that I try to
(08:38):
explain to them is like, listen,we're going to get some real
big wins here.
We're going to learn a lot, butyou're going to get some wins.
I can almost guarantee you that.
And so, once you start showingthose wins, what it really does
is it opens their mind to whatelse could be.
It expands their mind to biggerinitiatives, broader use cases
of it, and what I like to do isto let them get there on their
(08:58):
own.
That's very, very important.
I think of myself as a Sherpa.
I'm going to be with you andI'm going to guide you, but
you're doing the work.
You and your teams are doingthe work, because if you're not,
then you're getting nothing outof this, and shame on me.
But letting them get to that,oh wow, I see the impact.
This is really going well.
This is really going great.
We're four weeks in and theteam is already doing all these
wonderful things and it clicksand it's like, oh, it clicks.
(09:27):
And it's like, oh gosh, what ifwe did this in this part of the
group.
What if we did this for ourstrategic planning?
Kevin Kerner (09:29):
you know how do we apply it to that?
This bigger, larger scale, moreexecutive focused initiatives?
Yeah, yeah it's.
It's very similar in some waysto the whole digital
transformation thing that washappening yeah five or six years
ago.
But at the digitaltransformation time it was big
platforms.
Yeah, it wasn't superaccessible.
It it was top down and whatthis is is more of it's AI
transformation.
It's more bottom up.
(09:49):
It's sort of the pressure isdifferent.
I mean, you're still as abusiness owner, you still know
you need to do it, but you knowyour people are probably already
using it anyway.
It's almost like it's digitaltransformation without the
guardrails.
It's just like all over theplace, crazy stuff.
Ryan Bearden (10:04):
No.
And one thing you said that Ithink you really hit the nail on
the head, which is bottoms up,and I am a believer that and I'm
not saying top down is justgoing to fail, I'm not saying
that at all but when you startto see how it's impacting
day-to-day work individualcontributor level, people
manager level then you start toreally open your eyes to what
(10:26):
could be at that next level, asI said a minute ago, and so I'm
a big believer that start in thetrenches and start to see the
impact in the trenches, becauseit's not just, oh my gosh, we're
doing this faster, but whatelse are we doing now?
And that's probably one of myfavorite things is I ask my
students to students.
It feels funny saying that but,I, ask them to.
(10:48):
I have what's called atransformation journal where
they go fill it out andessentially just ask them each
time you use AI on a deliverablego what was the deliverable?
Describe it a little bit.
How did you use AI?
How long does it normally takeyou, how long did it take you
with AI?
And if you do this on a regularbasis, how much time do you
anticipate it saving each month?
But the more important questionin all that is was the quality
of the output, the same, betteror worse?
Because if we're just doing abunch of the same stuff, faster
(11:11):
but crappier, well, what's thepoint?
Right, like we're movingbackwards, and so that's really
important.
I could point all day long tohere's how much time you're
saving, here's how many hoursthis team is saving, and it's
really that first cohort at theend of it each month going
forward.
This is based on their words,kevin.
They are filling out thisinformation, but it's the two
(11:31):
biggest things I point to.
Is you just saved like threedays each person per month,
three full days in time?
But also, more importantly, howare they talking about they do
their work?
How are they talking about howthey do the work?
How are they talking about thethings that they're doing now,
that they weren't able to dobefore, and that, to me, is a
little bit fuzzier when you getto a ROI conversation with a CFO
(11:53):
, but, as you well know, that isso important.
I mean, think about your team Ifthey're completely doing hey, I
saved five hours a month overhere, but now I'm doing this.
I'm spending those five hoursdoing this, which is more
strategic work new businessopportunities.
How are we expanding theopportunities with this existing
client in your world?
That's the kind of stuff that'sreally really super important.
(12:13):
And then, once they see that,then at the leadership level,
it's really gosh.
These are all the things thatwe wanted to test, but they're
always on the back burnerbecause we never had time.
Well, now you have time.
You have time to do thosethings that were more ambitious
but just out of reach because ofbandwidth.
Kevin Kerner (12:29):
Yeah, that's great .
That's really great.
Well, we talked when we weresetting up for this about the AI
education stuff that we'redoing at Mighty and True, and
you were really helpful inguiding me on a few things I
want you to take me through,because I know a lot of people
are thinking about training fortheir teams.
I want you to just give us someof the different tactics you
(12:51):
use for training that aremeaningful, and I think the one
thing you told me about was likethere's an overwhelmed
component of all this andthere's keeping things practical
.
Tell me, tell us, a little bitabout the training formats that
are really having the mostimpact.
Ryan Bearden (13:06):
So one of the things that I really focus on is
, you know, when I first startedgetting into this, kevin, I was
really dead set on.
I really want to be on thecutting edge.
I want to stay on top of allthe new stuff that's coming out,
and you actually do this quitewell.
I will say, I don't know howyou do it, but you do it pretty
darn well.
Yeah, it drives my team crazy,but it's like I quickly realized
(13:27):
all of this kind of newswhether it's agents, any sort of
automations that is so far offfrom the mainstream, when most
companies have maybe mostindividual contributors and even
leaders have maybe openedCopilot or Gemini and done a few
things.
And so I quickly like settledown, ryan, let's go focus on
(13:49):
practical skills at the mostbasic level, and what I truly
believe in my experience ofplaying with various tools and
looking at them is mastering thelarge language models, and I
don't care which one you prefer.
Mastering those is critical,foundational skills for you to
really harness AI to its fullpotential, not only today, but
in three years, when it willlook vastly different than it
(14:11):
does today.
I also believe that the LLMslarge language models will be
able to do the majority of whatthese point solutions claim to
do just as well, if not better,and so what I really do, my
approach, is we're going tofocus on building your skills,
on using the large languagemodels in your work, and I think
that in your work is a reallyimportant key is that I might
(14:32):
have a few slides.
I have, maybe, in each trainingsession, two to three slides
but we spend 95% of the time.
What are you working on today?
What is the deliverable you'reworking on this week?
What is a problem or obstacleyou're facing this week that
you're having trouble overcoming?
Okay, so that's what we'regoing to do today.
In each session, it's laserfocused on something you're
working on or something you'retrying to overcome.
(14:52):
And once you really apply it totheir real work and one of the
things I always harp on one ofthe slides I show them every
time is work on your work is,you know, one of their three key
principles?
Ai is your blank.
For each person that's verydifferent.
How is AI going to help youtoday?
Incremental gains You're goingto get better and better and
better at this each time.
But, most importantly, work onwork.
I'm not here to pull up arandom scenario and show you how
(15:14):
cool the tool is.
We are here to work on yourwork and that has really
resonated the most.
And when they see the impactand they see, think about how
much time we spend at our jobs.
Kevin, over the course of ourlife we will spend far more time
at our job than we will withour families.
That's just a fact.
If I can show you how to do itfaster, easier and even better,
(15:35):
then we're all going to win.
That is my ultimate goal.
And I had one of the clients inthat pilot program.
She texted me a few weeks intoit.
She goes I'm having more funnow at work than I can ever
remember and I thought, wow,that really is awesome.
That makes me feel good, thatmakes me feel great.
And she's in a very stressfuljob.
(15:55):
So to hear that was reallygreat.
And I think that is really thekey thing is we're going to
focus on your work.
It's eight.
My training, my kind of coretraining, and I can customize
this for anybody and I've doneit before but, like the core
foundational program is eightsessions, just like martial arts
white belt all the way to black, and each one it focuses on a
different area of your business.
(16:16):
We're going to create SOPs.
We're going to automate somecertain deliverables.
Once we've created thosestandard operating procedures,
I'm going to teach you how totap into experts who, whatever
problem you're facing todaysomebody has written a book
about it, I can almost guaranteeyou, or done a TED talk about
it.
I'm going to show you how totap into those to create an
action plan to overcome thischallenge, to creating GPTs
using APIs and automations, yada, yada, yada, the whole gambit
(16:37):
of things.
But it's really.
You're going to walk away.
I guarantee you will walk awaywith skills that you never would
have been able to develop onyour own.
Kevin Kerner (16:46):
What are those?
I mean, that sounds great.
What are those LLMproficiencies?
What are the types of thingsthat you would say these are the
proficiencies that you need,that you need that you help
people improve on?
Like, I think of them kind ofblind spots at this point,
because it's like they justdon't know.
And if they if they did knowthe LLMs could do certain things
(17:06):
, there'd be a reflex to usethem more.
But what are they from yourperspective?
Ryan Bearden (17:10):
Yeah, I don't know how this answers your question,
but let me say it and then I'llfind a better way to say it.
The single biggest thing whereI see people get hung up is
you're trying to interact withGemini, chatgbt like it's
software, and chat GBT like it'ssoftware.
And well, I put this in thereand it didn't give me what I
wanted.
This doesn't work.
This is dumb or I don't knowhow to use this or whatever.
And what I tell them is talk toit like it's a person, like
(17:34):
it's an intern or a colleague.
And if you have an intern,you're going to give them.
You guys do internships.
You're going to give an interna task, go do this.
That intern comes back to youand says here's what I did, and
you go well, this isn't what Iwanted.
Well, you're not going to firethat intern, you're not going to
berate that intern or whoever.
You're going to give themfeedback.
You're going to give themadditional context.
You're going to redirect themand have them go back and do it
(17:55):
again.
That's how you communicate withAI.
That is how you get the mostout of it.
And so what I tell people isdon't worry about becoming an
expert, prompt engineer.
By the way, ai can createprompts better than you can, I
promise, and I'll show you how.
But you need to master how tocommunicate what it is you need,
what you're looking for.
Can you clearly articulate that?
(18:16):
And it's funny, kevin, becausethink about how many things
happen in Mighty and True thatare on autopilot, where, if I
ask you, if I ask Jennifer, if Iask anybody on your team, walk
me through the steps you take todo this.
That's not easy because, well,I just do it automatically.
It happens automatically.
And when you're thinking aboutimproving processes, when you're
thinking about acceleratingdeliverables, you need to be
(18:39):
able to, which is so funnybecause it's a very human
element, right, it's a veryhuman thing.
Can you break this down intosteps and the tasks?
Can you communicate?
This is what I'm trying to do.
This is where I'm struggling.
This is where I need help.
If you can do that, you're like60% there, you're 60% there,
and then it's just kind oflearning to go back and forth
and then accepting the fact thatI'm going to get not so great
(19:01):
output sometimes, but if I keepworking with it, I'm going to
get a better output, and I thinkthat that is a core,
fundamental element of gettingsuccess from these tools is
knowing how do I communicatelike this, how do I think like a
human and communicate like ahuman, because once I do that,
then this tool is going to,which sounds counterintuitive,
but this tool is going to giveme so much better output, so
(19:22):
much better results.
Kevin Kerner (19:23):
I think that's the key thing.
A lot of the people that areworking with the agents now are
anthropomorphizing the agentwith a name, like they call
their agent.
It's literally a worker ontheir behalf.
A lot of the tool providers aretalking about it that way,
which I think we'll come to atsome point.
They're not.
They're not ready yet at thispoint.
Ryan Bearden (19:41):
Yeah, we're still very early.
There's this guy, adamRobinson's his name, his company
are I'm going to butcher this,or anyway.
He owns a SaaS company and he'svery active on LinkedIn.
He's very he's kind of like you, he's very open.
Here's what we're doing, here'swhat we're trying to build this
company and if it doesn't work,I'm going to tell you.
And when it works, I'm going totell you.
And he put a post out recently.
It was like all five of ouremployees are going away for a
(20:03):
week and we're having theseagents run the company and my
first thought was environment.
But I that scared, like I'muncomfortable and I'm not
associated with your company andI'm a little uncomfortable with
that.
But yeah, I mean I, I, I thinkwe are early in that sense, but
I I'm not a fan of the namingyour agent type of thing, cause,
(20:23):
for we could go down a rabbithole for you know, for another
hour, just on the psychological,emotional aspects of that.
But it is funny, cause we willget there.
Where you are, you know, youtalk about it where you're
managing three or four agents,you might have someone on your
team that's managing three orfour agents that are doing work.
Hopefully they're, you knowthey're spot checking it, yeah,
but it is.
That day is coming.
I think it's further off thanwe think, but it's coming.
Kevin Kerner (20:45):
If you can get someone to be more mature in how
they're communicating with theLLM and prompting and they, you
know they're getting good atthat what's the next level?
What's the thing that you dowith them to get them to the
next level of proficiency?
Or do you have to Do they justthe spark is already there, they
just take off.
Ryan Bearden (21:04):
I think that's it.
I mean, I think it's so organicand the way that I set up my
training is very much like youknow.
I mentioned the transformationjournal and there's also like at
the end of each session likethere's homework, where you know
you go submit your homework andyou get certified for that belt
for that particular session,but going off and doing the
homework I have so much fun withthat I really encourage them to
record their screen andthemselves talking through.
(21:25):
You know like two to threeminutes record your screen to it
.
But I'm like you don't want todo that, put in a document
whatever.
But when I go through thehomework and I read it and they
usually do it within 36, 48hours after the session they're
getting it, they're grasping itand they're applying it
immediately what we learned inthat session.
They're applying it immediatelyto another deliverable and so I
(21:46):
do think it's pretty organic.
I like to tell people that whatI do is you do AI training.
I give people confidence andcapacity and once you give them
that human beings arespectacular, spectacular species
, right, we can do anything.
Kevin Kerner (22:08):
Yeah, your Sherpa thing is pretty much.
Ryan Bearden (22:10):
They're not on my back, I'm guiding them and
saying now, you see this.
And even I had the hate SVP ofmarketing.
He came to one of the first.
Back I'm guiding them andsaying now you see this.
And even I had the SVP ofmarketing.
He came to one of the firstsessions.
I told him I was like you, comefor free, I want you there.
I won't even charge you,knowing he wouldn't come to all
of them, but it was his firstever experience spending this
much time focused on it.
And the first thing he said ishe joked and said you've ruined
(22:33):
my life.
You've opened my eyes to somany rabbit holes I can go down,
my mind is spinning about whereto go and I was like good,
that's what I want.
I hopefully ruined your life ina good way.
But it is so organic, kevin, andit's just you know this well
where there are things where youcould take the textbook, you
(22:54):
could take the syllabus from acollege course or whatever and
never go to the class, butyou're probably not going to
pass the test, you're probablynot going to do well, right.
It's that there's that wholeelement of being taught, being
led down the path of learning,versus trying to go do it on
your own, and I think that thatis that's where the power is,
and you know the cool thing Iwill you thing kind of to answer
(23:14):
your question another way isthat first cohort we did they
were like.
Afterwards they were like, well, what's next?
We want to keep going, and soI've actually built a few
follow-up sessions that we'redoing within where we're going
to get more into moreautomations, more agent type,
even like introducing them toRelay, which you and I know very
well.
So some of these other toolsthat are out there, where it's
again, this is not a silverbullet for your organization,
(23:37):
this is getting your mindwrapped around that next level
of agentic workflows andautomations that are there.
Kevin Kerner (23:43):
And so once you get them to that level and
proficient, then the force isout of the table and they're
going to go off.
They're going to go.
Do you think?
I really love the idea of thataligning the Sherpa, the guide,
with the work that they'recurrently doing, because I can
immediately see that, oh, thisthing, this actually helps me in
my day-to-day job.
Are there circumstances whereyou want to train them in a
(24:07):
broader way, like the reason?
There's a question behind thisquestion, like we're we're
trying to create this, this,this environment're.
Yeah, we're trying to createthis, this, this environment of
what we call collaborativedelivery.
So, where you have a person whomight just be as a very specific
role without it.
Now they can stretch to anotherrole because they have this ai
assist with them now they mightnot have all the context of, you
(24:28):
know, whatever that role is,but they can at least help what
they can pitch in, and so it's'san amplified initiative for us
because we can have employees gooff and do things.
Is it worthwhile giving anemployee more perspective than
just the stuff that they work on, like having them work on
exercises that are not relatedto their role, just so they can
see how those things work?
(24:49):
Have you tried that?
Ryan Bearden (24:50):
Yes, I have, and it's a great, great point.
And I think there's certaintypes of organizations where
this is really good.
I mean, I think about yourcompany kind of fits this mold a
little bit.
But think on the non-serviceside, not agency side, like
you're a startup and you gotfive or six employees, well, you
probably don't have an HR team,you probably don't have a
marketing team, let's be honest.
(25:11):
But you should probably havesome HR functions happening,
deliverables happening,marketing things happening, and
so, in that sense, how I wouldapproach, I do think it's a very
good idea how I would approachthat is much more on a workshop
basis.
I've actually done this.
Actually, one agency that Iworked with their creative team
I actually built.
I knew their, I had access totheir processes.
(25:33):
This is our process, our bestpractices on how we do.
And for the creative, for theirops team, I took them through
the train because I knew theyneeded these kind of Swiss army
knife skills.
But for the creative team I didI think six or seven I'm going
to do a workshop for everyaspect of your process and I'm
going to show you exactly how AIfits into this.
So we're actually going to dosome real client work, not the
(25:55):
actual deliverable, but we'regoing to do sort of in unison,
if you will, in parallel.
We're going to do some realclient work incorporating AI to
give them a sense of how thiscould happen.
I would do that something verysimilar for a company of like
hey, here's this person, she'she or she's a very strong
project manager.
They don't really havemarketing experience or we need
really to get some HR thingsdone.
(26:16):
I would go and build that.
Let me show you how to do this.
The one caution I would say tothat and this is what I the rush
to automate and to there's alot of fear out there amongst
the creative teams.
I think to uncertainty aroundthis is I can teach someone
who's got an HR background howto use AI to do marketing
deliverables, but what I can'tdo is show them what good is.
(26:40):
The risk is when the outputcomes from.
You know you're building acampaign or you're writing a
blog something as simple as thator an email campaign, knowing
what is good and why or where itcould be approved as why.
I can help you get there prettyfar with AI, but I still
believe the human in the loop isthe single most important
aspect to all of this.
(27:01):
Or maybe expert in the loop,yeah expert in the loop, exactly
right, not just any human, butan expert or a specialist in the
loop to be able to understand.
This is good quality, this isappealing.
This is hitting the points ofour target audience, and here's
why good quality, this isappealing.
This is hitting the points ofour target audience and here's
why that's the only risks, andthat's a big one.
That is a big one, butabsolutely I could walk in and I
feel confident.
(27:21):
Within a month I could have alot of people cross-trained on
different functions.
That's, that's an easy thing todo.
But again, it's thatdiscernment of quality that is
just important that people needto be aware of.
Yeah, we got a lot of, as Imentioned at the start, that
people need to be aware of.
Kevin Kerner (27:33):
We got a lot of, as I mentioned at the start, we
got a lot of questions last weekat the dinner about, you know,
executives wanting this stuff toroll out real fast.
Ryan Bearden (27:41):
Yeah.
Kevin Kerner (27:41):
And maybe a couple questions.
One, what guidance would yougive those like these were all
marketers, so it was just thatspecific department.
What guidance would you givethem on how to message that back
to the executive team, likewhat?
What?
It seems like you'd want toacknowledge it.
Yes, we want to use AI but,like I, have another question
(28:01):
around measurement, like how doyou, how do you prove the ROI on
this stuff?
Ryan Bearden (28:05):
Yeah.
So the first question I wouldask to answer that question is
how do you define fast?
Like it's fast fast at a boardlevel might be in the next six
months.
I want every single person inthis company fluent in AI.
Okay, Well, what does that mean?
Like, do you want them buildingAI tools or do you want them
using AI to do their jobs,incorporating it into their
processes?
Kevin Kerner (28:25):
Or less people or less people.
Ryan Bearden (28:27):
Yeah, and I try to steer away from the less people
conversation, not because I'mscared of it, because I do not
think that is the right lens tolook at this through, at least
not initially.
That could be a byproduct ofall the work that goes into it.
Let's say for the six months.
But I really, personally, Ijust like I'm here to
supercharge your people, not getrid of them, and so.
(28:49):
But with that said, I would saylet's say it's six months.
I think that is a veryreasonable amount of time to
pilot some programs, expandthose, scale those programs
Obviously, find what's workingand scale that and begin to have
it across your organization.
If we're talking AT&T, probablynot, but if we're talking a
(29:12):
500-person company and dependingon the capacity they wanted to
do, I think that's veryrealistic.
The thing is, is that what Ilike about my approach?
I'm biased, but what I likeabout my approach is because I
am applying it to your job, yourday-to-day.
The adoption and implementationis going to be almost overnight
, and when I say that, what Imean is after one, two, three
(29:32):
sessions you're going to bedoing various things differently
and better, like I guaranteeyou you will, and the next time
I see it not work like that willbe the first time I see it not
work like that.
So I feel confident saying that.
But I think it really comesdown to listen.
We want to do this fast.
Okay, well, what is fast?
So let's build a roadmap, let'sbuild a plan and let's define
success.
I think to your point.
(29:53):
One of the biggest things, too,that people often miss, kevin
and I've brought this up a lotwith workshops I've done with
companies as well as the onesthat I'm training is you should
really have sort of policy orguidelines in place.
Those policies can change.
Think of your first AI policythat you create and maybe it's
(30:14):
for a marketing team or a salesteam at first, but it should
have guard rails.
But the guard rails are rubber.
They can bend because you don'tknow what you don't know and
the more you get into it, themore you see.
Then that might help reshapethat AI policy.
But I think you have to havesome guard rails in place.
There was a statistic I readtoday, as a matter of fact, of
the number of people that areemployees that are still hiding
(30:37):
their AI usage from leadership,which should scare the hell out
of.
It's very high.
It is very, very high 60 pluspercent in this one study, but
also within that.
It was a survey.
They talked to 50,000 workersacross the globe, but there was
also there might be puttingcompany information into LLM.
(30:58):
Maybe they're using a freeversion of the LLM.
They're not considering theprivacy and security things that
are really into this at aleadership level.
Eyes wide open of here's whatwe're going to go do.
Here's our gameplay we're goingto have some, establish some
(31:22):
guardrails first, and then we'regoing to go, let's just say,
six months, and at the end ofthat six months we're going to
reevaluate, revisit.
Where have we seen the mostimpact?
Where have we seen the mostsuccess?
Kevin Kerner (31:37):
Yeah, success.
Yeah, I was thinking to you.
I think it's all good and Iagree with it all.
I think the executive questionthat I heard last week was kind
of around overexcited executiveswanting to push it into
marketing such as there'd behuge efficiency gains, whether
that's in fast for stuff or morepeople.
If I'm a CMO, I might saythat's great.
A we're already using it.
We've been using automation foryears.
This is just automation withsome additional capabilities, so
(31:59):
we need to implement it like weimplemented our automation and
we can get better at that.
But it's not all ready forprime time.
What you're hearing on LinkedInand all the other things is not
exactly what you're going toget out of my marketing team.
They're just not ready yet.
We're not going to have agentsrunning everything.
We're not going to haveautomations with AI on top of
them.
Yet Now there are some pointsolutions that do that.
(32:20):
I think there's a really goodcase for SDR customer service
use cases, and there are a bunchof those.
But from the marketing team,there's so much nuance in
marketing You're reallyoverreaching to say, let's just
put AI in place and, you know,start seeing massive efficiency
gains and less people.
(32:41):
That's just.
Ryan Bearden (32:42):
That's right.
I think the you know what Iwould say to.
That is number one there.
What doesn't get near theheadlines that you know?
You and I have read theheadlines of.
You know Microsoft's cutting6,000 jobs and they're going to
do automation, duolingo.
You know a lot of thesecompanies that are out there
that have, like, been very boldcome out.
You know bold leadershipmandates, for lack of a better
(33:03):
word.
But what you don't hear aboutare the companies that cut
customer support teams becausethey want to automate it with AI
, that cut marketing people orSDRs because they want to
automate it with AI.
Well, six months later, whatare they doing?
They're hiring those peopleback.
Why?
Well, because it's notperforming as well as a human,
and you know not to sound likean armchair quarterback, but
(33:26):
yeah, I mean, somebody is goingto have to be the company that
goes all in first and and likehas to back up and say, well,
and like has to back up and say,well, that didn't work out the
way we wanted it right.
And you know, no matter whatyou know digital transformation,
e-commerce, whatever we go back, you know last 30, 40 years,
any innovation like that there'salways the people that are the
early adopters that are rushinginto it.
So, but also let those be thelessons that we don't have to go
(33:51):
and repeat, right, like, don'tgo with a mindset that you're
going to get rid of 5% of yourmarketing team because of all
this.
Go with a mindset of we'regoing to make smarter decisions,
we're going to be able topersonalize, to get more
personable with ourcommunications and our messaging
, we're going to be able tosupport our salespeople better.
We're going to get to marketfaster.
We're going to know what ourcompetitors are doing well and
(34:22):
not well faster.
Those are the things where it'slike I will show you how to do
all of those things and thensome very quickly and then start
to decide are we seeing theimpact?
What is the impact of this?
Is it fewer lost deals?
Is it higher conversion?
Put the marketing hat on Higherconversion rates, lower cost
per opportunity, more closerates, whatever that may be.
But the one thing I will tellyou, which, again I say, is
foundational I'm not hanging myhat on the fact that you're
going to be able to do the samework in a third of the amount of
hours.
That is a good thing, but it'snot the end.
(34:44):
All be all.
At the end of the day, is ourbusiness growing?
Is it functioning moreefficiently?
Are we getting revenue growingwith revenue?
Are we growing faster?
All of those things.
You got to be able to tie it tothat, which is not terribly
difficult to do, but you justgot to go in there with the
onset from the onset.
You've got to document that andknow that this is how we're
measuring success.
Kevin Kerner (35:02):
Yeah, that's, that's awesome.
You gave me some really goodadvice advice last week or last
time we talked around.
You know different types oftraining stuff that I do.
I just want to really quicklytop five things that you've
learned not to do when you'retrying to train a new group on
AI.
Like, what are the five thingsyou say don't do this If you're
(35:23):
going to try it?
Ryan Bearden (35:25):
Yes, the biggest one is no matter how much
they've told you they use AI orhow much experience they have
with AI, don't throw more atthem than your program already
does.
I did this one time where Ithrew like, hey, I've been using
it for three to six months.
It's like okay, well, I'm goingto kind of accelerate these two
sessions I'm going to puttogether and you're like nope,
(35:46):
didn't work.
I mean, you used this wordearlier, so overwhelmed they got
so overwhelmed.
Kevin Kerner (35:52):
Don't overwhelm, that's a good Don't overwhelm,
that's a good.
Ryan Bearden (35:54):
Don't overwhelm that I mean that's.
I cannot say that enough.
That's that looks different forevery single person.
But, like the over, I've got ademo that I do that.
It's just like I'm going toprove to you how well I knows
your job and you potentially putit in your job title or your
LinkedIn profile and it givesyou it's a GPT.
That is matrix of like.
Here's your top eight coreresponsibilities and all the
(36:15):
deliverables.
And I have seen more people justshut down and disengage because
they're impressed but they'reoverwhelmed.
And when you get overwhelmedlike that, it rarely is a good
thing.
So that's the big one is, evenif it seems so basic, nine times
out of 10, every person sittingin that session, that class, is
(36:36):
gonna get something out of it,something positive out of it.
That's the number one thing.
The second thing I would say isit is absolutely imperative.
I push hard, as hard as I can.
They don't work for me.
But do the journaling, takenotes, keep a journal of what
you're doing and how you'redoing it, what's working,
because I really push them.
Also, this is not about megetting numbers that I can go
(37:00):
promote my business If there arethings that you did that didn't
work.
I want to know that.
In fact, more so than thethings that did work, Go,
identify and highlight thethings that are working well and
the things that aren't workingwell, Because that's one of the
things that I tell people is Imentioned to you, like the hey,
talk to it like it's an internor a person, not like it's
(37:21):
software.
But also context is everythingthat's like hey, write me an
email.
Okay, we're going to get acrappy output, so put context to
that.
Yeah, and when you do those twothings, you're going to very
quickly realize what it's goodat and what it's not good at.
And spoiler alert it is notgood at everything.
Contrary to what you might read, it is not good at everything.
Kevin Kerner (37:42):
So don't overwhelm , don't miss the opportunity to
document, which I think is great.
Anything else you can think of.
I'm taking notes for my owntraining program.
Ryan Bearden (37:53):
Those are the absolute biggest ones that I
would say, and this is for youand your position, kevin.
This is important.
So when I I do my trainings, wedo like one hour, like usual.
Wednesdays we do the sessionand then on Fridays I have
office hours.
We're like listen, I'm gonnaopen up the bridge for one hour.
This is your time.
Come to me.
Is there something you'rethinking about?
(38:13):
Or you have another opportunity, or are you struggling with
something we learned this week?
Whatever it is, but when you getthem together, I used to think
that and I still think this.
You know, if you had a trainingsession that had HR, ops,
marketing, sales, all in one,they would get a lot out of it.
And the way that I'vestructured this training is to
where you could have thosepeople together and they would
still get a lot out of it.
But when you have a marketingteam together or an ops team
(38:34):
together, just them talkingamongst each other about how
they've used it, like I just sitback and I'm like this is gold,
the serendipity, this is gold.
Kevin Kerner (38:44):
The opt-in to share.
Ryan Bearden (38:46):
And I went to the SVP when this happened and I'm
like these are the common themesthat they talk about on the
office hour calls, when they gettalking amongst each other, and
it was really cool because hesaid to me it was four key
things.
And he said these are the fourthings that keep me up at night
the most.
And I'm like and now yourpeople are thinking about this,
they're thinking about it indifferent ways, and so the point
(39:07):
there, kevin, I think againfrom a position of leadership
like yourself is let them talkand listen, celebrate, get them
together, yes, and let them talk.
And celebrate the failures.
Kevin Kerner (39:18):
Awesome we're smarter now.
We're smarter now and celebratethe failures.
Awesome.
We're smarter now.
We're smarter now.
Cool.
This is great.
Okay, so I wish I could.
I wish I could go on for more,because I'm taking notes with
all this stuff, or we're in theright in the middle of this
stuff, so super helpful for meand, I'm sure, for others.
I warned you that we do thisthing called uh ai roulette and
(39:40):
I've loaded your LinkedInprofile into a space in
perplexity and that space hassome instructions to try to
throw you off your mark here.
Good, no, it's basically justgive me a crazy question.
Give me a really uniquequestion.
It's been pretty good so far,so I'm going to hit send here
and see what it gives me.
It's only using your LinkedInprofile, okay, okay.
(40:03):
Okay, it says a little setuphere.
It always is long-windedperplexity.
You've transitioned from leadingmarketing and large
organizations to helpingbusinesses and even your own
family embrace AI for both workand daily life.
But recent studies show trustand authenticity are becoming
pain points.
80% of consumers still cravereal human connection over AI,
(40:27):
and more than half of US workersfeel uncomfortable when brands
use AI-generated content withouttransparency.
So here's my roulette questionfor you If inauthentic
AI-generated marketing contentcan actually damage brand trust,
even as AI becomes unavoidable,do you think we'll soon have
brands going out of their way toprove they are human behind the
(40:50):
curtain?
And, as an AI transformationconsultant, what's the most
delightfully human mistake youhope AI never learns to fix,
because it actually makes brandsmore lovable or at least more
real.
So that was a long one, yes.
So do you think brands will goout of their way to prove
they're human, even thoughthey're using AI, and they'll
(41:10):
make mistakes doing it, and doyou think it'll make them more I
?
Ryan Bearden (41:13):
do think they will go out of their way.
I have seen one example of this, and I will not name the names
or the company, but one personwhom I know very well smart,
smart, smart, and shecontributes blogs for her
company and she puts at thebottom of her blogs AI was not
used at all in the writing ofthis, which I kind of snickered
at.
Who cares?
But I do think they will go outof their way.
(41:34):
I think the complaints, thepissing and moaning of AI
content I think is overblown.
There's oftentimes.
I'd want to challenge people.
I want you to show me, of allthe content you're talking about
, what was AI created and whatwas not AI created, and also
what about the stuff that fitsin the middle.
It's not black and white, it'sjust not.
But I do think, in terms of ajust reacting to that, because
(41:57):
that is a very loud that whatyou just said is very loudly
getting echoed out on linkedin.
Oh yeah, and so I do thinkpeople are going to react to
that and they aren't going to goout of their way to to
demonstrate the human element.
And what was the other part?
What is one?
Kevin Kerner (42:10):
as an ai transformation consultant.
What's the most delightfullyhuman mistake you hope ai never
learns to fix, because itactually makes brands more
lovable or at least more realMdashes.
Don't get me started on theMdash.
Ryan Bearden (42:25):
I think jokingly like this is a pet peeve of mine
, but jokingly I'll say themisuse of there, there and there
.
Yeah, yeah, yeah.
No, I do think I believe thatpassionate, loquacious writing
is something I don't see with AI.
I use AI a lot for writing.
I never take what it gives me.
(42:46):
I take it and I go make it, Irun with it.
Sometimes I'll rip it to shreds, sometimes I'll change this or
that, but I use it all the timebecause it helps me get it done
faster.
The way that I speak, I have atendency to be wordy.
We're proving this right now onthis podcast and so I think
that the kind of loquaciouscheeky, that's not an error,
(43:09):
though that's not an error,that's a style.
That's a style.
Kevin Kerner (43:17):
That may need some ripening over time.
Maybe we'll look back inanother five years from now and
this will be we'll think of ARAI as kind of like Ms Pac-Man
and we'll be like, oh, that wascute back then.
It was so cute or Frogger orsomething.
Ryan Bearden (43:35):
I would say you know, maybe it definitely can
fit this.
But you know, I always get akick out of when people, like,
are very passionate aboutsomething and put their foot in
their mouth, not intentionally.
That's always entertaining tome, that uncomfortable feeling
that you get when you see that.
But it's certainly something,again, ai can fix.
But I don't know.
That's.
I think you're right.
It's it's hard to, it's hard tothink of and I'm very much
(43:57):
locked into like work Right,it's hard to think of and I'm
very much locked into work right.
Kevin Kerner (44:00):
But in life there's yeah we're in the middle
of its mistakes now.
They're cringey, but thatcringe eventually might become
something that's cute at somepoint.
Who knows?
I don't know.
Ryan Bearden (44:14):
We'll know in the fullness of time how all this
works out.
I do think the MDash peoplelosing their mind over the MDash
cracks me up A little crazy.
The writer guy.
Kevin Kerner (44:20):
I still have, by the way, a GoFundMe to get to
know that yeah that's right, youkeep that going and promote
that.
Ryan Bearden (44:27):
You might be making a trip to Costa Rica soon
taking the whole family, butyeah, I do think we'll have to
come back and look at that one.
But it is a very interestingquestion I would need to ponder
that one Perplexity wins.
Kevin Kerner (44:37):
Perplexity wins at stumping us.
It's really good at throwingthe sideways stuff.
So this is great, ryan.
I really appreciate you beingon.
I'm sure people are going towant to get a hold of you.
I would encourage them to reachout to you for all of your
training, expertise and AIknowledge.
What's the best way to get ahold of you?
And I know you really like totalk through this stuff.
Ryan Bearden (44:59):
Yeah, I love it and thank you for having me,
kevin, this is always a blast.
You know, beardmarketingcom iswhere you can go to site.
You can get ahold of me there.
I have a YouTube.
I'm actually getting veryactive in my YouTube trying to
do more videos.
Beard Marketing Solutions isthe YouTube handle and you can
go check out videos.
You can reach out to me thereas well, but it kind of gives
you that those videos will giveyou a little bit of a taste of
(45:22):
sort of my style, what I gothrough and what I can teach you
.
But yeah, always love talkingshop about this.
So welcome anyone and everyone.
Kevin Kerner (45:30):
Yeah, this has been great, Ryan.
We'll get together soon.
I really appreciate it.
All right, thanks, kevin.
Okay, thank you.
Hey everyone.
This is Kevin Kerner with TechMarketing Rewired.
I'm right in the middle ofbuilding out AI training for my
own team, and when I talked toRyan Bearden, my next podcast
guest, last week, I knew I hadto get him on the podcast.
Ryan spent over 25 years in B2Bmarketing and now helps teams
actually implement AI in a waythat's practical, not
overwhelming, which is one ofthe mistakes I was making with
(00:21):
my team earlier.
In this episode we talked aboutwhat adoption maturity really
looks like right now, how to getstarted without getting stuck,
and why journaling yourexperiments might be the most
underrated AI tactic out there.
We also got into how agenticworkflows are changing, what
collaboration looks like andwhat most executives still get
wrong when they try to scale AIacross the organization.
(00:44):
So this is really fantastic,especially if you're an
executive like me that's tryingto figure out some AI training
for your team.
So I'm really excited for youto hear it.
Let's get to it.
This is Tech Marketing Rewired.
All right, hello everyone, andwelcome back to Tech Marketing
Rewired.
(01:04):
I'm your host, kevin Kerner,and today's guest is Ryan
Bearden, founder of BeardenMarketing and AI Solutions.
Ryan's got over 25 years ofleading B2B marketing at
companies like AT&T and someother top, very large SaaS
brands really innovative SaaSbrands.
Ryan now helps businessesimplement real-world AI
strategies that actually work,and what I know him for is
(01:26):
bridging the gap betweentechnical innovation and really
practical human-centricmarketing and really making AI
feel approachable along the way.
So it's great to have you here,ryan.
This is a great topic.
I'm really excited to have youon the show.
Ryan Bearden (01:40):
Hey, kevin, thank you so much.
It's great to be back with you.
Kevin Kerner (01:42):
Yeah, yeah, it's been a while since we've talked.
I wonder if you could well.
First of all, why don't youjust give us a little
introduction on who you are anda little bit about the company?
Ryan Bearden (02:03):
Yeah, so I, as you mentioned, I've got over 25
years of marketing experience,predominantly B2B marketing.
I did a little couple ofdetours over on the consumer
restaurant side we won't go intothat, though and a couple of
years ago I really noticed thisAI thing, and in my previous
role, I actually was looking athow could we start implementing
with this, testing this, andwhen I left that role, I really
immersed myself in it and wentall in on it and went and did
some certifications training andtransformation certifications
(02:24):
and have really kind of built mybusiness all around this, and
so what I do is I work withcompanies small to mid-sized
businesses and really help themto gain practical skills on
applying AI to their jobs, totheir work, in a very, what I
believe, easy to understand,easy to implement in very
practical ways, and I'm enjoyingthe heck out of it, to be
honest.
Kevin Kerner (02:43):
Yeah, that's awesome.
So this AI thing is not a fad.
It's actually something that'sgoing to stick around.
Ryan Bearden (02:49):
I believe so.
Yes, I certainly hope so,because I need to find another
gig, but no, I really trulybelieve.
You know, all the hyperboleyou're going to read out there,
aside, it is really.
It is a very real, verytangible thing that I think is
only going to become more so inthe coming years.
Kevin Kerner (03:10):
Yeah, I'm super excited to talk about this stuff
because it's been six months orso since we've talked and, of
course, the whole world haschanged over the six months.
Ryan Bearden (03:14):
It's a lifetime ago.
Kevin Kerner (03:14):
Yeah, it's unbelievable.
My first question is just tryto maturity.
Like are people more, how muchmore mature are they from where
we were at six months ago?
Like, what are they good at andwhat's missing in terms of,
like, their understanding?
I wonder just, are peoplegetting better at this stuff at
this point?
Ryan Bearden (03:32):
You know I mature is an interesting word I will
use aware.
Are people more aware of whatit is, what it can do, what
could be Absolutely?
Is the confidence there?
No, not in my experiences, andI don't say that as a negative,
I'm not knocking people,obviously but I think that it is
adoption, maturity andcompetence around it.
(03:55):
I think is nowhere near whatyou might read in the trade
publications on LinkedIn andother social channels, but we're
getting there.
It's just, you know, I think,human beings, we move much
slower than technology.
Right, we have to getcomfortable with it, we have to
learn how to use it, we have tobe unafraid of it, and we do
that through knowledge, throughunderstanding, through education
.
So I think we're moving towardsthere.
(04:15):
I would say maybe a slightincrease in maturity, but it's
really.
I still say we're still in theinfancy of this in terms of
mainstream adoption, to beperfectly honest.
Kevin Kerner (04:23):
Yeah, do you think the hype is kind of it kind of
drives a lot of urgency to tryto learn, but it's it's actually
catching up to the height isdifficult because it changes
everybody and we just had agentslast week and it's like it just
changes so quickly.
Ryan Bearden (04:36):
Yeah, it's really something else.
But you know, again, the peoplethat I'm working with and I'm
speaking with it's.
You know, hey, I've openedChatGPT.
I've used Cloud a little bithere and there, but they really
don't know how or.
And there's experimentation'sgreat.
I'm a big believer in it.
I tell people all the time justopen it up, like, stop reading
Grox, better than Gemini, betterthan Chat.
(04:57):
Just open it up and startexperimenting with it.
Start playing with it andyou're going to get comfortable
moving from experimenting andplaying with it at an individual
level to more.
We're having a real impact onhow we work and the outcomes
that we're driving with ourbusiness.
I still think we have a goodways to go.
Kevin Kerner (05:12):
Yeah, and six months ago too, I was thinking
like the discussion withleadership was probably don't,
maybe even don't use it or useit.
You know, people might havebeen scared to use it.
Now it's probably.
Well, I heard in the we did adinner last week where I had
some executives speaking aroundthis stuff and they were getting
(05:33):
pressure now from theirexecutive teams to use it and
use it fast Are you seeing thatsame thing.
Is that what's driving thaturgency?
If you're seeing the same thing?
Ryan Bearden (05:41):
Yeah, Just pressure it's.
It is the you know in this dayand age, right?
If you look at the businesslandscape, there's always
pressure to perform, right, anda lot of this is how do I say
this?
Fabricated pressure, right,Like, well, our goals are we
need to grow by 25% next year?
Well, is that very realistic,right?
I mean, you and I have workedwith companies.
I've worked, you've worked withcompanies.
(06:02):
I've worked for companies thatare very hyper growth focused,
private equity funded, and theyreally want to grow fast and
they private equity groups andother investors want a return on
that investment.
We all get that, we allunderstand that.
And AI, I believe, and in somepeople's eyes, is that next
darling that's going to help usget there, going to help us
double down and get there, andso I do think a lot of the
pressure is coming there.
(06:24):
But I think there's also on theflip side is I don't even know
where to start.
And if I start researching, Istart searching, I start digging
into where to start, I'm evenmore overwhelmed because it's so
easy to get overwhelmed withwhat's out there, and so I think
that is driving what I'll callsome sense of paralysis.
It's just not knowing where tostart and you know, do I just
(06:47):
get a blank check to go do this?
Or how do I do this smartly?
How do I do this effectively?
That's not easy to navigate Ifyou haven't dug into it this has
been my whole life for twoyears and if you haven't done
that, it's not super simple togo and find your starting point
to go and it's going to lookthree different companies.
Kevin Kerner (07:04):
It's going to look three different ways.
So in the companies that you'recoaching the leaders, I'm in
the same boat.
You know we're all trying tofigure out as business owners,
like, how do you get your teamor team managers?
Or, you know, departmentmanagers, how do you get your
teams around this stuff?
Is it that they don't knowwhere to start when they come to
you, or do they have an ideaabout doing it a certain way?
Like are you having to coachthem from day one, Like here's
(07:27):
how you do this, or do they cometo you?
Ryan Bearden (07:30):
and say hey, I want these things implemented.
Yes, a little bit of both, andthere's definitely an eagerness,
an interest there and a senseof urgency there, but it is.
You know, how I help to frameit with them is let's start
small.
Let's do a pilot.
I'm not asking you to come jumpin bed with me with your entire
organization, your entire team,whatever.
Let's start small and let's seewhat could be.
Now I tell them here's what youshould expect, and I'm very
(07:53):
upfront about that, here's whatyou should expect.
And I do not shy away fromthings like ROI and the actual
results and impact.
I want to put that front andcenter.
What I want to do is I want tohelp you realize these benefits,
these outcomes, these results.
But this is uncharted watersfor a lot of them and a little
scary.
So let's start small and let'ssee what could be possible.
And that really resonatesbecause it gives them a little
(08:16):
bit of flavor, gives them ataste of what could be.
And, knock on wood, kevin,every time I've done it, it's
worked out.
There's been an expansion ofwork.
We want to continue on this.
Hey, with this, pilot's workedgreat.
This current client I'm workingwith halfway through that first
pilot, he was already signing upthe next two cohorts, so
they're definitely seeing thevalue there, and there's a lot
of low hanging fruit, and that'sanother thing that I try to
(08:38):
explain to them is like, listen,we're going to get some real
big wins here.
We're going to learn a lot, butyou're going to get some wins.
I can almost guarantee you that.
And so, once you start showingthose wins, what it really does
is it opens their mind to whatelse could be.
It expands their mind to biggerinitiatives, broader use cases
of it, and what I like to do isto let them get there on their
(08:58):
own.
That's very, very important.
I think of myself as a Sherpa.
I'm going to be with you andI'm going to guide you, but
you're doing the work.
You and your teams are doingthe work, because if you're not,
then you're getting nothing outof this, and shame on me.
But letting them get to that,oh wow, I see the impact.
This is really going well.
This is really going great.
We're four weeks in and theteam is already doing all these
wonderful things and it clicksand it's like, oh, it clicks.
(09:27):
And it's like, oh gosh, what ifwe did this in this part of the
group.
What if we did this for ourstrategic planning?
Kevin Kerner (09:29):
you know how do we apply it to that?
This bigger, larger scale, moreexecutive focused initiatives?
Yeah, yeah it's.
It's very similar in some waysto the whole digital
transformation thing that washappening yeah five or six years
ago.
But at the digitaltransformation time it was big
platforms.
Yeah, it wasn't superaccessible.
It it was top down and whatthis is is more of it's AI
transformation.
It's more bottom up.
(09:49):
It's sort of the pressure isdifferent.
I mean, you're still as abusiness owner, you still know
you need to do it, but you knowyour people are probably already
using it anyway.
It's almost like it's digitaltransformation without the
guardrails.
It's just like all over theplace, crazy stuff.
Ryan Bearden (10:04):
No.
And one thing you said that Ithink you really hit the nail on
the head, which is bottoms up,and I am a believer that and I'm
not saying top down is justgoing to fail, I'm not saying
that at all but when you startto see how it's impacting
day-to-day work individualcontributor level, people
manager level then you start toreally open your eyes to what
(10:26):
could be at that next level, asI said a minute ago, and so I'm
a big believer that start in thetrenches and start to see the
impact in the trenches, becauseit's not just, oh my gosh, we're
doing this faster, but whatelse are we doing now?
And that's probably one of myfavorite things is I ask my
students to students.
It feels funny saying that but,I, ask them to.
(10:48):
I have what's called atransformation journal where
they go fill it out andessentially just ask them each
time you use AI on a deliverablego what was the deliverable?
Describe it a little bit.
How did you use AI?
How long does it normally takeyou, how long did it take you
with AI?
And if you do this on a regularbasis, how much time do you
anticipate it saving each month?
But the more important questionin all that is was the quality
of the output, the same, betteror worse?
Because if we're just doing abunch of the same stuff, faster
(11:11):
but crappier, well, what's thepoint?
Right, like we're movingbackwards, and so that's really
important.
I could point all day long tohere's how much time you're
saving, here's how many hoursthis team is saving, and it's
really that first cohort at theend of it each month going
forward.
This is based on their words,kevin.
They are filling out thisinformation, but it's the two
(11:31):
biggest things I point to.
Is you just saved like threedays each person per month,
three full days in time?
But also, more importantly, howare they talking about they do
their work?
How are they talking about howthey do the work?
How are they talking about thethings that they're doing now,
that they weren't able to dobefore, and that, to me, is a
little bit fuzzier when you getto a ROI conversation with a CFO
(11:53):
, but, as you well know, that isso important.
I mean, think about your team Ifthey're completely doing hey, I
saved five hours a month overhere, but now I'm doing this.
I'm spending those five hoursdoing this, which is more
strategic work new businessopportunities.
How are we expanding theopportunities with this existing
client in your world?
That's the kind of stuff that'sreally really super important.
(12:13):
And then, once they see that,then at the leadership level,
it's really gosh.
These are all the things thatwe wanted to test, but they're
always on the back burnerbecause we never had time.
Well, now you have time.
You have time to do thosethings that were more ambitious
but just out of reach because ofbandwidth.
Kevin Kerner (12:29):
Yeah, that's great .
That's really great.
Well, we talked when we weresetting up for this about the AI
education stuff that we'redoing at Mighty and True, and
you were really helpful inguiding me on a few things I
want you to take me through,because I know a lot of people
are thinking about training fortheir teams.
I want you to just give us someof the different tactics you
(12:51):
use for training that aremeaningful, and I think the one
thing you told me about was likethere's an overwhelmed
component of all this andthere's keeping things practical
.
Tell me, tell us, a little bitabout the training formats that
are really having the mostimpact.
Ryan Bearden (13:06):
So one of the things that I really focus on is
, you know, when I first startedgetting into this, kevin, I was
really dead set on.
I really want to be on thecutting edge.
I want to stay on top of allthe new stuff that's coming out,
and you actually do this quitewell.
I will say, I don't know howyou do it, but you do it pretty
darn well.
Yeah, it drives my team crazy,but it's like I quickly realized
(13:27):
all of this kind of newswhether it's agents, any sort of
automations that is so far offfrom the mainstream, when most
companies have maybe mostindividual contributors and even
leaders have maybe openedCopilot or Gemini and done a few
things.
And so I quickly like settledown, ryan, let's go focus on
(13:49):
practical skills at the mostbasic level, and what I truly
believe in my experience ofplaying with various tools and
looking at them is mastering thelarge language models, and I
don't care which one you prefer.
Mastering those is critical,foundational skills for you to
really harness AI to its fullpotential, not only today, but
in three years, when it willlook vastly different than it
(14:11):
does today.
I also believe that the LLMslarge language models will be
able to do the majority of whatthese point solutions claim to
do just as well, if not better,and so what I really do, my
approach, is we're going tofocus on building your skills,
on using the large languagemodels in your work, and I think
that in your work is a reallyimportant key is that I might
(14:32):
have a few slides.
I have, maybe, in each trainingsession, two to three slides
but we spend 95% of the time.
What are you working on today?
What is the deliverable you'reworking on this week?
What is a problem or obstacleyou're facing this week that
you're having trouble overcoming?
Okay, so that's what we'regoing to do today.
In each session, it's laserfocused on something you're
working on or something you'retrying to overcome.
(14:52):
And once you really apply it totheir real work and one of the
things I always harp on one ofthe slides I show them every
time is work on your work is,you know, one of their three key
principles?
Ai is your blank.
For each person that's verydifferent.
How is AI going to help youtoday?
Incremental gains You're goingto get better and better and
better at this each time.
But, most importantly, work onwork.
I'm not here to pull up arandom scenario and show you how
(15:14):
cool the tool is.
We are here to work on yourwork and that has really
resonated the most.
And when they see the impactand they see, think about how
much time we spend at our jobs.
Kevin, over the course of ourlife we will spend far more time
at our job than we will withour families.
That's just a fact.
If I can show you how to do itfaster, easier and even better,
(15:35):
then we're all going to win.
That is my ultimate goal.
And I had one of the clients inthat pilot program.
She texted me a few weeks intoit.
She goes I'm having more funnow at work than I can ever
remember and I thought, wow,that really is awesome.
That makes me feel good, thatmakes me feel great.
And she's in a very stressfuljob.
(15:55):
So to hear that was reallygreat.
And I think that is really thekey thing is we're going to
focus on your work.
It's eight.
My training, my kind of coretraining, and I can customize
this for anybody and I've doneit before but, like the core
foundational program is eightsessions, just like martial arts
white belt all the way to black, and each one it focuses on a
different area of your business.
(16:16):
We're going to create SOPs.
We're going to automate somecertain deliverables.
Once we've created thosestandard operating procedures,
I'm going to teach you how totap into experts who, whatever
problem you're facing todaysomebody has written a book
about it, I can almost guaranteeyou, or done a TED talk about
it.
I'm going to show you how totap into those to create an
action plan to overcome thischallenge, to creating GPTs
using APIs and automations, yada, yada, yada, the whole gambit
(16:37):
of things.
But it's really.
You're going to walk away.
I guarantee you will walk awaywith skills that you never would
have been able to develop onyour own.
Kevin Kerner (16:46):
What are those?
I mean, that sounds great.
What are those LLMproficiencies?
What are the types of thingsthat you would say these are the
proficiencies that you need,that you need that you help
people improve on?
Like, I think of them kind ofblind spots at this point,
because it's like they justdon't know.
And if they if they did knowthe LLMs could do certain things
(17:06):
, there'd be a reflex to usethem more.
But what are they from yourperspective?
Ryan Bearden (17:10):
Yeah, I don't know how this answers your question,
but let me say it and then I'llfind a better way to say it.
The single biggest thing whereI see people get hung up is
you're trying to interact withGemini, chatgbt like it's
software, and chat GBT like it'ssoftware.
And well, I put this in thereand it didn't give me what I
wanted.
This doesn't work.
This is dumb or I don't knowhow to use this or whatever.
And what I tell them is talk toit like it's a person, like
(17:34):
it's an intern or a colleague.
And if you have an intern,you're going to give them.
You guys do internships.
You're going to give an interna task, go do this.
That intern comes back to youand says here's what I did, and
you go well, this isn't what Iwanted.
Well, you're not going to firethat intern, you're not going to
berate that intern or whoever.
You're going to give themfeedback.
You're going to give themadditional context.
You're going to redirect themand have them go back and do it
(17:55):
again.
That's how you communicate withAI.
That is how you get the mostout of it.
And so what I tell people isdon't worry about becoming an
expert, prompt engineer.
By the way, ai can createprompts better than you can, I
promise, and I'll show you how.
But you need to master how tocommunicate what it is you need,
what you're looking for.
Can you clearly articulate that?
(18:16):
And it's funny, kevin, becausethink about how many things
happen in Mighty and True thatare on autopilot, where, if I
ask you, if I ask Jennifer, if Iask anybody on your team, walk
me through the steps you take todo this.
That's not easy because, well,I just do it automatically.
It happens automatically.
And when you're thinking aboutimproving processes, when you're
thinking about acceleratingdeliverables, you need to be
(18:39):
able to, which is so funnybecause it's a very human
element, right, it's a veryhuman thing.
Can you break this down intosteps and the tasks?
Can you communicate?
This is what I'm trying to do.
This is where I'm struggling.
This is where I need help.
If you can do that, you're like60% there, you're 60% there,
and then it's just kind oflearning to go back and forth
and then accepting the fact thatI'm going to get not so great
(19:01):
output sometimes, but if I keepworking with it, I'm going to
get a better output, and I thinkthat that is a core,
fundamental element of gettingsuccess from these tools is
knowing how do I communicatelike this, how do I think like a
human and communicate like ahuman, because once I do that,
then this tool is going to,which sounds counterintuitive,
but this tool is going to giveme so much better output, so
(19:22):
much better results.
Kevin Kerner (19:23):
I think that's the key thing.
A lot of the people that areworking with the agents now are
anthropomorphizing the agentwith a name, like they call
their agent.
It's literally a worker ontheir behalf.
A lot of the tool providers aretalking about it that way,
which I think we'll come to atsome point.
They're not.
They're not ready yet at thispoint.
Ryan Bearden (19:41):
Yeah, we're still very early.
There's this guy, adamRobinson's his name, his company
are I'm going to butcher this,or anyway.
He owns a SaaS company and he'svery active on LinkedIn.
He's very he's kind of like you, he's very open.
Here's what we're doing, here'swhat we're trying to build this
company and if it doesn't work,I'm going to tell you.
And when it works, I'm going totell you.
And he put a post out recently.
It was like all five of ouremployees are going away for a
(20:03):
week and we're having theseagents run the company and my
first thought was environment.
But I that scared, like I'muncomfortable and I'm not
associated with your company andI'm a little uncomfortable with
that.
But yeah, I mean I, I, I thinkwe are early in that sense, but
I I'm not a fan of the namingyour agent type of thing, cause,
(20:23):
for we could go down a rabbithole for you know, for another
hour, just on the psychological,emotional aspects of that.
But it is funny, cause we willget there.
Where you are, you know, youtalk about it where you're
managing three or four agents,you might have someone on your
team that's managing three orfour agents that are doing work.
Hopefully they're, you knowthey're spot checking it, yeah,
but it is.
That day is coming.
I think it's further off thanwe think, but it's coming.
Kevin Kerner (20:45):
If you can get someone to be more mature in how
they're communicating with theLLM and prompting and they, you
know they're getting good atthat what's the next level?
What's the thing that you dowith them to get them to the
next level of proficiency?
Or do you have to Do they justthe spark is already there, they
just take off.
Ryan Bearden (21:04):
I think that's it.
I mean, I think it's so organicand the way that I set up my
training is very much like youknow.
I mentioned the transformationjournal and there's also like at
the end of each session likethere's homework, where you know
you go submit your homework andyou get certified for that belt
for that particular session,but going off and doing the
homework I have so much fun withthat I really encourage them to
record their screen andthemselves talking through.
(21:25):
You know like two to threeminutes record your screen to it
.
But I'm like you don't want todo that, put in a document
whatever.
But when I go through thehomework and I read it and they
usually do it within 36, 48hours after the session they're
getting it, they're grasping itand they're applying it
immediately what we learned inthat session.
They're applying it immediatelyto another deliverable and so I
(21:46):
do think it's pretty organic.
I like to tell people that whatI do is you do AI training.
I give people confidence andcapacity and once you give them
that human beings arespectacular, spectacular species
, right, we can do anything.
Kevin Kerner (22:08):
Yeah, your Sherpa thing is pretty much.
Ryan Bearden (22:10):
They're not on my back, I'm guiding them and
saying now, you see this.
And even I had the hate SVP ofmarketing.
He came to one of the first.
Back I'm guiding them andsaying now you see this.
And even I had the SVP ofmarketing.
He came to one of the firstsessions.
I told him I was like you, comefor free, I want you there.
I won't even charge you,knowing he wouldn't come to all
of them, but it was his firstever experience spending this
much time focused on it.
And the first thing he said ishe joked and said you've ruined
(22:33):
my life.
You've opened my eyes to somany rabbit holes I can go down,
my mind is spinning about whereto go and I was like good,
that's what I want.
I hopefully ruined your life ina good way.
But it is so organic, kevin, andit's just you know this well
where there are things where youcould take the textbook, you
(22:54):
could take the syllabus from acollege course or whatever and
never go to the class, butyou're probably not going to
pass the test, you're probablynot going to do well, right.
It's that there's that wholeelement of being taught, being
led down the path of learning,versus trying to go do it on
your own, and I think that thatis that's where the power is,
and you know the cool thing Iwill you thing kind of to answer
(23:14):
your question another way isthat first cohort we did they
were like.
Afterwards they were like, well, what's next?
We want to keep going, and soI've actually built a few
follow-up sessions that we'redoing within where we're going
to get more into moreautomations, more agent type,
even like introducing them toRelay, which you and I know very
well.
So some of these other toolsthat are out there, where it's
again, this is not a silverbullet for your organization,
(23:37):
this is getting your mindwrapped around that next level
of agentic workflows andautomations that are there.
Kevin Kerner (23:43):
And so once you get them to that level and
proficient, then the force isout of the table and they're
going to go off.
They're going to go.
Do you think?
I really love the idea of thataligning the Sherpa, the guide,
with the work that they'recurrently doing, because I can
immediately see that, oh, thisthing, this actually helps me in
my day-to-day job.
Are there circumstances whereyou want to train them in a
(24:07):
broader way, like the reason?
There's a question behind thisquestion, like we're we're
trying to create this, this,this environment're.
Yeah, we're trying to createthis, this, this environment of
what we call collaborativedelivery.
So, where you have a person whomight just be as a very specific
role without it.
Now they can stretch to anotherrole because they have this ai
assist with them now they mightnot have all the context of, you
(24:28):
know, whatever that role is,but they can at least help what
they can pitch in, and so it's'san amplified initiative for us
because we can have employees gooff and do things.
Is it worthwhile giving anemployee more perspective than
just the stuff that they work on, like having them work on
exercises that are not relatedto their role, just so they can
see how those things work?
(24:49):
Have you tried that?
Ryan Bearden (24:50):
Yes, I have, and it's a great, great point.
And I think there's certaintypes of organizations where
this is really good.
I mean, I think about yourcompany kind of fits this mold a
little bit.
But think on the non-serviceside, not agency side, like
you're a startup and you gotfive or six employees, well, you
probably don't have an HR team,you probably don't have a
marketing team, let's be honest.
(25:11):
But you should probably havesome HR functions happening,
deliverables happening,marketing things happening, and
so, in that sense, how I wouldapproach, I do think it's a very
good idea how I would approachthat is much more on a workshop
basis.
I've actually done this.
Actually, one agency that Iworked with their creative team
I actually built.
I knew their, I had access totheir processes.
(25:33):
This is our process, our bestpractices on how we do.
And for the creative, for theirops team, I took them through
the train because I knew theyneeded these kind of Swiss army
knife skills.
But for the creative team I didI think six or seven I'm going
to do a workshop for everyaspect of your process and I'm
going to show you exactly how AIfits into this.
So we're actually going to dosome real client work, not the
(25:55):
actual deliverable, but we'regoing to do sort of in unison,
if you will, in parallel.
We're going to do some realclient work incorporating AI to
give them a sense of how thiscould happen.
I would do that something verysimilar for a company of like
hey, here's this person, she'she or she's a very strong
project manager.
They don't really havemarketing experience or we need
really to get some HR thingsdone.
(26:16):
I would go and build that.
Let me show you how to do this.
The one caution I would say tothat and this is what I the rush
to automate and to there's alot of fear out there amongst
the creative teams.
I think to uncertainty aroundthis is I can teach someone
who's got an HR background howto use AI to do marketing
deliverables, but what I can'tdo is show them what good is.
(26:40):
The risk is when the outputcomes from.
You know you're building acampaign or you're writing a
blog something as simple as thator an email campaign, knowing
what is good and why or where itcould be approved as why.
I can help you get there prettyfar with AI, but I still
believe the human in the loop isthe single most important
aspect to all of this.
(27:01):
Or maybe expert in the loop,yeah expert in the loop, exactly
right, not just any human, butan expert or a specialist in the
loop to be able to understand.
This is good quality, this isappealing.
This is hitting the points ofour target audience, and here's
why good quality, this isappealing.
This is hitting the points ofour target audience and here's
why that's the only risks, andthat's a big one.
That is a big one, butabsolutely I could walk in and I
feel confident.
(27:21):
Within a month I could have alot of people cross-trained on
different functions.
That's, that's an easy thing todo.
But again, it's thatdiscernment of quality that is
just important that people needto be aware of.
Yeah, we got a lot of, as Imentioned at the start, that
people need to be aware of.
Kevin Kerner (27:33):
We got a lot of, as I mentioned at the start, we
got a lot of questions last weekat the dinner about, you know,
executives wanting this stuff toroll out real fast.
Ryan Bearden (27:41):
Yeah.
Kevin Kerner (27:41):
And maybe a couple questions.
One, what guidance would yougive those like these were all
marketers, so it was just thatspecific department.
What guidance would you givethem on how to message that back
to the executive team, likewhat?
What?
It seems like you'd want toacknowledge it.
Yes, we want to use AI but,like I, have another question
(28:01):
around measurement, like how doyou, how do you prove the ROI on
this stuff?
Ryan Bearden (28:05):
Yeah.
So the first question I wouldask to answer that question is
how do you define fast?
Like it's fast fast at a boardlevel might be in the next six
months.
I want every single person inthis company fluent in AI.
Okay, Well, what does that mean?
Like, do you want them buildingAI tools or do you want them
using AI to do their jobs,incorporating it into their
processes?
Kevin Kerner (28:25):
Or less people or less people.
Ryan Bearden (28:27):
Yeah, and I try to steer away from the less people
conversation, not because I'mscared of it, because I do not
think that is the right lens tolook at this through, at least
not initially.
That could be a byproduct ofall the work that goes into it.
Let's say for the six months.
But I really, personally, Ijust like I'm here to
supercharge your people, not getrid of them, and so.
(28:49):
But with that said, I would saylet's say it's six months.
I think that is a veryreasonable amount of time to
pilot some programs, expandthose, scale those programs
Obviously, find what's workingand scale that and begin to have
it across your organization.
If we're talking AT&T, probablynot, but if we're talking a
(29:12):
500-person company and dependingon the capacity they wanted to
do, I think that's veryrealistic.
The thing is, is that what Ilike about my approach?
I'm biased, but what I likeabout my approach is because I
am applying it to your job, yourday-to-day.
The adoption and implementationis going to be almost overnight
, and when I say that, what Imean is after one, two, three
(29:32):
sessions you're going to bedoing various things differently
and better, like I guaranteeyou you will, and the next time
I see it not work like that willbe the first time I see it not
work like that.
So I feel confident saying that.
But I think it really comesdown to listen.
We want to do this fast.
Okay, well, what is fast?
So let's build a roadmap, let'sbuild a plan and let's define
success.
I think to your point.
(29:53):
One of the biggest things, too,that people often miss, kevin
and I've brought this up a lotwith workshops I've done with
companies as well as the onesthat I'm training is you should
really have sort of policy orguidelines in place.
Those policies can change.
Think of your first AI policythat you create and maybe it's
(30:14):
for a marketing team or a salesteam at first, but it should
have guard rails.
But the guard rails are rubber.
They can bend because you don'tknow what you don't know and
the more you get into it, themore you see.
Then that might help reshapethat AI policy.
But I think you have to havesome guard rails in place.
There was a statistic I readtoday, as a matter of fact, of
the number of people that areemployees that are still hiding
(30:37):
their AI usage from leadership,which should scare the hell out
of.
It's very high.
It is very, very high 60 pluspercent in this one study, but
also within that.
It was a survey.
They talked to 50,000 workersacross the globe, but there was
also there might be puttingcompany information into LLM.
(30:58):
Maybe they're using a freeversion of the LLM.
They're not considering theprivacy and security things that
are really into this at aleadership level.
Eyes wide open of here's whatwe're going to go do.
Here's our gameplay we're goingto have some, establish some
(31:22):
guardrails first, and then we'regoing to go, let's just say,
six months, and at the end ofthat six months we're going to
reevaluate, revisit.
Where have we seen the mostimpact?
Where have we seen the mostsuccess?
Kevin Kerner (31:37):
Yeah, success.
Yeah, I was thinking to you.
I think it's all good and Iagree with it all.
I think the executive questionthat I heard last week was kind
of around overexcited executiveswanting to push it into
marketing such as there'd behuge efficiency gains, whether
that's in fast for stuff or morepeople.
If I'm a CMO, I might saythat's great.
A we're already using it.
We've been using automation foryears.
This is just automation withsome additional capabilities, so
(31:59):
we need to implement it like weimplemented our automation and
we can get better at that.
But it's not all ready forprime time.
What you're hearing on LinkedInand all the other things is not
exactly what you're going toget out of my marketing team.
They're just not ready yet.
We're not going to have agentsrunning everything.
We're not going to haveautomations with AI on top of
them.
Yet Now there are some pointsolutions that do that.
(32:20):
I think there's a really goodcase for SDR customer service
use cases, and there are a bunchof those.
But from the marketing team,there's so much nuance in
marketing You're reallyoverreaching to say, let's just
put AI in place and, you know,start seeing massive efficiency
gains and less people.
(32:41):
That's just.
Ryan Bearden (32:42):
That's right.
I think the you know what Iwould say to.
That is number one there.
What doesn't get near theheadlines that you know?
You and I have read theheadlines of.
You know Microsoft's cutting6,000 jobs and they're going to
do automation, duolingo.
You know a lot of thesecompanies that are out there
that have, like, been very boldcome out.
You know bold leadershipmandates, for lack of a better
(33:03):
word.
But what you don't hear aboutare the companies that cut
customer support teams becausethey want to automate it with AI
, that cut marketing people orSDRs because they want to
automate it with AI.
Well, six months later, whatare they doing?
They're hiring those peopleback.
Why?
Well, because it's notperforming as well as a human,
and you know not to sound likean armchair quarterback, but
(33:26):
yeah, I mean, somebody is goingto have to be the company that
goes all in first and and likehas to back up and say, well,
and like has to back up and say,well, that didn't work out the
way we wanted it right.
And you know, no matter whatyou know digital transformation,
e-commerce, whatever we go back, you know last 30, 40 years,
any innovation like that there'salways the people that are the
early adopters that are rushinginto it.
So, but also let those be thelessons that we don't have to go
(33:51):
and repeat, right, like, don'tgo with a mindset that you're
going to get rid of 5% of yourmarketing team because of all
this.
Go with a mindset of we'regoing to make smarter decisions,
we're going to be able topersonalize, to get more
personable with ourcommunications and our messaging
, we're going to be able tosupport our salespeople better.
We're going to get to marketfaster.
We're going to know what ourcompetitors are doing well and
(34:22):
not well faster.
Those are the things where it'slike I will show you how to do
all of those things and thensome very quickly and then start
to decide are we seeing theimpact?
What is the impact of this?
Is it fewer lost deals?
Is it higher conversion?
Put the marketing hat on Higherconversion rates, lower cost
per opportunity, more closerates, whatever that may be.
But the one thing I will tellyou, which, again I say, is
foundational I'm not hanging myhat on the fact that you're
going to be able to do the samework in a third of the amount of
hours.
That is a good thing, but it'snot the end.
(34:44):
All be all.
At the end of the day, is ourbusiness growing?
Is it functioning moreefficiently?
Are we getting revenue growingwith revenue?
Are we growing faster?
All of those things.
You got to be able to tie it tothat, which is not terribly
difficult to do, but you justgot to go in there with the
onset from the onset.
You've got to document that andknow that this is how we're
measuring success.
Kevin Kerner (35:02):
Yeah, that's, that's awesome.
You gave me some really goodadvice advice last week or last
time we talked around.
You know different types oftraining stuff that I do.
I just want to really quicklytop five things that you've
learned not to do when you'retrying to train a new group on
AI.
Like, what are the five thingsyou say don't do this If you're
(35:23):
going to try it?
Ryan Bearden (35:25):
Yes, the biggest one is no matter how much
they've told you they use AI orhow much experience they have
with AI, don't throw more atthem than your program already
does.
I did this one time where Ithrew like, hey, I've been using
it for three to six months.
It's like okay, well, I'm goingto kind of accelerate these two
sessions I'm going to puttogether and you're like nope,
(35:46):
didn't work.
I mean, you used this wordearlier, so overwhelmed they got
so overwhelmed.
Kevin Kerner (35:52):
Don't overwhelm, that's a good Don't overwhelm,
that's a good.
Ryan Bearden (35:54):
Don't overwhelm that I mean that's.
I cannot say that enough.
That's that looks different forevery single person.
But, like the over, I've got ademo that I do that.
It's just like I'm going toprove to you how well I knows
your job and you potentially putit in your job title or your
LinkedIn profile and it givesyou it's a GPT.
That is matrix of like.
Here's your top eight coreresponsibilities and all the
(36:15):
deliverables.
And I have seen more people justshut down and disengage because
they're impressed but they'reoverwhelmed.
And when you get overwhelmedlike that, it rarely is a good
thing.
So that's the big one is, evenif it seems so basic, nine times
out of 10, every person sittingin that session, that class, is
(36:36):
gonna get something out of it,something positive out of it.
That's the number one thing.
The second thing I would say isit is absolutely imperative.
I push hard, as hard as I can.
They don't work for me.
But do the journaling, takenotes, keep a journal of what
you're doing and how you'redoing it, what's working,
because I really push them.
Also, this is not about megetting numbers that I can go
(37:00):
promote my business If there arethings that you did that didn't
work.
I want to know that.
In fact, more so than thethings that did work, Go,
identify and highlight thethings that are working well and
the things that aren't workingwell, Because that's one of the
things that I tell people is Imentioned to you, like the hey,
talk to it like it's an internor a person, not like it's
(37:21):
software.
But also context is everythingthat's like hey, write me an
email.
Okay, we're going to get acrappy output, so put context to
that.
Yeah, and when you do those twothings, you're going to very
quickly realize what it's goodat and what it's not good at.
And spoiler alert it is notgood at everything.
Contrary to what you might read, it is not good at everything.
Kevin Kerner (37:42):
So don't overwhelm , don't miss the opportunity to
document, which I think is great.
Anything else you can think of.
I'm taking notes for my owntraining program.
Ryan Bearden (37:53):
Those are the absolute biggest ones that I
would say, and this is for youand your position, kevin.
This is important.
So when I I do my trainings, wedo like one hour, like usual.
Wednesdays we do the sessionand then on Fridays I have
office hours.
We're like listen, I'm gonnaopen up the bridge for one hour.
This is your time.
Come to me.
Is there something you'rethinking about?
(38:13):
Or you have another opportunity, or are you struggling with
something we learned this week?
Whatever it is, but when you getthem together, I used to think
that and I still think this.
You know, if you had a trainingsession that had HR, ops,
marketing, sales, all in one,they would get a lot out of it.
And the way that I'vestructured this training is to
where you could have thosepeople together and they would
still get a lot out of it.
But when you have a marketingteam together or an ops team
(38:34):
together, just them talkingamongst each other about how
they've used it, like I just sitback and I'm like this is gold,
the serendipity, this is gold.
Kevin Kerner (38:44):
The opt-in to share.
Ryan Bearden (38:46):
And I went to the SVP when this happened and I'm
like these are the common themesthat they talk about on the
office hour calls, when they gettalking amongst each other, and
it was really cool because hesaid to me it was four key
things.
And he said these are the fourthings that keep me up at night
the most.
And I'm like and now yourpeople are thinking about this,
they're thinking about it indifferent ways, and so the point
(39:07):
there, kevin, I think againfrom a position of leadership
like yourself is let them talkand listen, celebrate, get them
together, yes, and let them talk.
And celebrate the failures.
Kevin Kerner (39:18):
Awesome we're smarter now.
We're smarter now and celebratethe failures.
Awesome.
We're smarter now.
We're smarter now.
Cool.
This is great.
Okay, so I wish I could.
I wish I could go on for more,because I'm taking notes with
all this stuff, or we're in theright in the middle of this
stuff, so super helpful for meand, I'm sure, for others.
I warned you that we do thisthing called uh ai roulette and
(39:40):
I've loaded your LinkedInprofile into a space in
perplexity and that space hassome instructions to try to
throw you off your mark here.
Good, no, it's basically justgive me a crazy question.
Give me a really uniquequestion.
It's been pretty good so far,so I'm going to hit send here
and see what it gives me.
It's only using your LinkedInprofile, okay, okay.
(40:03):
Okay, it says a little setuphere.
It always is long-windedperplexity.
You've transitioned from leadingmarketing and large
organizations to helpingbusinesses and even your own
family embrace AI for both workand daily life.
But recent studies show trustand authenticity are becoming
pain points.
80% of consumers still cravereal human connection over AI,
(40:27):
and more than half of US workersfeel uncomfortable when brands
use AI-generated content withouttransparency.
So here's my roulette questionfor you If inauthentic
AI-generated marketing contentcan actually damage brand trust,
even as AI becomes unavoidable,do you think we'll soon have
brands going out of their way toprove they are human behind the
(40:50):
curtain?
And, as an AI transformationconsultant, what's the most
delightfully human mistake youhope AI never learns to fix,
because it actually makes brandsmore lovable or at least more
real.
So that was a long one, yes.
So do you think brands will goout of their way to prove
they're human, even thoughthey're using AI, and they'll
(41:10):
make mistakes doing it, and doyou think it'll make them more I
?
Ryan Bearden (41:13):
do think they will go out of their way.
I have seen one example of this, and I will not name the names
or the company, but one personwhom I know very well smart,
smart, smart, and shecontributes blogs for her
company and she puts at thebottom of her blogs AI was not
used at all in the writing ofthis, which I kind of snickered
at.
Who cares?
But I do think they will go outof their way.
(41:34):
I think the complaints, thepissing and moaning of AI
content I think is overblown.
There's oftentimes.
I'd want to challenge people.
I want you to show me, of allthe content you're talking about
, what was AI created and whatwas not AI created, and also
what about the stuff that fitsin the middle.
It's not black and white, it'sjust not.
But I do think, in terms of ajust reacting to that, because
(41:57):
that is a very loud that whatyou just said is very loudly
getting echoed out on linkedin.
Oh yeah, and so I do thinkpeople are going to react to
that and they aren't going to goout of their way to to
demonstrate the human element.
And what was the other part?
What is one?
Kevin Kerner (42:10):
as an ai transformation consultant.
What's the most delightfullyhuman mistake you hope ai never
learns to fix, because itactually makes brands more
lovable or at least more realMdashes.
Don't get me started on theMdash.
Ryan Bearden (42:25):
I think jokingly like this is a pet peeve of mine
, but jokingly I'll say themisuse of there, there and there
.
Yeah, yeah, yeah.
No, I do think I believe thatpassionate, loquacious writing
is something I don't see with AI.
I use AI a lot for writing.
I never take what it gives me.
(42:46):
I take it and I go make it, Irun with it.
Sometimes I'll rip it to shreds, sometimes I'll change this or
that, but I use it all the timebecause it helps me get it done
faster.
The way that I speak, I have atendency to be wordy.
We're proving this right now onthis podcast and so I think
that the kind of loquaciouscheeky, that's not an error,
(43:09):
though that's not an error,that's a style.
That's a style.
Kevin Kerner (43:17):
That may need some ripening over time.
Maybe we'll look back inanother five years from now and
this will be we'll think of ARAI as kind of like Ms Pac-Man
and we'll be like, oh, that wascute back then.
It was so cute or Frogger orsomething.
Ryan Bearden (43:35):
I would say you know, maybe it definitely can
fit this.
But you know, I always get akick out of when people, like,
are very passionate aboutsomething and put their foot in
their mouth, not intentionally.
That's always entertaining tome, that uncomfortable feeling
that you get when you see that.
But it's certainly something,again, ai can fix.
But I don't know.
That's.
I think you're right.
It's it's hard to, it's hard tothink of and I'm very much
(43:57):
locked into like work Right,it's hard to think of and I'm
very much locked into work right.
Kevin Kerner (44:00):
But in life there's yeah we're in the middle
of its mistakes now.
They're cringey, but thatcringe eventually might become
something that's cute at somepoint.
Who knows?
I don't know.
Ryan Bearden (44:14):
We'll know in the fullness of time how all this
works out.
I do think the MDash peoplelosing their mind over the MDash
cracks me up A little crazy.
The writer guy.
Kevin Kerner (44:20):
I still have, by the way, a GoFundMe to get to
know that yeah that's right, youkeep that going and promote
that.
Ryan Bearden (44:27):
You might be making a trip to Costa Rica soon
taking the whole family, butyeah, I do think we'll have to
come back and look at that one.
But it is a very interestingquestion I would need to ponder
that one Perplexity wins.
Kevin Kerner (44:37):
Perplexity wins at stumping us.
It's really good at throwingthe sideways stuff.
So this is great, ryan.
I really appreciate you beingon.
I'm sure people are going towant to get a hold of you.
I would encourage them to reachout to you for all of your
training, expertise and AIknowledge.
What's the best way to get ahold of you?
And I know you really like totalk through this stuff.
Ryan Bearden (44:59):
Yeah, I love it and thank you for having me,
kevin, this is always a blast.
You know, beardmarketingcom iswhere you can go to site.
You can get ahold of me there.
I have a YouTube.
I'm actually getting veryactive in my YouTube trying to
do more videos.
Beard Marketing Solutions isthe YouTube handle and you can
go check out videos.
You can reach out to me thereas well, but it kind of gives
you that those videos will giveyou a little bit of a taste of
(45:22):
sort of my style, what I gothrough and what I can teach you
.
But yeah, always love talkingshop about this.
So welcome anyone and everyone.
Kevin Kerner (45:30):
Yeah, this has been great, Ryan.
We'll get together soon.
I really appreciate it.
All right, thanks, kevin.
Okay, thank you.
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