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0:54

Welcome to Season 7 of the Agile

0:56

Brand, where we discuss the trends and topics

0:58

marketing leaders need to know. Stay

1:00

curious, stay agile, and join the

1:02

top enterprise brands and Martek

1:04

platforms as we explore marketing technology,

1:07

AI, e -commerce, and whatever's next

1:09

for the Omni -Channel customer experience. Together,

1:12

we'll discover what it takes to create

1:14

an Agile Brand, built for today and tomorrow,

1:16

and built for customers, employees,

1:19

and continued business growth. I'm

1:21

your host, Greg Kilstrom, advising

1:23

Fortune 1000 brands on Martech, AI,

1:25

and marketing operations. The

1:28

Agile Brand Podcast is brought to you by Tech

1:30

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in full -stack technology services, talent

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services, and real -world application. For

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more information, go to

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1:41

you always get the latest episodes, please hit subscribe

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on the app you listen to podcasts on, and

1:45

leave us a rating so others can find us

1:47

as well. And now on to the show. As

1:53

AI continues to evolve, how can marketing leaders

1:55

ensure that they're staying ahead of the

1:57

curve instead of simply keeping up with it?

2:00

And how do you navigate the complexities

2:02

of using AI while maintaining a personal

2:04

human touch in your campaigns? Joining

2:06

us today is Courtney Baker,

2:08

Chief Marketing Officer at KnownWell. and

2:11

co -host of the AI Know How

2:13

podcast. With a wealth of

2:15

experience in marketing and AI, Courtney

2:17

is leading the conversation about how

2:19

artificial intelligence is transforming the marketing

2:21

industry and redefining business strategies. She's

2:23

going to share insights on the next

2:25

era of client intelligence and the five levels

2:27

of AI that are reshaping businesses. Welcome

2:30

to the show, Courtney. Thank you.

2:32

Really glad to be here. Yeah, looking

2:34

forward to talking about this. I mean,

2:36

of course, we talk about AI plenty

2:38

here, but I really like this angle

2:40

here and looking forward to diving in.

2:42

But before we do, why

2:44

don't you start by giving a little

2:46

more about your background and your

2:48

role at Nongwal and what kind of

2:50

inspired this interest in AI and

2:52

marketing? One of the things

2:55

I love about being a marketer is

2:57

I've always felt like I could take

2:59

my craft and deploy it. to what

3:01

I was interested in. You know, I

3:03

used to joke that I felt like

3:05

I could market anything, you know, if

3:07

it was a tube, a tube. I

3:09

was like, I can market that. And

3:11

so I think my career has really

3:13

showcased that in a way that, you

3:15

know, in my 20s, I really spent

3:17

a lot of time in nonprofit and

3:19

traveling the world and getting to really

3:21

figure out how to market to unique

3:23

audiences to get them to do something

3:25

to change the world. I've

3:28

worked in professional services

3:30

companies where we're

3:32

doing executive coaching and

3:34

really working on

3:36

productivity for executives. And

3:39

so in a lot of different ways,

3:41

I've been able to take things that my

3:43

craft and what I'm passionate about at

3:45

that time and be able to use it

3:47

in conjunction, which I think makes for

3:49

a really Marketing is such a

3:51

fun career. Personally, obviously, I'm

3:53

very biased, but it's

3:55

just really neat to be able to do that. In

3:58

my career, I was connected

4:00

with David DeWolf, who's our CEO

4:02

at Known Wealth, the company

4:04

that I was working with, was

4:06

building an app with his

4:08

previous company, Three -Pillar Global. And

4:11

we just hit it off.

4:13

I remember from the very beginning,

4:15

I was like, this guy

4:17

is very impressive. I think I

4:19

just would love to learn

4:21

from him. And so as he

4:23

started to look at launching

4:25

a AI platform for professional services.

4:28

I joined the founding team, and

4:30

so that was two years ago.

4:32

The rest is really history from

4:34

what we've built and done it

4:36

and done well. Nice, nice. Well,

4:38

yeah, let's let's dive in here

4:40

and definitely you are the right person

4:42

to talk about this this topic

4:44

here So love this love your experience

4:46

here. So let's talk about the

4:48

next era of client intelligence So as

4:50

you mentioned briefly and want to

4:52

dive in a little more, you know

4:54

known well focuses on client intelligence

4:56

for marketing and professional services firms that

4:58

sounds like so can you define,

5:00

you know first What do you

5:02

mean by client intelligence and, you know,

5:04

what does that mean today? And maybe,

5:06

you know, where does it come from?

5:08

Right. Well, speaking specifically

5:11

for professional service

5:13

firms, in so many ways,

5:15

it's hard to be a professional

5:17

service firm because unlike SaaS

5:19

companies or e -commerce companies that

5:21

have all of this rich transactional

5:24

data on their customers. In

5:27

professional service firms, you don't

5:29

have that. What you have is

5:31

rich relational data. And

5:33

funny enough, we don't think of it

5:35

that way. And so in a lot of

5:37

ways, a lot of these tools that

5:39

we've kind of had over on the e

5:42

-commerce side or SaaS side, it's just it

5:44

doesn't apply for professional service firms. And

5:46

so if you think

5:48

about a small marketing firm

5:50

or small technology service

5:53

firm, at the very beginning, when

5:55

you're small, you just know

5:57

your customers. It doesn't take

5:59

anything special because you've got 25

6:02

customers. You have your thumb

6:04

on the pulse of what's happening.

6:06

with your customers. But as

6:08

you scale a professional service firm,

6:10

that becomes harder and harder. And

6:12

when you're early on, there's somebody that's

6:15

just really good at that. They just

6:17

have intuition. They know, hey, the Stanley

6:19

account, something was off

6:21

there in our meeting today. I

6:23

think we need to have an

6:25

executive way, jump in, reach

6:27

out to their connection there. Obviously,

6:29

as you scale that becomes harder

6:31

and harder and you're just you're less

6:33

able to get your hands around

6:35

what's really happening in that client relationship.

6:37

And what we are doing is

6:39

really what that person does on a

6:41

small firm of being able to,

6:43

you know, use their intuition to say

6:45

like, hey, we should flag

6:47

this, somebody should reach out to them

6:49

with AI. We can

6:51

do that now. So at

6:54

scale, we can take all

6:56

the exhaust from those relationships,

6:58

all those communications, all

7:00

those transcripts, emails, Slack conversations, and

7:02

really provide an objective view

7:04

of what's going on in the

7:06

health of that relationship with

7:08

that client and signal, hey, you

7:11

need to take action here.

7:13

Something needs to happen here. And

7:15

so we're really excited about

7:17

this new era of client intelligence.

7:19

for professional service firms and

7:21

excited to see, you know, I

7:23

always joke with our team,

7:25

you know, we say, see,

7:28

we talk about marketers, we talk

7:30

about CRMs all the time. And it's

7:32

a customer relationship management, you know,

7:34

we all know that's what it stands

7:36

for, but it's not actually what

7:39

it is. You know, it's really an

7:41

acquisition platform. It's really

7:43

actually a terrible way to

7:45

track what's happening in

7:47

your client relationships or your

7:49

client management. And so

7:51

what we're doing today, sometimes

7:54

I'm like, what we're

7:56

doing is real client intelligence,

7:58

client management in modern

8:00

era. Yeah. I mean,

8:02

I think, so two things there. I mean,

8:04

I think what you're saying is, you

8:06

know, a CRM is trying to quantify There's

8:10

some emotion and some

8:12

real relationship stuff that's

8:14

happening. What's the

8:16

drop -down value for angry clients

8:18

or whatever, something like that.

8:20

But also, I think maybe

8:23

to use an analogy, if

8:25

a company sells products, sells widgets,

8:27

let's say, and they can have

8:29

100 or they can have a

8:31

million, and AI actually probably does

8:33

a decent job at scaling to

8:35

that. But to your point, when

8:38

there's so much nuanced conversation

8:40

happening, when sometimes the thing that's

8:42

happening is what doesn't happen. I

8:45

would imagine there's so

8:47

much nuance there that the

8:49

idea of structuring that

8:51

data must be a challenge,

8:54

right? Yeah, absolutely. And

8:56

at the end of the day,

8:59

What what we're trying to do, what

9:01

we believe wholly in is really

9:03

using AI to help us humans do

9:05

what only humans can do. And

9:07

what we believe is humans are the

9:09

ones that engage in relationship that

9:11

actually know other people and know them

9:14

well. And that's where our name

9:16

known well comes from. And so that's

9:18

what we're trying to do is

9:20

take. you know, give professional service firms

9:22

the information they've always needed and

9:24

not known that there would ever be

9:26

the kind of technology to help

9:29

them do that for them to go

9:31

be in relationship with their customers. Yeah.

9:34

Well, so then, you know, next

9:36

logical thing, what does that allow people

9:38

to, you know, for these companies

9:40

to do and do better with their

9:42

marketing strategies? Yeah, I mean,

9:44

I think there's so much,

9:47

especially in the growth opportunity side,

9:50

so many times where upsells fall

9:52

in an organization. It's like a

9:54

revolving door. You just don't know.

9:56

It gets changed all the time.

9:58

Whose responsibility is it? And I

10:00

think when you have a intelligent

10:03

source like known well, helping you

10:05

see when there's opportunity and when

10:07

it takes the guesswork out of

10:09

that, it makes it a lot

10:11

easier to figure out how to

10:13

solve that problem. the best way

10:16

you can in your organization. It

10:18

makes it where, hey, if it needs to be

10:20

a collaborative process, but we've

10:22

taken the hard work of figuring

10:24

out when that collaboration needs to

10:26

happen, it takes those

10:28

opportunities to the next level. And

10:31

so we're really excited about what

10:33

that means for the growth of

10:35

the existing bases within these organizations.

10:38

Yeah. And so to dive in

10:40

a little deeper here, so

10:42

with enough time and resources, I'm

10:45

sure a marketing company, a

10:47

professional services company, could probably make

10:49

a really, really detailed spreadsheet

10:51

that has a lot of information

10:53

here. To your point, you're

10:55

using AI to take things much

10:57

further. Can you talk a

11:00

little bit about what's the power

11:02

of AI in this to

11:04

really do what you're saying? You

11:06

bring up a great point.

11:08

We have interviewed hundreds and hundreds

11:10

of professional service firms and

11:12

even the most successful firms. They

11:15

are using a spreadsheet, a red,

11:17

yellow, green. What's the status

11:19

of our clients? There

11:21

is value in that. But

11:24

at the end of the day, it is

11:26

still subjective. It takes

11:28

a lot of work to wrangle, hey, has

11:30

everybody got that in? If

11:32

you're in leadership, you're

11:35

having to just trust people. perception

11:38

of things, their subjective

11:40

assessment of what's happening.

11:43

And what you want is actually

11:45

to know that you've got

11:47

something covering the blind spots, the

11:50

things that help you not have that

11:52

surprise turn. I think it's the worst kind

11:54

of turn is that surprise turn. You think

11:56

you've got a great client and then you

11:58

find out they're leaving. That is painful. And

12:01

so, you know, what this does is

12:03

really give you that other source, that

12:05

objective source, again, both very

12:07

powerful. It's not that you're not

12:09

going to need subjective. It's just

12:11

that you're going to use both and really

12:13

create kind of a powerhouse of knowing, confidently

12:16

knowing that you know what's

12:18

actually happening with your clients. Yeah.

12:20

Yeah. mean, I think that that objective source

12:22

is really important because, you know, I

12:25

would imagine in some case somewhere, you

12:27

know, someone doesn't really want to say that

12:29

the client's upset and report a problem.

12:31

But I would say probably in most cases,

12:34

people are well -intentioned, they

12:36

just may not have

12:38

all the data to

12:40

change that from yellow

12:42

to red. I've

12:44

seen that spreadsheet way too many times,

12:46

by the way. So

12:48

AI being more objective,

12:51

it applies the same

12:53

rules to everything. I

12:55

think that's a really powerful thing. And then

12:57

to your point, then leaders

12:59

can adjust, I'm sure, or they

13:01

can interpret still, but at

13:03

least it's a the level playing

13:05

field, right? Well, and I

13:07

think the other powerful thing that

13:09

I'm not mentioning is the

13:11

red -yellow -green is on a client

13:13

-by -client basis, a subjective at

13:15

the client level. There's nothing

13:18

to really take the level up of

13:20

what's happening and actually being able

13:22

to apply and see the trends and

13:24

connect the dots between all of

13:26

these things. That is hard

13:28

work. And that's what

13:30

AI is so good at. And

13:32

so not only are you looking

13:34

at what is the health of

13:36

these clients, what's the objective score

13:38

with these clients, but what's the

13:40

intelligence sitting above all those clients

13:43

and able to say, hey, here's

13:45

what's happening to your portfolio. All

13:47

of your clients that have

13:49

this certain product, they always churn

13:51

after 90 days. And here's

13:53

what you can do to fix

13:55

that. It's really being able

13:57

to help you connect dots like

13:59

you've never been able to

14:01

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14:05

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14:41

fee. I can't wait

14:44

to see you

14:46

there. So

14:55

I mentioned at the top of

14:57

the show of the five levels of

14:59

AI and I wanted to get

15:01

back to that and have you kind

15:03

of walk us through that and

15:05

explain how each level impacts various business

15:08

functions. Yeah, thanks.

15:10

This is one of my favorite topics

15:12

because obviously AI, I'm passionate about

15:15

it. I talked about being able to

15:17

deploy my craft in different ways. This

15:20

area specifically with AI, I

15:22

think it's really exciting. If

15:24

you're listening, I think early

15:26

on, we got really used

15:28

to thinking about AI as

15:30

just a tool to help

15:32

me be more productive in

15:34

my own job. I

15:37

think this frame really helps unlock

15:39

a little bit of where we're going

15:41

all the time. You probably hear

15:43

like, this is just the beginning, but

15:45

it's hard to really think of,

15:48

okay, well, what could or will the

15:50

feature look like? That's tough with

15:52

this new technology. And so

15:54

I'll break it down this way.

15:56

If you look at the very

15:58

bottom layer of work, it's really

16:00

manual labor. And if you think

16:02

of how AI applies to manual

16:04

labor, we all get its robotics. And

16:07

we've had it for a long time.

16:09

And so really easy concept. The

16:11

level up from that is

16:13

execution. And it's

16:15

really automating core knowledge

16:18

work and driving individual performance

16:20

excellence. And that's really

16:22

what we've had with chat

16:24

GPT, starting two years

16:27

ago. And a lot of

16:29

the AI tools that we've had up

16:31

to date, they're all on this

16:33

level of execution, helping us do our

16:35

jobs better and certainly valuable. But

16:38

if you start to look at these levels

16:40

above this, this is where I think it

16:42

gets really interesting about examining where AI is

16:44

going to take us in the future. So

16:47

the level above that is

16:49

operations. And it's really

16:51

how do we work together

16:53

across the organization to move

16:55

the business forward to drive

16:57

results? That's where

16:59

you're starting to see

17:01

more AI platforms like

17:04

knownwell and other platforms

17:06

that are actually helping

17:08

work across organizations, not

17:10

just to drive individual

17:12

performance, but to drive

17:14

the entire business forward. Hopefully

17:17

that's helpful for unlocking. Oh, I

17:19

can start to see how AI is

17:21

going to start changing business on

17:23

the operational level. Now, obviously,

17:26

if we go above that, you have

17:28

the strategy of the organization. I don't

17:30

think we're there yet with AI, but

17:32

certainly I think we will start to

17:34

see a more AI impacting strategy. And

17:36

then at the very top, we have

17:39

the ideology of our businesses. don't

17:42

think. I hope, and this

17:44

is where we have to do some

17:46

work as a society of figuring out where

17:48

does AI, how far do we let

17:50

AI go? And I hope that maybe this

17:52

is an area we retain as humans,

17:54

that we drive the ideology of our business,

17:57

our values, our purposes. Hopefully

17:59

we retain that. But I think

18:01

thinking about it in this frame

18:03

really helps maybe unlock what could

18:05

the future look like as it

18:07

escalates through these different levels. I

18:09

love that framework. And yeah, mean,

18:11

I agree. When we get to

18:14

that top level, it's going to

18:16

look a lot different than we

18:18

could imagine it right now, right?

18:20

So in other words, you know, because I

18:22

think even over the last couple of

18:24

years, there's been, you know, as

18:26

with anything, I mean, it used to

18:28

be like back in the day with like

18:31

social media, like Facebook changed the placement

18:33

of a button and society like cried out

18:35

that, you know, life was unfair or

18:37

whatever. And now it's like, AI

18:39

is going to take our jobs. Yes,

18:41

it will take some of them, but

18:43

we're actually making a lot of progress

18:45

in how we work with AI and

18:47

stuff. I guess I'm an optimist when

18:49

it comes to a lot of this

18:51

stuff, not hopefully cautiously optimistic, but I

18:54

guess to get to the operational piece

18:56

because I feel like that's where a

18:58

lot of companies either are or that's

19:00

where they're striving to get to to

19:02

your point is like that's kind of

19:04

the next the next step, if

19:06

not current state for a lot of

19:08

companies. To me, that's where

19:10

I see a lot of the

19:13

agentic AI and those things that are,

19:15

that's like the buzzword of the

19:17

month or whatever in AI circles. But

19:19

I think there's tons of promise

19:21

there because we have had a lot

19:23

of people in their little silos,

19:25

like somebody using Claude and somebody using

19:27

ChatGBT and all in the same

19:29

company. And then when a company tries

19:32

to do something, it's like, okay,

19:34

well, What do we do? Which one

19:36

do we use? So

19:38

I think there's so much promise.

19:40

And good to see that

19:42

I've been on the other side

19:44

of things too, but I've

19:46

been at plenty of professional services

19:48

firms with some of the

19:50

challenges you describe. And so knowing

19:52

that someone's trying to tackle

19:54

this problem is very reassuring. Where

19:57

do you see most marketing

19:59

firms today? Have

20:01

they gotten quite to the operational

20:03

piece or are they still before

20:05

that? Yeah, I would say

20:07

they're usually before that. And I

20:09

think partly just because we haven't

20:12

seen a lot of offerings on

20:14

that operational level yet, I

20:16

think we will continue to see

20:18

more. If you think back early,

20:20

hindsight is 20 -20, but so

20:22

many of these large enterprises we're

20:24

talking about building their own AI,

20:26

how do you get that talent

20:28

in? And in many

20:30

cases, I think probably jumped the

20:32

gun on spending the

20:35

resources to go build their own

20:37

thing. And I think we're going to

20:39

have a lot of options here

20:41

to help us solve problems that are

20:43

going to be off the shelf

20:45

and hopefully a lot more affordable for

20:47

mid -market firms and smaller firms to

20:49

still be able to leverage that

20:51

technology without the cost of trying to

20:53

maintain the technology. And so,

20:55

I think today, you know, a lot

20:57

of marketing firms don't have the

20:59

option of these operational tools yet, again,

21:02

known well as one of them. I think there are

21:04

going to be quite a bit more. I

21:06

do see them deploying,

21:08

you know, at the execution

21:11

level of, you know, evaluating

21:13

how do we get more

21:15

out of, you know, for

21:17

everybody on this team with professional

21:19

service firms, we know if we

21:22

can You know, there's such a

21:24

cost with people. We have to

21:26

have people and professional service firms

21:28

to scale. We can't scale without

21:30

people. That's been the recipe for

21:32

so long. But with AI, you

21:35

can actually that curve of

21:37

that growth. curve doesn't have

21:39

to be so linear between

21:41

clients and people needed to

21:43

provide the delivery. And

21:46

so that's what's really exciting to

21:48

me for marketing firms is can

21:50

we start to bend that curve

21:52

more than we ever have before?

21:54

And so I do see them

21:56

working with a lot of the

21:58

different AI tools for execution because

22:00

that, of trying to bend that

22:02

curve and get more than they've

22:04

ever been able to do before

22:06

out of their individual contributors. Yeah.

22:09

mean, I think what's interesting here to

22:11

totally agree on the execution side, it's

22:13

like there's, I think, and I think

22:15

in the long run, people will find

22:17

more value in their jobs because of

22:19

it. I think in the short term,

22:22

you know, certainly there's, there's some, you

22:24

know, and right, rightfully said, there's, there's

22:26

some trepidation there as far as, you

22:28

know, not wanting to lose their role

22:30

or whatever. But I think on the

22:32

other side, on the relationship side, I

22:34

think that was the harder

22:36

thing to scale to, I mean,

22:38

obviously, known well, found a business model

22:40

there, right? So it's like, I

22:42

think that's, that's promising too. Because yeah,

22:45

I mean, if you're, it's

22:47

going to come down to, I

22:49

think a lot of clients are going

22:51

to want to rethink the way

22:53

that they're compensating firms. And so I

22:55

know even with some firms, I

22:57

deal with, they're rethinking how, you know,

23:00

their business model. And no, they

23:02

can't just cut their costs because they've

23:04

reduced some people but have

23:07

AI. It doesn't quite work

23:09

like that, but they also need to

23:11

be able to scale their ability

23:13

to have relationships with their clients too

23:15

as they scale the ability to

23:17

churn out content with AI and stuff

23:19

like that. I don't know

23:21

what the question is there. I

23:23

guess maybe my next question would just

23:25

be, I think

23:27

there are some aspects. Again, marketing

23:30

firms, professional services firms have been really focused

23:32

on, you know, again, how do we execute and

23:34

all that? What are they overlooking? Like, what

23:36

do you see as like, what's the low hanging

23:38

fruit that people aren't just paying enough attention

23:40

to now? Yeah, that's a

23:42

great question. I, in

23:44

some ways, I feel

23:46

like especially when it

23:48

comes to churn, and

23:51

I would say even going

23:53

back to what I said

23:55

at the beginning of just

23:57

not being able to have the

23:59

information they need to really

24:01

successfully run their firm because

24:04

when you're having to run

24:06

off subjective information, you're really

24:08

having to use your gut. Do

24:10

I trust this subjective

24:12

information? And it only takes

24:15

a few times of eroding that

24:17

subjective that you start to question.

24:19

And it's just natural. It's going

24:21

to happen because At the end

24:23

of the day, it's people working

24:25

with people. There's perception on perception,

24:27

and it's a hard job. What

24:29

these teams do, these people dealing

24:31

with their clients, they

24:33

are some of the most, absolute

24:35

most important people in your

24:38

organization. It's a hard job, but

24:40

it's also hard for the

24:42

leadership to be able to make

24:44

data -driven decisions off those subjective

24:46

analysis of what's happening with

24:48

their clients. You know,

24:51

they're missing that there is a

24:53

new world being open where there

24:55

is platforms that are able to

24:57

bring in all of these different

24:59

resources to really give them where

25:01

they can lead from confidence and

25:03

not having to lead from get

25:05

really being able to make decisions

25:07

from data. I would say that's

25:09

the big unlock here. Yeah.

25:11

I mean, I think, you know, as

25:13

as an entrepreneur myself, you

25:15

know, there's a fair amount of I'd

25:18

like to think it's not delusion,

25:20

it's optimism. You

25:22

have to be optimistic as an

25:24

entrepreneur or I'll broaden it

25:26

as an entrepreneurial person because I

25:28

think salespeople and client services

25:30

account people within organizations. They're entrepreneurial

25:32

in the sense they're either

25:34

trying to grow the business or

25:36

get more clients. So you

25:38

get a bunch of entrepreneurial people

25:40

there that want to look

25:42

at the glass half full and

25:44

to your point, Again,

25:46

best intentions, you

25:48

know, it's but but it's still it's

25:50

a a bit skewed sometimes and

25:52

you you know, there's a by there's

25:54

an anchor bias. There's a whatever

25:56

whatever kind of bias that's that's causing

25:58

you to think that way. But

26:01

again, best intentions aside, it's still it

26:03

can lead to that. unintentional churn

26:05

that you mentioned earlier. Right.

26:07

Absolutely. That's the whole thing is like we

26:09

all have blind spots. So this

26:11

is a platform that helps you make

26:13

sure you don't have that blind spot on

26:15

every level of the organization from the

26:17

person on the ground dealing with the client

26:19

to the CEO. Yeah, yeah.

26:21

So I want to switch gears just a

26:23

little bit here. As I mentioned,

26:25

you host your own podcast. So definitely highly

26:27

recommend everybody checks that out as well.

26:29

Don't stop listening to this one. There's

26:32

plenty of hours in the day. Listen

26:34

to both, please. I'm

26:36

always curious other's journey as

26:39

well here. How has podcasting, whether

26:41

it's deep into your understanding

26:43

or just kind of broaden your

26:45

understanding, or what impact has

26:47

it had on just how

26:50

you think about AI and marketing and business.

26:53

Yeah, it's been an absolute game

26:55

changer on that front. I

26:57

think there is something to

26:59

be said to just being able

27:01

to have conversations with people

27:03

that are thinking about, excited about,

27:06

really examining what AI

27:08

is going to look

27:10

like for business and

27:12

society. There's a lot

27:14

that we have to think

27:16

about as business leaders. as

27:20

professional service

27:22

firms, but all the

27:24

way down to just at

27:26

the individual level of, hey,

27:28

how is this going to change

27:30

our society? What things

27:32

are we good with? Which things

27:34

are we not? How do we

27:36

start to... really question what makes

27:39

humans human? And then how do

27:41

we retain those things that are

27:43

so core to being a human?

27:46

Those are heavy topics. And I

27:48

think being on the podcast and

27:50

talking to a really, really

27:52

sharp, and I would say

27:54

a lot of times very technical

27:56

people has been really enlightening. And

27:58

then trying to try to help

28:00

executives, especially those of us that

28:02

aren't necessarily technicians, you know,

28:05

translate those very smart

28:07

technologists and what they know

28:09

into things that are

28:11

very practical for, hey, what

28:13

should we be examining in our business? How

28:15

should we be thinking about AI? How do we

28:17

deploy it well? How do

28:19

we deploy all these different questions? It's

28:21

been really helpful for me of

28:23

just challenging my own thinking. And

28:26

I don't know, for those of

28:28

you that are listening. If

28:30

you're anywhere close to my age bracket,

28:32

which I'll just tell you, I was in

28:34

college when Facebook came around. Do you

28:36

remember when you had to have a college

28:39

email address? You know, and so

28:41

I think I'm especially primed for, you

28:43

know, if I look back, you know, I'm

28:45

always like, if I only would have

28:47

known, you know, like I was one of

28:49

the earliest people using this platform. If

28:51

I would have done something different earlier

28:54

in my career, could have really paid

28:56

off. And so I think now that

28:58

we're here with AI, we see this

29:00

as, hey, this is a huge moment

29:02

in time. And, you know, I'm

29:04

not going to, you know, I'm smarter now than

29:06

I was when I was, you know, 18. I'm

29:08

going to engage in this differently than I

29:10

did back then. And so I think it's, if

29:13

you're in this similar age bracket,

29:15

you're looking at this and being like,

29:17

this is either, for

29:19

me, it's very exciting of, okay,

29:21

how do I, there are

29:23

things hopefully that we've learned. in the

29:26

past about how these new technologies, how

29:28

we need to be thinking about them.

29:30

And so for me, it's really exciting to

29:33

have a platform to be able to do

29:35

some of that wrestling and that thought -provoking work,

29:37

and then hopefully to be able to share

29:39

it with people that are listening. Yeah,

29:42

yeah, love it. Well, Courtney,

29:44

thanks so much for joining today. One last

29:46

question I'd like to ask everybody. What

29:48

do you do to stay agile in your role and how

29:50

do you find a way to do it consistently? Oh,

29:53

such a great question. You

29:55

know, I would say it's so

29:57

much of as the people around

29:59

me that helped me do that

30:01

and the collaboration with really smart

30:04

people and helping, you know, totally

30:06

be there to challenge and to

30:08

think through and push me to

30:10

new levels. That is when you

30:12

find those people, hang on to

30:14

them. They're worth it, even when

30:16

it's hard. It's not

30:18

always easy. Love it. Well,

30:20

thanks again to Courtney Baker, CMO at Known Well

30:22

for joining the show. You can learn more

30:24

about Courtney and Known Well by following the links

30:26

in the show notes. Thanks

30:30

again for listening to The Agile Brand, brought

30:32

to you by Tech Systems. If

30:34

you enjoyed the show, please take

30:36

a minute to subscribe and leave us

30:38

a rating so that others can

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find the show as well. You can

30:43

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30:45

at theagilebrand.com. That's theagilebrand.com. And

30:47

contact me if you're

30:49

interested in consulting or

30:51

advisory services or are

30:53

looking for a speaker

30:55

for your next event.

30:57

Go to www .greggkilstrom.com. That's

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