KOPYA NG SALIN 🔗
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how do you
also make sure that you're leveraging AI?
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But there's some type of governance.
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You don't have 20 people asking,
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20 salespeople asking something different.
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But yet what's happening at the enterprise
level?
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Right. Absolutely.
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And we're going to get into we're going
to get into the implementation of AI.
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But, we're joined here
by Stephen Cassell, who is with Chief
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Outsiders,
with a chief marketing officer.
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Focus, at a fractional component,
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which means you go in and help companies.
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And not are
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not a permanent employee position
with inside the company.
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Correct? That's correct.
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That's correct. be.
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Faster!
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Our stalled.
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Our our funnel
not working the way it should work.
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And then
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or exit
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or we've purchased as that look like
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those are typical scenarios.
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And you know I think it's it's
really something that I enjoy.
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And after many years working
for corporations and an operator role,
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you know,
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everything from big to,
you know, PE owned.
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It's,
it's been a really interesting way to,
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to really help accelerate growth for,
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for a lot of mid-sized companies
who are looking for that next stage.
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Well, a mid-sized company is unlikely
to have a chief marketing officer.
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That's you see that at a higher,
you know, fortune 500 company will have.
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So it gives you somebody
that has the knowledge base.
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So how did you how did you get into this
fractional position.
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Yeah, it was Cigna
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Healthcare here.
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And then also went worked
for a company up in Boston.
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032 health.
So a lot of health and services.
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And really I kind of boil it down
to it's all about B2B.
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And are you working with another business
or are you selling through
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another business
or you also selling to consumers.
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And so
how do you really think about those?
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Really struck me
after years of thinking about okay,
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well there's always another operator
roll out there.
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There's always another kind of next job.
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And then I was what I really love doing is
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either opportunities or
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if there's potentially something
that's not working well.
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Why am I not focusing on that and helping
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with those
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a lot of companies.
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Things are working well for things
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in all beauty of.
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Okay,
I'm going to have you on a full time right
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CMO basis.
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Yeah, I get what you need.
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I don't need lower price. Yep.
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You know, a full time
position hits the penal pretty hard
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when you are at that level.
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So if you can do that
for a fraction of that,
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then that's helpful.
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Well, Stephen, you and I met
and we had some great conversations about
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AI, the use of it,
and the governance and management of it.
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So that's kind of why
I wanted to get your input today.
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I've
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last year,
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even though everybody was screaming
AI from the
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the top of their lungs,
I have been a very slow believer,
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and a very cautious,
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to many science
fiction novels from my liking.
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So I feel like
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we're finally at the point
that everybody needs
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to at least be aware of it
and think about, can it help?
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Does it help?
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Or should I be making a
I do something that a I can't do?
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And if that's the case then I should be
marketing the heck out of that.
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So there's all all different ways
to consider it.
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What are your thoughts?
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Yeah, my thoughts are and it's obviously
evolving very, very quickly.
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Where we, where we are now.
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And I think that
there are some clear cases
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now where
Load full transcript
and actually see
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you know efficiency improvements from,
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from implementation.
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It's I think there's also places
where you can see, you know,
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performance improvements.
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And then increasingly
what you're beginning to see
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is where you places
where you can see execution improvements.
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And if I break that down a little bit,
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I think it's really important
to realize that for years
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we've been leveraging what I would call
kind of the predictive analytics, and
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which is a type of what AI is now
accelerating.
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When you think about from a marketing lens
or a sales lens,
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how companies have leveraged,
predictive analytics for lead
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generation and identify and prospects
and all of these different things.
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That's been around for a bit.
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Now, what's accelerated is the idea
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that, okay, I can do
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parts of that process so much more quickly
than I could ever do before.
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And I think the, the,
the thing we have to avoid
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is thinking that fast is always better
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without the proper oversight
and and review
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of what fast is actually producing.
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And so so that's where I think
the, the place where we are
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now is should a company be thinking about,
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okay, how do I improve my my growth.
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How do I see how do I think
about my performance and my execution?
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Of course, because now some of
these things really are accelerated.
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It's much easier now to, get out
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and, and do an hour's.
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What used to take weeks.
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But guess what.
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You still have to understand and
put a human eye on that to validate it.
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And, and so parts of it may be truncated,
but there's parts of it
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that you still need to really.
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Wait a second.
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Maybe we do need to talk to some real
customers and not just a chat agent. Yes.
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And maybe we need to really kind of
get out in the field.
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And if we're talking about $1 million
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decision, doesn't that doesn't
that validate warrant the time.
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Little bit of time and energy.
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I think it's quickly accelerating.
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And those are just some of the
the ways that I think about,
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you know,
that that efficiency and performance.
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And then he I think that a lot of people
when this first hit
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equated it to the robot, right,
the robot arm that comes in
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and does the same thing over and over
and over very fast, very, you know,
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automation,
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and when I first started hearing
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AI, it was, I don't need interns,
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I have ChatGPT.
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And that's problematic
for a lot of reasons.
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Right? Short and long term.
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In the in the short term, what happens to
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those people that we're going
to start learning from you?
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As an intern,
they're not going to get the internship.
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So you're not
you're not growing the candidate pool.
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And it's problematic
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from the oversight of the AI
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because you can't set it
and forget it like you
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possibly could a robot arm
and go work on something else.
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You need to be validating
that what you're getting is accurate.
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And certainly it's learning,
and certainly it's getting better.
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But, I don't know that
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we want to get rid of our interns
just yet.
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Agree with you because I think,
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not even shedding roles.
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It's how do you adjust roles that leverage
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to some things can be accelerated,
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but that doesn't mean you can take humans
completely out of the system.
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That's my perception.
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And yeah, what I've seen in
and to use the internet
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example, if you're not breach,
well guess what.
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When everybody is going out and retiring.
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We're going to put in their jobs. Right.
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And it's not like
AI is going to completely tight.
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Right now, can it
help?
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Of course, of course.
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I had a lunch last week with a
a large firm,
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and, they said, oh,
we were told our mandate this year
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is to find 20%
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of every job in the firm
and attribute it to AI.
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And I said, to what end?
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Like, because you're firing 20% of your
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people resources the following year.
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Like, why are we.
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What are you trying to accomplish?
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And they went. Oh.
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Said, wait a second.
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Maybe I can use identify
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the segments
where I should be selling or targeting,
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and I can become more efficient
in my sales process
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or my
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improve
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how we're actually distributing,
you know, other parts of the business,
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not necessarily marketing,
but operations versus one who doesn't.
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Well, okay,
probably the value of the one that's doing
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some of these things
is going to be higher.
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Because you're going to see higher
those types of things.
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But nowhere in that sentence is it.
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Oh well let's, let's eliminate
all the humans
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who are actually helping to, to
to to make this happen.
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And I think that's
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one of the keys is again, it's
how do you augment, how do you accelerate.
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And at the same time,
if you're employing some of these things,
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how do you also adjust
people's roles and jobs
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so that they're then overseeing
if something is also on the way?
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Yeah.
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To make sure that you're in the jeopardy!
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Well, and I think to use AI just because
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I said use AI is probably the wrong
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the wrong adjustment.
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That's right.
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So if there's a purpose to employing AI,
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then I think it's a little
and it's a little easier
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to make it concrete
and to make it efficient.
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But not just in their functions.
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As an advice level.
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Right. Governance and oversight.
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Really easy to have where it might be.
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When suddenly there's a reputation brand
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or you know one same thing.
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And guess what. They don't, they don't,
they don't square.
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Right. Market. Right.
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And so I think those are some kind of as.
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Yeah. Do we have our arms around this
the right way.
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Do do you solve that
with an enterprise system.
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Like is that the is that the solution.
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I think it's an enterprise approach.
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Okay. And and how do you think
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inside of things.
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How do you
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what are our rules,
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those kinds of kind of, questions
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that used to be reviewed
by legal compliance etc..
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They don't go away.
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Right. But
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because my understanding
of an enterprise system
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is that you can give it
things like brand scope and,
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and it can operate within the
that parameters.
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And then you train it.
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Right? Right.
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So that it learns your brand the way
you want things talked about the way.
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So that kind of governance and oversight
can create a powerful tool.
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Versus not having it right.
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Versus Bob uses chat, and and Jane uses
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Claude, and, you know,
and somebody else is used Gemini.
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And and there's not any specific,
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colons between everyone.
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That's right.
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Kind of small and mid-sized companies.
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And she
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kind of accelerates
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if you thought it or growing
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your business, it
it accelerates the strategy
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and the insights and,
and kind of those types of things.
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But how do you know things.
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And so I think that's
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going to be one of the interesting things
that we'll start to see more
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and kind of switching it
over into
how do we actually use this
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in a systematic way.
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Enterprise system
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as well as you know these things are okay.
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Absolutely.
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We we're having a conversation
with a, a buying group
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that uses AI to read line there in days.
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Right.
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So in our process, you
when you go to market, you sign
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an NDA prior to receiving information
that proprietary.
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And we can get to confidentiality
and AI in a minute.
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But the, the NDA
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itself is, you know, a one page document.
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It's not really generally
that big of a deal.
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00:16:49,883 --> 00:16:53,637
There's a few terms that are, you know,
we like 12 months.
254
00:16:53,637 --> 00:16:55,347
We like eight, you know, 24.
255
00:16:55,347 --> 00:16:57,099
We'll settle on 18.
256
00:16:57,099 --> 00:17:01,729
So they put the document into,
257
00:17:02,563 --> 00:17:05,065
not even chat into Gemini.
258
00:17:05,065 --> 00:17:08,444
And they had Gemini added it
and they sent it back.
259
00:17:08,610 --> 00:17:12,823
And they said,
we assume that you're using an AI tool
260
00:17:13,032 --> 00:17:15,951
to redline this.
261
00:17:15,951 --> 00:17:18,954
I was like, no.
262
00:17:19,455 --> 00:17:20,748
100% no.
263
00:17:20,748 --> 00:17:25,502
And one of our partners I touched on
goes, well, why aren't we then?
264
00:17:25,669 --> 00:17:29,548
And I'm like, because now
you're going to have a redlining for AI.
265
00:17:30,632 --> 00:17:31,675
What?
266
00:17:31,675 --> 00:17:33,969
How long is that going to take?
267
00:17:33,969 --> 00:17:36,138
Right. It's going to not even come back.
268
00:17:36,138 --> 00:17:37,514
It's going to come back and say
269
00:17:37,514 --> 00:17:40,100
we won't talk to each other or something
silly, right?
270
00:17:40,100 --> 00:17:43,103
Because they're each going to go back
and forth and cut things out.
271
00:17:43,395 --> 00:17:46,356
What do you end up with? Is it actually.
272
00:17:46,356 --> 00:17:47,649
Is it actually stable?
273
00:17:49,193 --> 00:17:50,652
So I do worry that
274
00:17:50,652 --> 00:18:00,871
about things like that as we head
further down into an interesting article.
275
00:18:01,872 --> 00:18:02,790
So whatever.
276
00:18:02,790 --> 00:18:05,375
You're
277
00:18:05,375 --> 00:18:08,378
right, a discoverable
278
00:18:09,004 --> 00:18:09,505
formation.
279
00:18:09,505 --> 00:18:12,966
So correct
that that gets to the what guardrails
280
00:18:12,966 --> 00:18:16,720
do you have right in mind,
especially with sensitive information and.
281
00:18:16,762 --> 00:18:17,429
Right.
282
00:18:17,429 --> 00:18:20,724
And of agents.
283
00:18:21,141 --> 00:18:26,063
Well and we you know on our we are highly
sensitive to confidential information.
284
00:18:26,105 --> 00:18:26,355
Right.
285
00:18:26,355 --> 00:18:29,358
We're getting all of the information
about a company.
286
00:18:29,525 --> 00:18:32,945
And discoverability is a key factor
287
00:18:33,112 --> 00:18:36,532
because ultimately somebody's
going to diligence it.
288
00:18:37,116 --> 00:18:40,410
And if there's a problem in a transaction,
289
00:18:40,577 --> 00:18:43,580
everything that we have communicated
290
00:18:43,831 --> 00:18:45,499
is discoverable.
291
00:18:45,499 --> 00:18:50,254
So, you know, even even using AI,
292
00:18:50,254 --> 00:18:55,425
we don't do a lot of it
within the operations of the company.
293
00:18:55,843 --> 00:18:58,011
We use it more for
294
00:18:59,096 --> 00:19:00,264
I have a report
295
00:19:00,264 --> 00:19:03,267
about the people
that are coming to the meeting.
296
00:19:04,101 --> 00:19:05,602
Yeah. Help me put together.
297
00:19:05,602 --> 00:19:07,646
Right. Right.
298
00:19:07,646 --> 00:19:09,481
Yeah, exactly.
299
00:19:09,481 --> 00:19:12,484
So it's more assistant based,
300
00:19:12,651 --> 00:19:15,904
whereas I know that
there are organizations that are like.
301
00:19:15,904 --> 00:19:18,532
Right. My sim.
302
00:19:18,532 --> 00:19:21,493
And we just don't think
that's a good idea.
303
00:19:29,334 --> 00:19:30,460
What's not possible?
304
00:19:30,460 --> 00:19:30,836
Right.
305
00:19:30,836 --> 00:19:36,091
And what what could agree with you?
306
00:19:36,175 --> 00:19:37,217
Yeah.
307
00:19:37,217 --> 00:19:38,302
We don't.
308
00:19:38,302 --> 00:19:43,182
And the other one that that we do that,
I, I think we're starting to get
309
00:19:43,182 --> 00:19:47,603
some pushback on buyers
love to have a note takers
310
00:19:48,478 --> 00:19:51,481
in meetings with owners.
311
00:19:52,649 --> 00:19:55,277
Why is that good for the owners?
312
00:19:55,277 --> 00:19:56,111
Right.
313
00:19:56,111 --> 00:19:59,072
So anything and everything they say
314
00:19:59,531 --> 00:20:03,160
is gonna be transcribed and can be
315
00:20:04,161 --> 00:20:06,955
effectively used against them.
316
00:20:06,955 --> 00:20:09,499
And so I, I said that to,
317
00:20:10,626 --> 00:20:15,088
to one of the groups that we're working
with a, a larger leadership team
318
00:20:15,088 --> 00:20:20,969
and they have an advisory board and etc.,
and I said, we don't use AI in meetings.
319
00:20:21,094 --> 00:20:23,764
And they're like, why? Well,
remember what they ask.
320
00:20:23,764 --> 00:20:28,477
I said, take notes on paper with a pencil,
321
00:20:28,977 --> 00:20:32,606
because everything you say in
that meeting will be in that transcript.
322
00:20:32,773 --> 00:20:35,692
And if there's ever a problem,
323
00:20:35,692 --> 00:20:37,611
it's on record.
324
00:20:37,611 --> 00:20:40,572
And
they're like,
does that apply to other meetings?
325
00:20:40,572 --> 00:20:43,575
I'm like, pretty sure pretty sure it does.
326
00:20:43,825 --> 00:20:48,288
I think we're also going to see,
down the down the line.
327
00:20:48,288 --> 00:20:51,291
Not yet, but not far down the line.
328
00:20:51,500 --> 00:20:54,711
I think that companies
that are using enterprise
329
00:20:55,420 --> 00:20:58,048
AI, the AI itself,
330
00:20:58,048 --> 00:21:01,051
is going to become part
of the diligence process.
331
00:21:01,051 --> 00:21:03,804
Because it's the IP of your company.
332
00:21:03,804 --> 00:21:05,305
That's right.
333
00:21:05,305 --> 00:21:06,265
That's right.
334
00:21:06,265 --> 00:21:10,143
Once an enterprise system is set up,
then suddenly that becomes part of the
335
00:21:10,185 --> 00:21:12,271
it's part of what you're selling.
Part of what you're selling.
336
00:21:12,271 --> 00:21:12,437
Yeah.
337
00:21:12,437 --> 00:21:20,570
They bought all their data
because they just want to ingest that IP.
338
00:21:20,696 --> 00:21:22,281
Right. And and learn
339
00:21:26,410 --> 00:21:27,452
that happening very clearly.
340
00:21:27,452 --> 00:21:28,036
Yeah.
341
00:21:28,036 --> 00:21:31,415
I think that's, I think that's and I,
I think they're starting
342
00:21:31,456 --> 00:21:34,626
to see it at the larger deal levels.
343
00:21:34,960 --> 00:21:38,255
And we what we see is that trickles down
pretty quickly.
344
00:21:38,630 --> 00:21:41,633
So if you're building an enterprise
345
00:21:42,092 --> 00:21:44,511
documentation,
346
00:21:44,511 --> 00:21:47,514
all those guardrails, all the governance,
all that policy,
347
00:21:48,515 --> 00:21:51,226
you're going to need all of that
and diligence
348
00:21:51,226 --> 00:21:54,896
to show the buyer
that you have created something.
349
00:21:56,023 --> 00:21:58,233
And the companies
that are doing that better,
350
00:21:58,233 --> 00:22:00,235
more efficiently, more effectively.
351
00:22:00,235 --> 00:22:01,737
I think we'll see a bump in there.
352
00:22:01,737 --> 00:22:03,530
Multiples. Right.
353
00:22:03,530 --> 00:22:14,207
Which is it's a it's the analog getting
the sales and those types of things.
354
00:22:14,207 --> 00:22:19,588
If you have time in terms
355
00:22:19,588 --> 00:22:26,261
of how I'm going to market.
356
00:22:26,595 --> 00:22:28,138
That's a that's a better.
357
00:22:28,138 --> 00:22:31,975
But who's not doing that.
358
00:22:32,017 --> 00:22:34,519
Yeah. So yeah absolutely.
359
00:22:34,519 --> 00:22:39,900
So in marketing
what's the most valuable AI component.
360
00:22:39,983 --> 00:22:40,692
Yeah. I think
361
00:22:44,696 --> 00:22:45,739
predictive analytics
362
00:22:45,739 --> 00:22:53,914
that's clearly for the direct
to consumer side
363
00:22:53,955 --> 00:22:56,958
from, from
364
00:23:00,629 --> 00:23:02,464
I think the other bread and butter
365
00:23:02,464 --> 00:23:10,263
is really at this point around of assets.
366
00:23:10,806 --> 00:23:13,683
Which by the way
still have to check them out.
367
00:23:13,683 --> 00:23:16,645
Yeah. We've all seen out there.
368
00:23:16,645 --> 00:23:21,691
Oh my goodness I saw one on my Facebook
feed like yesterday.
369
00:23:22,067 --> 00:23:25,070
And it was,
370
00:23:25,362 --> 00:23:28,407
it had a heading on top of it
371
00:23:28,407 --> 00:23:32,160
that said something
about retail clothing.
372
00:23:32,411 --> 00:23:35,372
And then it was a picture of a completely
373
00:23:35,372 --> 00:23:38,375
unrelated, like, kitchen item.
374
00:23:38,417 --> 00:23:42,963
And I was like,
I still can't get it right, guys.
375
00:23:44,172 --> 00:23:47,175
Not ready for no governance.
376
00:23:47,467 --> 00:23:48,051
Exactly.
377
00:23:48,051 --> 00:23:54,975
It's about dimension
378
00:23:54,975 --> 00:24:00,021
and account based market, these systems
to do that more efficiently.
379
00:24:00,147 --> 00:24:04,151
But you still send me
human review right.
380
00:24:04,151 --> 00:24:05,026
Whatever.
381
00:24:08,822 --> 00:24:09,322
The second
382
00:24:09,322 --> 00:24:15,787
I think is really and then increasingly
383
00:24:16,413 --> 00:24:20,083
you see it starting to take place
on the execution side.
384
00:24:20,125 --> 00:24:23,962
So can I create an orchestrated,
385
00:24:24,379 --> 00:24:28,633
the product
386
00:24:28,633 --> 00:24:32,137
or service
in a much quicker way than I could before?
387
00:24:32,179 --> 00:24:34,222
So that's kind of where we are right now.
388
00:24:34,222 --> 00:24:37,809
So that could be not just
automated email campaigns,
389
00:24:37,809 --> 00:24:41,062
but when you tie it
to the creative generation
390
00:24:41,062 --> 00:24:45,984
together,
391
00:24:46,318 --> 00:24:49,279
I can see whether Deborah, has
she opened it.
392
00:24:49,279 --> 00:24:51,281
If she didn't, then what's my next action?
393
00:24:51,281 --> 00:24:53,700
Those are all common things before AI.
394
00:24:53,700 --> 00:24:59,331
But now the difference there a new idea.
395
00:24:59,331 --> 00:25:02,209
There's something that's already
kind of percolating in the system.
396
00:25:02,209 --> 00:25:05,212
So I think that's
where from a marketing perspective.
397
00:25:05,253 --> 00:25:09,758
And that's really the go to market
kind of selling.
398
00:25:10,050 --> 00:25:10,634
Buying
399
00:25:13,970 --> 00:25:14,888
the other bread and
400
00:25:14,888 --> 00:25:18,600
butter I see is really on the insights
side of things.
401
00:25:18,767 --> 00:25:19,100
Yeah.
402
00:25:19,100 --> 00:25:24,105
Where, you know, what used to take 3
or 4 months to, to to really understand
403
00:25:24,105 --> 00:25:27,359
what's happening in market can now like
take place in a matter of hours.
404
00:25:27,817 --> 00:25:31,196
And that's a substantial change.
405
00:25:31,571 --> 00:25:33,365
But it also brings with it.
406
00:25:33,365 --> 00:25:35,617
How do you validate that. It
does.
407
00:25:35,617 --> 00:25:37,577
And so so it brings some good.
408
00:25:37,577 --> 00:25:39,204
But then there also is the
409
00:25:39,204 --> 00:25:43,124
how do you validate what you've actually
just gotten in a matter of hours.
410
00:25:43,208 --> 00:25:48,380
And there's a phrase that,
that I sometimes use, where, where CEOs
411
00:25:48,380 --> 00:25:52,175
and other members of the leadership team
become kind of in effect, pocket moss.
412
00:25:52,759 --> 00:25:54,427
And it's well, wait a second.
413
00:25:54,427 --> 00:25:58,098
I just asked ChatGPT and said
I want to launch this new product
414
00:25:58,098 --> 00:26:03,478
and it just literally in 15 minutes told
me, you know, brought a placement pricing
415
00:26:03,478 --> 00:26:07,566
all of these things and then why can't,
why can't let's just go with it.
416
00:26:07,566 --> 00:26:11,236
And it's like yes, well
you should make sure it's right first.
417
00:26:12,028 --> 00:26:12,612
Right.
418
00:26:12,612 --> 00:26:15,282
So you've, you've you've sped up perhaps
419
00:26:15,282 --> 00:26:18,451
the, the insights
and a little bit of the strategy.
420
00:26:18,451 --> 00:26:19,953
But then you have to make
421
00:26:22,122 --> 00:26:24,374
execution and oversight.
422
00:26:24,374 --> 00:26:27,502
Sure.
423
00:26:27,961 --> 00:26:29,754
But you still have to have that
human oversight.
424
00:26:29,754 --> 00:26:33,758
That's how I see things really coming
alive right now in the marketing sector.
425
00:26:34,134 --> 00:26:37,137
The other thing that that I would say
426
00:26:37,596 --> 00:26:40,599
that that we see a lot now is
427
00:26:41,182 --> 00:26:43,810
think of it
as a creation of durable assets.
428
00:26:43,810 --> 00:26:46,771
So it used to be somebody would say, oh,
429
00:26:46,938 --> 00:26:49,816
you know, my sales are down
or I need to launch this new product.
430
00:26:49,816 --> 00:26:52,819
And it's it's a very tactical one time.
431
00:26:53,903 --> 00:26:55,614
Assignment so to speak.
432
00:26:55,614 --> 00:26:56,948
Okay. We don't know how to do that here.
433
00:26:56,948 --> 00:27:01,244
So let's bring in a fractional or sales
or marketing or whatever it might be.
434
00:27:01,870 --> 00:27:05,665
And that was
what was kind of the, the, the output.
435
00:27:05,790 --> 00:27:10,045
And now I think some of the things
that are able to be created
436
00:27:10,045 --> 00:27:13,381
are much more durable assets in terms of,
okay.
437
00:27:13,423 --> 00:27:16,468
It's not just a one time thing on
how are we going to increase sales?
438
00:27:16,468 --> 00:27:20,430
It's here's
this process that you can leverage AI for
439
00:27:20,847 --> 00:27:24,142
to help you create a repeatable process
that becomes
440
00:27:24,142 --> 00:27:27,771
one of your durable assets over time
and, and again,
441
00:27:27,896 --> 00:27:31,399
have to have the right oversight,
have have the right kind of people looking
442
00:27:32,817
--> 00:27:34,277
at that switch
443
00:27:34,277 --> 00:27:37,280
is one I think that's really important,
especially for,
444
00:27:38,114 --> 00:27:40,241
small and mid-sized companies who perhaps
445
00:27:40,241 --> 00:27:43,244
didn't have access to that before.
446
00:27:43,244 --> 00:27:45,997
Where you would have to hire a big agency
to do a lot of things,
447
00:27:45,997 --> 00:27:51,920
which common at a huge company,
but where mid-sized company,
448
00:27:52,170 --> 00:27:55,131
that's where you've got to really
make sure you've
449
00:27:55,131 --> 00:27:58,885
leveraging these things,
but also making sure you're leveraging for
450
00:27:58,968 --> 00:28:03,390
for the duration and the right oversight
and how you set up your team for success.
451
00:28:03,765 --> 00:28:05,475
Yeah, I think that's key.
452
00:28:05,475 --> 00:28:09,270
But again, governance, human being.
453
00:28:09,646 --> 00:28:10,605
Right.
454
00:28:10,605 --> 00:28:14,526
And there's still going to be things
and jobs and roles
455
00:28:14,734 --> 00:28:17,737
that I can't do.
456
00:28:18,279 --> 00:28:21,032
And I think that
457
00:28:21,032 --> 00:28:25,078
it's an important distinction to know
when you're working with a company,
458
00:28:25,120 --> 00:28:28,123
what's going to be a
I, what's going to be a person
459
00:28:29,249 --> 00:28:34,713
for that conversation.
460
00:28:35,338 --> 00:28:38,341
And and really
461
00:28:40,802 --> 00:28:43,304
and and to the point used earlier
462
00:28:43,304 --> 00:28:46,307
we're going to 20%.
463
00:28:46,558 --> 00:28:50,228
You know we're going to implement
20% use of AI.
464
00:28:50,311 --> 00:28:53,273
Well what does that mean. Right.
465
00:28:53,481 --> 00:28:54,607
Like I.
466
00:28:54,607 --> 00:28:56,943
Does that's been some parameters.
467
00:28:56,943 --> 00:28:59,863
And spike that out a little bit. Right.
468
00:28:59,863 --> 00:29:04,367
Oh 20% increase in
469
00:29:04,451 --> 00:29:08,455
what is our normal, you know, sales rate.
470
00:29:08,496 --> 00:29:09,372
Right.
471
00:29:09,372 --> 00:29:13,293
We're able to things faster
472
00:29:13,293 --> 00:29:16,296
or get insights more quickly.
473
00:29:16,463 --> 00:29:21,050
But the blanket statements mean people
could also use it for the wrong things
474
00:29:21,050 --> 00:29:24,888
that don't grow the business right,
or the business interest in the right way.
475
00:29:25,013 --> 00:29:25,346
Right.
476
00:29:25,346 --> 00:29:30,101
Or at least in the way that the leadership
team has decided is the right way.
477
00:29:30,185 --> 00:29:30,769
That's right.
478
00:29:30,769 --> 00:29:34,355
Because I think you could easily
go down a rabbit hole,
479
00:29:35,190 --> 00:29:39,444
with AI
and just tangentially go that way
480
00:29:48,411 --> 00:29:49,829
down a rabbit hole.
481
00:29:49,829 --> 00:29:54,042
If the enterprise is not saying this is
what we're doing, what we're doing.
482
00:29:54,209 --> 00:29:56,085
Yeah. Then then that's time.
483
00:29:56,085 --> 00:29:57,378
That's also lost.
484
00:29:57,378 --> 00:29:58,463
Correct. Correct.
485
00:29:58,463 --> 00:30:01,466
20% in the wrong direction is
486
00:30:01,633 --> 00:30:04,636
less than helpful.
487
00:30:05,178 --> 00:30:08,181
40% less for helpful, actually.
488
00:30:09,390 --> 00:30:12,477
Oh, well, Stephen,
thank you so much for for joining me.
489
00:30:12,519 --> 00:30:16,022
I always wrap up with a single question.
490
00:30:16,105 --> 00:30:21,861
If you weren't doing what you do now
and you could go in any other direction
491
00:30:22,904 --> 00:30:25,907
in terms of a job,
where would you be going?
492
00:30:40,296 --> 00:30:41,422
The approach to how
493
00:30:41,422 --> 00:30:44,509
I would think about where I've been
because I love I love my
494
00:30:44,551 --> 00:30:48,596
my experience and everything
I've done from living in Brazil, Mexico,
495
00:30:48,680 --> 00:30:51,683
working in Asia, those,
these, these types of things,
496
00:30:57,105 --> 00:30:58,731
just much earlier
497
00:30:58,731 --> 00:31:06,948
kind of understanding as I work
with people and I just want to understand
498
00:31:06,948 --> 00:31:11,953
kind of their North Star
a lot faster earlier days.
499
00:31:12,120 --> 00:31:12,537
Okay.
500
00:31:12,537 --> 00:31:16,624
So really coming in and understanding,
you know, so you just want to be younger.
501
00:31:17,250 --> 00:31:19,878
Well, don't we all know that?
502
00:31:19,878 --> 00:31:21,170
I can handle that. But yeah,
503
00:31:23,548 --> 00:31:25,174
no regrets from where I've been.
504
00:31:25,174 --> 00:31:31,472
Just really looking forward to.
505
00:31:32,098 --> 00:31:34,225
Great. Well, thank you very much.
506
00:31:34,225 --> 00:31:35,560
If you'd like to get in touch
507
00:31:35,560 --> 00:31:39,772
with Steven, his, contact
information is on the podcast page.
508
00:31:39,772 --> 00:31:44,027
And if you have not already,
like, subscribe and follow touchtone talks
509
00:31:44,027 --> 00:31:46,487
so you don't miss any more.
Great speakers.
510
00:31:46,487 --> 00:31:47,155
Great to be here.
511
00:31:47,155 --> 00:31:47,572
Thank you.
512
00:31:47,572 --> 00:31:50,575
Thank you.
513
00:31:51,117 --> 00:31:56,414
Meet. Him.
514
00:31:58,082 --> 00:32:01,085
Maybe it.
515
00:32:02,545 --> 00:32:04,005
Means we.