One of the most essential ingredients to success in business and life is effective communication.
Join Matt Abrahams, best-selling author and Strategic Communication lecturer at Stanford Graduate School of Business, as he interviews experts to provide actionable insights that help you communicate with clarity, confidence, and impact. From handling impromptu questions to crafting compelling messages, Matt explores practical strategies for real-world communication challenges.
Whether you’re navigating a high-stakes presentation, perfecting your email tone, or speaking off the cuff, Think Fast, Talk Smart equips you with the tools, techniques, and best practices to express yourself effectively in any situation. Enhance your communication skills to elevate your career and build stronger professional relationships.
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Matt Abrahams: When it comes to
AI, catharsis catalyzes change.
My name is Matt Abrahams and I
teach strategic communication at
Stanford Graduate School of Business.
Welcome to this special live episode
of Think fast Talk Smart the podcast
recorded at South by Southwest.
Many of us know about AI
and some of us even use it.
But how do you bring AI to your
organization and make it have
a positive, productive impact?
This is what I have been
curious about for a long time.
So when my friend and two time former
guest, Jeremy Utley asked me to facilitate
a panel to discuss his AI implementation
work with the MBA's, Portland Trail
Blazers, I jumped at the chance to
speak with Jeremy, Christa and David.
And I have to say it was a slam
dunk for AI best practices and
learnings we all can implement.
So without further ado, let's
listen in to our conversation
on the South by Southwest stage.
Well, good afternoon.
My name is Matt Abrahams.
I teach strategic communication at
Stanford's Graduate School of Business.
I host a podcast called
Think Fast Talk Smart.
It's all about communication skills.
We're very excited today to talk about
the particular application of AI within
a business, uh, this business is in
the world of professional sports,
the NBA team the Trail Blazers.
And I am honored to be on stage
with these wonderful guests who have
actually employed and deployed AI, and
we're here to share their experiences
and best practices with all of you.
So with that, I thought we'd just
start with quick introductions.
I'll start with Jeremy,
farthest away from me.
Go ahead and introduce
yourself briefly and share how
you're connected to the team.
Jeremy Utley: Hey everyone.
I'm Jeremy Utley.
I am an adjunct professor at Stanford.
Been there since 2009 or so, teaching
mostly design thinking innovation,
creativity at entrepreneurship courses.
And then my world, much like
many of you was rocked a couple
years ago when ChatGPT came out.
Unlike most of you probably, I had
just written a book about creativity
and a month later this tool that's
amazing for creativity came out
and I look in the index of my own
book, the AI is not even in it.
So I strapped myself into the front
row of the classroom as a student,
and I spent the last couple years
trying to get as close as I can to
people like David and Christa who are
doing this stuff in the real world and
learning from them as much as I can
and then sharing as publicly as I can.
And so it's really fun to
be here with all of you.
And I thank Matt and Christa and David
for allowing me to join the conversation.
Matt Abrahams: Thank you,
David, how about you?
David Long: Yeah, I'm the VP of
Digital Innovation with the Trail
Blazers and the Rose Quarter.
We're, uh, dual business for
concert events and basketball.
My teams run digital products, app,
web and arena, digital products as
well, and then digital marketing.
And then recently we are taking on
the strategy and implementing the
strategy around Gen AI for our company.
Matt Abrahams: Thank you.
Christa?
Christa Stout: I'm Christa Stout.
I oversee strategy and
innovation for the Trail Blazers.
I've been there about 11 years and
get to work with David and Jeremy on
our AI strategy and implementation.
Matt Abrahams: Excellent.
Thank you.
So many of us know how basketball is
played and we see what your team does,
but a lot of us might not understand
the business behind basketball.
Christa, could you spend a few
minutes talking about the business
side of what you do and then Jeremy,
I'd love to have you share how the
Trail Blazers came to explore AI and,
and get this whole project started.
So we'll start with you.
Christa Stout: Yeah, for sure.
So our business is set
up into three areas.
The first area is the one that
people probably think of when they
think of the Trail Blazers, which
is our basketball operations.
So that's players, health and
performance coaches, et cetera.
It's one element of the business.
Another element is actually our venue
operations, so the people that put on
the concerts and events and all that.
And then we have our business
operations, which for us is
about three hundred people.
And that is run in the same way
that probably any organization
you've ever worked at is run.
HR, finance, sales, marketing, et cetera.
So for today, we thought we'd focus on
that part of the business operations
because hopefully it's most relevant
to you all as well in your AI journeys.
And my boss, who's our president of
business operations, in August of
2023, we took the time to go to this
AI training and he came back and he was
like, Christa, we gotta figure out how
to implement AI across our organization.
Like it's the future.
We have to figure it out.
And at the time David and I had been,
because we're in charge of figuring out
emerging tech, we had been talking to
Jeremy about a whole other thing and we
pivoted and we were like, so Jeremy, can
you help us figure out how to implement
and create a strategy for AI instead?
He was like, yeah, let's do it.
Matt Abrahams: So David, AI came about
as a result of your boss essentially
saying this is an important thing to do.
What were some of the burning
questions that you guys had
that brought you to Jeremy?
David Long: It's an emerging tech.
It was something we were excited
about, but there was no professionals
on staff that understood like how to
take this and run with it necessarily.
'Cause it's brand new.
And machine learning obviously
is something that's been
around for a little while.
But this from a Generative AI
side and being an accessible
technology was new to us.
So who's gonna take that and run with it?
We looked internally, we found
people who could turn ideas into
action, but we needed someone to
be the barrier breaker for us.
And the way I refer to that is someone
who says, who could show that it's
accessible, that it's something that's
fun, it's something really impactful.
Remove some of the fear from our
staff around something new and then
just tear it away brick by brick
and the wall that people might have
put up around, I can't do this.
It's too challenging and I'm scared of it.
Like all these sort of things.
And so how can we remove those?
Whether that's within one-on-one sessions,
a group learning sessions, sharing how you
use AI personally was a big one for us.
So that's the thing that kind
of jumpstarted everything.
Matt Abrahams: I wanna come back to
the change management piece of this
because it's definitely challenging
and I'd love to hear what you all did.
But Jeremy, what excited you about
this part of the relationship
that you had with the team?
Jeremy Utley: These guys are the ball
game for me because we had already
been collaborating, as Christa
mentioned, exploring different kind
of technologies or businesses or
we were doing all sorts of stuff.
'Cause we had kinda had a kindred spirit
in terms of our willingness to experiment,
try new things, and I came to appreciate
and admire the way they were approaching
experimentation in the business.
As Matt, you and I actually talked about
this on another episode of the podcast
and we talked about that research there,
but I had been privileged to be a part
of this research program where a partner
and I were basically studying how
does Generative AI impact creativity?
And we found some kind of
counterintuitive stuff.
But I would say armed with those
observations and insights about
how do normal people get the most
leverage outta this technology.
But I had, there were
a lot of ideas I had.
And when they came to me saying,
hey, is there something here with AI?
To me, I saw an incredible kind
of almost sandbox and opportunity
to collaborate with folks who I
could test some of my ideas with.
So because I already knew them and
I knew they were the kind of people
I wanted to work with, and because
I had a bunch of ideas that I had
studied in the lab, so to speak, it
felt like the perfect opportunity
to test some of those hypotheses.
Matt Abrahams: Excellent.
And David, I'm curious, how did you
identify the problems first to apply AI
to, and how did you prioritize those?
David Long: Yeah, I think after we
had done some learning sessions with
Jeremy and try to get the baseline
up with Gen AI knowledge for our
staff in general, we started to reach
out to individual departments, well
all departments actually, invite
them to a lunch and launch is what
we coined these type of practices.
Matt Abrahams: Lunch and launch.
David Long: Lunch and launch.
Matt Abrahams: Like it.
Yeah.
David Long: And we would get as many
people from the department as we
could to get into a room with us.
And the whole concept was to share
with them, let's talk about your
systems and within your systems,
what pain points do you have?
Let's identify those pain points and
let's, let's not start with one and say,
this is the one we have to make it work.
We want ten pain points,
we want twenty pain points.
'Cause who knows, like the way AI
works, we can solve for one and
then potentially have a list of
a ton more we can tackle next.
Let's find that first one.
And so we'd go through and we let
people talk cathartically about
their job and what bothered them
and what could be done better.
They could spend more
time doing something else.
And then we would take that, we would
assign a co-pilot from that department
to assist us throughout the process with
the strategy in mind that keep these
people as close to the build as possible.
'Cause they're closer to the
problems than we'll ever be.
So with them in tow and in helping us
out, we would build, utilizing AI, to
either build a software, build a Slack
integration, build simple GPT, that
sort of stuff, and then pitch it back
to them, and then get the response.
And then from there we would
then a level of measurements.
We can see how it's performing
under a couple filters of is this
feasible and sustainable long term?
Does it impact business efficiency,
revenue, or fan engagement?
Are they gonna adopt it?
And what checkpoints can we put in
place so that there is adoption?
So lunch and launches
have been super powerful.
We plan to do two builds per
department for every department.
Jeremy Utley: Can I say one
thing about lunch and launch?
There's a clear role of branding.
And Christa as a marketer,
she understands that.
I can't overestimate the importance
of branding, and I've got an AI
focused podcast where I talk to AI
leaders in different organizations.
I think about JJ Zhuang , who's
the head of AI at Instacart.
Their internal effort they
call the Carrot AI team.
Because the carrot is their mascot, okay?
I talked to Brice Challamel,
the head of AI of Moderna.
They call their internal team the GCAT,
which are the core components of DNA,
but the Generative AI champions team.
But I think there's a role of even
thinking about the effort as branding it.
It gives it a sense of credibility.
Oh, you've heard of the lunch
and launch and you, you haven't
been to a lunch and launch?
There's something to that that I think
when you talk about change management,
thinking about branding stuff is
actually a meaningful part of it.
Matt Abrahams: And it sounds to me
that not only did you take the time
to brand it, but you started with
people identifying their pain points.
So all of a sudden you're not
coming in and saying, we're gonna
use this new thing to fix things.
You had them share what their concerns
are, where their challenges are, and then
had them thinking about how AI can help.
And what's very clear in the literature
on influence and persuasion is that
when you get people to buy into the
problem early, they're much more
likely to adopt and follow through.
So I think that's beautiful
that you did that.
In addition, it sounds like you also
came up with very clear criteria or
what success would look like, so you'd
build some things and then you had
some clear criteria, which I think
is a good bit of advice for everyone.
Did you do anything in particular
to help prioritize which
things you focused on first?
David Long: We managed the
project from a top level, right?
We were running all these
different lunch and launches.
So we saw that what was coming in and
then we could use the same filters
without everyone involved and say, this
one's gonna really impact our revenue.
This one's really gonna
improve customer experience.
And then communicating
that back to stakeholders.
And we had a copilot along with us
too, so we can utilize them to spread
that message within their group.
Like it looks like the timeline
for your build is in two weeks.
Hope you're all excited.
So like, just kind of managing
that, the expectations around this.
'Cause everyone was excited, but
from an overall top down, what's
most impactful for the business, that
was something that we would manage.
Matt Abrahams: I love that as
somebody who teaches strategic
communication, that you were including
communication throughout the process.
That's really important to bring people
along and to keep it going long after
you've created that particular solution.
I'm hoping each of you can give us
a concrete example of something you
did that is impacting the business.
Christa, do you mind starting
with something that you saw
really impact the business?
Christa Stout: Yeah, for sure.
So the builds that David's talking
about, we have about thirty-five
of those that we've done across
the company, and my favorite one
currently is called David Detractor
and his counterpart Kelly Kindness.
So I assume that you all, like us,
send surveys to your stakeholders,
to your customers, to get qualitative
and quantitative feedback.
We were doing a really good
job getting and visualizing the
quantitative feedback so that we
could learn from it and implement it.
But the qualitative feedback
was much more complicated.
So we dug into it during one of the
lunch and launches and learned that a
couple different people were spending
combined almost forty hours a week.
So almost an entire full-time
employee's worth of time just digging
into the qualitative responses
from our post-event surveys.
We have like millions of responses
over the course of the year, not all
of them have qualitative responses.
But people go into the system, read
it, decide if they needed to send it to
someone else or not, decide if they should
respond, get approval to do a make good,
if they had a bad experience, et cetera.
It was just like a lot of mundane work.
And so David, I guess you, did
you name this after yourself,
David Detractor David?
David Long: It was the first one, so
I think it was the easiest one for me.
Christa Stout: David built an
alliterative tool, David Detractor,
that ingested all of the post-event
verbatims, filtered out the ones
that we didn't need to respond to.
When people were like, boo.
You're like, okay, I'm
not responding to that.
But if people have a specific thing
that we need to respond to, that
would actually go to a specific
Slack channel where people that were
relevant to that Slack channel, and
I'll give an example in a second,
could read it, put a specific emoji on
it that then creates a draft in their
outlook outbox to send to that person.
So before took forty hours of people's
time, now takes seconds and two clicks.
So my favorite example of this recently
is actually this person who came to a game
and really wanted a vegan hotdog, but the
hotdog bundle didn't include vegan hotdog.
So she has this detractor feedback, it
surfaces automatically to our head of
F and B who reads it and is amazing.
And she's like, hey, we should include
the vegan hotdog in the hotdog bundle.
So she makes a change in the
operations of the business.
Hits one click, responds to the
person, gives her an F and B credit
to come back and to get a free hotdog.
And this person now hears back
from us right away, right?
So it works really well on the
detractor side, as you can see, but it
also works on the promoter side where
we can surface really any positive
experience someone has at a game.
We surface actually
across the whole company.
Which is really nice because if
you work somewhere and you have no
idea how the experience is, it's
really rewarding to see these and
read about these positive examples
that people have across the company.
And on top of that, they're often like
the warmest leads we could possibly have.
Like they're hand raisers.
Someone literally said the other
day, I had the best time at the game.
I wanna come every week.
And so we're like, hey, sales
team, you wanna call her?
She seems interested.
So to close on this example, it drives
revenue 'cause it services warm leads.
It improves our customer experience
'cause people hear back from us.
And it improves efficiency, so we
basically cut out one FTE's worth of
mundane tasks as part of this process.
Matt Abrahams: It's a great example
of how it was able to help you.
F and B, food and beverage.
Christa Stout: Sorry.
Yes.
Matt Abrahams: Just making sure
everybody's following along.
David, please, what's one of the things
that you're proud of or impressed by?
David Long: One other addition
to the Kelly Kindness piece.
One, name your bots.
That's also a part of
our branding strategy.
People can refer to them easily.
It's great.
Jeremy Utley: It's a pro, it's a pro tip.
Name your bots and give
them a human personality.
David Long: Correct.
I think a lot of talk around Gen
AI is one of those concerns around
disconnecting human to human connection
because of the use of these tools.
This is a perfect example of
how it's actually increased
human to human connection.
I think on Kelly Kindness in particular,
we're acknowledging folks who had
really good experiences trying to
solidify like a core memory, a core
moment for them, and build fandom.
We'll admit there's areas where that
was happening and very small scale, but
now the scale for that is like immense
because of this tool, and so I really
like to call that one out in particular.
Matt Abrahams: I recently was interviewing
somebody else and they were talking
about how they have built into their
system whenever an employee calls in
sick, they have a bot that automatically
will send them chicken soup for their
house, and it's a way of showing
kindness and showing that they care.
And that somebody's monitoring
that you're not at work that day.
So it does a whole bunch of things.
So this ability to drive
connection, I think is important.
Is there another tool that
you are pleased about?
David Long: Yeah.
Another named one Billy Brand.
So Billy Brand is trained on
our complete content style
guide, our brand guideline book.
Some history about the Portland
Trail Blazers, anything else that
our brand team, PR team deems
appropriate to be within there.
And the main pain point we're trying to
solve here is try to avoid is revisions.
And I think that's one thing that this
thing was trying to solve for is, if
you're having copy, if you're having
creative, if you're having anything that's
supposed to be public facing, let's have
a tool that we can load it up, it can
audit all that stuff for any brand things
that are not aligned, give that feedback,
give suggestions on how to fix it.
And so we're trying to cut revisions
from six, seven down to one, two, three.
Can we get it down so we're not
spending time doing that stuff,
moving these campaigns forward and
moving the best campaigns forward.
So Billy Brand has been really impactful.
Jeremy Utley: Just, just to make sure I
understand the kind of economic impact.
You're saying a typical, say somebody
in marketing or insert department here,
they're getting feedback on how to
align more with the brand voice, six,
maybe six or seven times in some cases.
And this tool's taking it
down to two or three times.
David Long: Yeah.
Jeremy Utley: That's cool.
Christa Stout: We also been
upwards of ten or fifteen times.
Jeremy Utley: Wow.
Christa Stout: Six or seven is
Jeremy Utley: It's generous, conservative.
David Long: Yeah, the best, for adoption
purposes, it's still, this is one of
the first ones I built, so I actually
built it without someone helping me with
it who was closest to the pain point.
So it actually went through
a couple different systems.
One, it was like, it previously used
to be within Slack, but people were
like, I don't want to use it in Slack
'cause then everyone can see that I
don't know how to do this or that.
I was like, great point.
So it's now a web-based software
that we're rolling out to folks
and I had one member of my team who
complained that he ran outta tokens
the other day and I was like, that's
the best problem I could ask for, so.
Matt Abrahams: And I'm sure
it's one hundred percent
brand compliant, that website.
David Long: Absolutely.
Matt Abrahams: Excellent.
Very good.
Jeremy, what's one of the tools
that you're excited about?
Jeremy Utley: I, I'll give a non Trail
Blazers example, if that's okay, just
to broaden the aperture a little bit.
But I've had the privilege of working
with a bunch of, this is gonna
sound crazy, but a bunch of park
rangers in the National Park Service.
Which is super cool.
They reached out somehow.
I don't even know how.
Hey, all of our backcountry
rangers and facilities folks
wanna learn how to use this tool.
Can you help?
I was like, totally.
And we did some kind of basic
foundational training, and one of the
things that we focus on, similar to
the conversation about pain points
that Matt's drawing out of David
here is what sucks about your job?
What takes way more time than it should?
And a really great kinda stem for
finding opportunities is to finish the
sentence, it sucks that dot dot dot.
And we had people just think
about that, what sucks.
And one of the folks on, in this group
as a group of about sixty folks, he
said, it sucks every time I've gotta
replace the carpet in the lodge.
He worked at Yellowstone or
Yosemite, something like that.
Every time I gotta replace the
carpet tiles, I've gotta fill out
10 pages of federal funding requests
that include OSHA requirements
and ANSI standards and historical
heritage site removal preservation.
He's, I'm like a back country ranger, man.
I don't know the answer to this stuff.
So he built in forty-five minutes a
tool that could reference all of the
relevant databases of information,
including expense information, all that
stuff, and would take a crack of first
pass at drafting the document for him.
And it took him, he said, whenever,
he said the last time he had to
replace a carpet tile, it took three
days to fill out the paperwork.
This thing took fifteen minutes.
It took him forty-five minutes to
build it, so call it an hour in total.
But three days minus an hour is not bad.
But here's the really cool thing.
When you codify these workflows and
simple kinda shareable tools, the
individual who builds it gets the
benefit, but then anybody else for whom
it's relevant also gets the benefit.
So in his case, name's Adam.
I try to tag him on
LinkedIn to shout him out.
Homeboy doesn't even
have a LinkedIn account.
Alright, so it's like this is
someone who literally has no presence
on the web, no tech experience,
and someone shared his tool.
There are four hundred and fifty parks
across the US where there's a role
like his, the National Park Service
is estimating that tool is gonna
save the National Park Service seven
thousand days of human labor this year.
Just his tool.
Christa Stout: Wild.
Matt Abrahams: That's amazing.
Jeremy Utley: But the
shareability of it, right?
The fact that Billy Brand is shareable, it
would be useful maybe just to you, right?
But now it's useful to
anybody who's trying to create
brand aligned communication.
Christa Stout: Which is everybody.
Jeremy Utley: Which is everybody, right?
Yeah.
Matt Abrahams: So I'm hearing a
couple things to take away from this.
First and foremost, that these tools can
build connection, not reduce connection.
Two, it's really important to think
about where you place the tools.
And how you involve people in the process.
Three, the shareability of these things
is really important, and so I love the
specific examples, but the lessons that
we learn, I think are really important.
AI for non-technical people can be
intimidating, maybe not for one Park
Ranger, but for many people it can be.
Christa, how did you help make AI
accessible to your less technical folks?
Christa Stout: Yeah, I think you
said it as part of your recap.
It was, for us, it was figuring
out how to connect with people
and bring people into the process.
So when my boss Dwayne said, hey,
you gotta figure out how to like
have everyone at our company using
AI eighteen months ago, I was like,
well, I don't know how to do that.
So the first thing I did was on a full
team call, I just asked if anyone that
was using AI wanted to come talk to
me or be part of a conversation about
how they're using it, what they liked
about it, what they don't like about it.
Let's just talk and then go from there.
And so it's like tapping into people
who were like, we had thirty-five people
who were already using AI eighteen
months ago, who were then excited to
share what they were using it for.
And whose job is not to create
strategy for new tech across a
business, but they got to be a part
of that and got to help shape it.
Matt Abrahams: I'm curious, Jeremy,
what have you seen beyond the Trail
Blazers that helps organizations
bring AI beyond just this as an IT
initiative, but how do you bring it
to everybody in the organization?
Jeremy Utley: I don't think we have to
look very far beyond the Trail Blazers.
I think they're like a great case study
of creating space for folks, creating
venues and mechanism, venues for sharing
and for celebrating mechanisms, for
learning incentives where we can get
into all that stuff as well, right?
But there's a bunch of pieces there.
I think one simple thing that has
really helped a lot of folks I
talk to is when they say, I don't
know how it's relevant to my job.
The kinda meta hack, which feels
like a Yodaism, but is not,
is you can use AI to use AI.
The basic idea is if you're not
sure how AI can impact your work,
you can actually pull up Chat
or Claude or Gemini, whatever.
I, I'm not model agnostic, but I'm
not hyping a model here, but you can
pull up any of 'em and say, hey, I
have no idea how to use AI in my work.
Would you act like a insert LLM here,
Chat expert or Claude expert or Gemini
expert or Grok expert, act like a
Grok expert and interview me about my
job so that you could recommend three
to five obvious and maybe totally
non-obvious ways I could use AI.
And you know what?
It'll totally do that.
The biggest thing is actually
getting your imagination sparked.
And most failure to use is actually a
failure of imagination and part of the
value of mechanisms and forums like lunch
and launch and like gathering people
together, is it helps broadcast and
showcase a bunch of things that people
go, I would've never thought to do that.
And basically what you want do is
create these forums where you kinda give
these forehead slap, I can't believe
I've never thought to do that, right?
And if you can provide enough of
those moments and then celebrate
how people are trying stuff, it's
just kind of a snowball effect.
Christa Stout: I'd just say, just to
build on that, but one of the things that
Jeremy unlocked for us that also helped
with the change management was tapping
into personally relevant AI examples.
And so rather than starting with
how can AI help me do my job better,
which is great and helpful, we started
with prompts that, that really tapped
into personal issues that people had.
So not work appropriate personal issues.
So for example, think of a decision
that you have to make in your life.
It's a hard decision.
And then Jeremy had a whole specific
prompt that we just like copy and paste
it into ChatGPT where we described
the decision we had to make and some
of the challenges, and asked ChatGPT
to interview us to get more context.
And then to work through
that challenge with us.
So I did it about my daughter
starting kindergarten.
Schools and whatever, and
it was so helpful, right?
Like the kind of advice that I wouldn't,
I just never would've thought that an
AI tool could help me with that then
sparked a million more ideas around
how it could benefit me at work.
Jeremy Utley: That was actually
inspired by a life experience, right?
We ended up doing a series of emails
or Slack something, right, where we
basically said, here's a use case.
Here's a prompt you can copy paste, and
here's a video of a professional nerd
in California doing the thing, right?
And the only reason we even did that,
by the way, is 'cause I had this true
story about my, in my personal life.
I'm riding with my grandma
in the car one day.
She lives in Oklahoma, she's mid nineties.
I love her.
I love you, granny.
If you're listening to this and we're
driving the car, she's like, hey, what is
this chat thing that you're working on?
And think about, how do
you answer that question?
Your ninety-five year old
grandma asks you, what is Gen AI.
You know, and I'm like, what's
an emotional question you'd ask
Faye Ann, who's her neighbor,
that she'd ask Faye Ann about.
And she goes, I thought
this was technology.
I go, just bear with me just for a second.
She said, we don't even know how
to think about assisted living.
And I said, let's invite my friend
ChatGPT to the conversation.
And I'm driving, she's
in the passenger seat.
I just said, hey, my grandma just
asked me about assisted living.
I don't even know what
framework to reference.
I don't, I have literally no
idea how to think about this.
Before you give us any advice, would you
ask her three or four questions so that
you can customize your advice to her?
And said, sure.
Have there been any changes
to her mobility recently?
You know, I hand her my phone
and she's like, this is amazing.
And I said, the tech's pretty cool, right?
She goes, not the tech.
I've never thought about
assisted living like this.
Two days later, I get the, my favorite
text message ever from granny.
Jeremy, we're out of cream, of mushroom
soup for the green bean casserole.
Do you think your chat thing could help?
To Christa's point, the reason she thought
of the work application was because
she had this personal experience and
that made me realize, and then I just,
all these random things in my life,
we happen to have this opportunity.
I said, hey, instead of starting
with work, let's start personal.
Let's give the first prompts personal
so that people feel like they have
this kind of imagination opening
experience where work effectiveness or
productivity isn't hanging in the balance.
Matt Abrahams: That story is
amazing for so many reasons.
One that your ninety-five year
old grandmother is texting.
I find that fascinating.
And second, this notion of making it
personal first to get people connected.
And this idea of bringing people
together to share at Stanford,
where Jeremy and I both teach, they
do this thing called Appy Hours.
So people come together to share
the different apps that they've
built so that you can then learn
to leverage it and just the name
Appy Hour and they do serve drinks.
It's a fun experience to share
building more on that creativity.
I wanna pick back up on that notion
of allowing for time for this.
How did you at the Trail
Blazers actually give permission
to people to take the time?
Because I'm sure people are saying,
I already have a full-time job.
I don't have the time to do this work.
David, did you do anything in
particular to give people permission?
David Long: I think to couple along
with what you all are just saying, I
think it does start individually and
looking at personal uses cases to,
with an end goal of like empowerment.
Can this tool empower me?
Because if you reach that level, then
you stop thinking about replacement.
You stop thinking about things that
are negative connotations with Gen AI
and then you can be a proud displayer
of what you're able to come up with.
This is what I did.
Lemme share it with my staff, whether
that's personal or something work related.
They see it and then instead of
saying, hey, are you using AI?
So they're immediately
put on the defensive.
You say like, here's what I did.
Have you tried this?
Have you tried using AI for this?
Or something like that.
Just trying to rephrase it around
empowerment and trying to get an end
result has been super helpful, and
just making the time is difficult.
But in the end, once you start it,
you realize that there are benefits
of using it, that it cuts down
on some of the manual labor that
you have to do and allows you to
focus on more important things.
I refer to it as a utility.
It's gonna be a next utility for us.
Implementing electricity, okay?
Companies got rid of gas lamps.
It's one of the most obvious things to
do right away, but the people who really
take it to the next level is like, how
can they use electricity to improve
their production lines, improve revenue,
improve all those different things.
So I think you have to do
it 'cause it's a utility.
It's not, it's not a new flash in the pan.
Christa Stout: Yeah.
And we would also, like, we had a Slack
channel where we would just encourage
people to share like, hey, I just took
a picture of my lunch and asked it how
much protein is in it, and guess what?
It knew exactly how much protein and
what I was eating and blah, blah, blah.
And so we just were like constantly
encouraging people to share
how they're using it so that it
is demystified and encouraged.
And so the result of that is that
David has someone that works on his
team who just like went off without
even asking, built her own software
that replaces an existing software
that we spend a lot of money on today.
And I think it's because we, like she
knew top down that Dwayne, our president
and others supported its part of our
business planning process, et cetera.
But also it's just so encouraged across
the organization from that initial AI
committee, from David's lunch and launches
like it's encouraged and celebrated.
And when you celebrate something,
people tend to wanna do it.
Matt Abrahams: The literature on
motivation is very clear that if you
put people on the defensive, they're not
going to be motivated to do something.
And it sounds like you've worked very
hard to reduce that defensiveness
and give people an opportunity and to
celebrate, as you said, to help them,
and that's really an important step.
Can we talk a little bit about the change
management to actually get people across
the organization to use these tools?
It's one thing to build them.
Is it simply that people see the
benefits, so therefore they use them?
I can imagine some people are
really comfortable in what
they're currently doing and the
current way they're doing it.
Have you done anything to help
with the change management
to keep the momentum going?
David Long: I think individual
groups adopt faster than others, and
I think the best thing is just to
come back to the lunch and launches.
Within those groups, there's
people who have not used AI yet.
There's people who have, but it's
a shared space where we can talk
about a similar topic and talk about
solving problems and it's specialized
to what their main focus is.
So I would say that those
are incredibly powerful.
One, for we are there to build something
impactful, but for the shared space
of communication and things like that.
That's major motivator
for change management.
Christa Stout: And to go back to Jeremy's
sandbox point, the David Detractor Kelly
Kindness example that I shared earlier.
So when David first built it and
launched it, it's not like people
just started using it right away.
People, a lot, sometimes a lot
of people didn't use it at all.
So then we had another
meeting and a conversation.
We're like, hey, what is
keeping you from using this?
What would make it easier for
you to use what, you know?
And so like I, you iterated that product
for a couple months before, and now
it's just like everyone's using it and
it's everywhere, but it took months
of iteration and learning and feedback
and communication to get to that point.
Jeremy Utley: Were there any key revisions
or key iterations that you feel like
unlocked people's ability to use it?
Like what was keeping
someone from using it?
I'm just dying to know.
David Long: It was me.
I think one, one part of it was that I was
not solving for the user's problem, so I
needed to stop and overproduce something
that I envisioned would be helpful.
And that's, this was before a lot
of these lunch and launches a big
component of what we now implement,
but getting with them and saying,
does this actually solve your problem?
In what ways?
Why?
And what does it allow you to do?
What impact do you think this will have?
So that, that's the main thing.
If you're solving for it by yourself,
you're gonna have revisions, you're
gonna overdevelop, and you're
gonna probably have less adoption.
Jeremy Utley: Matt, just thinking about
your question of what drives adoption
is kinda what you're getting at.
To me, as I'm listening, I go back to
the very beginning, which is everything's
rooted in employee pain points.
Of course, people want to use something
that's actually making their life better,
but I think importantly, critically, David
and Christa did the hard work of figuring
out how their lives need to be improved.
So they didn't start with a
broad mandate of, let's just
use Gen AI in general, right?
I think the usage metrics
are largely irrelevant there.
What they did is they said,
what are the problems?
What really stinks in your job?
Let's build a solution there.
And then it just creates
suction, it creates pull.
This makes it easier.
This makes it better.
No brainer, right?
Matt Abrahams: Absolutely.
Christa Stout: And like I love
the, it sucks, that prompt.
It's a really good framing.
It turns out people really enjoy talking
about what they hate about their jobs.
And so we had, we set up hour
sessions and then we would always
have to cut people off at the fifty
minute mark and be like, okay, now
we're going to switch to solutions.
You used the word earlier, it's cathartic
for people to be like, oh, and if only.
And for us to get that insight across
the company of like the systems, like
the key systems across our company and
how they do and don't work effectively.
And then the problem solve for those
also gives us a lot of insight, which
my hypothesis is that ultimately
it will help us be able to figure
out where and how AI is going to
significantly transform our business.
Like right now, this is all incremental
innovation across a lot of different
work streams, but by getting this
insight across a whole company, it
is already opening our eyes into
ways we can like really potentially
transform the business more broadly.
Matt Abrahams: Anybody who knows anything
about me knows I love alliteration,
so catharsis catalyzes change.
I like that.
For those in the audience looking
to expand AI in their organizations,
whether they're technical or not, I'd
love to hear from each of you what's
one concrete action they could take next
week to start making progress with AI?
Why don't we start, Christa with you.
We'll just go down the line
this way, if that's okay.
What's one thing they could do?
Christa Stout: I mean, it's self-serving
'cause this is what we did, but
I think just recognizing that you
don't have all the answers and don't
need to have all the answers when it
comes to AI and how to implement it.
Like you have to step and trust
that the path will follow.
And also admit that you
don't know everything.
'Cause literally nobody in the
world knows everything about ai.
So the idea that you would be
expected to is a little crazy.
So I think just admitting vulnerability,
starting with curiosity and
understanding like what's already
happening at your organization so you
can tap into the latent motivation
and create momentum from there.
Matt Abrahams: Excellent.
So start with vulnerability,
follow with curiosity.
Very good.
David, what's one thing people
could do starting next week?
David Long: I think at the leadership
level, critically about who within
your company or under your team who
exhibits like behavior of taking
ideas and turning them into action.
I think that's a person that you
should have a one-on-one with and
present AI as an opportunity for them.
'Cause that's a huge unlock if you have
someone who can move things forward that
way, 'cause this is a powerful tool in
the right hands of someone like that.
As an individual, like I
mentioned earlier, do a complete
audit of some of your systems.
Whiteboard out.
Here's one for example.
Like every month I have to balance my
credit card and so I need to know all the
codes to send all these different charges
to across marketing, across our corporate
partners, all that sort of stuff.
I know it takes four different sheets.
I know I have to reference control
F, all these different sheets
to find these different codes.
It takes me two hours.
Talking about cathartic, like this
is one that I absolutely do not like.
And so within that I was able
to mark just with little carrots
maybe I could use something that
understands all of our codes.
Maybe I could do something
that can be accessible within
Slack and answer it right away.
So that's something that's,
that's taking it to the next step.
But to, to your answer your question,
it's just like audit something and see
what's possible and then go from there.
Matt Abrahams: So the audit point is
well taken, but you bring up something
that we haven't really talked about,
although you mentioned it, is buy-in from
more senior leaders is really helpful.
And taking the time to make
sure they're on board can help.
And in your case, to
really drive the event.
Jeremy, what's one thing these folks
could do next week to make a difference?
Jeremy Utley: We talked about earlier,
but I think have AI interview you
about either your life or your
work to identify opportunities.
Tell AI it's an AI expert.
Which, by the way, a
role is a critical part.
If you've been playing with AI at all,
you know this, you gotta give it a role.
If you're talking about a parenting
challenge, hey, you're a child life
psychologist with a specialty in
childhood development in teenage girls.
I have four daughters, so I've
used that prompt a lot, right?
But the point is, you're an AI expert.
You're here to give me a consultation
of how I can use AI better in my blank.
Would you ask me five questions
one at a time, because I'm a human
and struggle to answer more than
one question at a time, please?
Something that simple.
The other thing I would say about
leaders, by the way, leadership buy-in
is not some nebulous, abstract thing.
If you're a leader and you want to
give buy-in, do something yourself
and tell the team what you've done.
Because to say, hey, y'all have
permission to go do it, is totally
insufficient and it's far too passive.
And the best leaders I have observed,
they are actively showcasing
what they're doing on Zoom calls.
Let me share my screen for five minutes.
I wanna show you guys
what I've been doing.
That goes so much farther than,
no, really, you're free to try
it on your own time, no problem.
Matt Abrahams: And what's even more
important is to, as a leader, to
share your struggles and challenges
and failures, because that gives
permission for others to do that.
Because it's one thing to say, go
do it, and here's what I'm doing.
If people feel there's has to
be perfect, just like yours
was, that can be challenging.
Before we wrap up every episode of my
podcast, I ask some typical questions.
Due to time, I'm just
gonna ask one question.
We'll do it very quickly.
The final question I always ask is, what
are the first three ingredients that go
into a effective communication recipe?
And since there are three of
you, and I'm asking for three
ingredients, just very quickly, name
an ingredient and then we'll wrap up.
Christa, what's one important ingredient
that for successful communication?
Christa Stout: Oh, since it's his
birthday, I am gonna say something that
Jeremy does really well, which is turn
complicated objects into very clear
messages, and communicate them very well.
Matt Abrahams: Make 'em accessible.
David Long: Constructive problem solving.
If you have a problem and you want to
present it to your leader or your staff
present it, but now you have this tool, AI
potentially, where you can come with lots
of solutions and you can flood a problem.
And so I think anytime you can come
to a leader and say, hey, I have this
problem, but here's some things I want
you to consider about how I want to go
about solving it, that's a completely
different type of conversation.
Matt Abrahams: Lead with solutions.
Very good.
Jeremy Utley: Conviction.
If you don't believe it, don't say it.
Matt Abrahams: Three very valuable bits
of advice and important ingredients.
And lots of interesting steps and
recipes today to help all of you
be successful in deploying AI.
Thank you very much for your time.
I hope you're taking
something of value away.
Thank you for joining us for this
special South by Southwest live version
of Think Fast Talk Smart, the podcast.
To learn more about AI and communication,
please listen to episode 77 where
I interview ChatGPT and episode 134
with Jeremy Utley and Kian Gohar.
This episode was produced by Ryan
Campos and me, Matt Abrahams.
Our music is from Floyd Wonder.
With special thanks to
Podium Podcast Company.
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