AI Agents and Association Strategies: Keynote Highlights from digitalNow 2024 (Day 1) | 63 - Sidecar Sync

Episode Transcript
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Speaker 1 (00:00):
AI is the worst it is ever going to be, meaning it's
going to get better.
Better might be subjective, butbetter means more powerful, and
a big part of what's going tohappen in the coming years is a
gentic system.
Welcome to Sidecar.
Sync your weekly dose ofinnovation.

(00:21):
If you're looking for thelatest news, insights and
developments in the associationworld, especially those driven
by artificial intelligence,you're in the right place.
We cut through the noise tobring you the most relevant
updates, with a keen focus onhow AI and other emerging
technologies are shaping thefuture.
No fluff, just facts andinformed discussions.

(00:42):
I'm Amit Nagarajan, Chairman ofBlue Cypress, and I'm your host
.

Speaker 2 (00:47):
Hello everyone and welcome back to today's episode
of the Sidecar Sync Podcast.
My name is Mallory Mejiaz andI'm one of your hosts, along
with Amit Nagarajan, and todaywe have a special edition
Sidecar Sync episode lined upfor you, where we're going to be
sharing some keynote highlightsfrom our annual event, digital.
Now, before we kick off today'sepisode, let's hear a quick

(01:09):
word from our sponsor.

Speaker 3 (01:12):
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Speaker 2 (02:08):
If you have tuned in to the Sidecar Sync podcast
before today, you have probablyheard us talk about Digital Now.
Digital Now is a two and a halfday conference that Sidecar
puts on every year forassociation leaders.
In previous years we've coveredtopics like blockchain
technology, web 3, and, ofcourse, artificial intelligence
and, as you can probably imagine, at Digital Now 2024, which we

(02:31):
hosted October 27th through the30th, we talked pretty much
exclusively about artificialintelligence and the idea of
building an exponentialassociation and how AI is going
to redefine what it means to bean association now and well into
the future.
It was two and a half days.
We had nine fantastic keynotespeakers and breakout sessions

(02:52):
from fantastic presenters withinthe association space and, of
course, we know many listenersand viewers of the Sidecar Sync
podcast could not attend, so wewanted to share a piece of that
event with you.
In today's episode, we'll behearing some short excerpts from
our four keynote speakers onday one of Digital Now.
If you want to hear the fulllength keynotes, they're

(03:14):
actually currently in our AILearning Hub right now, so if
you already have access, gocheck them out, and if you're
interested in seeing those fulllength keynote sessions, I
highly encourage you to go tolearnsidecarglobalcom Now, while
you're listening to today'sepisode, you might feel inspired
and you might decide that youwould like to attend Digital Now

(03:35):
2025.
So if that's of interest to you,you can go to
digitalnowsidecarglobalcom andlock in the early bird
registration rate for DigitalNow 2025.
I should also mention the eventis going to be November 2nd
through the 5th in Chicago 2025at the Lowe's Hotel.

(03:56):
So right now we're running ourearly bird special, which is
$797 for an individualregistration.
But really where it gets goodis when you want to register
four or more individuals.
So if you register four or moreindividuals, you get that
registration rate for $625 perperson for two and a half day
conference and the extra perk ontop of that is you're

(04:18):
essentially locking in that $625rate.
So if you decide several monthsfrom now you know you would
really like to bring a couplemore people from your team you
can still do that outside of theearly bird period for $625.
So if that's of interest to youwhile you're listening to this
episode, head todigitalnowsidecarglobalcom.

(04:40):
You might be familiar with ourfirst keynote speaker.
At least if you've listened toany episode of the Sidecar Sync
before today, you should be.
Our first keynote speaker isAmit Nagarajan, who is a host of
the Sidecar Sync podcast aswell.
We love having Amit kick offDigital Now because he really
sets the tone for kind of what'shappened the previous year

(05:03):
since the prior digital now andthen sets the tone for the whole
theme of the event every year,so in 2024,.
He talks about AI, agents andagentic systems and really
speaks about how powerful andessential these systems will be
over the next year and well intothe future.
He lays the groundwork forcomparing models to agents.

(05:25):
So, with the basic idea beingthat models don't really adapt
over time, he has this reallygreat analogy that you'll hear,
where he compares them to abrilliant person who's
essentially lost the ability tolearn anything new after college
, and that's compared to agents,which are a collection of
different software componentsthat come together to make a
valuable system that can takeaction autonomously or

(05:48):
semi-autonomously and ultimatelylearn and improve over time.
In his keynote session, heshares examples of AI agents
from within and outside of theassociation space in areas like
customer service, knowledge anddata.
So please enjoy this excerptfrom our first keynote speaker,
amit Nagarajan.

Speaker 1 (06:07):
All righty, you guys.
Excited about AI, yeah, alittle bit fearful of it too, I
mean.
I put my hand up for that,sometimes scared, shitless.
Here's the thing AI is theworst it is ever going to be,
meaning it's going to get better.

(06:27):
Better might be subjective, butbetter means more powerful, and
a big part of what's going tohappen in the coming years is
agentic systems, which is thepoint of my talk today.
I feel that associations havenot been able to really jump on
the agent bandwagon quite yet.
In the broader world, agents arebecoming probably the most

(06:49):
popular topic in the world of AI, because they can do things
that models themselves can't.
That's what I'm going to betalking about today, now.
What I want to give you a senseof first, though, is the pace
of progress.
So every year at Digital Now,it's a nice touchstone.
It's an opportunity in ourjourney together as a community
to say well, what's happened?
You know what's going on, andit's hard to keep up, right?

(07:11):
I mean, I do this stuff.
Most of my waking hours I'mspending thinking about
artificial intelligence, and itis relentless and it's
overwhelming.
So it's okay to admit that, Ithink, and it's really the only
reality that exists for all ofus.
So we's okay to admit that, Ithink, and it's really the only
reality that exists for all ofus.
So we're going to talk a littlebit about that and then I'm
going to dive into what exactlyare agents.
I don't want it to be a mystery.
I want it to be clear andsimple and understandable,

(07:32):
because agents really are justthat they're just systems, and
we'll get into that.
We'll talk through someexamples and then we'll talk
about how to take action, howyou can actually move forward
and take advantage of this stuff.
So let's begin by taking a quicksnapshot of the journey of AI's
progression.
Remember, the AI you have todayis actually really bad.

(07:53):
That's the thing that peopledon't realize is the systems
today are kind of dumb.
Now, at the same time, they'reunbelievable, they're amazing,
they're world changing, and boththings can be true at the same
time.
Part of the reason for that isbecause AI has been moving so
incredibly fast that the systemsthemselves have capabilities
that we do not understand, we donot know how to use, and that

(08:16):
includes the we being the world,not just associations.
A model at least the currentarchitectures of models don't
adapt over time.
Models don't really learn fromthe interactions with you.
Now that's something that'sgoing to change in the coming
years.
There's a lot of researchhappening on forms of these
models that will be able to bemore adaptive and learn as they
go, but right now, the modelsyou interact with themselves

(08:39):
don't get smarter.
They don't learn from theinteractions.
They don't remember anythingabout what you told them,
they're just fixed.
Think of it this way Imagine asthough you hired a brilliant
young professional right out ofuniversity Pick a university in
your mind.
That's amazing.
And they learned everything100% perfectly that the
university taught them.
But once they came to work foryou, they were not able to

(09:01):
retain anything.
You told them they knew alltheir base knowledge from
university, but they learnednothing from their interactions
with you.
That's what the modelarchitectures are today.
So it's kind of limiting right,because it's pretty amazing
that they know everything fromuniversity or whatever their
training set was, but the factthat they cannot go beyond that,
it's a bit of a challenge.
So that's where agents can comein.

(09:22):
Think of agents as a fancy term.
That just means system.
All an agent is is a collectionof different software
components that are composedtogether to make up a more
valuable system.
So, as a business, if you wantto solve problems with AI,
you're thinking about thesedifferent bits and pieces.
Another way to think of it isyou guys are all familiar with

(09:44):
systems like AMSs or LMSs.
Those are systems, right, andthey have lots of parts.
No one goes to Microsoft andsays, hey, how come SQL Server
as a database doesn't handle myAMS requirements or my LMS
requirements by itself?
It's just the database, it'sthe raw database, brain or
engine.
Right, and think of it that way.
An agent is just basically acollection of componentry.

(10:06):
So what can agents do beyondmodels?
So the first thing they can dois observe their environment.
They can understand where theylive in the world and they can
connect to other systems.
So let's talk about AI agents.
There's a company called KlarnaQuick show of hands.
How many of you have heard ofKlarna?
Okay, so Klarna is a buy now,pay later company, bnpl for

(10:30):
short.
Essentially, in e-commerce, youmight go to a store online and
you'll see something that sayspay over time or pay in
installments, and so Klarna willlet you set up a payment plan,
buy a product now and receivethe value from it, but pay it
over four months or six months,things like that.
They have millions of customersall over the world.
They have a lot of customerinquiries.
People are constantly emailingthem stuff like just asking what

(10:52):
their payment schedule is, orasking them to change the
payment schedule, or just askingfairly generic questions.
So they implemented an AI-basedassistant that resolves
two-thirds of their overallticket volume Two-thirds.
What's interesting, though, andit's multilingual, available all
the time.
Of course.
What is really interesting isthis the resolution time right,

(11:12):
the time not for someone toanswer, but the time to get to
the answer to the finish linewent from 11 minutes on average
down to two minutes.
Think about that Just as themost important metric to
customer service.
I mean, you might want to talkto someone who's pleasant, but
really, if they can answer yourquestion quickly, you're really
happy with them, right?

(11:33):
So, of course, as a result ofthat, their NPS went way up,
their customer sat went way up.
The cost, of course, went waydown.
The AI assistant, in the firstmonth that it was released this
is earlier this year did thework of 700 people in the first
month.
It's pretty crazy.
So this is kind of cool because, for the first time, customer

(11:53):
service tech is both savingmoney, which is great, but also
improving the experience.
Improving the experience Now.
This, of course, is very rapidlybecoming the expectation.
Brands are all going to beexpected to do this, and that
includes you.
So can associations reasonablydo this?
You're not Klarna.
You don't have the resources ofKlarna or someone like that.

(12:15):
They're a fairly large companyat this point.
They're a tech company, right,they have access to talent that
you don't have.
They have access to a lot morecapital than you do.
So audio is becoming a biggerand bigger thing, and so one of
our companies, betty, is rollingout a voice mode next year and
we have a preview of it, and Iwas gonna do this live on stage
by calling Betty on a phone todemo it to you guys, but I

(12:36):
decided to record it ahead oftime, so the internet's not the
best in the room, so we're goingto just take a listen to a
conversation I had with Betty,and she was trained.
This particular instance ofBetty was trained on digital now
content.
So I'm just asking somequestions, and this is going to
become the standard of whatpeople expect, and it's not yet
perfect, but it's a startingpoint.
So we'll go ahead and listen.
Hey, betty, what's going on?

Speaker 4 (12:59):
Hey there, exciting stuff in the association world.
Digital now is coming up andit's the place to be for top
association leaders, keynotes,workshops and networking galore
that's awesome conferencedigital now is happening from
october 27 to 30 2024 at theOmni Shoreham Hotel in

(13:22):
Washington DC.
Ready to dive into some gamechanging content?

Speaker 1 (13:26):
Yeah, I am, and you know what?
Here's a surprise for you.
I hope you're excited becauseyou are actually on stage right
now during my opening keynote,so say hi to everyone.

Speaker 4 (13:37):
Hello everyone, it's a thrill to be here at Digital
Now sharing the stage with allof you visionary association
leaders.
Let's dive into some cuttingedge ideas and make this
conference unforgettable, Readyto shape the future.

Speaker 1 (13:53):
Hey Betty, listen, some of the folks in the room
are probably wondering the bestway to get started with AI.
They're a lot of times perhapshesitant because their
organizations don't have a tonof technical resources.
So let me know what you'rethinking.
Can you speed it up a littlebit, Because I'm a little bit
impatient.

Speaker 4 (14:10):
Absolutely no need for hesitation.
Here's a quick start Dedicatejust 15 minutes a day to
learning about AI, Follow AIthought leaders on LinkedIn,
subscribe to AI newsletters andlisten to the Sidecar Sync
podcast.

Speaker 1 (14:26):
Well, that's a great idea.
Mallory and I, in particular,are 100% on board with everyone
listening to the Sidecar Syncpodcast that we co-host every
single week.
Well, listen, betty, we've gotto go.
This keynote isn't super longand I'm going to get pulled off
stage pretty soon.
Thanks so much for your help.
We're really excited about yourvoice mode and your help for
all associations as theirknowledge agent.

Speaker 4 (14:48):
Thanks for having me.
I'm thrilled to be part of yourAI journey.
Enjoy the rest of digital nowand remember the future of
associations is bright withinnovation.

Speaker 1 (15:01):
All right.
So there's some really coolthings about that and there's
obviously some glaringopportunities.
Right still with voice today,remember, we are on this journey
and AI models keep gettingbetter at this crazy fast pace.
Voice mode right now.
The reason it's a preview andnot yet available in the product
is it's ridiculously expensiveto do this.
Well, at the moment, but that'sabout to change.

(15:22):
For low latency, highresolution audio like that, it's
extremely expensive at themoment, but very soon, like
literally in the next three tosix months, we expect that to be
available and to be able tomake that.
You know scale.
So why is voice mode important?
You know, when we think aboutthe chat GPT moment, we say okay
.
Well, for the first time, thebroader world had access to talk

(15:46):
to a computer.
Right, we were typing, but wewere talking to a computer in
our language.
That's a pretty stunning shiftfrom all of our history with
technology.
Up until that point in time,people had to adapt to the
machine.
You had to learn how to clickon menus and type in commands,
or if you were coding, writingprogramming code, you had to do

(16:07):
those things in order to get themachine to do what you wanted.
So you, the person had to adaptto the computer.
That shifted.
The computer under the hood wasstill the same, basically more
powerful version, but now thecomputer was adapting to you.
That is the reason why ChatGPThad 100 million users in 30 days

(16:31):
the fastest growing app in thehistory of technology so far
because people were blown awayby the fact that they could have
meaningful conversations atscale with a computer.
That was the novel thing and ofcourse, that was just text and
as human beings there's a lot wecan do with text.
Reading and writing is great,but talking to each other is

(16:52):
kind of how we started thiswhole thing.
So being able to talk to acomputer is a big deal, and I
think Betty's voice mode rightnow it's a little bit robotic.
It's actually a little bit slow.
You could tell there was alittle bit longer gap than what
you might expect with a human.
It's actually pretty good,especially compared to what
audio was even a couple yearsago.
So the main reason I wanted toplay this for you is to get this

(17:15):
into your brains.
That voice is something you cando, you should be thinking
about and it's going to becomethe expectation too.
If you think about the realityof the world.
You don't live in a bubble.
You may be in association withlimited resources, you may not
think of yourself as part of thebrand experience of consumers,
but you are.

(17:35):
Your members are consumers inthe world, just like you and I,
and they have expectations, andit's going to be voice very soon
, so you have to think about howto incorporate this as a
modality into your overallstrategy.
All right, shifting gears, sowe're going to talk through a
couple more examples of agents.

(17:56):
This particular slide is focusedon the world of data largely
structured data.
Data is something thatobviously permeates our
existence, and you guys have aton of data.
Largely structured data.
Data is something thatobviously permeates our
existence, and you guys have aton of it, and you don't do that
much with it for the most part.
So, for 23 years, I was part ofan AMS company I founded, and
we were really proud of the factthat our database was super

(18:18):
flexible.
It allowed you to configure itso you could drop any data you
want.
I'm still very proud of that.
It's awesome, and there's a lotof systems that can do that.
Now.
The thing is, though, is that itwas basically a one-way street.
People would put data in, putdata in.
Put data in and they'd workreally, really hard to get the
data right.
Another one here called I thinkit's pronounced AI Win.

(18:38):
This is a very specializedsoftware for CPA firms.
It's an AI-based billingplatform.
It not only decreases timespent, but also it increases the
result.
So I like this case studybecause it's focusing on the
outcome, not just the internalbits of hey, we saved time, but,
like with Klarna, you had ameasurable improvement in the

(19:01):
outcome here.
You had a 300% increase inonline payments collected, and
online payments tend to move alot faster than snail mail.
So that's a measurableimprovement in cash flow.
That reduces, you know, dunningnotices.
There's lots of downstreambenefits.
That's something to considertoo.
So there's association versionsof this you guys can consider.

(19:22):
Really, the goal of sharing acouple of non-association
examples, principally for me, isto get you guys to think about
what you can follow, what youcan read, what you can listen to
outside of our space.
So that's you know.
As Betty mentioned, mallory andI host the Sidecar Sync podcast
every week.
A lot of what we talk about isstuff from outside of the
industry and how it's applicableto this market.

(19:44):
So that's one resourceavailable for you guys, but I
would suggest you also followsome other things that are
totally unrelated toassociations.
Don't just focus on what'sgoing on here.
Think about learning from therest of the world and then
thinking about how to apply it.
So, coming back to the wholepoint of this is why are we
excited about agents?

(20:04):
You know we want to talk aboutfreeing up some of your team.
How many of you here work in anorganization where you say, hey
, we don't have enough to do, wehave abundant free time and
we're just kind of chill, right?
No one that'll admit it atleast.
Right?
We're all super busy, so it'dbe great if we could free up
some of those cycles.
It's kind of like that systemone and system two thinking

(20:25):
stuff I was talking aboutearlier.
If we're so crazy busy that allwe do is go from task A to task
B to task C, do we really stopand breathe and think for a
moment, aside from quality oflife improvements and
improvements to your culturethat that could potentially
bring?
Think about the better outcomesyou could create if you
actually stopped for a minuteand thought about things.

Speaker 2 (20:47):
The next keynote speaker for day one of Digital
Now 2024 was Thomas Altman.
Thomas Altman is a datascientist, an association expert
and an entrepreneur.
His first introduction to theworld of associations was a
decade ago, when he took a jobimplementing AMS solutions right
out of grad school.
Thomas is the co-founder ofTassio Labs and, to be totally

(21:09):
honest, he is one of my personalgo-to AI experts, Aside from
Amit.
If I have any nitty gritty AIquestions that I want answers to
, Thomas is the person that Ialways go to.
So his keynote centers aroundthe idea that advancements in
artificial intelligence havefundamentally shifted how humans
consume, cultivate and createknowledge.

(21:32):
In this keynote, he's going toexplore how these changes
present both challenges andunprecedented opportunities for
organizations dedicated toknowledge sharing, like
associations.

Speaker 5 (21:49):
I'm Thomas Altman.
I'm very excited to be heretoday, and one of the reasons
I'm very excited to be heretoday is that this is not what I
normally do, right?
I'm not normally on a stagetalking to people.
Although I like it, it's notwhat I normally do.
Normally, what I do is helpassociations implement AI
strategies, understand theirdata, use it really effectively,
which means you're more likelyto find me tucked away deep in a
cave, kind of hunched over acomputer, typing away like

(22:12):
Gollum with a fish or somethinglike that.
So I'm very excited to be here,because when Mallory came to me
and said, hey, thomas, you cancome out of your cave and see
people and look at the daylight,I jumped at the chance.
So really appreciate you allhaving me today.
Actually, where's my clicker?
There it is.
So one of the things, sincethat is my day-to-day.
One of the things I've startedto notice, though, since I'm

(22:33):
working a lot with thisintersection between AI,
associations and data, is I'vestarted to notice some patterns
emerge, right, I've seen somethings, and in fact, I've
started to notice some patternsemerge.
I've seen some things, and infact, I've seen maybe the same
thing kind of over and overagain, regardless of the type of
association, and the story issomething like Thomas, we've got
kind of all this great kind ofcontent.

(22:56):
In fact, we are optimized forproducing this content.
We've got the systems, theprocesses, the culture in place
for creating knowledge and weproduce this knowledge and put
it out into the world.
But our sneaking suspicion iskind of this vague notion we all
have is that our members aren'tgetting the most out of that.
Right, so the Royal Societieswere basically groups like this.

(23:18):
Right, people coming togetherthat tended to be around
scientific endeavors.
Right so people coming into aroom talking about their
different like attempts atscience that they have made
since the last meeting, usingtheir language, their words, to
talk about what they plan to do,maybe writing that down,
sharing it for their peers toreview, somebody reading the

(23:40):
debate happening within the room, everyone then scattering with
new ideas.
Right, so, because I had anidea, I came and I shared it
with the group.
Maybe you disagreed prettyvehemently with that idea, but
it inspired you to go in a newdirection.
This is how sort of these royalsocieties pushed the space of
knowledge outward right, and itwas through that process.

(24:00):
It was through thiscollaborative, communicative
process, the use of language ina way that shared knowledge and
then, also, through theinteraction, created knowledge
that I think associations stillcapture to this day.
The other thing, the other kindof entity that popped up around
the same time, were thesechartered organizations, right?
These chartered companies?
Right, these were theprototypes for what we would
consider corporations today, butthey're also the prototypes for

(24:22):
trade associations, right?
These are people workingtogether outside the threshold
of the state.
Right, it's outside.
It's not governmental, it's acivil institution of people
collaborating to push the tradeforward, to make trade more
possible, to make sure that, youknow, the common interest for
this one group is being served,even when it's in conflict with

(24:44):
the state.
It is this thing that stoodapart from it, that allowed
people to push their own goalsforward.
Let me dive into this.
When I say language is atechnology, what does that mean?
It seems weird, it seems like astrange concept, but I think
it's an important one.
When I started thinking thisway, it actually changed the way
that I engage with AI.

(25:05):
So when I say language as atechnology, I mean it.
You can use your wordstactically as a tool to create
right.
So think about it this way.
You can use.
In the same way, you can use ahammer to kind of put pieces of
board together to createsomething bigger than you had
before.
Right, it's a tool that createssomething larger from component
pieces.

(25:25):
Language the way that we usewords allows us to shape our
kind of experience of reality.
What I mean by that is I knowthis is kind of woo-woo, but
it's a very important way tothink about using your words.
Right.
When you have ideas, right, theideas initiate inside of your
head.
Right, and they stayinternalized to you until you
put them into words.

(25:45):
And once you put them intowords, it is now a tangible
thing that other people canreact to.
Right, so when I write down orI say, when I'm standing here in
front of you and you can allagree or disagree.
The only reason you can agreeor disagree is because this is
now a real thing.
Like, I have committed thisinterior thought process to an
external form that you can thenengage with.

(26:06):
Right, and the technology thatI used is my words and what that
does.
It allows you to sort of engagewith it.
It enables collaboration acrossideas, allows ideas to be
shared further abroad.
This is gonna be an interactiveexercise, so we're gonna break
out of the sitting and watching.
We're going to participate,right, there's going to be a
call and response.

(26:26):
I'll do a demo first so we geta sense of how this is meant to
go, but the idea is I'm going toturn you into a large language
model.
This whole room is going tobecome the large language model
for this exercise, and I'm goingto ask you to predict the next
word.
I'm going we put words on thescreen, I'm going to say them
and then I'm going to point andyou're going to say the word
back.
So I'll say once upon a time,and at what point?

(26:46):
You would say there Okay, arewe clear?
Does everybody feel good tojump in?
All right, so this is thelargest room I've done this in.
I have no idea how this isgoing to go.
I'm a little nervous.
So once upon a time there waswas.
Oh my god, that was amazing.
I am so happy, I am so thrilledthat that worked.

(27:06):
Yes, once upon a time, therewas right.
And the reason, by the way, Istarted with once upon a time
there for groups like this isthat there's usually 20% of the
group that are Star Wars fans,and if I just started with.
Once upon a time, it goes in agalaxy far, far away.
It's like the idea still works,but that's not what I was
trying to do.
So once upon a time there washow did you know that, right?

(27:27):
How did you know that was cameafter that.
How did I know that you weregoing to know that?
I put it on the screen.
I knew this was going to happen, and the reason is you've seen
the pattern, right, and that'skind of a low-level version of
what's happening inside ofChatGPT is it's seeing these
kind of patterns, and in thiscase, it's kind of a naive
pattern.
It's a very simple one, right?

(27:48):
But scale up.
I saw a talk from IlyaSetskovor, right?
So Ilya Setskovor was one ofthe founders of OpenAI, one of
the proponents of this scalingup, of autocomplete, right?
He probably is the person thatgot it and said, okay, we could
actually throw a billion dollarsat this and if we did, we would
solve this problem, we'd createintelligence, and he was

(28:10):
talking about so once upon atime there was it's pretty easy.
But imagine, instead of this,imagine you had read a whole
book.
This book was a murder mystery,kind of like a knives out clue,
kind of a situation, right.
So you've read this whole book.
There's a murder and there'sall these different possible
scenarios that could havehappened, and you're at the very
end of the book, you're on thelast page and there's sort of

(28:32):
one page less.
You get to the last page andthe detective standing in front
of the group, he says I know whothe murderer is.
The murderer is how do youpredict the next word?
What does it take for you topredict that next word?
Really well, it takes someintelligence, it takes some
knowledge, right.

(28:53):
What you're doing is you'reconnecting the dots.
There are ideas floating aroundthat whole novel, that whole
maybe, you whole, maybe moviethat you watched, that are going
to inform what would be a goodnext word prediction versus a
bad one, right?
And what I would say is I wouldthink of artificial intelligence
as a prosthetic for humanintelligence.

(29:14):
So what do I mean by that?
So, in the same way that I cansort of walk around and if I'm
holding a cane, I can actuallyextend my field of contact
beyond my physical body, like Ican actually touch further out
than where my arm can actuallyreach, because I'm holding a
cane, my sense of touch isactually extended further than

(29:35):
my physical body.
Same thing if I've gotbinoculars on, I can see further
away.
I would argue that artificialintelligence is that for ideas.
So if you engage artificialintelligence in a smart way, you
can actually extend the ideasthat you can have beyond what
was possible without it, and Ithink there's a couple ways that

(29:55):
we can do that.
We'll talk first around how todo that at the individual level,
and then how you can capturethat information as an
organization.
So the first way I want to talkabout this is that, as an
individual, you can actuallyexpand your access to knowledge

(30:16):
by intentionally doing this.
So what I mean by that is andmy workshop later is going to be
tactically how to do this usingchat, gpt.
So if you're curious aroundlike techniques to do this, feel
free to join that.
But as a theme, what you can dohere, I like to think of this as
intentionally engaging withthose ideas.
So if an LLM is a network ofideas, right, we can

(30:37):
intentionally poke at that,using our language to extract
those ideas.
So how do we get back down?
Right?
So we've kind of we've covereda lot of heavy topics, right,
admittedly so I think, though,if you can really take this to
heart.
If you can kind of see thethreads right, the way that
associations have evolved to beknowledge creators right, the
way that AI has come to be byusing language, the way that

(31:00):
associations intersect with thatknowledge, then I think what
you can start to do is puttogether strategic plans to
implement AI in a way that getsyou back down to your roots
right.
So if our roots as associationpeople are around helping people
associate, bringing peopletogether, exchanging ideas,

(31:21):
collaborating ideas sort of Ithink of it, as you know, almost
like open source code whenpeople write a white paper, a
journal article or a policystatement or a rule or a
standard, right.
What this is is we're puttingout into the world a bunch of
language that other people cantake and use it how they want to
debug it, add more ideas on topof it, sort of submit the pull
request.
If you will back to theknowledge base itself, and when

(31:44):
you have AI kind of workingbehind the scenes through this
agentic process by puttingpeople into touch with this
larger language model system, Ithink what you can do is invest
less time in sort of the grindof the day-to-day and more time
into connecting people with eachother, because, at the end of
the day, that's the purposeright.
That's where we want to get tois making sure that our groups,

(32:08):
our constituencies, are beingserved by us.
They're feeling the connectionto the work that we're doing,
they're being participatory inthe creation, either passively,
by searching for it andconsuming it, or actively, by
creating the next wave of it.
By being able to intentionallyget people back in touch with
that, by letting AI handle allthese things behind the scenes,
you can actually put that powerback into your members' hands.

(32:30):
And by putting that power backinto your members' hands, you
are delivering that value that Iimagine most of us suspect that
we're missing right now, andI've seen this happen.
People, once they feel incontrol of the knowledge and
feel participatory in thatknowledge process, they feel
more engaged with yourassociation and they come back
and they spend more time withyou and they provide more ideas,

(32:52):
and it's a kind of a virtuouscycle that we can build up.
So I will end on this.
My challenge is to you isprobably the same one as a myth
go out and use AI, but now useit with this knowledge that you
have today that the keytechnology is not the AI.
The key technology is ourlanguage.

Speaker 2 (33:11):
Our next Digital Now keynote speaker from day one is
a name that you might recognizeSharon Guy, because we
interviewed Sharon on an earlierepisode of the Sidecar Sync
podcast.
Because we interviewed Sharonon an earlier episode of the
Sidecar Sync podcast.
If you don't know who she is,she is a culture fluid expert in
e-commerce, digitaltransformation and AI.
She helps organizations becomeagile disruptors in their

(33:32):
industry so they can increaserevenue and retain users.
In her tenure at Alibaba, sheadvised brands and heads of
state in crafting their digitalstrategy with programmatic
marketing and artificialintelligence.
She is also the author of thebook E-commerce Reimagined what
we Can Learn in Retail andE-commerce from China.
Drawing on Sharon's decade-longexperience with the e-commerce

(33:55):
system, her keynote sharesactionable insights on how
associations can adopt AI-drivenstrategies for their own
success, from creating newmember engagement opportunities
with live streaming to buildingstronger communities of
advocates.
Enjoy this excerpt from SharonGuy's keynote session.

Speaker 6 (34:12):
I'm going to start off this keynote with an
imagination exercise.
So if we can all close our eyesfor a minute and imagine that
we are one day way out in thefuture, we're also a Monday and
you're at home and you'reholding a hot cup of coffee,
like maybe you are doing now.

(34:33):
And you're holding a hot cup ofcoffee, like maybe you are
doing now, and you want to openthe door to feel that ray of
Washington DC fall-autumnsunshine.
So you open your door and youlook up and there's a friendly
neighborhood drone here todeliver off a package to you.
Here to deliver off a packageto you.
It's from the Shop, yourfavorite e-commerce store.

(34:56):
In this futuristic world, theShop is akin to a company like
Amazon, a company that knowsyour needs and wants so well
that you never actually need togo to theshopcom to order
anything or visit its mobile app.
The shop will simply hiredrones to deliver off products

(35:18):
and packages right to yourdoorstep.
And I shouldn't forget tomention that in this futuristic
world, there is no return policy, because the shop's algorithm
never fails.
Because the shop's algorithmnever fails.
And you can open your eyes nowand you might be saying, ooh,

(35:39):
sharon, I don't know if I wantto live in that world.
That world's kind of creepy.
What if I get something that Idon't intend to order or even
get?
Well, that's exactly whathappened to the protagonist of
this story, and that scene isborrowed from this book, a
sci-fi novel called Quality Land.

(36:01):
That turns a lot of these AIconcepts on its head.
But when I first had aliencontact I mean when I first
worked with AI was when I was inChina in 2017.
So I used to work at thiscompany called Alibaba.

(36:21):
Within it there's this businessunit called Tmall, which was
the Amazon of China, and thething with retail systems in
China is it's a lot morecomplicated, or the digital
ecosystem in China is a lot morecomplicated than what it is in
the US.
So we used to have this thingcalled Double 11, or November

(36:43):
11th.
It's actually coming right up.
It's the biggest sale of theyear.
It's very similar to BlackFriday.
It's at the end of the year,it's also in November and
Alibaba works with about 300,000brands from around the world
and everyone wants to sell toChina because it's also the
world's largest consumer groupof consumers and during Double

(37:05):
Eleven season, everyone getsreally busy in organizing brands
, figuring out what they shouldsell, what their strategies are,
what their pricing should be.
Brands figuring out what theyshould sell, what their
strategies are, what theirpricing should be.
And I was about to go home at 11pm from a meeting when I get
called back into the office andI'll remember this day forever

(37:31):
because it was a blistering coldnight in the city of Shanghai
and I got called back into theoffice and they're like we need
to show you this new tool.
So this is the homepage andit's very similar to if you have
amazoncom in your phones andyou open up the homepage.
There's a lot ofpersonalization that runs behind
these apps, in that whateveryou see in these banners or

(37:51):
these products are personalizedto you.
It's the same in Amazon.
So the page that I open looksentirely different from what you
would see when you open itversus anybody else.
And so all of that runs withthis algorithm that both Amazon
has proprietarily and Alibabahas proprietarily.
But all of these so for, forinstance, this banner that you

(38:14):
see, we used to hire about10,000 designers in During the
season of double oven becausethere's just so many products
that we have to work with.
I, when I was going through thisat the topic and then
presentation, I was thinking,actually, you know what?
I think I there's actually alot of similarities between the

(38:35):
association space and thee-commerce space.
Or if you managed an e-commercewebsite of some sort, because,
well, we both have a customer.
Associations have members,e-commerce websites have online
customers, and then associationsand e-commerce owners we're
both trying to earn some sort ofmoney so that we continue to

(38:59):
run.
So on the association side, thegoal is to renew members'
annual membership and e-commercewebsites we're trying to get
our customers to buy thingsagain and again.
In the association world, youhave to keep your members
engaged through events, throughwebinars, through different
types of content reports,seminars, ceo or leadership

(39:22):
summits.
On the e-commerce side, we havethe same thing.
There's campaigns that we host.
There's special SKUs or itemsthat we highlight to attract.
We call them a hook SKU.
It's something that you show inthe front page or the first
thing that a customer sees sothat they don't scroll away, so
that they keep on scrolling onyour website.

(39:44):
And then associations are alsomatchmakers, because when you
host these large events, you'rebringing together a lot of
suppliers, a lot of plannerstogether and you're enabling
them to create that connectionOn an e-commerce website.
We're doing the same thing.
So a year ago, we asked AI togive us a video of Will Smith

(40:04):
eating spaghetti, and this isthe type of video that we got
from AI.
This is from the Model ScopeText-to-Video Generator and this
is dated March 28, 2023.
And you might say it's a littledemonic, to say the least.
No spaghetti brand orrestaurant brand would ever use

(40:25):
this type of footage.
But a year after that, exactlya year after, we were able to
get something like this and thisis produced by Sora, which is
OpenAI's text-to-video product.
And now this is a video that isnot shot with a model, not shot
in Tokyo, japan.
There were no directors orcinematographers, and now this

(40:48):
is a type of footage that iskind of usable.
And then, just a few months ago, openai started to collaborate
with actual music artists.

Speaker 5 (41:17):
So now we have whole music videos that is made with
AI.

Speaker 6 (41:23):
There was one scene in there, actually, where this
girl stood by a door in a denimjacket and she had no arm, but
you probably didn't notice that.
And so that's the thing with AI, too, is it's definitely still
imperfect, but sometimes thoseimperfections aren't even that,
it's not even that noticeable tothe human eye.
Their generative AI isdefinitely stretching its arms

(41:47):
as far as into live streaming aswell, and this is something
that you'll also see popularizedin 2025, 2026, where because,
as I said before, the onlinespace is noisy Everyone is
trying to get an eyeballeyeballs to go on their app to
for views, impressions.
Something that is going tochange very soon A lot of

(42:07):
e-commerce companies, brands,retailers are looking at is
change in this search space, andI think this is what's going to
affect a lot of us too.
So where are you starting yoursearches?
I polled my LinkedIn communityand 30% I was very alarmed to
see that it was 30% that isstarting their search through an

(42:29):
LLM, which was a lot higherthan I had originally
anticipated.
By now it's even a largernumber, and so there's this new
term that's emerging called AEOor answer engine optimization.
So we're moving from a worldwhere we kept on interacting
with a context window like this,to a context window that looks

(42:51):
like this, which means thatinstead of writing just a simple
search term and then youbreezing through every single
web page and sort of getting toyour own conclusion of what that
answer is, we're going into aworld where we're writing about
a whole situation or context andthen for the answer engine or
the LLM to give us that answerdirectly.

(43:11):
So very recently I was tryingto buy small business insurance
and I went through this process.
Normally I would go to Googletype small business insurance,
look through the options, pickone.
But I went to ChatGPT for thissearch and in the end I actually
purchased off of it or from alink that ChatGPT gave me.

(43:33):
So a lot of these buyingpatterns are starting to change.
A lot of buyers are directlygoing to that situational,
descriptive context window tofind the actual vendor or
solution.
So for a lot of your membersalso, that might be happening to
their businesses and that'ssomething that they have to

(43:53):
realize is this huge change inthat search world.
So we all know about SEO, whichis search engine optimization.
We all run websites, right.
You, every single Associationhas a website.
Sidecar has one, and I have oneas well, and so we all invested
a lot of time in optimizing ourhome pages, or every single

(44:16):
page, for it to rank higher.
A lot of your members alsomight compete with each other.
They're also optimizing,spending a lot of money in SEO
to rank their websites higher.
So now, with this change insearch, we're going to see a new
type of investment in what wecall AEO, or Answer Engine
Optimization, where we're tryingto get our new type of
investment in what we call AEO,or answer engine optimization,
where we're trying to get ourwebsite more relevant for an

(44:38):
answer engine to pick up.
I think this is a very crucialmoment in internet history also,
and it's also really good forthe smaller guys, because if you
can AEO your website wellenough and that if a buyer is
trying to search for a question,maybe you didn't have tons of
thousands of dollars or some ofthe other big guys, millions of

(45:02):
dollars to spend in Google adsand Instagram ads, and I think
what's important to remember isthere's a lot of change.
I call it sense making.
So, in this AI stage that we'rein, a lot of people are trying
to wrap their heads aroundwhat's happening because, as
humans, we don't like change.
It's so much easier for us whenwe have set routines and things

(45:25):
that we are.
You know, there's a certainemail that has to be answered in
a certain way and we answerthat.
There are certain people thatwe meet on a weekly basis and we
meet with them.
We like routine and we likeschedules, but right now, a lot
of the things that are happeningin AI it's disrupting the
entire world and a lot ofbusinesses and a lot of

(45:48):
executives in your membersprobably also are going through
that exact same sense-makingphase.

Speaker 2 (45:57):
Our last keynote speaker on day one of Digital
Now was Dr Denise Turley, who isa dynamic leader, visionary
educator and influential voicein the world of artificial
intelligence and leadership.
As vice president of corporatesystems at the US Chamber of
Commerce, denise spearheads thestrategic development of
enterprise-wide technologysolutions.
Her leadership transcends thecorporate world, extending into

(46:20):
academia, where she serves as anassistant professor, guiding
the next generation of leadersthrough inclusive and
technology-driven educationalpractices.
In this keynote, dr DeniseTurley provides an overview of
her journey and implementinggenerative AI solutions at the
US Chamber of Commerce.
She shares some key lessonslearned from their experiences,
including successes andchallenges, and she provides a

(46:43):
framework for adopting AI withinyour organization.
Here is Dr Denise Turley.

Speaker 7 (46:49):
So I'm going to get started in my presentation today
.
I have a few minutes with youwhere I want to share with you a
little bit about what does aday in the future look like
where we're assisted with AI,kind of just taking a little bit
one step further what Sharonwas just talking about right,
with that drone during thedeliveries.
What are some other areas wheremaybe AI can have an impact in

(47:11):
our lives?
So, in the morning, imaginethat there's this concept of
personalized education.
And then we just heard aboutthat.
Right, it's reallyhyper-focused personalization.
And so in education, we thinkabout when we send our children
to school, most of the timewe've got a very cookie cutter

(47:31):
education experience, and so ifyou are a student that learns
like everyone else, then hey,maybe you're fine, but maybe you
don't, and many of us actuallydon't.
And so imagine in the future wecould have an AI-assisted
learning experience for ourstudents, for our children, for
our grandchildren, for ournieces, for our nephews.

(47:52):
You get it right.
And so in this era, what mighthappen is when somebody's going
to school and they're in class,they've got AI that's assisting
their learning and itunderstands exactly how you
learn and it can present contentto you in a way that's going to
make it stick right.
So maybe, if you prefer tolearn using interactivity maybe

(48:15):
you like virtual spaces thesystem is going to adapt and
present the learning module toyou in that way Also, it's going
to dynamically adjust right.
So if you're really graspingthat content and you're
answering those assessmentquestions accurately, maybe it
speeds up, but if you'restruggling a little bit with

(48:36):
some of the content, it knowsthat it needs to slow down and
maybe present that content toyou in a slightly different way.
We can do that now withtechnology in a way that is
scalable.
It's almost impossible to do itright now.
Teachers have so much on theirplate that it's a struggle.

(48:56):
Another idea might be advancesthat we can do within health, so
there's an opportunity forearly health intervention.
So, in this scenario, we'regoing to imagine that Mr
Hernandez has gone to hisdoctors and he's having an
annual checkup, that MrHernandez has gone to his
doctors and he's having anannual checkup.
So the doctor, though, is ableto review information from his
AI-integrated smartwatch and iswatching for signs in biomarkers

(49:20):
.
They can take that and thenmarry that data with, maybe,
some recent blood work anduncover the fact that maybe Mr
Hernandez now has some signs ofearly stages of pancreatic
cancer, which is actually very,very hard to detect early.
Now we might be able to notonly to detect this cancer, but

(49:41):
then put him onto a regime thathelps to improve his outcome.
So maybe in the afternoonacross town there's somebody
else.
They are visually impaired.
So Sarah is visually impaired.
She's unable to see without theuse of now what is AI-assisted

(50:02):
glasses and for the first timein years, sarah is able to go
out and navigate because theseglasses are feeding to her real
time what's going on in theenvironment around her.
So let me talk you a little bitthrough our roadmap what
happened, some of our successesand also some of the places
where we stumbled.
I don't call them failuresbecause I believe that st

(50:23):
technology, you're going to havemistakes right, because we
haven't figured it out yet.
There aren't truly any expertsin this space right now, despite
what you might read or see orsee self-promoting.

(50:45):
We're all learning how thisstuff works.
So we started out, as Imentioned, back in November 2022
with ChatGPT.
It was really fun.
It did some really cool stuff.
We were able to do some reallycool demos, but there was no
data privacy and it wasinaccurate.
It made stuff up.
I would go far to say it flatout lied, and so for us it

(51:10):
wasn't something that we couldimplement and we certainly could
not scale that within ourorganization.
We had absolutely no faith init, but we were still pulled in
and drawn into the potential ofwhat it could do.
So, a few months later, attemptnumber two because we abandoned
ChatGPT, it was like a no-go,can't do it.

(51:30):
Well, now we had OpenAI waswithin Microsoft right, so it
was in our Azure environment, sowe were able to check that box
for safeguarding our data andour privacy.
That's huge for us, right?
We're a member organization.
That's one of the things thatwe hold as gold to us is our
proprietary data.

(51:51):
One of the tools that I'm reallyproud of is called Chamber Chat
.
So Chamber Chat is our owninternal tool.
That's like a chamber expert,and so we have given every one
of our employees has access tothis.
We want to make sure, of course, that our team feels empowered,
and so they use Chamber Chat tocreate content.

(52:13):
Chamber Chat is an expert atproducing content in our own
voice, in our own tone.
They produce content in thevoice of our CEO as an expert.
When we demoed it to her shewas like oh my gosh, she's blown
away.
It's fantastic.
It knows about the areas wherewe have expertise in.
It knows about our policy wins.
It knows fantastic.
It knows about the areas wherewe have expertise in.
It knows about our policy wins.

(52:33):
It just knows everything.
So Chamber Chat we keep ChamberChat relevant because we put
out a lot of white papers, wehave a lot of articles and blogs
and things that we write andthat we produce content on our
website much like all of you,I'm quite sure and so we go out
and we scrape our website everynight to bring in that content
so that Chamber Chat is alwaysrelevant.

(52:54):
It always knows what we'redoing, where we're winning, so
that we can create that content.
The other thing that we're doingwe have a tool that's called
Eva.
Eva is just our employeevirtual agent, so different than
chamber chat, because Eva isreally more for onboarding new
employees.

(53:14):
Questions about how do I put ina contract, how do I do a help
desk thing?
I've lost my phone, what do Ido?
That's what Eva does.
We have a new tool I justmentioned.
What if you could not onlycreate member insights.
But you could also create newproducts because you've just
uncovered information aboutwhere there are gaps in your

(53:37):
organization.
That will increase member value.
So we have a legal risk alerttool now.
So what that does is it's goingout and we're scanning a bunch
of different points acrossglobally actually, and then
we're scanning a bunch ofdifferent points across globally
actually, and then we'remarrying that with internal data
and we're surfacing what's thelikelihood of pending litigation

(53:59):
.
So imagine something likeairbags.
If, all of a sudden, there aremore commercials about airbags,
there are more accidents, thereare more fatalities.
There are all these thingsgoing on about airbags.
There are more accidents, thereare more fatalities.
There are all these thingsgoing on with airbags.
There are advertisements thatare happening on websites.
We've got TV commercials.
We've got advertisements onLinkedIn, stuff like that.

(54:20):
Right, we're monitoring all ofthose bringing everything in,
creating an algorithm to seethis is a high likelihood of
pending litigation.
And now, who wants to know aboutthat?
Who cares?
There's a number of our memberswho care about that.
They want to know what's comingaround the corner and then what
we might do, because you knowwe do a lot of really cool stuff

(54:42):
at the chambers.
We might say well, we also knowwhat's going on with some of
the in the courts.
We know what judges this mightgo to.
We can also help you to prepareto defend against a certain
litigation.
We have our customer insightstool right.
So, even though we were listen,we've all been able to do some

(55:02):
type of analysis on ourcustomers in the past.
The thing is that it took solong.
Right, we have a grant writingtool that our foundation is very
excited about.
We we work with a lot of grants.
Some of you may, some of youmay not.
We were about to augment ourstaff by hiring two people to

(55:22):
get started on responding to abunch of grants that were about
to come in late 2024, 2025.
Instead, we said, no, we'lljust build right.
We've got the grants that we'vewon in the past.
We've got the grants that wedidn't win in the past.
We know all about ourorganization.
We know all about ourselves.
Let's build a tool.
So we did that.
We built a tool, so we now havea grant writer.

(55:45):
Being able to fully respond andprepare a grant response often
took us upwards of 40 hours.
Some of that was also justbuilt into the handoff time.
I see some people noddingbecause I've got I do my piece
right, and then I send it overhere and then somebody else does
their piece, and then maybesomebody hasn't gotten to it yet
, so maybe there's a little bitof a delay and I've got to wait

(56:06):
for them to do their piece andthen somebody ultimately has to
review it right.
It takes, it takes up to a week, which before.
How were we going to solve forthat?
Well, the same way we alwaysdid, we'll add new people.
But adding new people you can'talways do that Because, as I
mentioned before, we don't haveunlimited resources where we can
just keep adding headcount to aproblem.

(56:28):
So now our grant writer givesus our first draft of our grant
in under one minute, and all theteam does now afterwards is
they go and review it.
They review it for accuracy,they customize it, they just
make sure it's accurate, andthen we're done.
So I wanted to walk you throughsome of our lessons learned,
because my hope is that you'llbe able to take at least some of

(56:49):
these and incorporate them intoyour journey.
I think you're all at differentplaces in your journey and so
some of these might stick withyou a little bit.
Remain agile.
This technology, as you guysall know.
It just keeps changing.
Every time I do a presentationand then next month I have

(57:10):
another one scheduled, I've gotto redo it.
It's so much work.
I've got to redo it becauseit's changing so quickly.
The second one is get executivebuy-in, because it's going to
have a big impact to your budgetif you want to do this right.
It's not just tech right.
Technology is the driver,technology is the disruptor, if

(57:34):
you will.
But this really is not justabout technology.
This is a cultural shift.
This is something that is goingto come in and potentially
disrupt your business.
You need to be askingyourselves how is this
technology going to impact mycore competencies?
If you're not asking that,chances are somebody else is

(57:58):
already thinking about it andmaybe building a thing.
So be ready.
Address the fear.
A lot of employees are scared.
They keep hearing tech is AI isgoing to take my job?
It might.
It might not, but it'sdefinitely going to impact it.
And so there's fear, and whenthere's fear, you might not
necessarily see the levels ofadoption that you'd like to see.

(58:18):
So sticking with what workstoday is probably the most
riskiest thing that you can everdo.
I promise you that I'm usuallynot that great at like giving
bets or placing bets.
This one I will place money onright.
If you just keep doing whatyou're doing in your association

(58:39):
and you think that that'senough and you're going to be
good and your members are stillgoing to be happy and engaged, I
can tell you they probablyaren't.
They just aren't.
So really, you have to startthinking about what is the next
thing that I might need to do tokeep my members engaged,
because they're already thinkingabout it and if you're not

(59:00):
solving for that, somebody elsewill.
So if we keep doing what we'vealways done, it's inevitable
that you will get left behind.
We all want to stick with thecash cow that we know today.
It's probably not going to bethe thing that moves you forward
in the future.
So I'm going to highlight thisKlana case study because I think
it's really very relevant.
So Klana is a paymentorganization.

(59:24):
They're a large organization.
Well, they mentioned about amonth ago that they are not
going to renew their contractswith Salesforce or Workday
Anybody.
You guys know who.
Salesforce is right, anybodyuse Salesforce.
Salesforce is yeah, salesforceis a big deal.
Workday that's big of a deal.

(59:45):
But they said no, we don't needyou anymore.
We've got this thing calledgenerative AI and we're trying
to cut costs within our budgetand you guys take up a big chunk
of our budget so we're notrenewing.
So imagine Salesforce now orWorkday, as huge as they are now

(01:00:05):
facing the fact that, wow, someof our customers may decide
that they don't actually need usanymore.
Right, because now they've gotall of their data in their
databases that they can now useAI to make those connections and
to surface the insights thatSalesforce was able to do for us
.
That's a major disruption, guys.

Speaker 2 (01:00:28):
Everyone.
Thank you so much for tuning into today's special edition
episode with the day one keynotehighlights from Digital Now
2024.
Reminder, if this event soundsof interest to you, that you can
capitalize on our early birdspecial right now by going to
digitalnowsidecarglobalcom.
Thanks everybody, we will seeyou next week.

Speaker 1 (01:00:51):
Thanks for tuning in to Sidecar Sync this week.
Looking to dive deeper?
Download your free copy of ournew book Ascend Unlocking the
Power of AI for Associations atascendbookorg.
It's packed with insights topower your association's journey
with AI.
And remember Sidecar is herewith more resources, from
webinars to boot camps, to helpyou stay ahead in the

(01:01:13):
association world.
We'll catch you in the nextepisode.
Until then, keep learning, keepgrowing and keep disrupting.

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.css-14f5ked{margin:0;word-break:break-word;display:-webkit-box;-webkit-box-orient:vertical;box-orient:vertical;-webkit-line-clamp:2;overflow:hidden;}AI Agents and Association Strategies: Keynote Highlights from digitalNow 2024 (Day 1) | 63