AI, Leadership, and Innovation: Keynote Highlights from digitalNow 2024 (Day 2) | 65 - Sidecar Sync

Episode Transcript
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Speaker 1 (00:00):
The usage of data is sub-5% in most organizations.
That's what it is.
You have 100 decisions, data isgoing to come in in less than 5
of them, and so we acknowledge,first of all, that data is hard
.

Speaker 2 (00:13):
Welcome to Sidecar Sync, your weekly dose of
innovation.
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.

(00:36):
I'm Amit Nagarajan, chairman ofBlue Cypress, and I'm your host
.

Speaker 3 (00:41):
Hello everyone and welcome to today's episode of
the Sidecar Sync Podcast.
My name is Mallory Mejiaz and Iam one of your hosts, director
of Content and Learning atSidecar, and today I'm flying
solo without my co-host, amitNagarajan, because we are
bringing you a special editionDigital Now episode.
So, if you recall, a few weeksago we shared a day one keynote

(01:04):
highlight episode from our event, digital Now, and so today we
are sharing with you the fivekeynote speakers from day two.
Really excited to kick that off.
But before we do, I'd like youto hear a quick word from our
sponsor.
If you're listening to thispodcast right now, you're
already thinking differentlyabout AI than many of your peers
, don't you wish there was a wayto showcase your commitment to

(01:25):
innovation and learning?
The Association AI Professional, or AAIP certification is
exactly that.
The AAIP certification isawarded to those who have
achieved outstanding theoreticaland practical AI knowledge as
it pertains to associations.
Earning your AAIP certificationproves that you're at the
forefront of AI in yourorganization and in the greater

(01:49):
association space, giving you acompetitive edge in an
increasingly AI-driven jobmarket.
Join the growing group ofprofessionals who've earned
their AAIP certification andsecure your professional future
by heading to learnsidecaraiyour professional future by
heading to learnsidecarai.
To give you all a quick recap,digital Now is our event at

(02:14):
Sidecar that we host everysingle year.
It's for association leadersand we focus on emerging
technologies and adjacent topics.
So in the past previous years,we've talked about Web3,
blockchain technology and, ofcourse, artificial intelligence.
We held our event in 2024october 27th through the 30th in
washington dc.
It's actually our first time inwashington dc ever and we
brought in some fantastickeynote speakers from outside of

(02:35):
the association space.
So, if you didn't get thechance to attend, we wanted to
share with you some highlightvideos from those keynote
speakers.
As I mentioned, a few weeks ago, we dropped the day one keynote
highlight, and so today we arefocusing on the five keynote
speakers from day two.
If you hear some excerpts thatyou love, I want you to keep in

(02:55):
mind that you can access thefull keynotes in our AI learning
hub, which you can access atlearnsidecarai.
And if, while you're listeningto these keynote speakers, you
were feeling inspired, you feellike you wanna take action, you
feel like you would love toattend an in-person event like
this and hear from somefantastic, similar keynote
speakers, reminder that rightnow you can purchase

(03:18):
registration for Digital Now2025.
You can do that atdigitalnowsidecarai.
The event is November 2ndthrough the 5th, and we are
hosting it in Chicago at theLowe's Hotel for the first time
ever, so I hope, hope to see youall there.
To kick off today's episode, weare starting with our first

(03:39):
keynote speaker on day two, andthat was Robert Plotkin.
Might sound a little bitfamiliar to you, because we've
had Robert Plotkin on thepodcast before.
For over 25 years, ai patentattorney, robert Plotkin has
secured patents for his clients'innovative software, but he
does not stop there.
He then guides his clients indeploying these patents to

(04:00):
withstand the pressures of newcompetitors and big AI and win
historic patent sales andlicenses.
A lifelong AI aficionado andMIT computer science graduate,
robert possesses a uniquetechnical background among
lawyers.
As a patent attorney andco-founder of the boutique
patent law firm BlueShift IP, hesecures and leverages IP to

(04:22):
attract investment, to raisefunds, generate revenue and
secure successful exits onbehalf of his high-tech clients.
This keynote will guide leadersin safeguarding and amplifying
the unique essence or the soul,as he calls it that
distinguishes theirorganizations.
You'll learn how intellectualproperty, or IP, serves as a

(04:42):
vital layer of armor, protectingthis essence from threats while
empowering growth.
This presentation will revealhow AI can be harnessed to
articulate, preserve and expandan association's soul, embedding
it into products, services andinteractions.
So, by strategically combiningAI and IP, associations can
secure sustainable growth,defend against competitors and

(05:05):
unlock new revenue opportunities.
Enjoy this excerpt from RobertPlotkin's keynote.

Speaker 4 (05:11):
I'm going to start by talking about AI, which is the
topic of this conference,leading me to strategies for
using a combination of AI andintellectual property to
preserve combination of AI andintellectual property to
preserve, protect and promoteyour association's unique wisdom
, essence and identity in waysthat are sustainable for many

(05:34):
years to come.
But to get there, we have tostart with a recognition of the
role that AI is playing today.
As Mallory said, I wrote a bookabout AI about 15 years ago,
when it didn't have thewidespread impact on such a wide
swath of the world as it is now.

(05:54):
I did just a quick Googlesearch for what is AI radically
changing?
And this is just a few of theresults.
You can do the same.
Ai will radically change theapproach to dating in apps.
Ai is radically changing thepractice of law.
I better worry.
Ai is already radicallychanging video games, and on and

(06:16):
on and on.
Pick any topic, any field, anyjob, any industry, any type of
association, and you'll findpeople concerned or excited or
both about how AI is radicallychanging it.
Yes, there's some hype involvedin that.
There's a lot of parties whohave an interest in exaggerating

(06:40):
the degree to which AI isradically changing things.
But there is a real grain morethan a grain of truth in this.
It's quite real and when youhear that, if you imagine and
think about how AI is alreadychanging or has a potential to

(07:02):
change what you do in your work,in your associations, I'm sure
you've already been experiencingit, maybe you've already been
leveraging it, maybe you'reconcerned about it, maybe you're
exploring what does that bringup for you?
I'm going to talk about this asthe AI fight flight freeze

(07:23):
response.
You all are familiar with thefight or flight response.
Sometimes it's AI fight flightfreeze response.
You all are familiar with thefight or flight response.
Sometimes it's called fightflight or freeze.
I've even heard it go so far asto be called fight flight,
freeze, faint or fake.
Ask yourself what's yournatural reaction to a threat?
Right, these are naturalphysiological reactions that are

(07:45):
built into us from evolution inresponse to what we perceive as
a threat.
I don't know, maybe some of youknow that your natural instinct
is to fight when you face athreat.
That is, some people arenatural fighters.
In the context of AI, what is anexample of a fight response?
It would be to say we are notgoing to change in the face of

(08:08):
AI.
That's a fight response.
We are going to keep doingthings the way we've always been
doing them and AI is not goingto affect that.
We're not going to adopt AI.
We're going to do things betterwithout AI, the way we've been
doing.
It still works.
That's an example of a fightresponse and many people and
organizations have been havingthat response Ignore it, don't

(08:41):
even pay attention to it, whichmight result in you doing
something that looks on thesurface equivalent to fighting,
but internally is different.
You just ignore it and maybehope that it'll go away, and
sometimes that does happen withtechnological trends.
Sometimes things come alongthat are hyped up.
People say they're going tochange everything and they don't

(09:04):
, and maybe that's your hope inthe case of AI.
I tend to think it's not.
I think AI is here to stay.
I think it's only going tobecome both more powerful
technologically and moreinfluential on individual roles
and organizational roles andmodels.
But you could flee from it andthen freeze.
This might be the most common,I think, in my experience.

(09:24):
Response to AI is to freeze,which might mean literally
internally freezing, just notbeing able to think about it at
all.

(09:47):
Today is presenting us with somany options, even within a
single product like ChatGPT thateveryone's familiar with.
There are so many ways you canuse it.
There are so many things it cando, and then you look at the
variety of AI products andservices out there, you might
have many different vendorsknocking down your door offering
to provide you with servicesthat are going to save you,

(10:08):
enable you to beat yourcompetitors.
Data, you could say, is anindividual unit, like a fact.
It might be my height, my age,my weight.
It might be your organization'sannual revenue.
It's a fact, isolated from anycontext or meaning, which takes

(10:30):
us to information.
Information builds on data toadd context or meaning which can
help us to understand the data.
Knowledge builds on both dataand information to imbue it with
a higher level of meaning thatcan start answering questions

(10:52):
for us like how or why?
Why am I this tall?
Why am I this weight?
Which might help us to answerquestions like what can I do to
make a change?
Scientific theories, you couldsay, are a form of the next
level, which is knowledge,integrates all of this I'm sorry

(11:22):
relationships, history, evenethics, to enable us to make
decisions that are wider ranging, that take into account our
unique personality, identity onan individual level.
In the case of an association,that might be your association's

(11:46):
unique identity, the thing thatsets it apart from other
associations.
If we look at what are calledwisdom traditions in the world,
there are many of them that,whether they be religious,
cultural, even in business, thatwere started inspired by a

(12:07):
single individual and thatperson's unique philosophy,
their way of approaching life orwork, or a certain way of
approaching problems of aparticular constituency,
particular constituency, andthat person had such a unique

(12:28):
essence and approach that itinspired an entire way of doing
things and that's sometimescaptured in a wisdom tradition.
We're living in a world where Iwould put a pretty bright line
just around two years ago, whenChatGPT was first launched.
Of course, the technologyexisted before then, but that is
what brought essentially thepower of today's AI into the

(12:50):
public realm, made it availableto anyone with internet access,
essentially for free, and what?
Something like ChatGPT?
The reason I say it's startingto commoditize not just
information but but knowledge isthat when you ask it a question
, it does much more than justspit back something that's

(13:12):
stored in a database.
You can ask it to brainstormsolutions to problems.
Right, that's the kind of thingwhich normally, if you're
asking a legal question beforechat GPT, even if you had access
to the internet, you would needto go to a legal professional
to get that kind of knowledge.

(13:33):
Knowledge meaning applyinginformation to solve a problem,
to develop a strategy, to takean action.
Maybe many of you are inassociations where your strategy
for creating, providing valuehas lied primarily in your

(13:57):
knowledge your ability to takeeven publicly available
information and help people andother organizations answer
questions, solve problems,develop strategies, implement
strategies.
That's where knowledge lies,beyond just information.
I suspect many of you havefully adopted the premise that

(14:26):
information is not the levelwhere you can be a gatekeeper
anymore and therefore you'regoing to rely on knowledge.
And that is where today's AI issignificantly challenging that
premise that we can remaingatekeepers to knowledge.

(14:47):
Today's AI is still at a fairlylow level there.
But if you deny that that'swhat it's doing, then I would
argue you're back on thatprevious slide in the fight,
flight or freeze mode.
Authorship is what copyrightprotects.
That's one of the key forms ofintellectual property.

(15:08):
Protects works of authorshipLike this slideshow, text,
images, video, music in thecontext of companies and
associations, websites, anycontent on there.
Internally, documentation,process documentation Any kind

(15:28):
of text, video, audio, sourcecode and software all
protectable by copyright.
In the legal world, we callthem works of authorship,
invention.
This is the world that I livein most of the time that's
patent.
Another core form ofintellectual property protects
machines, processes implementedin software, algorithms,

(15:51):
chemicals, even DNA, new formsof biological material all
protectable by patent, whichprotects inventions.
What I'm labeling here asbranding is what's protected by
trademark law that protects yourassociation's unique brand
identity.
Extremely valuable, it's whatenables you to stop others from

(16:21):
promoting their products orservices, or even information,
under a logo or a name that'sconfusingly similar with yours
and that attempts to free rideon your association's goodwill
that you've put so much time andenergy into developing.
What I'm labeling here asconfidentiality is what's
protected by trade secret law.
Trade secrets are reallymisunderstood form of

(16:43):
intellectual property law,because you don't apply to the
government for trade secretprotection like you do for a
trademark registration or apatent.
Trade secret, though, isextremely valuable, I suspect,
within many of your associationsto customer lists.
It's your know-how, it's yourunique way of doing things.
It's anything that'sconfidential, that's not

(17:06):
generally known to the public orto your competitors, that gives
you a competitive advantage.
For many organizations and evenprivate companies, trade secret
is the most valuable form ofintellectual property that they
have property that they have.
The thing that ties both ofthose together AI and
intellectual property is that AIis moving up that pyramid.

(17:36):
It's enabling us to capture andsynthesize information into
knowledge at a higher level.
As a patent attorney, I havealways worked with clients when
they develop a new piece ofsoftware to try to generalize,
abstract from the specificmethod they've created
protection for you that is at ashigh a level as possible.
So this is the way in which Isee AI and intellectual property

(18:14):
as being really consistent withand mutually supporting of each
other that you can now use AIto encapsulate your knowledge
and then you can useintellectual property to protect
that knowledge using the formsthat I've talked about, and even
to protect the wisdom of yourorganization, to preserve it and

(18:39):
to promote it at a much widerscale than has ever been
possible before.

Speaker 3 (18:52):
Our next keynote speaker is Dr Gio Altamirano
Rayo.
Dr Rayo is the Chief DataScientist and Responsible AI
Official at the US Department ofState's Office of Management
Strategy and Solutions Centerfor Analytics.
Since serving in this rolesince June 2023, dr Rayo has
spearheaded numerous initiativesin artificial intelligence and
data science, including thedevelopment of the Enterprise AI
Strategy, a strategic vision tomodernize the department's
approach to AI policies andpractices.

(19:14):
In this keynote, she sharesinsights on the department's
journey in implementingresponsible AI across its
diverse portfolio of globalmissions.
Since the release of itsenterprise AI strategy in
November of 2023, the StateDepartment has been a leader in
the federal government on AI,rapidly building and deploying
tools and policies to guide thenext generation of diplomacy.

(19:35):
In this keynote, she highlightsways the department is using AI
to enhance operationalefficiency and strengthen
America's Decision Advantage.
Enjoy this excerpt.

Speaker 5 (19:47):
I'm here to talk about the Center for Analytics
at the Department of State, andthis is within an office called
Management, strategy andSolutions, and I just want to
give a huge shout out to one ofmy biggest fans, my boss, danny
Stoyan.
He's over there and one of thereasons why we have actually
something to talk about today isbecause he's been a great

(20:08):
champion of responsible AI.
I'm the responsible AI officialof the State Department, so I
take ethics operationalizationseriously, and I also wanted to
say that we actually do readthese very long EOs, these very
long OMB memos, everything thathas to do with what the

(20:30):
standards are for ethics.
We ingest it and we really takeit seriously.
So what is AI?
People have said that AI is likeup in the sea now, because Chai
GPT landed and democratized AI.
Ai is everything from a linearregression model to a machine

(20:51):
learning model, to a naturallanguage processing model All of
these fancy words.
Well, we have an executiveorder, and that's executive
order 14110, on safe, secure andtrustworthy AI.
That tells us what we have toconsider at AI and from this
definition, what the takeaway isis that AI is any machine-based
system that can give a set ofrecommendations or labeling and

(21:15):
the important part is that therehas to be like a stochastic
process involved so that it'snot RPA.
That's the key thing.
If it's just a computer notdoing anything different from
what we as humans feed it to do,that's RPA, that's not AI.
We focus on risk management ofAI and, of course, we have to do

(21:38):
things well to do good by ourworkforce, by our people.
So in this slide I want to giveyou a little bit of an overview
of what we've been up to in thepast year and a half, and it's
been a whirlwind year.
It's been absolutely fantastic.
Back in June, my leader, thechief data and artificial

(22:03):
intelligence officer, wasappointed, and in October 23,
the EO that I just mentionedlanded, which basically says
that we have to seize the powerof AI.
So don't be afraid of it, butdo it wisely.
So take measured risks and makesure that you know what you're
getting yourself into and have aplan to mitigate those risks

(22:27):
when they arise.
Right at the heels of that EO,we had been working on this
enterprise AI strategy so thatwe were able to meet the moment,
and we did that.
I remember that the EO landedlike on October the 30th, and
then our secretary, thesecretary of state, signed the
enterprise AI strategy, like thenext week.

(22:49):
So we're literally at the heelsof EO 14110.
That's a huge hallmark.
After the EO came OMBM 2410,which is basically what tells us
how it is that we have toconsider risks and manage those
risks.
I know that you know we'regetting into these uncharted
waters, but we have to have aplan if something arises and

(23:11):
then we take that seriously.
So at the end of, basically,june 2024, at the end of the
summer, danny Stoyan, matthewGravis, who's our chief data and
artificial intelligence officer, kelly Fletchers, who's our CIO
they all sat together with thesecretary of state and the
secretary of state himself saidjust give it a shot, just try it

(23:35):
out and nerd out.
So he was incentivizing ourworkforce to be able to leverage
, like the EO said, leverage thepower of AI while mitigating
the risks.
So again, this is a slide.
The takeaway for this slide isbasically that we take
responsible AI seriously.
We're reading all of thesethings, we're making sure that
we understand what it is andwhat it isn't.

(23:56):
I have tons of nerdycredentials so I can actually
speak that and I can translatethat.
And we take the NIST AI RiskManagement Framework, the
National Institute of Standardsand Technologies Framework,
seriously, and within theenterprise AI strategy, we
bathed in a section onresponsible AI.

(24:18):
So that strategy that I wastalking to you about.
It has four goals and I have alittle mantra for that.
The first goal is get the techright, because if we don't get
the tech right, we can'tactually serve as our workforce.
The second thing is make surethat we're holding our workforce
hand so that they can actuallyuse the tech.
So get the culture right.

(24:39):
The third thing that's where Icome in, that's where all the
nerdiness comes in.
The third thing is apply AIresponsibly.
So get the ethics right, makesure that you understand what
you're doing and make sure thatyou have a risk management plan
in place if something goes awry.
And then the fourth thing isinnovate or do smart things.
Do things that people reallywant you to do, not do things

(25:01):
that you want to do onlyyourself.
Now, by the way, we didn't dothis, like at MSS, ourselves,
together just, you know, all ofus together in a room, dark room
, with no windows.
This enterprise strategy was awhole of the department effort
and there are over 25 leadersacross the department actually
hashed it out and when it wascleared cleared means that

(25:23):
everybody has to read it andaccept what it says.
It was cleared by over 55bureaus, so absolutely everyone
within the department got achance to say what they wanted
and also got a chance to moldthe enterprise AI strategy so
that it truly reflected thevision or the aspiration of the

(25:44):
department or the aspiration ofthe department in the space of
responsible AI.
Again, this is you're alwaysgoing to see me saying this is
what we're doing and this is howwe're managing risk.
This is how we're doing it.
We know that this is not likesomething that you could just go
wild with.
This slide is meant to say thatwe're aware, we're cognizant, we
understand we've alreadyincorporated that AI can do some

(26:07):
harm.
It could do harm to people,organizations and ecosystems.
However, we do have riskmanagement in place.
We're making sure that weprovide policy to people so they
have clarity about what theycan and cannot do with AI, what
they can and cannot do withpublic-facing tools like GPT or
CLOD or any other public-facingtool, and what they can do once

(26:27):
we provide those capabilitieswithin the sort of system,
infrastructure or the ecosystemwithin our organization.
Again, we are not like comingup or inventing the standards
that we are abiding by.
Standards already exist.
It's the National Institute forStandards and Technology.

(26:47):
We saw the development of thegenerative AI companion resource
.
We understand what it means.
We are absolutely in sync withits vision.
Yes, we want to do things thatare cool but at the same time,
want to make sure that we have arisk management in place.
So we ended up creating, forthe department as a whole, a

(27:09):
generative AI risk managementplan, and I could talk for hours
on about the risk managementplan and all of the details and
everything.
So if you want to talk, if youwant to nerd out, let me know
I'm happy to do that.
In addition to that, we alsowant to see what see, not just
what our office is doing, whatDirector Stolian's office is
doing, but, in addition to that,what everyone else is doing at

(27:30):
the department.
This is a requirement.
The AI inventory is arequirement that comes from the
White House, but it's also smartto know what other people are
doing within your department, sothat you can learn from each
other or encourage each other orsee if you have similar
interest and pool resources.
You bring something beautiful,more complete, instead of what

(27:55):
you were initially thinking.
So I do this task and we'reliterally in the middle of it
right now.
The AI inventory fun, fun factin December 17,.
We will have our AI use caseinventory live on stategov slash
AI.
So if you guys are interestedabout what else is going on,
what else is still not tellingus, don't worry about it, it's
going to be there.

(28:15):
It's at stategov slash AI.
That's in December 17.
And so that everybody is likeknows what's happening and
there's transparency over whatwe're doing, what the plans are,
what risk management is, whatto do in the event that you, you
know, see something.

(28:37):
We have a resource that's forthe workforce within the State
Department.
That's called AIstate, theworkforce within the State
Department.
That's called AIState.
So absolutely everyone in theState Department can go to
AIState and learn about thepolicies, what we're doing, what
the inventory is, how to learnright, how to do AI, how to use
it.
This is a one-stop shop foreverything related to AI.

(29:04):
So I was talking about all ofthe things that we do in risk
management.
We're also doing pretty coolthings in terms of innovation.
We have something called theDCT data collection tool, which
is basically a researchassistant right now.
We've calculated that it savesabout 16,000 hours to be able to
categorize primary sources forreport writing, which is a huge

(29:27):
task in the department.
We also have another toolthat's called North Star.
This tool ingests like amillion articles, like news
articles a day and summarizesthose things in an instant.
These are public facing newsarticles and it actually helps
the division of the StateDepartment that does public
diplomacy.
And then, finally, our latestinnovation and the thing that

(29:52):
we're really psyched and excitedabout, something that we got
TMF funding for.
Tmf funding is a pocket of goldthat comes from the GSA
Technology Modernization Fund.
We got funding for this.
We applied and we got fundingfor this.
It's basically we call itStageHat.
Stagehat is the first everdepartment-wide SBU means

(30:18):
sensitive or declassifiedinformation chatbot available
for the entire department, sothis department can process
information in a safe and securemanner.
It has all of the guardrailsalready in place embedded in it
within the tools of the botitself, so we're mitigating the
risk of data breaches ormitigating the risks of some of

(30:45):
the harmful aspect of AI that Imentioned before.
So it does a lot of things.
It does summarization,translation, drafting and
brainstorming.
That thing is what I use.
I use State Chat forbrainstorming.
I always want to know feedback.
I always want to receivefeedback so that I'm improving.
It's hard to know feedback.
I always want to receivefeedback so that I'm improving.

(31:05):
It's hard to get feedback.
Well, sometimes I'm asking StayChat, okay, how would you do?
How would you read these words?
Would you read it differentlyfor me?
And lo and behold, stay Chat isgood for coming up with new
ideas or actually seeing whatyour blind spots are, and it's
actually a very good sort ofinterlocutor in some ways.

Speaker 3 (31:29):
The next keynote speaker we have lined up for day
two was Dr Parham Dadia, andyou will realize shortly, as I
introduce Dr Dadia, why he is alittle bit different from all
the other keynote speakers.
He is an MD, a curious internalmedicine doctor and a
passionate integrative medicinepractitioner.
Parham's career was rooted inhis 10 years at Johns Hopkins as

(31:49):
a clinician, researcher andteacher.
Thereafter he expanded his workover 12 years at Canyon Ranch
as an integrative medicinedoctor.
He was the co-director of theexecutive health program,
director of sleep Medicine andArchitect of the Weight Loss
Program.
He has founded Moveo Health,which combines and extends all
the work he has done in hiscareer.

(32:11):
So what is Dr Dadia going totalk about at Digital Now 2024?
Well, in his keynote he talksabout separating health from
hype and fact from fiction.
It can feel as though there isa never-ending list of things
that we must do to be healthy.
Dr Jadia says that this isneither correct nor helpful.
Instead, we must move into theconcept of high-yield health,

(32:36):
which focuses on a few thingsdone well.
The idea behind this keynotewas really that in times of
disruptive change, technologicalchange, leaders need to take
care of themselves first andforemost and also take care of
their teams.
So that is why we brought in DrDadia.

Speaker 6 (32:54):
Enjoy this excerpt from his keynote the intention
of this talk is really simpleallowing you to live the life
that you've always wanted to bea part of, and therefore, not to
make it an idea, but put itinto action.
So when we call this talk highyield health, the true
opportunity in these exponentialtimes isn't about how many more
things can you get done in aday, but what are those few

(33:16):
things that have been shown timeand time again.
What are those thingsproverbially to put on your
dashboard, to be curious about,to lean into?
So is this brand new?
No, this isn't a brand new talkat all.
You guys have seen this before.
Right, it's grandma's medicine.
Let's think about it.
What did grandma tell us to do?
Grandma told us to do what?
Basically, honor the fact thatshe wanted to eat your veggies.

(33:40):
Yes, we're going to get intonutrition.
We are going to talk abouthonoring, getting out and play.
What is that of movement andmovement science?
And and get your sleep right.
This isn't brand new, butnevertheless, this is a
conversation that is nowsupported by modern science and
a few things done.
Well, so, with all of this, aswe could take a look at it, when

(34:02):
I often get asked to talk abouthealth, I'm really puzzled
Because most of the time, whatdoes it mean?
When I go to a corporate eventor to any group, it becomes a
checklist, it becomes static, itbecomes a noun, it becomes
something incredibly forgettableand therefore not helpful
whatsoever.
What we want to do instead isreally talk about what brought

(34:22):
you to this meeting.
What brings you to the life youwant to be living, is this With
everything being said, we wantto talk about energy, and the
whole conversation in these nextset of minutes is how you can
curate that being able to peakwhen you want to, how you can
therefore perform and how youcan have that clarity.
What we want to do is buildthis into our daily lives.

(34:43):
So when I used to teach inBaltimore, I'd ask the students
unknowingly, thoroughly,thoroughly frustrating them to
define a simple word.
What does it mean to be healthy?
What is health?
It was hysterical.
These folks were not just typeA, they were, like me, type AAA.
They were really grumpy.
They wanted to try to be ableto find this definition.

(35:03):
What I would eventually do ispull out the dictionary.
I wish I saved the copy.
I'd open up the dictionary.
You know what it said Not sick.
How ridiculous right we havedefined in medicine.
Okay, what do I do?
What am I trained?
I'm trained to do what?
To make a diagnosis?
What's your sign?
What's your symptom?
What's your diagnosis?

(35:24):
Am I trained in health?
My friends, it's not correct todo a default discussion.
So what I would wish for youand I to know is that,
thankfully, I'm not the firstperson to be thinking about it,
nor anybody here.
In 1948, very austere the WorldHealth Organization, over 70
years ago, brought peopletogether Brilliant.

(35:46):
Take a look at what they shared.
They noted this to be thedefinition of health a state of
complete physical, mental andsocial well-being and and not
merely the absence of disease orinfirmity.
Let me say it another way Oneof my big roles back in the
hospital was a hospitalist.
That means I worked on the ward.

(36:08):
What was I called for?
The emergency department,literally 10 times an hour,
would call me about somebody whohad chest pain.
If you go to a hospital withchest pain, what happens?
You ain't going homeimmediately.
Over the next 12 to 24 hours,they're going to figure out did
you, did you not have the bigone, the heart attack?

(36:31):
What do we know?
97% of the time?
What do we tell people?
Yet again, good news you didn'thave a heart attack.
You're fine Sign here you cango.
But again, we want to definethis proactively on the physical
, the mental.
Anytime I get an opportunity Ialso want to talk about that of
emotional and spiritual.
We want to bring all thesetogether for the life we want to
be living.
So my first fellowship afterdoing internal medicine, meaning

(36:54):
adult medicine, was this workin something called gerontology,
the study of aging.
So I steal this from the groupthat's been going on for 70
years doing research and acohort in downtown Baltimore,
the Baltimore LongitudinousStudy on Aging, the BLSA.
So take a look at it.
They define it on the physicallevel right, because it's a lot
easier to do that than themental, emotional, spiritual.

(37:15):
So what they do is they take alook at our organs and they look
about what happens over time,in other words, how well is your
heart and how does it look likeat over time.
So in general conversationsthis is like good old George
telling jokes to a hundred.
All right, yeah, you knowfamously that he smoked cigars,
but the guy was a fitnessfanatic and, by the way, he had
come to Canyon Ranch and I knowa bunch of people knew George.

(37:37):
Here's something really cool.
He traveled with a massagetherapist.
He had a massage every singleday, just throwing it out there,
right.
A few fun things to be able tounderstand how we want to bring
things into our lives.
What we want to do is be likeGeorge, telling great jokes,
being proactive for this greenline, very little change from
that optimal, that upper dashedline.
What we do not want to sign upfor is going down to this red

(38:00):
curve, and it's not that youslope down suddenly excuse me,
slowly, but tends to be morequickly.
So what we do know is that thiscan be those disease illnesses,
but also what many of youexperience and more or less are
seeing about that of burnout.
What we want to do as much asyou can fall onto the red line,
you can also drift back up.
In other words, we know,classically, the way we eat, the

(38:23):
way we move, the way we sleepand the way we honor stress can
take us down to the red or moveus back up to the green.
Thus the part of what we wantto get into in the next bit of
time.
So what I want you to know is,every single night when you
sleep, here it is.
You had a good workout, feelinga few muscles you haven't felt
in a while.
You want to get the fullbenefit, get your sleep.
That makes growth hormone,testosterone, proteins that

(38:46):
repair the body.
The Olympics does itbeautifully.
They'll tell you the secret tosome of these top performers
getting their sleep.
Lebron James, age 40, I thinkhis 22nd year in the NBA he has
a sleep coach.
He sleeps on the order of eightto 10 hours during the season.
I want you and I to appreciateit feels like a leftover time.

(39:06):
In a few moments you're goingto be like uh-uh.
This is incredibly productiveto help sleep the body, the mind
, everything.
But, ladies and gentlemen, ifwe're not here to talk about joy
, why are we here?
Really bored, you just needsomething to fill in the time
before lunch.
Without joy, all the things wetalk about are just things
they're not connecting to thatof the opportunities we want to

(39:28):
be a part of.
Let me say it another wayWithout joy, what do you call
food If you don't like your food?
What do you call that A diet?
How long do diets last?
They don't.
On a diet, 1% continues out tosix months.
Awful return on the investmentIf you don't enjoy your workout.
What do we call that?
A boot camp?

(39:50):
No, soldier is permanently putin boot camp.
If you don't have joy, can youget your head on the pillow, get
to sleep, stay asleep and wakeup feeling refreshed?
So we will bring all of this.
Now here's something else Iwant you and I to think about.
Many people coming to a sleeptalk are going to get worse
sleep, so let me be reallycareful not to mess you up.

(40:10):
What do I mean by that is thatevery single night I want you to
know it's natural every 90 to120 minutes to have a brief wake
up.
So tonight, when you roll over,you're like, oh gosh, I'm never
going to be healthy.
This is terrible.
What can I do?
I want you to take a deepbreath and to center yourself
and really understand thathappens to everyone.

(40:31):
Put your head back down on thepillow.
What I want to do as I finishthis up is to understand that
the first half of the nightyou're reviewing facts.
The second half of the night,you're making creative thoughts.
Think about what you're doingevery single night when you're
sleeping Physical repair,emotional clearing that
opportunity to bring in factsand to more or less clear that

(40:52):
opportunity of negative and becreative.
Who here wants to donate theirsleep any longer?
Now, I know I'm out of time.
Can I get 90 seconds?
Two minutes?
All right, 90.
Okay, so she's great.
What I want you to know this isall great, it's easy to put up
on a slide.
You'll have my contactinformation.

(41:15):
Iq is not the challenge here.
What I want us to do is tounderstand where is our IQ most
effective.
If you're like most humans, wehave to understand the brain.
We have neuroplasticity.
We get into patterns.
What's the biggest pattern?
We get into the negative.
What I want you to know is thisis from my dear, dear buddy, my

(41:36):
mindfulness teacher.
He's only taken one gift fromme and this is it.
You may or may not be able tosee back there.
This is a snow globe and I'mshaking it up, but I want you to
see.
This is our daily lives Emails,phone calls, should-haves,
could-haves, what-if, what-if.
Am I going to understand allthe policy related to AI, all of

(41:58):
that stuff.
But what I want you to do notimmediate, but if you can
somehow get a good look at thiswhat's starting to happen, give
it a moment and over thesemoments when you are able to get
to that stillness, what do youfind?
It starts to clear.

(42:19):
And now what happens?
Now I can see more clearly.
This is the analogy of whatthey call mindfulness.
Every tradition of prayer,worship, of stress reduction
taps into getting to thatclarity.
What I want you to know is thisthis conversation of putting

(42:40):
the snow globe down is somethingwe must practice.
What you want to know is we havea negative bias.
If I'm petting a bunny rabbitand someone says saber-toothed
tiger, I'm going to look.
Someone goes, oh, just bepositive, check out the bunny,
be happy.
Really, you want to make sureof what's wrong.
What you'd want to know is thestress curve, low stress, red

(43:05):
hot, angry, foaming at the mouth.
How effective?
When I'm red, hot, foaming atthe mouth, my insight is down
and I'm reactive.
I'm going to say and do thingsI regret and I'm not going to be
very effective.
When I'm down here, I can bringin the information, I can
process it by insights higherand I can respond.
So what I want you all toappreciate is some of you just

(43:26):
did it with me, you took abreath.
Some of you will wiggle yourtoes and just really be present.
Some of you will say a poem,prayer, hymn, throughout the day
, five times a day.
I want you to spend a minutebreathing.

Speaker 3 (43:40):
Our next keynote speaker from day two was Neil
Hoyne, another name that youmight recognize because he's
been on this podcast before.
Neil Hoyne is Google's chiefstrategist and he's had the
privilege to lead more than2,500 engagements with the
world's biggest advertisers.
His efforts have helped thesecompanies acquire millions of
customers, improve conversionrates by more than 400% and

(44:03):
generate billions in incrementalrevenue.
In this keynote, the CEO ofRasaio, which is part of our
family of companies, ericMcDonald, interviews Neil and
through their dialogue you'lldiscover fresh perspectives on
the key drivers of exponentialgrowth transforming member
relationships into sustainablecompetitive advantages,
leveraging technologicaldisruption and building the

(44:26):
organizational culture neededfor breakthrough success.
Enjoy this conversation withNeil Hoyne.

Speaker 7 (44:32):
Hello everyone.

Speaker 1 (44:35):
I like that introduction.
I should have done a moremodest introduction.
That's why we found this guyoutside and he knows something
about data and AI.
It's all downhill from here.

Speaker 7 (44:45):
Go ahead.
I think it's about to be uphill.
I wouldn't worry about that,Neil.
So thank you everyone forjoining us.
I was thinking about Amit'skeynote yesterday and we were
looking at his graph showing howmuch computing power changes,
and when you're at the brink ofbig change, it kind of can feel
slow at the beginning, and thenexponential growth really takes

(45:08):
off, and what I would like to dotoday is talk about ways where
we can unlock value forassociations so we can try to
start to drive that exponentialgrowth, and one of the tools
that we have to do that is AI.
So that's where I want to startand I'm going to leave it very

(45:28):
open for you.
So what's going on with AI?

Speaker 1 (45:32):
So if you go through any airport, you'll see
everything is AI.
I flew out of San Franciscowhere it seems that every
advertisement has been everytraditional company but they now
say they're doing something AIrelated.
This is the world we're inright Technical change.
I'll give you my best sense asto what I see and these are just
my personal opinions on it.

(45:53):
The first stage of anytechnology, unfortunately, is
you get into this cycle ofmassive hype of what's going to
happen.
And just for comparison, if youwere to look at Citi's report,
you can look at Citi, you canlook at McKinsey Citi forecasts
that by 2030, so about fiveyears from now we're looking at

(46:14):
AI, generative AI at least beinga $1 trillion opportunity which
we all think like that is hugeand you think about that and how
disruptive and how much money.
That is opportunity of ourlifetimes, unless you go back to

(46:38):
Citi's projections two yearsago where they actually had a $9
trillion opportunity called themetaverse, and now nobody even
talks about it.
We don't do keynote sessions onthe metaverse and so we go
through these cycles veryquickly.
We're like, yes, this will takeover and this will do
everything where that metaverseI'm not sure if anybody here
bought.
Nfts are familiar with it, buteffectively people would buy for

(47:01):
people and buy things like notphysical goods, but pictures
will not actually even pictures.
You just get a little thingthat says you own this picture.
Jack Dorsey's first tweet, Ithink, sold for 2.9 million
dollars 2.9 million dollars.
And then the gentleman thatpurchased it tried to sell it.

(47:22):
He put it up for 48 milliondollars, I think the bidding
capped off around 250, 260dollars and so quickly
everyone's like, well, we're notdoing the metaverse thing,
that's not going to work.
And then all of a sudden peopleare like, ah, ai, and we follow
those same things where peopleget excited about growth and
opportunities, and what thatleads to is confusion in the

(47:45):
market to say what do I do andhow do I adjust?
Because nobody wants to be leftbehind through innovative
technology and disruption.
And none of this is a mandateagainst AI, as much as it is a
reflection that a lot ofcompanies are saying they're
doing things with AI that Iquestion if it's really real.

(48:06):
So, in a moment of pure honesty,data is really hard and even I
don't like it at times.
We love data.
We hold data in very highesteem.
I don't like it at times.
We love data.
We hold data in very highesteem.
This allows us to make betterdecisions.
The usage of data is sub 5% inmost organizations.
That's what it is.
You have 100 decisions.
Data is going to come in inless than five of them, and so

(48:27):
we acknowledge, first of all,that data is hard.
Part of the problem that youuncover with data is how it's
used, and I'll kind of give youan example of this.
Is a large well, it's a Fortune100 company who you would all
know, but I'm not going to namethem because I don't like
shaming these parties, but theyspent, over three years, $60
million organizing, collectingall their data.
And it was a beautiful planvery expensive consultancy, a

(48:50):
lot of new tech.
And I asked their CMO, I said,great, once the system's in
place, what are you going to dowith it?
And she was like well, we'regoing to hire a whole bunch of
data scientists.
I said, okay, good, what arethe data scientists going to do?
And she's like well, they'regoing to do data science to the
data.
I was like, all right, soyou're hiring new people.
Day one, here's a whole bunchof data.

(49:12):
Go do data science and findvalue in this.
This is not uncommon in a lot oforganizations.
It just doesn't happen incandid conversations.
It happens over months andyears, and here's what happens.
You have a whole bunch ofreally talented data scientists
and they get all this data andthey sit there and they come to
some conclusions and then theyhand them over to people in like

(49:32):
marketing and sales that haveto use it.
But it's divorced from thereality.
So the salespeople look at itand they say what do I do with
all this data you gave me?
And nothing happens.
And then the data people goback to their corner of the
office and are like all thosesalespeople they don't use data
at all.
And all the salespeople arelike the data people are really
smart, but we don't know whatthey're saying, so I can't use

(49:52):
any of it.
And then everyone getsfrustrated that they're not a
data-driven organization.
Instead of data being the firststep in the process, I like to
think the first step on anycompany's transformation is what
the hypothesis is, what theidea is.
If we do this for our members,we expect them to do that.

(50:12):
Members are asking us for thisfunctionality, this service,
this offering.
What's great is that thesehypotheses are everywhere in
your organizations, they're fromyour members, they're from your
partners, they're fromtechnology vendors telling you
these are different things youcould do.
Now, on this first step, wherethings tend to go astray is that

(50:37):
we jump not to the data toprove or disprove.
We jump to how we feel.
And so we often see this atconferences, where someone comes
up and they're like I think youshould do this, you get this
guy, I think you should dolifetime value, and some of you
may be like, yes, we'll do that,and others will say no, we
won't.
The goal of this first stage isyou don't judge at all, you
simply say it's an idea, this isan idea that somebody gave me.

(50:57):
Why do we want to lose it?
It's not.
We have to jump throughorganizations, we have to narrow
it down.
These are our three or fiveideas.
I encourage you capture everyidea, every hypothesis you can
from this conference, from theconversations you have with each
other.
Put it in.
I love spreadsheets.
Put it in a spreadsheet andcolumn, get hundreds of ideas.
Now the next question you askand this is where it goes to it

(51:18):
is what data do we have?
But now here's what we did.
We didn't say here's a wholebunch of data makes sense out of
it.
We said here's a whole bunch ofhypotheses that are worthwhile.
Do we have any data to supportit or to disprove it?
Nobody comes into the officeand be like hey, neil, what are
you doing today?
I'm going to go fail atsomething?
No, we don't.

(51:39):
And if you go to any leader andbe like so what's the
likelihood that this is going towork?
50-50.
That's not getting through.
Let me tell you what I want toavoid.
There was an organization I metone time that gets on stage at
these keynotes and it's like andwe are a test and data-driven
culture, like, wow.
And the CEO's like and I comeup with an idea and it gets

(52:00):
implemented right away.
Wow, that's incredible.
And so naturally, you want togo meet these people.
You want to learn what they'redoing, what's their special
sauce?
So beers.
Afterwards I meet a few of theiranalysts and I said your CEO is
on stage running tests.
I was like amazing.
I was like how did you get thatto work?
And they're like oh well,they're like first of all, it's

(52:23):
not three to four days to run atest, so how long does it take?
They're like eight to 12 monthsto run a test.
I said eight to 12 months.
And I was like, walk me throughit.
And they're like well, first Ihave an idea, good.
And they're like now I need toconvince my manager, and then
their manager, and then theirmanager, and then I need to find
budget, and then I need toconvince engineering that it

(52:45):
needs to be part of their sprintlegal, to sign off on a
creative, to build an asset.
And then, after that time,maybe I get my test running.
And I said, okay, but you're atest-driven culture, right?
And they're like well, here'sthe secret.
They said, if any of our testsfail, we're in a bad spot,
because now, all of a sudden,the CEO, cmo, are looking and
saying you took $50,000 out ofour budget, which we know how we

(53:09):
were going to spend itotherwise, and you took it on
something that didn't work.

Speaker 7 (53:17):
We're never giving you budget again.
We were talking earlier aboutinvesting in the customer,
investing in the member, and youwere talking to me about how
you might invest differently forsomeone who is new, a new
member, versus someone who'sbeen around for a while.
I just was wondering if youcould talk about that, my
actions.

Speaker 1 (53:35):
What do we do with in a few minutes?
What do you do with customers?
I group customer activitiesinto three simplified perhaps
overly simplified buckets.
You can acquire and meet newpeople, you can develop the
relationships that you have, oryou can keep people around
because they're going to leave.
90% of my time and my money isspent on acquiring people, but
acquiring the right people.

(53:55):
You acquire great members earlyon.
This is where that behavioralsegmentation people that are
aligned with your organization,its values, its mission will buy
lots of stuff.
They're going to be great andthe time and attention you need
to give them should be less thanthose other people you try to
fix.
Now, on the development side,this is actually where some
organizations can go astray, andI use a simple metaphor just

(54:17):
because it works and I likepersonal relationships.
It's the equivalent of one ofyour friends not any of you, but
one of your friends coming upto you and saying I met the
perfect person.
If only I can change them first.
Now you know what's going tohappen.
You'll be like no, no, no, no.
That's going to lead toheartbreak, and it often does.
The same thing happens when wetry to develop customers.

(54:38):
Oftentimes companies will goout and say we just want to
acquire them and once they seehow great we are and how well we
treat them, then they'll bewith us forever.
Yes, but it's really expensiveand it's really time consuming
and it leads to a lot ofheartbreak.
I prefer to meet great peoplefirst, develop them where I can.
How do you develop If you launchnew services, new offerings

(55:01):
that they're not aware of?
If you have a moment or youhave their time and attention to
bring them in closer to theorganization, yes, the classic
McDonald's upsell.
Would you like fries with that?
It fits into the same model.
Oh well, I already want asandwich.
This works.
That's a development stage.
But compared to acquisition, if90% of my time is spent on
acquisition, only about 1% of mytime is spent on development,

(55:24):
just from an ROI perspective,acquisition is infinitely better
.
The last 9% of your counting ison retention.
Is somebody not doing what Ithought they would do?
Now, how does this actuallylook like in the math when you
do this lifetime value?
Well, I said cashflow is right.
Here's how much we expect aNeil to give us this year.
Neil's behind what happened.

(55:45):
How do we change it?
And that's our retention bucket, where you simply want to have
some measurement put it on yourdashboard, where you know that
somebody's not behaving in theway that you expect, and then
it's a question for yourorganization.
How do we want to respond?

Speaker 3 (55:59):
Our last keynote speaker from day two was John
Spence, and he was a fantasticperson to wrap up day two,
because he is just a bundle ofenergy on stage.
You will see very shortly.
John Spence is recognized asone of the top business thought
leaders and leadershipdevelopment experts in the world
and was named by the AmericanManagement Association as one of

(56:20):
America's top 50 leaders towatch, along with Sergey Brin
and Larry Page of Google andJeff Bezos of Amazon.
He has been a guest lecturer atmore than 90 colleges and
universities, including MIT,stanford, cornell and the
Wharton School of Business.
In his keynote session, he'llintroduce his formula for
business excellence, focusing onfour pillars talent, culture,

(56:43):
extreme customer focus anddisciplined execution.
He will help you figure out howto attract and retain top
talent, build a motivatingculture and create stronger
customer relationships.
Figure out how to attract andretain top talent, build a
motivating culture and createstronger customer relationships.

Speaker 8 (57:01):
Enjoy this excerpt from John Spence.
I'm going to look at four majorareas and I'll tell you how
this comes about, but first Iwant to challenge each of you to
think of who your top threecompetitors are in your
organization, your association.
Give them a second.
Who are the top three peoplethat you compete against most
fiercely?
Everybody got a few.
Okay, here's what I wouldsuggest.

(57:24):
This is who you compete against.
You compete against Amazon foranticipating your needs and
speed.
You know you're orderingsomething.
Okay, they recommended this, Igot to get this.
I mean, it's right here onAmazon and you push the button,
it goes ding dong.
How'd they do that?
They're already at the doorwith the damn thing.
By the way, they are alreadystarting to deliver packages

(57:44):
with drones.
This is total stress.
You can be in the backyardcooking hamburgers, like you
guys, for lunch, and run out ofketchup Bing, bing, bing, bing,
bing.
Drone comes in, drops offketchup or barbecue sauce in
your backyard and flies back out.
So some of this, everything Icover today, is happening right
now.

(58:05):
I'm going to talk a little bitabout strategy and it's going to
mix in really well with whatAmit said and some of the other
folks yesterday To be a reallygood strategic thinker.
There are five levels and I'dlike to get up here and be next
to my slide.
At the bottom is solid businessacumen.
If you want to be a goodstrategic thinker, you have to
understand how business works,how to finance it.
It doesn't mean you have to bea CPA, but you have to get the

(58:25):
fundamentals.
How many books business orself-help books, personal
development books do you thinkthe average business person
reads per year?
What?
Two Five Zero, it's 0.5.
It's 0.5.
And Amit challenged you to read15 minutes a day, five days a

(58:48):
week.
If you did that, you'd readwell.
Let me give you the statistics.
If you were to read six books ayear business books or
self-development books you'dread well.
Let me give you the statistics.
If you were to read six books ayear business books or
self-development books, six ayear you're in the top 5% on the
face of the earth forprofessional development.
Personal If you read a dozen ayear, you're in the top one to
3% on the face of the earth forpersonal and professional
development.

(59:08):
If you read 15 minutes a day orthe equivalent thereof podcasts
, blogs, articles, magazines,whatever it might be but if you
were to do the equivalent of 15minutes of research a day.
You would read about 11 books ayear between 8 and 11,
depending on the length of thebook.
That would put you in the top 1to 3% in the world for

(59:29):
professional development.
So if you take nothing awayfrom this talk except for this,
I hope you take some more, trulydo, but take Amit's challenge,
invest in yourself.
They.
You know how many of you haveever read Malcolm Gladwell's
book Outliers?
Anybody remember the numbers?
10 years or 10,000 hours.

(59:50):
Yeah, they say, if you practiceanything and look at it 10
years, 10,000 hours you canbecome among the best in the
world at that.
That's how low the bar is Ifyou look at people who are
world-class at what they do.
The reason is is they seepatterns before other people do.
This is how a great musicianlooks at a sheet of music and
hear the music in their head.

(01:00:11):
This is how a great athlete canyou know I'm not a big football
fan, but drop into the pocketand see all of the you know the
receivers on the field at thesame time and be able to look at
the defense and find thepattern of where they aren't.
This is how chess grandmasterslearn Actually, they learn a
fascinating way.
They start at the end of thegame and learn backwards to the
beginning.

(01:00:31):
What does a winning game looklike Then?
How do I back up?
What's every possible move thatcould get me to that winning
game?
That's why sometimes you'll seethem start a game and then,
after 20 or 30 minutes, justturn a piece over, go there's.
Neither one of us can winbecause they know all the
patterns that would get themthere.
So when you look at people whoare the best at what they do
from a strategic standpoint,from an organizational

(01:00:58):
standpoint, from an expertisestandpoint, they have the
ability to identify patternsfaster than their competition,
which is what createscompetitive advantage.
Am I going at a good speed?
I can go faster.
I always tell this story.
I used to coach a gentleman inVienna and he asked me to come
over and visit with his seniormanagement team.
And I'm there and he got a roomprobably 60 people there.

(01:01:18):
I won't walk to the lectern.
He walks up to the lectern andgoes.
I've spoken to John.
I've asked him to speak slower.
He could not.
You will all have to listenfaster.
So I'll keep it moving at agood pace Then.
So I'll keep it moving at agood pace.
Then you go and get at.
The highest level is strategicinsight.
Yeah, the highest level ofthinking is strategic insight.
I've been studying, I've beenreading, I've been learning.

(01:01:40):
I have a solid base of businessacumen.
I then look at my own personalexperience and combine those two
, looking for patterns.
Once I recognize a pattern, Iget an insight that says here's
where my association can go in,here's where we can get ahead,
here's some new thing in AI, anagent or a chatbot or something
that we can deploy faster thanour competition to gain

(01:02:01):
advantage in the marketplace.
But all of this is uselesswithout disciplined execution.
Ideas are great, but you haveto be able to take those ideas
and put them into action.
So I mentioned just earlierthat I've been spending about 30
years traveling worldwide.
I've had the chance to look atthousands of companies, and what
I do every time I'm there islook for the what Pattern, what

(01:02:24):
are the best companies tend todo over and over, that makes
them so incredibly good, andwhat are the companies that fail
do consistently?
That causes them to go out ofbusiness?
I wrote a book.
Not plugging the book here itis.
Well, I'll take it off, boom.
The reason I put my book up fortwo seconds is it's about
67,000 words.
That's an average 200 page bookis about 67,000 words and after

(01:02:47):
I wrote it I used an algorithmto create a word cloud of the
main ideas in the book.
I used an algorithm to create aword cloud of the main ideas in
the book.
So I put it in there, you know,and pops out this word cloud.
I'm like awesome, this isfantastic.
My entire book on one piece ofpaper.
I'm highly visual.
I'm like this is.
Then I realized I'm not thatsmart so I said I better get
some more information here.
So I reached out to a wholebunch of my friends that are

(01:03:09):
authors Jim Collins, good togreat Tim Sanders, written some
crazy great books.
I've got Drucker and a wholebunch of stuff.
I did a research project severalyears ago asked 10,000 high
potential employees and topcompanies around the world why
do you work where you work?
These are what I call voluntaryemployees.
I'm sure some of you have these.

(01:03:29):
These are people that are sogood that if I quit today, they
could have a job at thecompetition tomorrow.
They're highly talented andthey don't have to come back to
work there because they have to.
They come back because theywant to.
So I asked him why do you workwhere you work?
Here's what they told me.
Number one was fair pay, whichwas 10% above or below what I

(01:03:49):
would make to do the same job atany place else.
As long as you basically getparity on pay, pay comes off the
table as a major motivator.
If pay is the major motivator,as soon as you give someone
money, what do they want?
More money, and it's going tobe a cycle like that.
However, if we get fair pay andput that over here, here are
the things that really driveloyalty.

(01:04:10):
Number one is challenging,meaningful work, purpose-driven
work, what all of you focus on.
You heard Mallory mention thatearly in my career, I was the
CEO of one of the RockefellerFoundations, and the other
organizations I work are myorganization.
Well, let's put it this way wewere driven by an incredible

(01:04:31):
passion to do scientificresearch on fish species, to
help save fish species in theAtlantic and Pacific Ocean.
However, I went to my team andI said we're going to run this
like the best business in theworld.
We're going to steal ideas fromall of the top companies so we
can make as much money as wepossibly can, then we'll put it
all back into scientificresearch to help more people.
So I think there are somefundamentals of leadership stuff

(01:04:55):
that will never change ever.
Honesty never going to go outof style.
There'll never be a time thathonesty is a leader.
Courage and this is also fromanother research study I did
where I asked what are thecharacteristics of a leader that
you would willingly follow.
I made them all C's, so I'lljust give you the Cs.
First one was character Tellthe truth all the time period.

(01:05:16):
Next one was courage thecourage to make tough decisions,
to do big, bold things, butalso the courage to be
vulnerable.
I would call that authentic.
The next one was communicationskills Gotta be able to stand up
and talk, talk about the vision, explain things.
But what they really said inthe research projects is I want
a leader that is asked greatquestions, who's curious and is

(01:05:39):
an intense listener.
The next one was competence.
I just told you about that.
Spend your 15 minutes a day,five days a week, a couple of
years.
You're constantly gettingbetter at what you do and you're
setting an example foreverybody else.
Next one was collaboration Gotto be a great team player.
The next one was compassion.
Especially today, you've got tobe someone who genuinely cares

(01:06:00):
about the people that work foryou.
And then the last one wascontribution.
When you get to a certain levelin your life, in your leadership
journey, it's time for you togive back Member retention
sentiment analysis.
I'm following them to see.
Are they disengaged?
Are they not using our products?
Are they complaining?
That way, I can head it offearly and spot this

(01:06:22):
dissatisfaction before they quit, before they leave.
I can target my using all thisAI.
It's very hyper-personalized todifferent stages in their
career Early stage, mid-stage,late stage.
They need different things,they want different messages,
they attend different things.
So I'm not going to send aninvite to someone brand new in

(01:06:44):
the industry.
That would really be moreappropriate for a senior leader
that's been in 5, 10, 15 years.
They'd be in over their head.
It wouldn't be a fun event forthem, or the reverse.
I don't want old people like meshowing up at some for the young
people and then event-basedcheck-ins, which is after you've
renewed, I get a highlypersonalized email thanking you.
After your anniversary, I get ahighly personalized email based

(01:07:07):
on all this other informationwe have that says thank you for
being part of our associationfor 15 years.
How often do you guys do thisflawlessly that every single
time somebody has an anniversary, you send them a really nice,
highly personalized note.
Ai will do that for you everysingle time you guys are like
this one sponsorship matchingfor immediate revenue generation

(01:07:29):
I can look out and say, okay,I've got this event I'm doing.
Here's the audience it's goingto attract.
Here are the corporations ororganizations I work that would
love to be able to like we haveout here sponsors be in front of
this particular group.
So there's a higher likelihoodI'll get the sponsorship.
Same thing with fundraising.
If I'm trying to create ascholarship fund, I can use AI

(01:07:52):
to scan all of my databases andgo to the handful of people who
have the highest likelihood ofdonating that money and wanting
to get a scholarship fund intheir name.
I can do e-commerceoptimization so I can upsell.
You buy A.
You're probably going to want B, based on your background and
everything I've seen.
You just purchased this.
You're probably going to wantthis other product.
So I'm using AI to upselleverybody.

(01:08:15):
Oh, and I said abandoned cart.
Somebody doesn't buy what youwant them to.
You send them a highlypersonalized hyperlink saying
hey, I noticed you put this inyour cart and you didn't buy it.
Can I help you?
You know what?
What made you drop it?
What can we do to get you tocome back and purchase it?
How can we get back on yourteam?
Last one, I believe, is contentcreation.

(01:08:35):
I have a custom GPT that writesexactly like I do.
I program it.
I put in all my writing.
I create about athree-paragraph prompt of the
kind of writing I want it tocreate.
My social media team uses it todo drafts of things on my
behalf and I just read them,check them, change them a little
bit.
But I wrote one through thereand I gave it to my staff and
they said we didn't know it wasyou.

Speaker 3 (01:08:56):
Everyone, thank you for tuning in to today's episode
.
Hopefully, you got to see alittle sneak peek of what we
offer at Digital Now.
We are gearing up for anincredible Digital Now 2025.
Again, I hope to see you allthere.
If you are interested inattending, head to
digitalnowsidecarai.
I'll see you all next week.

Speaker 2 (01:09:18):
Thanks for tuning into 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

(01:09:41):
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, Leadership, and Innovation: Keynote Highlights from digitalNow 2024 (Day 2) | 65