December 2, 2025 • 27 mins
Most leaders are waiting for a perfect AI strategy. Meanwhile, their teams are already experimenting — just not out in the open. Charlene Li joins me to talk about the real blockers to AI adoption inside organizations, and it’s not the tech. It’s fear, control, and a lack of imagination.
We unpack why chasing ROI misses the point, how cultural mindsets shape our fears, and what it really takes to build AI fluency across your team — starting with yourself. If you’re still stuck in “pilot mode,” this conversation is your wake-up call.
Related Links:
- Join the People Managing People Community
- Subscribe to the newsletter to get our latest articles and podcasts
- Check out this episode’s sponsor: Intuit QuickBooks Payroll
- Connect with Charlene on LinkedIn
- Check out Quantum Networks Group
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
David Rice (00:23):
You are in back-to-back meetings all day.
Your team keeps askingabout AI, the strategy, and
honestly, you're not sure.
You're supposed to have answers.
That's why you gotpromoted, isn't it?
But with AI, everybody'sfiguring it out
at the same time.
And the uncomfortable truthis, if you're not using AI
yourself, you're alreadyfalling behind the people
you're supposed to be leading.
(00:43):
Today's guest on thepodcast is Charlene Li.
She's the founder of QuantumNetworks Group, and she's gonna
tell us why 83% of people inChina's AI is beneficial while
only 39% of Americans do.
More importantly, she'sgonna show you how to break
out of pilot purgatory andactually start building AI
fluency in your organization.
We're gonna cover why your fearof losing control is the real
(01:04):
problem, not the technology,how to deal with shadow AI
usage, the four dimensions ofAI fluency every leader needs to
master, and how one sales leaderuses AI to be in every customer
conversation without attendinga single extra meeting.
I'm David Rice.
This is People Managing People.
And if you've been paralyzedabout what to do with AI, this
(01:26):
episode is your permissionslip to start experimenting.
So let's go.
Welcome to the People ManagingPeople Podcast, the show
where we help leaders keepwork human in the age of AI.
My name is David Rice andI'm your host, as always.
Today I'm joined by Charlene Li.
She is a strategicadvisor and the founder
(01:47):
of Quantum Networks Group.
We're gonna be talkingabout the current state of
how leaders are using AIand what needs to change
for leadership developmentin this new era of work.
Charlene, welcome.
Charlene Li (01:58):
Thank you for having me.
David Rice (01:59):
Yeah, absolutely.
We were talking before this andyou said that many leaders, they
struggle with AI because theyfeel threatened, they're used
to having the answers, right?
Everybody goes to them for theanswer, and then this shift
leads to a lot of uncertaintyand change of like what
good leadership looks like.
So take me through thatfor what a lot of leaders
are experiencing right now.
Charlene Li (02:18):
Right.
I mean, again, a lot ofleaders are, were promoted
because they knew how to dothe job better than other
people, and they're seen as.
Being able to, again, asyou said, have the answers.
And with AI, we're all figuringit out altogether at the same
time, and it puts an extrapressure on leaders to say, so
what are we doing with this?
(02:40):
Where are we going with it?
When there really isn't ananswer all the time, we may
have a directional travel, soit's really hard for leaders,
and AI already creates alot of fear and anxiety.
Add on top of that, that you'resupposed to have everything
figured out as a leader, that'sjust not going to happen.
So I think we have to movefrom needing to have all
(03:01):
the answers to being ableto ask great questions that
were direct people in theway that we wanna go to.
It's like, okay, so how are yougoing to use AI to create value?
Not what's the ROI of AI?
Those are two verydifferent questions.
And a leader needs tounderstand what the difference
is between those two.
David Rice (03:20):
Yeah.
I just come back from aconference and I listen to a
lot of leaders kind of talkingto each other and obviously
talking with me as well.
And I feel like one of thebig skills, the biggest skill
maybe for leadership of thefuture is just that sort of
comfort in your own skin.
Your ability to like embrace theuncertainty and just kind of say
like, yeah, I don't really know,but I'm interested in this.
(03:41):
I'm interested in that thisis the group of people that
I've brought together tohelp me figure this out.
You know what I mean?
The ability to sort of seethe network connections
that are gonna make the bigdifference in your project or
in your, you know, initiative.
I feel like that's like whereleadership is gonna have
to flex its muscle, so tospeak, rather than expertise.
Charlene Li (04:01):
Exactly.
And especially with AI, Ithink a really important part
is that leaders set, createan environment where people
can experiment and learn.
This is different from thepilots that people were running
because that's a whole differentissue of the pilot purgatory
that AI's experiencing.
This is about you gettingin, using AI, experimenting
(04:23):
and figuring out whatworks and doesn't work.
And creating that environmentso that you can learn
individually, but alsolearn together is a really
important part for a leaderin this day and age of AI.
David Rice (04:36):
You were pointing out to me that Americans are far
more likely than people in othercountries to see AI is harmful.
And I'm curious what you thinkis behind that fear and how
much of it comes down to cultureand leadership narratives?
Charlene Li (04:48):
Again, I think one of the things we have in
our society and most Westernsocieties is, a) culture
narrative of individualism.
And in other countries likeChina, Indonesia, Thailand,
where there's a stronger senseof collectivism as the overall
cultural narrative, AI is seenas a incredibly positive force.
(05:10):
So only 39% of people here inthe US believe that AI is gonna
be more beneficial than harmful.
And in China it's 83%more than twice as many.
And so they see AI as anenabler for the collective to
do more things, not as a threat.
In the US we see it aspotentially taking away the
(05:30):
things that make us individual.
And I think the leadershipnarrative that needs to shift
is we keep talking aboutAI, eliminating jobs versus
AI will amplify what we doas humans and will help us
do more meaningful work.
Both are true, but which areyou going to emphasize and
talk about and steer peopletowards and work towards as a
(05:51):
leader and as an organization?
David Rice (05:53):
Yeah.
I'm going for like,what are your actions
gonna support, right.
Because I think a lot of peoplein this country where they're
reacting to what they seeand they're seeing headlines
about all kinds of crazystuff to all these layoffs.
And so it's, the actions aren'tlining up with the idea that
it's gonna help us be better.
And we do, like you said,it's a very individualistic
society, and so there's alwaysthe feeling of like, this could
(06:15):
be the thing that leaves meout to dry or, you know, we
struggle with isolation anyways.
It's interesting to seewhat's playing out, like
on the psychology front.
There's so many different facetsto the, what AI is doing right
now, but you know, you can seethe fear from a lot of people
who don't maybe have a goodconnection to their community.
Charlene Li (06:34):
It's also, we have this myth of control.
We believe that when you'rea leader or you're doing
well, you are in control.
And what AI, and frankly,if you ever believe that
leadership is really aboutcontrol, then you don't
really understand leadership.
You're never in control.
And the only thing thatkeeps you in a leadership
position is the credibilityyou have as a leader.
(06:55):
It's not your title, it's thatrelationship that you form
with the people who follow you.
So for us to feel like we'relosing control because of AI,
the threat of it, the fear andanxiety that it creates when
you flip onto the other sideand see AI as not a loss of
control, but a huge enabler.
The way you talk aboutAI, the way you use
it, completely changes.
(07:17):
And so I can tell, usually whenleaders talk to me about the
fear and anxiety side of AI.
My very first question is,what do you use it for?
And it turns out they'renot actively using it.
They haven't been giventhe training, they haven't
been exposed to thepowerful tools that can
really make a difference.
They have experienced areally bad hallucination,
so they just go, I wantnothing to do with this.
(07:38):
It is not good.
It is error prone.
It gives me bad answers.
I can't trust it.
So understanding what AIcan do, developing a fluency
around it, I think is a toppriority for organizations.
David Rice (07:51):
Yeah, definitely at the leadership level too, right?
Like.
There's, I've noticed thisin talking to a few different
CHROs where they're just almostin the state of paralysis
around what to do with it,and I'm like, well, you maybe
just start experimenting.
But even that, some of 'em,especially if you're in a larger
org, but if you're in a largerorg where there's a lot of
(08:11):
pieces to move, to do anything,I think it makes it immensely
harder to feel like you havethe ability or the freedom or
the time, quite frankly, totest things out and just be
experimental and be innovative.
Charlene Li (08:23):
And you have the flip side of that where
some organizations havereally cut off the use of AI.
They may have Microsoftcopilot, but that's a
slim down version of AI.
But the irony was I wastalking to is one technology
company, and they'retalking about AI agents.
They built it in theirproducts, but inside the
own company, they don'tallow the people to use it.
And I go, butyou're all using AI.
(08:45):
She goes, yeah, we havesecond laptops, we have
second phones and we'redoing all this shadow AI.
I'm like, does itknow about this?
'cause they shut you downin order to not keep you,
let you do those things.
And so there's a big disconnect.
Between how we sometimes talkabout AI and actually how we
use it, and the more we canbe upfront and transparent
(09:06):
to say, this is not a fad,AI is not going to go away,
so let's deal with it anddeal with it realistically.
And instead of putting our headin the sand and hoping that
it'll just go away, or that Ican outlast it until I don't
have to deal with it anymore.
It's not a smart way to do it.
And so people, youremployees are watching
(09:27):
to see how you're talkingabout how you're using AI.
And if they don't see youtaking a proactive stance
about this, they go,well, we have no strategy.
We have no play in this game.
And it's coming.
It's coming.
And it don't wanna be at acompany that doesn't know
what it's going to do.
This is my career,this is my livelihood.
I need to be at a companythat is embracing AI
(09:47):
and running towards it.
So I think it's areal retention issue.
If you don't have a roadmapof how you're going to use
AI, then in that absence,people are going to make
things up and assume thatthere's nothing going on.
David Rice (10:00):
Well, so you said it there.
There's all thisshadow AI usage, right?
And then thatcreates capabilities.
They're learning, they'rebecoming more capable
and how they're using it.
But you have no say inwhat they're becoming
capable of, right?
You have no say in howthey're developing.
So I think like part of theproblem is that currently a lot
of leaders are thinking of AIpurely in terms of productivity
(10:21):
measurements, right?
And I'm curious about how dowe shift the conversation away
from that into more imaginingand thinking about what's
possible as people developthose capabilities, whether
you are steering it or not.
Charlene Li (10:34):
I think if leaders need to stop asking what's ROI
first, and start asking what'sthe value, but especially the
new value that AI can create.
So instead of justautomating your processes,
one of the worst thingsyou could do is automating
an existing bad process.
What if you could imagine anew process that AI enables?
(10:55):
How would that not only makethings more efficient, but also
allow you to do new things?
One of the things we companieswe spoke with for the book was
Call center and they of courseuse AI to get the call center
agents to be more productiveand in particular to have higher
quality, fewer errors, and theyuse all those gains to tackle
(11:16):
a big, long list of customerexperience initiatives that they
wanted to tackle but didn't havethe time and resources to do it.
Now they had it.
Then they realized that withadditional capabilities they
could take on new products andservices, they were reinventing
themselves because of thisAI capability, and they knew
(11:36):
that their clients weren'tgoing to develop this, so
they did it on their behalf.
Again, it was a three tieredstrategy right from the very
beginning to create value,not just as efficiency,
but also creating a bettercustomer engagement and also
reinventing the business.
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(12:42):
Yeah, it's interesting likebecause based on what you do,
value looks differently orit looks different, right?
But I am starting to notice morepeople thinking, okay, I saw
this graphic, this guy said gofrom T-shaped professional to
comb shaped professional, butmore in thinking about how do I
drive a bit of value across eachone of these things and have
(13:02):
more of the ability to do thatrather than being so specialized
in my one thing that's the onlything I can create value in.
Because you know, AI formarketing, it's gonna look
like one thing versus AIin HR that's gonna look
very different, right?
So I think it's interestingto see how people are
developing themselves as well.
Charlene Li (13:21):
And the biggest problem I see
is that people have thislong list of use cases.
They have like hundredsof use cases and use
cases are not a strategy.
You already have abusiness strategy.
AI is not, you don'thave an AI strategy.
AI is a technology.
It's a tool.
It's not a strategy.
So figure out how you use AIas a technology, as a strategic
(13:44):
initiative, a strategicplatform to help you achieve
your business strategy,your business objectives.
So this is not abouthaving a separate strategy.
It needs to be deeplyintegrated to what's most
important to your organization.
So while HR can dotheir own initiatives.
Customer service cando their own existence.
Same.
Same thing with marketing.
(14:05):
Everyone can do all the thingsthat make sense with the
departments, but what are wegoing to do as an organization
to take the greatestimpact that we can have?
And this goes back toyour point, it takes
some imagination.
We as organizations are not verygood at thinking across silos.
We're very good at optimizingfor our departments.
(14:25):
To think broadly andstrategically about what are
the ways that AI can really helpus move that needle, achieve
our objectives better, faster,cheaper, all three, and also
safer in a more ethical way.
It's really important.
These are really importantquestions to be asking.
David Rice (14:42):
And just like you mentioned there, it's
hard to look at the wholeorganization, think holistically
about what we're gonna do it.
It also feels like there'sa lot of over-hyping the
short term and under hypingthe long term, right?
We are thinking about, well,what am I getting out of it now?
I mean, we've had thistechnology in its current form,
just a short time, really, andyet we're asking about ROI.
(15:05):
I can't think of a lot ofother technologies where we
just asked that quickly, well,what's it giving me back?
The expectation and the demandof it, I feel was different than
a of a lot of other technologiesthat we might've implemented.
So I'm curious, how doleaders find that right
balance between like healthyskepticism and visionary
optimism in this environmentwhere these expectations exist?
Charlene Li (15:28):
I think again, the healthy skepticism
is important to have.
It's not that AIcan't create value.
Absolutely, it can create value.
The question becomes howare we delivering value
right now and this quarterand the next quarter and
the quarter after that?
And that's why that AI roadmap,again, not a strategy, but
(15:49):
a roadmap of how you'regoing to use AI to create
value is so important.
Believe me, value is beingcreated left and right.
You just may notbe understanding.
It may not be capturing it,and it may not be prioritizing
what value you want tofocus on and deliver and
drive as an organization.
So just having that plan,that roadmap that says we
(16:09):
are going to do this andnot that this quarter.
And it's transparentto everyone.
Everyone knows whatthey're on the hook to do.
When somebody goes, Iwanna do this, now you can.
We're not doing that now.
We are going to do thatin two quarters from now
and this is why, and wecan still adjust things.
That roadmap iswritten in pencil.
(16:30):
Your strategy is written unique,but your execution roadmap is
written in pencil, so you canadjust it depending on skill
advancements, technology change,maybe there are some issues
that come up with your customersthat you now understand better,
so you move things around.
Having that plan is reallyimportant because what
we're seeing here isn't anissue in a hype cycle gap.
(16:53):
What we have is a transformationgap between us understanding
this technology that's readyto use, and our organization's
ability to actually adopt themand adapt our organization.
That's the gap.
So it's not that this technologycan't do it, we see hundreds
and thousands of companies.
Doing really amazingthings with AI and they're
(17:17):
not the usual suspects.
They're not the big technologydisruptive companies.
They're universities, theirhealthcare clinics, those small
companies that are finding andextracting value from AI today.
So buckle down, learn how to useAI and then figure out how it's
gonna create value right away.
David Rice (17:38):
Yeah.
It's interesting you saidthat the sort of understanding
your capabilities.
You mentioned there, there'shundreds of use cases, right?
And we even createdthis thing, it's like a
transformation explorer.
It's got 146 use casesin it for HR alone.
Right.
But the problem is that if youdon't have an understanding
of your maturity, we realizethis pretty quickly, that if
the person using it doesn'tunderstand that the maturity
(18:00):
of their organization andtheir readiness for AI, all of
that information is kind of,I mean, it's very difficult
to navigate or understandwhat's possibly useful for you.
Not that it's useless, but itlacks the true value of what
it's intended to do, and so.
Charlene Li (18:16):
Lemme challenge that a little bit
because I don't think anyorganization is ready for AI.
Again, nobody knowshow to use this stuff.
Show me an organization thatsays, oh yeah, we got it all.
We know exactly how to do this.
It's nobody knows how to do it.
And so if you are waitingto be ready or if you're
looking at feasibility, you'rewaiting for perfect data.
(18:37):
I hear that all the time.
We gotta clean our databefore we can use AI.
I'm like no.
You can use it now.
Go and clean up your data,but figure out all the
other things you can do.
Go find data that may notbe perfect, but it's usable.
You can use AI to clean itup pretty quickly and start
extracting value from it.
Learn from that.
It may not be the biggestuse case that you could have.
(18:59):
Then the other thing is whyare we looking at the use
cases and deciding basedon feasibility when instead
we should be looking at ourstrategic priorities because we
already know what's important.
And then based on the biggestpriorities that we have, what
are the biggest challenges oropportunities that we have with
those strategic objectives?
(19:20):
And then ask how can AIhelp us accomplish those
things, overcome thosechallenges, or actually tap
into those opportunities?
That should bethe prioritization
matrix that you use.
How welcoming, what's thevalue of achieving our
strategic objectives andwhat's the speed at which
we can realize that value?
(19:40):
Because in this space,everyone has access to
the same technology.
So speed is the new moat.
There's no other competitiveadvantage that you have other
than the speed of which youcan adopt these technologies
and adapt your organization.
That's it.
So if you're trying to be ready,well get ready, improve all the
things that you need to do, butthere's no substitute to getting
(20:03):
into it and having a focus.
We talk about the traitsof an AI ready culture.
Speed is one of them.
Focus is another one.
And there are things thatcontinuous learning and being
able to experiment and beingabsolutely customer focused.
But speed and focus arethe two foundational ideas,
half SB and the focus thatit is absolutely focused on
(20:25):
your strategic objectives.
David Rice (20:27):
I always say, we've all got this
thing at some point.
It's like you gotta realizeit's the people using it and how
they're using it and how they'reessentially directed to use it.
That's gonna be thebig difference for you.
Charlene Li (20:37):
Yeah, but that's your podcast.
This is what thisaudience is all about.
I've been in transformativetechnology and disruptive
technologies for threedecades now, and the thing
I've seen is that it'snever about the technology.
It is always about the people.
So this is a people problem.
Again, I don't wannasay people problem.
People opportunity.
David Rice (20:57):
Yeah.
Charlene Li (20:57):
To really take AI and the speed at
which it is being used.
And I guarantee you people inyour organization are using it.
They're using it.
All the time.
So you may have to declarewhat I call AI amnesty to
say, come out of the dark.
Show us what you'reusing with AI.
Use our preferred toolsthat are locked down,
(21:19):
not training the model.
Secure everything butcome out of the shadows.
No more shadow AI.
You have amnesty.
We won't care that youused this in the past.
We just won't care.
But please bring it out intothe open and let's figure
out how to do this together.
David Rice (21:33):
It's interesting that you say that, you
know, come outta the shadows'cause I, there's a lot of
executives who are curiousabout this, but like you say,
they're reluctant to commit.
I'm curious what haveyou learned about helping
risk averse leaders seeAI as a strategic ally
instead of a threat?
Because I think we agree it'salways about the people, right?
It's not really about thetechnology, but what does that
look like as organizationsstart leading humans and
(21:56):
autonomous systems side by side?
Like what do we have todo differently to get
the best out of both?
Charlene Li (22:01):
First of all, you have to overcome the
fear and anxiety 'causepeople will not use, they
will not learn about AI.
They won't go near it unless youaddress that fear and anxiety.
I know one organization intheir training process, they
have a special training that ifyou're skeptical about AI, go
to this training first and allthey do is answer questions.
(22:23):
Again, this is not about.
Watching show and tell.
This is about reallyaddressing that emotional
blockers that somebody mayhave and to understand where
they're coming from andto say, yeah, I hear that.
Let's go and address that inour training session the next
time, step by step address, allof those issues, and the fact
that they're not seen as crazyor dismissed for their fear
(22:45):
and anxiety means a big deal.
It's not like they're being, youknow, curmudgeonly or anything.
These are very realfears and anxieties.
Once you can addressthat, then you can say,
well, how do we use this?
And the only way I've been ableto reach across to people is
to take something that they areactively working on themselves.
(23:06):
So this is not about the usecases that I have inside of
a book or in a presentation.
Hands-on, what are you workingon, professional or personal?
What are you working on?
A question that you have,a task that you have to do.
Something that's justa pain to get done.
Let's go and look at howAI could potentially help
with that, and it may not.
And that's the importantthing to understand too.
(23:27):
So when I think aboutAI fluency, there
are a couple parts.
It's, do you understand whatAI can do and its limitations?
Do you understand how to useit responsibly and ethically?
Do you know how to useit to create value in
the work that you do?
And then final step, canyou teach somebody how to
use it because you knowyou're fluent when you can
(23:48):
explain it to somebody else.
It also has this niceboomerang effect that when
you are fluent, then you areteaching other people in the
organization to be fluent too.
So there's a nice cyclethere that's going on too.
So this is about developingthat fluency and it is a
very individual lies process.
(24:09):
You can do some trainingthat's highly centralized,
but the reality is it's a lotof individual experimenting,
handholding, sharing of bestpractices with people who are
doing similar work to you andthen learning along the way,
and you only learn and becomefluent if you practice it.
David Rice (24:27):
Most people learn by doing right.
My final question for youis, if you were redesigning
leadership development for thisera of work, what would you
include that's missing today?
Charlene Li (24:39):
I would definitely talk about AI fluency, and
this is about knowing howto use it in those four
dimensions, three dimensions,and they'd be able to teach it.
I would also include veryspecifically, how do you use it
to become better leader in termsof expanding the scope of what
you need to know and understand.
How do you speed upyour decision making?
(25:01):
And then also how do you scalethe impact that you have, for
example, through communications.
So these are all things thatin the past kept us from
expanding the scope of ourleadership because we just only
had so many hours in a day.
And if someone asked me, well,how do I have find time to use
AI after my 15 back-to-backmeetings all day long.
(25:24):
I'm like, well, why don'tyou use AI to not have 15
back-to-back meetings allday long, first of all.
David Rice (25:30):
That'd be a good start.
Charlene Li (25:31):
And then use it, for example, I know one
sales leader has all thetranscripts from every sales
meeting that the team has, andhe uses AI to analyze them.
All of them to understand whatare the biggest customer needs
that kept coming up this week?
What were the key themes thatcustomers were asking for?
(25:53):
What were the areas that ourteam was struggling with?
So he could see acrossall of the activities,
across all of the teams.
He could be in everysingle conversation.
You couldn't do this before.
You couldn't be onevery call, but now you
can with transcripts.
And having them all in oneplace where everyone can
see them and use them is asignificant change in how
(26:15):
you manage and lead a team.
I can use AI to understand mydevelopment conversations with
a team member, and it's hard toremember everything, but I can
have notes that are taken fromour confidential information.
Again, it's all protected.
The person knows that we'rerecording them, but I can
understand like these are thethings that they've been doing.
(26:36):
These are the things that I cannow look across the past quarter
and understand here are someways that we can do development.
Have a development plan that'shighly tailored to that person.
I mean, all the things that wewish we could have had time and
the ability to go do all thesethings we can now, but requires
us to say how do we want to useit in our leadership capacity
(26:57):
to help us be better leaders.
David Rice (26:59):
Charlene, thanks for coming on the show today.
I really appreciate it.
It was fun talking with you.
Charlene Li (27:03):
Thank you again for having me.
David Rice (27:06):
Alright listeners, until next time.
If you haven't done soalready, head on over to
this website, get signedup for the newsletter,
create your free account.
You'll be able to downloadall our templates, use any
tools that you find on thewebsite, so be sure to do that.
Until next time, experiment.
Don't be afraid.
You are in back-to-back meetings all day.
Your team keeps askingabout AI, the strategy, and
honestly, you're not sure.
You're supposed to have answers.
That's why you gotpromoted, isn't it?
But with AI, everybody'sfiguring it out
at the same time.
And the uncomfortable truthis, if you're not using AI
yourself, you're alreadyfalling behind the people
you're supposed to be leading.
(00:43):
Today's guest on thepodcast is Charlene Li.
She's the founder of QuantumNetworks Group, and she's gonna
tell us why 83% of people inChina's AI is beneficial while
only 39% of Americans do.
More importantly, she'sgonna show you how to break
out of pilot purgatory andactually start building AI
fluency in your organization.
We're gonna cover why your fearof losing control is the real
(01:04):
problem, not the technology,how to deal with shadow AI
usage, the four dimensions ofAI fluency every leader needs to
master, and how one sales leaderuses AI to be in every customer
conversation without attendinga single extra meeting.
I'm David Rice.
This is People Managing People.
And if you've been paralyzedabout what to do with AI, this
(01:26):
episode is your permissionslip to start experimenting.
So let's go.
Welcome to the People ManagingPeople Podcast, the show
where we help leaders keepwork human in the age of AI.
My name is David Rice andI'm your host, as always.
Today I'm joined by Charlene Li.
She is a strategicadvisor and the founder
(01:47):
of Quantum Networks Group.
We're gonna be talkingabout the current state of
how leaders are using AIand what needs to change
for leadership developmentin this new era of work.
Charlene, welcome.
Charlene Li (01:58):
Thank you for having me.
David Rice (01:59):
Yeah, absolutely.
We were talking before this andyou said that many leaders, they
struggle with AI because theyfeel threatened, they're used
to having the answers, right?
Everybody goes to them for theanswer, and then this shift
leads to a lot of uncertaintyand change of like what
good leadership looks like.
So take me through thatfor what a lot of leaders
are experiencing right now.
Charlene Li (02:18):
Right.
I mean, again, a lot ofleaders are, were promoted
because they knew how to dothe job better than other
people, and they're seen as.
Being able to, again, asyou said, have the answers.
And with AI, we're all figuringit out altogether at the same
time, and it puts an extrapressure on leaders to say, so
what are we doing with this?
(02:40):
Where are we going with it?
When there really isn't ananswer all the time, we may
have a directional travel, soit's really hard for leaders,
and AI already creates alot of fear and anxiety.
Add on top of that, that you'resupposed to have everything
figured out as a leader, that'sjust not going to happen.
So I think we have to movefrom needing to have all
(03:01):
the answers to being ableto ask great questions that
were direct people in theway that we wanna go to.
It's like, okay, so how are yougoing to use AI to create value?
Not what's the ROI of AI?
Those are two verydifferent questions.
And a leader needs tounderstand what the difference
is between those two.
David Rice (03:20):
Yeah.
I just come back from aconference and I listen to a
lot of leaders kind of talkingto each other and obviously
talking with me as well.
And I feel like one of thebig skills, the biggest skill
maybe for leadership of thefuture is just that sort of
comfort in your own skin.
Your ability to like embrace theuncertainty and just kind of say
like, yeah, I don't really know,but I'm interested in this.
(03:41):
I'm interested in that thisis the group of people that
I've brought together tohelp me figure this out.
You know what I mean?
The ability to sort of seethe network connections
that are gonna make the bigdifference in your project or
in your, you know, initiative.
I feel like that's like whereleadership is gonna have
to flex its muscle, so tospeak, rather than expertise.
Charlene Li (04:01):
Exactly.
And especially with AI, Ithink a really important part
is that leaders set, createan environment where people
can experiment and learn.
This is different from thepilots that people were running
because that's a whole differentissue of the pilot purgatory
that AI's experiencing.
This is about you gettingin, using AI, experimenting
(04:23):
and figuring out whatworks and doesn't work.
And creating that environmentso that you can learn
individually, but alsolearn together is a really
important part for a leaderin this day and age of AI.
David Rice (04:36):
You were pointing out to me that Americans are far
more likely than people in othercountries to see AI is harmful.
And I'm curious what you thinkis behind that fear and how
much of it comes down to cultureand leadership narratives?
Charlene Li (04:48):
Again, I think one of the things we have in
our society and most Westernsocieties is, a) culture
narrative of individualism.
And in other countries likeChina, Indonesia, Thailand,
where there's a stronger senseof collectivism as the overall
cultural narrative, AI is seenas a incredibly positive force.
(05:10):
So only 39% of people here inthe US believe that AI is gonna
be more beneficial than harmful.
And in China it's 83%more than twice as many.
And so they see AI as anenabler for the collective to
do more things, not as a threat.
In the US we see it aspotentially taking away the
(05:30):
things that make us individual.
And I think the leadershipnarrative that needs to shift
is we keep talking aboutAI, eliminating jobs versus
AI will amplify what we doas humans and will help us
do more meaningful work.
Both are true, but which areyou going to emphasize and
talk about and steer peopletowards and work towards as a
(05:51):
leader and as an organization?
David Rice (05:53):
Yeah.
I'm going for like,what are your actions
gonna support, right.
Because I think a lot of peoplein this country where they're
reacting to what they seeand they're seeing headlines
about all kinds of crazystuff to all these layoffs.
And so it's, the actions aren'tlining up with the idea that
it's gonna help us be better.
And we do, like you said,it's a very individualistic
society, and so there's alwaysthe feeling of like, this could
(06:15):
be the thing that leaves meout to dry or, you know, we
struggle with isolation anyways.
It's interesting to seewhat's playing out, like
on the psychology front.
There's so many different facetsto the, what AI is doing right
now, but you know, you can seethe fear from a lot of people
who don't maybe have a goodconnection to their community.
Charlene Li (06:34):
It's also, we have this myth of control.
We believe that when you'rea leader or you're doing
well, you are in control.
And what AI, and frankly,if you ever believe that
leadership is really aboutcontrol, then you don't
really understand leadership.
You're never in control.
And the only thing thatkeeps you in a leadership
position is the credibilityyou have as a leader.
(06:55):
It's not your title, it's thatrelationship that you form
with the people who follow you.
So for us to feel like we'relosing control because of AI,
the threat of it, the fear andanxiety that it creates when
you flip onto the other sideand see AI as not a loss of
control, but a huge enabler.
The way you talk aboutAI, the way you use
it, completely changes.
(07:17):
And so I can tell, usually whenleaders talk to me about the
fear and anxiety side of AI.
My very first question is,what do you use it for?
And it turns out they'renot actively using it.
They haven't been giventhe training, they haven't
been exposed to thepowerful tools that can
really make a difference.
They have experienced areally bad hallucination,
so they just go, I wantnothing to do with this.
(07:38):
It is not good.
It is error prone.
It gives me bad answers.
I can't trust it.
So understanding what AIcan do, developing a fluency
around it, I think is a toppriority for organizations.
David Rice (07:51):
Yeah, definitely at the leadership level too, right?
Like.
There's, I've noticed thisin talking to a few different
CHROs where they're just almostin the state of paralysis
around what to do with it,and I'm like, well, you maybe
just start experimenting.
But even that, some of 'em,especially if you're in a larger
org, but if you're in a largerorg where there's a lot of
(08:11):
pieces to move, to do anything,I think it makes it immensely
harder to feel like you havethe ability or the freedom or
the time, quite frankly, totest things out and just be
experimental and be innovative.
Charlene Li (08:23):
And you have the flip side of that where
some organizations havereally cut off the use of AI.
They may have Microsoftcopilot, but that's a
slim down version of AI.
But the irony was I wastalking to is one technology
company, and they'retalking about AI agents.
They built it in theirproducts, but inside the
own company, they don'tallow the people to use it.
And I go, butyou're all using AI.
(08:45):
She goes, yeah, we havesecond laptops, we have
second phones and we'redoing all this shadow AI.
I'm like, does itknow about this?
'cause they shut you downin order to not keep you,
let you do those things.
And so there's a big disconnect.
Between how we sometimes talkabout AI and actually how we
use it, and the more we canbe upfront and transparent
(09:06):
to say, this is not a fad,AI is not going to go away,
so let's deal with it anddeal with it realistically.
And instead of putting our headin the sand and hoping that
it'll just go away, or that Ican outlast it until I don't
have to deal with it anymore.
It's not a smart way to do it.
And so people, youremployees are watching
(09:27):
to see how you're talkingabout how you're using AI.
And if they don't see youtaking a proactive stance
about this, they go,well, we have no strategy.
We have no play in this game.
And it's coming.
It's coming.
And it don't wanna be at acompany that doesn't know
what it's going to do.
This is my career,this is my livelihood.
I need to be at a companythat is embracing AI
(09:47):
and running towards it.
So I think it's areal retention issue.
If you don't have a roadmapof how you're going to use
AI, then in that absence,people are going to make
things up and assume thatthere's nothing going on.
David Rice (10:00):
Well, so you said it there.
There's all thisshadow AI usage, right?
And then thatcreates capabilities.
They're learning, they'rebecoming more capable
and how they're using it.
But you have no say inwhat they're becoming
capable of, right?
You have no say in howthey're developing.
So I think like part of theproblem is that currently a lot
of leaders are thinking of AIpurely in terms of productivity
(10:21):
measurements, right?
And I'm curious about how dowe shift the conversation away
from that into more imaginingand thinking about what's
possible as people developthose capabilities, whether
you are steering it or not.
Charlene Li (10:34):
I think if leaders need to stop asking what's ROI
first, and start asking what'sthe value, but especially the
new value that AI can create.
So instead of justautomating your processes,
one of the worst thingsyou could do is automating
an existing bad process.
What if you could imagine anew process that AI enables?
(10:55):
How would that not only makethings more efficient, but also
allow you to do new things?
One of the things we companieswe spoke with for the book was
Call center and they of courseuse AI to get the call center
agents to be more productiveand in particular to have higher
quality, fewer errors, and theyuse all those gains to tackle
(11:16):
a big, long list of customerexperience initiatives that they
wanted to tackle but didn't havethe time and resources to do it.
Now they had it.
Then they realized that withadditional capabilities they
could take on new products andservices, they were reinventing
themselves because of thisAI capability, and they knew
(11:36):
that their clients weren'tgoing to develop this, so
they did it on their behalf.
Again, it was a three tieredstrategy right from the very
beginning to create value,not just as efficiency,
but also creating a bettercustomer engagement and also
reinventing the business.
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(12:42):
Yeah, it's interesting likebecause based on what you do,
value looks differently orit looks different, right?
But I am starting to notice morepeople thinking, okay, I saw
this graphic, this guy said gofrom T-shaped professional to
comb shaped professional, butmore in thinking about how do I
drive a bit of value across eachone of these things and have
(13:02):
more of the ability to do thatrather than being so specialized
in my one thing that's the onlything I can create value in.
Because you know, AI formarketing, it's gonna look
like one thing versus AIin HR that's gonna look
very different, right?
So I think it's interestingto see how people are
developing themselves as well.
Charlene Li (13:21):
And the biggest problem I see
is that people have thislong list of use cases.
They have like hundredsof use cases and use
cases are not a strategy.
You already have abusiness strategy.
AI is not, you don'thave an AI strategy.
AI is a technology.
It's a tool.
It's not a strategy.
So figure out how you use AIas a technology, as a strategic
(13:44):
initiative, a strategicplatform to help you achieve
your business strategy,your business objectives.
So this is not abouthaving a separate strategy.
It needs to be deeplyintegrated to what's most
important to your organization.
So while HR can dotheir own initiatives.
Customer service cando their own existence.
Same.
Same thing with marketing.
(14:05):
Everyone can do all the thingsthat make sense with the
departments, but what are wegoing to do as an organization
to take the greatestimpact that we can have?
And this goes back toyour point, it takes
some imagination.
We as organizations are not verygood at thinking across silos.
We're very good at optimizingfor our departments.
(14:25):
To think broadly andstrategically about what are
the ways that AI can really helpus move that needle, achieve
our objectives better, faster,cheaper, all three, and also
safer in a more ethical way.
It's really important.
These are really importantquestions to be asking.
David Rice (14:42):
And just like you mentioned there, it's
hard to look at the wholeorganization, think holistically
about what we're gonna do it.
It also feels like there'sa lot of over-hyping the
short term and under hypingthe long term, right?
We are thinking about, well,what am I getting out of it now?
I mean, we've had thistechnology in its current form,
just a short time, really, andyet we're asking about ROI.
(15:05):
I can't think of a lot ofother technologies where we
just asked that quickly, well,what's it giving me back?
The expectation and the demandof it, I feel was different than
a of a lot of other technologiesthat we might've implemented.
So I'm curious, how doleaders find that right
balance between like healthyskepticism and visionary
optimism in this environmentwhere these expectations exist?
Charlene Li (15:28):
I think again, the healthy skepticism
is important to have.
It's not that AIcan't create value.
Absolutely, it can create value.
The question becomes howare we delivering value
right now and this quarterand the next quarter and
the quarter after that?
And that's why that AI roadmap,again, not a strategy, but
(15:49):
a roadmap of how you'regoing to use AI to create
value is so important.
Believe me, value is beingcreated left and right.
You just may notbe understanding.
It may not be capturing it,and it may not be prioritizing
what value you want tofocus on and deliver and
drive as an organization.
So just having that plan,that roadmap that says we
(16:09):
are going to do this andnot that this quarter.
And it's transparentto everyone.
Everyone knows whatthey're on the hook to do.
When somebody goes, Iwanna do this, now you can.
We're not doing that now.
We are going to do thatin two quarters from now
and this is why, and wecan still adjust things.
That roadmap iswritten in pencil.
(16:30):
Your strategy is written unique,but your execution roadmap is
written in pencil, so you canadjust it depending on skill
advancements, technology change,maybe there are some issues
that come up with your customersthat you now understand better,
so you move things around.
Having that plan is reallyimportant because what
we're seeing here isn't anissue in a hype cycle gap.
(16:53):
What we have is a transformationgap between us understanding
this technology that's readyto use, and our organization's
ability to actually adopt themand adapt our organization.
That's the gap.
So it's not that this technologycan't do it, we see hundreds
and thousands of companies.
Doing really amazingthings with AI and they're
(17:17):
not the usual suspects.
They're not the big technologydisruptive companies.
They're universities, theirhealthcare clinics, those small
companies that are finding andextracting value from AI today.
So buckle down, learn how to useAI and then figure out how it's
gonna create value right away.
David Rice (17:38):
Yeah.
It's interesting you saidthat the sort of understanding
your capabilities.
You mentioned there, there'shundreds of use cases, right?
And we even createdthis thing, it's like a
transformation explorer.
It's got 146 use casesin it for HR alone.
Right.
But the problem is that if youdon't have an understanding
of your maturity, we realizethis pretty quickly, that if
the person using it doesn'tunderstand that the maturity
(18:00):
of their organization andtheir readiness for AI, all of
that information is kind of,I mean, it's very difficult
to navigate or understandwhat's possibly useful for you.
Not that it's useless, but itlacks the true value of what
it's intended to do, and so.
Charlene Li (18:16):
Lemme challenge that a little bit
because I don't think anyorganization is ready for AI.
Again, nobody knowshow to use this stuff.
Show me an organization thatsays, oh yeah, we got it all.
We know exactly how to do this.
It's nobody knows how to do it.
And so if you are waitingto be ready or if you're
looking at feasibility, you'rewaiting for perfect data.
(18:37):
I hear that all the time.
We gotta clean our databefore we can use AI.
I'm like no.
You can use it now.
Go and clean up your data,but figure out all the
other things you can do.
Go find data that may notbe perfect, but it's usable.
You can use AI to clean itup pretty quickly and start
extracting value from it.
Learn from that.
It may not be the biggestuse case that you could have.
(18:59):
Then the other thing is whyare we looking at the use
cases and deciding basedon feasibility when instead
we should be looking at ourstrategic priorities because we
already know what's important.
And then based on the biggestpriorities that we have, what
are the biggest challenges oropportunities that we have with
those strategic objectives?
(19:20):
And then ask how can AIhelp us accomplish those
things, overcome thosechallenges, or actually tap
into those opportunities?
That should bethe prioritization
matrix that you use.
How welcoming, what's thevalue of achieving our
strategic objectives andwhat's the speed at which
we can realize that value?
(19:40):
Because in this space,everyone has access to
the same technology.
So speed is the new moat.
There's no other competitiveadvantage that you have other
than the speed of which youcan adopt these technologies
and adapt your organization.
That's it.
So if you're trying to be ready,well get ready, improve all the
things that you need to do, butthere's no substitute to getting
(20:03):
into it and having a focus.
We talk about the traitsof an AI ready culture.
Speed is one of them.
Focus is another one.
And there are things thatcontinuous learning and being
able to experiment and beingabsolutely customer focused.
But speed and focus arethe two foundational ideas,
half SB and the focus thatit is absolutely focused on
(20:25):
your strategic objectives.
David Rice (20:27):
I always say, we've all got this
thing at some point.
It's like you gotta realizeit's the people using it and how
they're using it and how they'reessentially directed to use it.
That's gonna be thebig difference for you.
Charlene Li (20:37):
Yeah, but that's your podcast.
This is what thisaudience is all about.
I've been in transformativetechnology and disruptive
technologies for threedecades now, and the thing
I've seen is that it'snever about the technology.
It is always about the people.
So this is a people problem.
Again, I don't wannasay people problem.
People opportunity.
David Rice (20:57):
Yeah.
Charlene Li (20:57):
To really take AI and the speed at
which it is being used.
And I guarantee you people inyour organization are using it.
They're using it.
All the time.
So you may have to declarewhat I call AI amnesty to
say, come out of the dark.
Show us what you'reusing with AI.
Use our preferred toolsthat are locked down,
(21:19):
not training the model.
Secure everything butcome out of the shadows.
No more shadow AI.
You have amnesty.
We won't care that youused this in the past.
We just won't care.
But please bring it out intothe open and let's figure
out how to do this together.
David Rice (21:33):
It's interesting that you say that, you
know, come outta the shadows'cause I, there's a lot of
executives who are curiousabout this, but like you say,
they're reluctant to commit.
I'm curious what haveyou learned about helping
risk averse leaders seeAI as a strategic ally
instead of a threat?
Because I think we agree it'salways about the people, right?
It's not really about thetechnology, but what does that
look like as organizationsstart leading humans and
(21:56):
autonomous systems side by side?
Like what do we have todo differently to get
the best out of both?
Charlene Li (22:01):
First of all, you have to overcome the
fear and anxiety 'causepeople will not use, they
will not learn about AI.
They won't go near it unless youaddress that fear and anxiety.
I know one organization intheir training process, they
have a special training that ifyou're skeptical about AI, go
to this training first and allthey do is answer questions.
(22:23):
Again, this is not about.
Watching show and tell.
This is about reallyaddressing that emotional
blockers that somebody mayhave and to understand where
they're coming from andto say, yeah, I hear that.
Let's go and address that inour training session the next
time, step by step address, allof those issues, and the fact
that they're not seen as crazyor dismissed for their fear
(22:45):
and anxiety means a big deal.
It's not like they're being, youknow, curmudgeonly or anything.
These are very realfears and anxieties.
Once you can addressthat, then you can say,
well, how do we use this?
And the only way I've been ableto reach across to people is
to take something that they areactively working on themselves.
(23:06):
So this is not about the usecases that I have inside of
a book or in a presentation.
Hands-on, what are you workingon, professional or personal?
What are you working on?
A question that you have,a task that you have to do.
Something that's justa pain to get done.
Let's go and look at howAI could potentially help
with that, and it may not.
And that's the importantthing to understand too.
(23:27):
So when I think aboutAI fluency, there
are a couple parts.
It's, do you understand whatAI can do and its limitations?
Do you understand how to useit responsibly and ethically?
Do you know how to useit to create value in
the work that you do?
And then final step, canyou teach somebody how to
use it because you knowyou're fluent when you can
(23:48):
explain it to somebody else.
It also has this niceboomerang effect that when
you are fluent, then you areteaching other people in the
organization to be fluent too.
So there's a nice cyclethere that's going on too.
So this is about developingthat fluency and it is a
very individual lies process.
(24:09):
You can do some trainingthat's highly centralized,
but the reality is it's a lotof individual experimenting,
handholding, sharing of bestpractices with people who are
doing similar work to you andthen learning along the way,
and you only learn and becomefluent if you practice it.
David Rice (24:27):
Most people learn by doing right.
My final question for youis, if you were redesigning
leadership development for thisera of work, what would you
include that's missing today?
Charlene Li (24:39):
I would definitely talk about AI fluency, and
this is about knowing howto use it in those four
dimensions, three dimensions,and they'd be able to teach it.
I would also include veryspecifically, how do you use it
to become better leader in termsof expanding the scope of what
you need to know and understand.
How do you speed upyour decision making?
(25:01):
And then also how do you scalethe impact that you have, for
example, through communications.
So these are all things thatin the past kept us from
expanding the scope of ourleadership because we just only
had so many hours in a day.
And if someone asked me, well,how do I have find time to use
AI after my 15 back-to-backmeetings all day long.
(25:24):
I'm like, well, why don'tyou use AI to not have 15
back-to-back meetings allday long, first of all.
David Rice (25:30):
That'd be a good start.
Charlene Li (25:31):
And then use it, for example, I know one
sales leader has all thetranscripts from every sales
meeting that the team has, andhe uses AI to analyze them.
All of them to understand whatare the biggest customer needs
that kept coming up this week?
What were the key themes thatcustomers were asking for?
(25:53):
What were the areas that ourteam was struggling with?
So he could see acrossall of the activities,
across all of the teams.
He could be in everysingle conversation.
You couldn't do this before.
You couldn't be onevery call, but now you
can with transcripts.
And having them all in oneplace where everyone can
see them and use them is asignificant change in how
(26:15):
you manage and lead a team.
I can use AI to understand mydevelopment conversations with
a team member, and it's hard toremember everything, but I can
have notes that are taken fromour confidential information.
Again, it's all protected.
The person knows that we'rerecording them, but I can
understand like these are thethings that they've been doing.
(26:36):
These are the things that I cannow look across the past quarter
and understand here are someways that we can do development.
Have a development plan that'shighly tailored to that person.
I mean, all the things that wewish we could have had time and
the ability to go do all thesethings we can now, but requires
us to say how do we want to useit in our leadership capacity
(26:57):
to help us be better leaders.
David Rice (26:59):
Charlene, thanks for coming on the show today.
I really appreciate it.
It was fun talking with you.
Charlene Li (27:03):
Thank you again for having me.
David Rice (27:06):
Alright listeners, until next time.
If you haven't done soalready, head on over to
this website, get signedup for the newsletter,
create your free account.
You'll be able to downloadall our templates, use any
tools that you find on thewebsite, so be sure to do that.
Until next time, experiment.
Don't be afraid.
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Current and classic episodes, featuring compelling true-crime mysteries, powerful documentaries and in-depth investigations. Follow now to get the latest episodes of Dateline NBC completely free, or subscribe to Dateline Premium for ad-free listening and exclusive bonus content: DatelinePremium.com
Are You A Charlotte?
In 1997, actress Kristin Davis’ life was forever changed when she took on the role of Charlotte York in Sex and the City. As we watched Carrie, Samantha, Miranda and Charlotte navigate relationships in NYC, the show helped push once unacceptable conversation topics out of the shadows and altered the narrative around women and sex. We all saw ourselves in them as they searched for fulfillment in life, sex and friendships. Now, Kristin Davis wants to connect with you, the fans, and share untold stories and all the behind the scenes. Together, with Kristin and special guests, what will begin with Sex and the City will evolve into talks about themes that are still so relevant today. "Are you a Charlotte?" is much more than just rewatching this beloved show, it brings the past and the present together as we talk with heart, humor and of course some optimism.
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