October 3, 2025 • 30 mins
AI is reshaping every job from the C-Suite to the front line. It's happening at a pace unlike any change we’ve seen before.
But most leaders are uncomfortable leading this change. Despite all the talk about technology, AI-driven uncertainty is a deeply human topic. Sitting it out or waiting for someone else to solve the big questions of self-identity, value, and skills is not an option.
In this episode of "What’s the BUZZ?," host Andreas Welsch sits down with Alison McCauley, Author and Digital Change Strategist, to explore how leaders can navigate the uncertainty AI brings to the workplace.
Catch the BUZZ:
- Why will every role will change and how can leaders prepare?
- What's the critical role of expertise in the AI era?
- How can you equip your team with AI skills and big-picture thinking?
- When should you use AI as a thought partner?
Whether you’re a CEO, a mid-level manager, or just starting your career, this conversation offers actionable ways to lead with confidence when the future feels unclear.
Questions or suggestions? Send me a Text Message.
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Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Andreas Welsch (00:00):
Today we'll talk about how to lead when AI
creates uncertainty in theworkplace, and who better to
talk about it than someone who'shelping companies develop
digital strategies and leadinnovation around AI, Alison
McCauley.
Hey Alison.
Thank you so much for joining.
Alison McCauley (00:14):
I've been looking forward to this
conversation.
Andreas Welsch (00:16):
Awesome.
That makes two of us.
And I hope for those of you inthe audience, you're just as
excited as we are, but Alison,maybe not everybody in the
audience knows you, yet.
Why don't you tell us a littlebit about yourself, who you are
and what you do?
Alison McCauley (00:28):
Sure.
I have spent my entire career atthis really exciting
intersection of emergingtechnology and human behavior.
So how it affects emergingtechnology affects us as people,
as individuals, and asorganizations, as teams, as
culture and society.
(00:49):
And so I have to say it's neverbeen more interesting than it is
right now.
I begin my career at the whenthe field of change management
was just forming.
And it's been fascinating to seehow some things have stayed the
same since those early days whenwe were really literally writing
(01:09):
the playbook for changemanagement.
And some things are brand newand it, I started working in AI
in 2010.
Very different times, verydifferent kind of space.
And so it's been reallyfascinating how things have
changed over these last coupleyears.
And it is truly a whole new areathat needs to be navigated.
(01:31):
And so that's why this topicthat we're talking about today
is the topic of, the era.
Andreas Welsch (01:37):
Wonderful.
I couldn't agree more.
There's so much talk about techin bringing it to the business,
but at the end of the day, hey,there, there's still people
there that need to adopt it,that need to get comfortable
with it, that also need to helpother people manage the change
and lead through it when youknow.
Probably very few of us have theanswer of what does it mean,
where are we going?
(01:57):
So I'm looking forward todigging a little deeper there
and learning from you and fromyour insights.
Alison McCauley (02:03):
Wonderful.
Yeah.
Andreas Welsch (02:04):
Why don't we play a little game to kick
things off.
What do you say?
Alison McCauley (02:07):
A little improv maybe.
Andreas Welsch (02:09):
A little improv.
Exactly.
When I hit the buzzer, thewheels will start spinning and
you'll see a sentence I'd likefor you to answer with the first
thing that comes to mind andwhy, in your own words, to make
it a little more interesting.
You only have 60 seconds foryour answer.
For those of you watching uslive, please drop your answer
and why in the chat as well.
Alison, are you ready for,What's the BUZZ?
Alison McCauley (02:30):
Let's do it.
Andreas Welsch (02:31):
Okay.
Let's see.
Here we go.
If AI were a color, what wouldit be and why?
Alison McCauley (02:41):
Wow.
Okay there's some colors thatare that are yet to be
discovered.
And we hear about theseoccasionally and I have a
feeling that AI is a color thatwe haven't quite seen yet.
It's forming.
Andreas Welsch (03:02):
Oh, love it.
Alison McCauley (03:04):
So I think, we'll, we can't turn, I think,
to what we already know.
I think it's gonna be somethingthat is new that we all
discover.
Andreas Welsch (03:13):
Wonderful.
I like that.
You know what, when I ask mychildren, what's your favorite
color?
The answer I've recently beengetting is: rainbow.
All the colors of the rainbow.
I love rainbow color.
So definitely, there's a lot tobe discovered.
And I was lucky Il and I feellike the colors can change very
quickly as well as things evolveand adapt.
Alison McCauley (03:35):
Yeah.
And these analogies actually arereally apt, because AI is
adapting and changing so quicklyand there's so much to be
discovered that we're alldiscovering together because
this new acceleration is so new.
Yeah.
Andreas Welsch (03:50):
This newness and this newness factor also creates
a lot of uncertainty and a lotof changes.
We, we've seen in the lastcouple weeks a lot of coverage
about how recruiting for entrylevel jobs is slowing down
because of AI driven automation.
Companies are looking to do morewith AI, more entry level tasks,
things that are a little morecomplex than if this happens,
(04:11):
then do that.
Great.
Yes, AI can do that.
AI can also help professionalsand senior experts on more
complex tasks.
So we'll likely see this trendgoing up the hierarchy, if you
will, or seniority levels ofwhat AI can do.
And that also creates a goodamount of uncertainty and fear
about jobs, not just AI.
I just graduated where I find ajob.
(04:32):
Those are some of theconversations that I'm having
with students where I teach asan adjunct, but also more senior
professionals.
What are you seeing when youtalk to leaders in organizations
about these topics?
What AI means for jobs fororganizations?
What are people seeing?
Alison McCauley (04:46):
Yeah.
There's a big disconnect betweenwhat is possible and, what has
been newly unlocked with AI andwhere organizations are right
now?
So when I talk to differentorganizations, I travel around
the world giving talks andworkshops.
There's a range of where peopleare.
(05:09):
If I may on Andreas, be verydirect through your, viewers
are, okay with that.
I just wanna be really direct atevery.
Job is going to change everyjob.
So CEO jobs are gonna change.
Middle management jobs are gonnachange.
Entry-level jobs are gonnachange, and we haven't quite
(05:30):
ingested that and we haven'tquite.
We haven't quite taken that inand we certainly don't know yet
exactly how they will change.
Some are gonna adjust, some willadjust to this.
Some people will adjust to this.
Some organizations will adjustto this.
Some teams will, adjust to thisand some just won't.
And some jobs.
Will disappear and new jobs willbe created, and we just don't
(05:55):
know exactly how.
And we've seen shifts like thisbefore.
So the industrial revolutionbefore, before the Industrial
Revolution, we were a largelyagrarian economy.
And that shifted and everysingle role, every single job,
every single industry changed.
And now we're at the beginningof this cognitive revolution.
(06:17):
But we don't know where it'sheaded.
And when you look back at theindustrial Revolution, it's
almost like it unfolded withthis like choreography that was
so well orchestrated, but ithappened over 80 years.
And now what we're seeing is inthe matter of just a few years,
or even in some cases a fewquarters, it's it's changing
(06:39):
fast.
And so that, that throws peoplefor a loop.
And what I see when I, when I.
Talk to organizations is that noone's figured this out yet.
We're all, figuring this outtogether.
Those that are better equippedto see what's happening at that
front edge of change are thosethat have their hands in it and
(07:00):
are leaping into the unknown.
So I really advocate for thatbecause you need to see change
as it happens.
The best way is to get yourhands in it and really work to
understand it.
Andreas Welsch (07:13):
I love that call to action, right?
A lot of times it's really aboutseeing and feeling so that on
one hand you can either believeor you can also understand.
What does it actually mean?
What does it do?
What are the opportunities?
What are maybe some of thechallenges where this sounds
more like a big promise, but Iknow that here could be some
some holes that we might runinto.
(07:35):
It's also been a couple decadessince we've changed how
switchboards work andswitchboard operators, right,
that were superseded bytechnology or people pressing
the button for you in theelevator.
And must say it was in New YorkCity the other day for a tech
event and there was actually aperson pressing the right button
on the elevator.
So we got off on the rightfloor.
(07:55):
But we know that these are moreexceptions these days than, the
norm.
But I also feel that from theindustrial revolution some of
the robotics in the seventies inmany other evolutions it feels
like it's never been that fastor also it's been so far and so
long ago that very few of usactually relate to this.
(08:16):
So for our generation now in theworkforce in those going into
the workforce, this is reallynew.
It's the first time that thereis such a big monumental change
that's happening with us and tous.
Alison McCauley (08:26):
It's fascinating.
We forget every single timethere's a transformative
technology.
We forget how how much itchanges us and also how every
single change of that magnitudecomes with a combination of fear
and excitement.
So you mentioned elevatorbuttons.
You know when, things were firstelectrified, when electricity
(08:49):
first.
Came to us.
It was met with fear andexcitement.
The president of the UnitedStates, when electricity was
first installed in the WhiteHouse, would not switch the
lights on.
He had his staff do it'cause hewas scared of it.
It's just, it's thatcombination.
It's just that it's hurtlingtowards us so fast.
And that's also because it'schanging so quickly.
(09:11):
That's why it's important to bein it because things change.
Sometimes week to week, butdefinitely quarter to quarter.
And if you're not in it, youdon't see it.
Someone else, your competitormight, that's very true.
Andreas Welsch (09:26):
We're seeing that a lot and even competitors
that are not even born yet arejumping on this.
And, will at some point we'll gointo spaces that are
underserved.
But I'm curious what do yourecommend in addition to getting
hands-on how can leaders supportthe teams and organizations on
this journey?
And, maybe right from a team toorg unit, company level.
(09:47):
There many different layers ofof, that complexity if you will,
how can leaders under supporttheir organizations?
Alison McCauley (09:57):
So that's such a huge question.
I have several differentmethodologies to get at
different angles of that.
And so I'll give some hints onsome of those or over summer of
some of those.
But then I also wanna talkbigger picture about it as well.
'cause there's, a lot ofopportunity to step back and
think about it.
(10:18):
As I mentioned earlier, I havebeen, working in change
management and digital changesince the very beginning of that
profession when it was firstcodified into a formal
profession.
And a lot of the lessons that wedeveloped in some of our first
(10:38):
playbooks are still valid.
And so what's really critical?
Is to meet people where theyare.
So people all across yourorganization are all different
levels of understanding ofwhat's happening in this
organization.
We need to meet people wherethey are.
So you need to understand wherethey are, and you've got people
in your organization who are.
(10:59):
Maybe even using this in theirpersonal lives to do all kinds
of exciting things.
That's incredible expertise thatyou can tap into.
These are passionista that couldbe nurtured into change agents.
And so mapping in yourorganization, who's using what?
Where's the passion, where's theunderstanding is one way to
start to.
Bring your organization to buildthe AI muscle of your
(11:21):
organization.
Another piece that we couldtalk, about a lot more is how
you connect to value.
So we tend to talk about AI astechnology.
Of course it's a technology, butthe real opportunity and where
the unlocks really happen in anorganization are when we start
talking about.
What is the real business needthat you have in your
(11:44):
organization and focus there.
So put aside the technology.
Focus on where the business needare.
What could we do withoutconstraints?
What what would we do if wecould remove blocks and barriers
that we have today?
What would we be able toachieve?
And then start the AIconversation from that focal
(12:05):
point.
So that's about really showingpeople how to get to value in
it.
That changes everything.
And the other piece is aboutreally patiently showing people
the way this always takes longerthan people think.
Once you understand AI, youthink, oh, everybody gets this.
It's so obvious'cause you getbombarded in your echo chamber
(12:27):
around AI.
But.
Truly people need a long time tobe able to understand how to
move in that direction.
And so I emphasize a, wholearsenal of change, manage
techniques around being able tocreate learning circles.
And sharing networks,storytelling, feedback loops.
(12:49):
So there's a whole bunch oforganizational mechanisms that
we can put in place that have ahuge impact.
So anyway, those are some of thelittle summary of some tips and
tricks.
But just to bump it up a level,I'd say that, so when I give
talks, one of the big.
Surprises that a lot of leaderstell, a lot of leaders tell me
(13:11):
they were surprised byafterwards in, the q and a and
the discussions are howimportant expertise is in this
moment.
We're in a world where AI cangenerates a lot of it mixed
things up.
It can, it still hallucinates,right?
And only your experts in theorganization can really
(13:33):
identify.
AI garbage for what it is.
'cause it presents it in a waythat feels really great.
You were talking earlier aboutentry level and some of the
challenges for entry level.
People without the experiencecan't identify AI slop and AI
(13:54):
junk for what it is.
It's your experts that can, soyour experts are the one who can
understand how do we leveragethis technology?
And you have experts all overyour organization at every
single level, every singlefunctional area, every single
department.
And being able to equip yourexperts with the knowledge to
use AI is what unlocks theopportunity.
(14:16):
They're able to navigate thesystems and no matter what
organization at this point intime, you probably could use
more expertise.
And so if you experts understandhow to use AI to amplify the
knowledge they have, if they'reable to really, truly.
(14:36):
Orchestrate these systems tomake it work In that way, you un
you amplify your expertise.
And so that's so much of theopportunity around here.
And then the other thing that Iwould really encourage leaders
to do, and this takes some time,is that we have there's an
opportunity in this moment, notjust to automate.
Today's AI is not just aboutautomation and we have 30 years
(15:01):
of experience.
With automation more than 30years, but like a real focus
around 30 years of, expertisearound automation that works in
a certain way.
This new AI allows us to dothings in a completely different
way, so we need to, dig into ourimagination around reimagine
(15:25):
what we can accomplish and whatwe can achieve as humans in an
organization because we now havethese capabilities, and right
now there's a real.
Deficit of imagination.
We're not tapping into that.
We're in reactive mode.
We're not in, in in, this spacewhere we're really understanding
how could we go next level?
(15:46):
What new products and servicescan we introduce?
What new industries can wecreate?
Because we now have these tools.
And so that's the other pieceis.
To really tap into what's this?
What can we make out of this?
What can we do when we no longerhave the cognitive limitations
(16:08):
that organizations have beengoverned by forever?
Andreas Welsch (16:12):
That's such a great overview.
I've brought generative AI ininto the classroom where I teach
undergrads in business, how dowe actually use these tools?
In last fall, we talked aboutprompting techniques, and we
talked about ChatGPT andAnthropic, and probably half of
the class, maybe a little lessthan half, said yes I've used
these tools before, but I wouldlove to learn more how I use
(16:35):
them properly.
This spring, 95% of students inthe class raised their hand when
I asked who's used it before,and they said can we move on and
not talk so much about promptingtechniques and, what else can I
do with it?
So on one hand right there,there's this incredible
trajectory that even studentsand, younger people are on to
(16:56):
incorporate that into theirdaily work.
And we need to talk a lot aboutresponsible use.
And there's some good studiesabout your brain on ChatGPT,
what do you actually retain andlearn?
But the interesting part therefor me was when I said can you
create, for example a, samplequestions that a recruiter might
(17:16):
ask you about a certain job thatyou might apply for as an
intern?
And, then I asked them, what doyou think about the response?
How was chat, GT's response orcloud's response?
And my students said it wasgood.
And I said what do you mean?
It was good?
Oh, yeah.
It, gave me what I asked.
I got a list of questions.
Okay.
Are the questions specific?
(17:37):
Are they helpful?
Do you think they will ask youand they said I don't know.
Yeah, I think they're good.
So what I realized is similar towhat you shared, that depending
on your expertise and, I'mseeing this in corporate
trainings a lot whereprofessionals are able to
discern, is this good quality?
Is this okay?
Or is it really bad?
Unless you have a rule rubric orsome kind of a reference frame
(17:59):
of what does good actually looklike?
It's really, hard to discern.
Is this actually valuable,useful, good, or is it just
finer total garbage?
So that value of expertise andexperience, what you mentioned,
I think is incredibly important.
And to me that's a starkcontrast with this push that
(18:19):
we're seeing from some companiesand some leaders as well, we
want to be AI first.
We want to lead with AI.
We will do everything with AI.
And if AI cannot do it, onlythen we hire people or we hire
people back.
And you already have people inyour company and they're very
knowledgeable.
They know a lot about yourbusiness.
They have a lot of tacitknowledge.
So to your point, how can youaugment them with the right
(18:40):
tools and leverage theirexpertise?
I think that's criticallyimportant.
And I also feel a lot of timeswe talk so much about
leadership, but sometimes it, onone hand loses the meaning.
Or sometimes we also know thatthey're great leaders and
they're leaders, they're not asgood as they could be.
(19:00):
So specifically looking for teammembers that might need a little
more help or that are on theleading edge of things, how do
you bring them in?
I feel from a leadership pointof view, that changes the game
for you of how you need toassess and, decide again, who.
Should I nurture a little moreand give a little more guidance.
(19:21):
How can team members collaboratewith each other?
Again, who's more leading, whocan bring some information back
to the team?
So a lot of the soft skills andsoft factors I feel, and
interpersonal factors play a lotbigger role when you grow.
Alison McCauley (19:34):
And you know what?
The sort of the pro move herethat's so easy that anyone can
do is and you mentioned it withthe students, is.
Learning how to use AI as athought partner.
So it's the use case that canhelp anybody with any challenges
that they have.
And so even the one that yououtlined for leaders, where do I
(19:55):
start?
How do I understand how toactivate different members of my
team around it?
So if you learn how to use AI asa thought partner, as and you're
really interacting with AI as ifit is a incredible.
Peer or expert in differentareas and you're using it to
push your thinking and you'recontinuing to evolve that you
(20:17):
can unlock all kinds of newlevels of your own brain and
expertise.
You mentioned the studies thatwe're seeing where, AI in some
studies has shown they canbasically dumb you down.
But there's a juncture here.
AI can make you dumber or it canmake you smarter.
It's all about how you use it.
(20:38):
I, yeah, I had an interestingexample with a students.
What I tell them to do whenthey're interviewing for jobs is
go out and upload someinformation, the job
description, your resume.
Upload to AI, ask it to ask youthose hard, develop a bunch of
hard questions to ask you.
Then record yourself using AI.
(20:59):
Record yourself giving theanswers, and then have AI
evaluate that.
Do that three times now, seewhat happens.
So it's that thought partnershipand anyone can apply that to
anything and you build AI musclein the process.
Andreas Welsch (21:12):
I see we're thinking a lot alike that there
was one of the one of theexercises that I gave to my
students as, as well use it as asparing partner as, a coach, as
an interview coach.
So you develop confidence and,you see where are some areas
that you can improve upon.
And by the way what applies to,students.
And early in, in careerindividuals also applies to
professionals and leaders alike,looking to stand out in this
(21:34):
crowded job market.
Alison McCauley (21:35):
Yeah.
And frankly all the way up tothe CEO Yeah.
Andreas Welsch (21:38):
To use this as a thought partner.
Alison McCauley (21:39):
So I have clients that use it to pregame
their board presentations.
Yeah.
It's a fantastic use.
Yeah.
And this one anyone can dotoday.
Andreas Welsch (21:49):
I think that's one of the beautiful things
about it, right?
It's right at the editor orfingertips where you don't have
to be a trained mathmathematician, a statistician.
You don't need to have a PhD touse these tools anymore.
They're on your phone.
Go ahead, use them, obviously,use'em safely, responsibly.
Don't put confidential data inthere.
All the guardrails andboundaries that we need to set,
but it's there.
You can use it.
You can use it at the dinnertable if you want.
Alison McCauley (22:10):
Please do you know there's a flip side to
this.
Yeah.
So when we are confronted withtoo many choices, we tend to
freeze.
Have you ever had that happenwhere
Andreas Welsch (22:19):
Oh yeah.
Alison McCauley (22:20):
Yeah.
So this is called the paradox ofchoice.
And what happens is we actuallyhave this with AI because we are
used to technology.
What it does that's dictated bythe technologist, right?
It's dictated by the app.
All of a sudden you sit in frontof AI, what happens is people
freeze.
They have no, no idea what to,where to start.
And that's part of the challengeis how do we how do we know what
(22:47):
to engage?
How do we know where to start?
And so that's the one of thefirst things to do.
It's really focus in on whereit's gonna make a difference for
You
Andreas Welsch (22:56):
I love how practical your suggestions have
been so far throughout ourconversation.
I want to take us in into anegative rabbit hole, but I'm
looking for, some additionalpractical thoughts from you as
well, because I know a lot ofleaders are, also concerned
about.
What AI or agent AI means fortheir jobs, right?
Will I eventually have a smallerspan of control?
(23:17):
Are we not going to backfillroles with humans?
Am I having, are going to havea, lower personnel budget, but a
larger technology budget in OPEXbudget to, to spend on a
technology?
And, again, what does it mean,right?
When a lot of times I feel,especially in large
organizations.
Influence and status.
So much depends on how manypeople do you manage and do you
(23:40):
lead, do you have 5 50, 500,5,000?
How do you feel that the leaderscan prepare themselves?
Right now, you already gave somegood examples, but what would
you say to leaders who areconcerned about what does all
that AI change mean for me andfor my role, whether I'm at
first level, leadership,mid-level, or even senior
(24:01):
leadership.
Alison McCauley (24:02):
I've heard that concern from several different
areas about how do we measureleaders when it's no longer
about the number of people theymanage?
That's what our structure Yes.
Have long done.
So that's, that is a fear that'sout there.
That is a concern.
And so what I have observed isthat there's, a, what I've
(24:31):
noticed is that people often gointo the conversation about AI.
They're, like, okay, we know weneed to learn about it, but
they're coming in it, at, evenat an executive level with a lot
of fear about true what truly,what does it mean to me that the
emphasis on expertise and theimportance of expertise is a bit
of an unlock because all of asudden people understand that we
(24:52):
can, w we, need our expertise.
Yes, the expertise across myteams, we still need.
The other piece is when you gethands-on and I have a workshop
methodology that I've used thathas worked really well, I.
To help leaders go fromskepticism to actually a path
(25:14):
forward, to navigate the usecase or a perspective on the use
cases that are really gonna makea difference in their business
and how to make those firststeps in just a few hours when
you get to the point whereyou're thinking about your
business problems and how tosolve them with AI, and you can
collaborate as a thought partnerwith AI to do that.
(25:35):
That's where you see the shiftand all of a sudden it's wait a
minute.
I can solve these perennialproblems because of it, and I
can help with my team.
I can reimagine what a role isabout and how I can better serve
my customers or.
To build better products andservices because of this.
(25:56):
I'll give an example.
I was working with a team wherewe were actually the,
organization wasn't aware ofreally the kind of change that
was happening in the middlelevel of their organization with
AI.
And so they decentralizedinnovation.
I recommended a combination ofdecentralized and centralized
innovation around AI.
(26:16):
They'd done the decentralizationwork so people were equipped
with tools.
So one thing that we were doingis mapping out where are the
people who are using it in waysthat are effective, because a
lot of organizations don't evenknow how it's being used.
And I found a woman who hadworked with it was it, they had
(26:37):
a service that was a very costlycustom quote process.
It took weeks of back and forth.
So she created a tool usingClaude that enabled that work to
be done in a matter of hours.
So then I dug into her, with herabout w.
How'd the team feel?
Because all of a sudden thisthis team that had been doing
(27:00):
the custom quotes had beenspending weeks of time, and now
it's just hours.
Yeah.
Their job could disappear.
But of course they were excitedabout it in this situation
because now all of a sudden theycould spend all their time on
developing more strategic Yes.
Relationships.
Yeah.
So that's where that's where wecan start to see these kinds of
(27:21):
differences.
Andreas Welsch (27:23):
I love it.
I love the positive that is inthese transformations as well.
And thinking about the clientthat you mentioned, if you
previously spent weeks creatingthese custom quotes.
Now, it's a matter of hours.
So how many more quotes can youcreate in that same amount of
time?
Meaning how many customers inaddition can you serve or can
(27:43):
you serve more quickly?
Alison McCauley (27:45):
How deeper can you serve those customers?
Andreas Welsch (27:47):
Yeah.
Yes, that too, right?
So it's not just about how canwe now repurpose or reduce the
number of people that we have,because we still plan for that
same volume of custom quotes.
But what else can we do forbusinesses and for leaders like
to suss out what else can we doand, again, what can we deliver
in terms of value in customersatisfaction in that sense.
(28:09):
Now, Alison, we're getting closeto the end of the show and I was
wondering if you could summarizethe key three takeaways for our
audience today.
Alison McCauley (28:15):
Yeah, so I would say very clearly jump in
if you haven't already.
So that's that's number one.
Get hands on.
Really get hands on.
The other thing is really leaninto the expertise in your
organization.
Equip your experts with AI,enable them and help them chart
a path to how they're going toamplify their value through AI.
(28:39):
It's a huge opportunity.
And the next thing is, leadersshould really lean into
imagining and dreaming what isnow possible with these tools.
It's not just about automatingwhat we're already do doing,
it's about rediscovering,reimagining what's possible
(29:02):
because of these tools.
Andreas Welsch (29:04):
I love them, right?
It's all about dreaming big,getting hands on, experiencing
for yourself what it can do, andhelping those around you have
the same en enlighteningexperience as well.
Alison McCauley (29:14):
Yeah, there's a lot here.
There's a huge opportunity herefor those that are ready to jump
in.
Andreas Welsch (29:20):
Perfect.
Alison, thank you so much forjoining us and for sharing your
experience with us.
I've really enjoyed ourconversation.
Alison McCauley (29:26):
I love talking to you.
It's so great.
Today we'll talk about how to lead when AI
creates uncertainty in theworkplace, and who better to
talk about it than someone who'shelping companies develop
digital strategies and leadinnovation around AI, Alison
McCauley.
Hey Alison.
Thank you so much for joining.
Alison McCauley (00:14):
I've been looking forward to this
conversation.
Andreas Welsch (00:16):
Awesome.
That makes two of us.
And I hope for those of you inthe audience, you're just as
excited as we are, but Alison,maybe not everybody in the
audience knows you, yet.
Why don't you tell us a littlebit about yourself, who you are
and what you do?
Alison McCauley (00:28):
Sure.
I have spent my entire career atthis really exciting
intersection of emergingtechnology and human behavior.
So how it affects emergingtechnology affects us as people,
as individuals, and asorganizations, as teams, as
culture and society.
(00:49):
And so I have to say it's neverbeen more interesting than it is
right now.
I begin my career at the whenthe field of change management
was just forming.
And it's been fascinating to seehow some things have stayed the
same since those early days whenwe were really literally writing
(01:09):
the playbook for changemanagement.
And some things are brand newand it, I started working in AI
in 2010.
Very different times, verydifferent kind of space.
And so it's been reallyfascinating how things have
changed over these last coupleyears.
And it is truly a whole new areathat needs to be navigated.
(01:31):
And so that's why this topicthat we're talking about today
is the topic of, the era.
Andreas Welsch (01:37):
Wonderful.
I couldn't agree more.
There's so much talk about techin bringing it to the business,
but at the end of the day, hey,there, there's still people
there that need to adopt it,that need to get comfortable
with it, that also need to helpother people manage the change
and lead through it when youknow.
Probably very few of us have theanswer of what does it mean,
where are we going?
(01:57):
So I'm looking forward todigging a little deeper there
and learning from you and fromyour insights.
Alison McCauley (02:03):
Wonderful.
Yeah.
Andreas Welsch (02:04):
Why don't we play a little game to kick
things off.
What do you say?
Alison McCauley (02:07):
A little improv maybe.
Andreas Welsch (02:09):
A little improv.
Exactly.
When I hit the buzzer, thewheels will start spinning and
you'll see a sentence I'd likefor you to answer with the first
thing that comes to mind andwhy, in your own words, to make
it a little more interesting.
You only have 60 seconds foryour answer.
For those of you watching uslive, please drop your answer
and why in the chat as well.
Alison, are you ready for,What's the BUZZ?
Alison McCauley (02:30):
Let's do it.
Andreas Welsch (02:31):
Okay.
Let's see.
Here we go.
If AI were a color, what wouldit be and why?
Alison McCauley (02:41):
Wow.
Okay there's some colors thatare that are yet to be
discovered.
And we hear about theseoccasionally and I have a
feeling that AI is a color thatwe haven't quite seen yet.
It's forming.
Andreas Welsch (03:02):
Oh, love it.
Alison McCauley (03:04):
So I think, we'll, we can't turn, I think,
to what we already know.
I think it's gonna be somethingthat is new that we all
discover.
Andreas Welsch (03:13):
Wonderful.
I like that.
You know what, when I ask mychildren, what's your favorite
color?
The answer I've recently beengetting is: rainbow.
All the colors of the rainbow.
I love rainbow color.
So definitely, there's a lot tobe discovered.
And I was lucky Il and I feellike the colors can change very
quickly as well as things evolveand adapt.
Alison McCauley (03:35):
Yeah.
And these analogies actually arereally apt, because AI is
adapting and changing so quicklyand there's so much to be
discovered that we're alldiscovering together because
this new acceleration is so new.
Yeah.
Andreas Welsch (03:50):
This newness and this newness factor also creates
a lot of uncertainty and a lotof changes.
We, we've seen in the lastcouple weeks a lot of coverage
about how recruiting for entrylevel jobs is slowing down
because of AI driven automation.
Companies are looking to do morewith AI, more entry level tasks,
things that are a little morecomplex than if this happens,
(04:11):
then do that.
Great.
Yes, AI can do that.
AI can also help professionalsand senior experts on more
complex tasks.
So we'll likely see this trendgoing up the hierarchy, if you
will, or seniority levels ofwhat AI can do.
And that also creates a goodamount of uncertainty and fear
about jobs, not just AI.
I just graduated where I find ajob.
(04:32):
Those are some of theconversations that I'm having
with students where I teach asan adjunct, but also more senior
professionals.
What are you seeing when youtalk to leaders in organizations
about these topics?
What AI means for jobs fororganizations?
What are people seeing?
Alison McCauley (04:46):
Yeah.
There's a big disconnect betweenwhat is possible and, what has
been newly unlocked with AI andwhere organizations are right
now?
So when I talk to differentorganizations, I travel around
the world giving talks andworkshops.
There's a range of where peopleare.
(05:09):
If I may on Andreas, be verydirect through your, viewers
are, okay with that.
I just wanna be really direct atevery.
Job is going to change everyjob.
So CEO jobs are gonna change.
Middle management jobs are gonnachange.
Entry-level jobs are gonnachange, and we haven't quite
(05:30):
ingested that and we haven'tquite.
We haven't quite taken that inand we certainly don't know yet
exactly how they will change.
Some are gonna adjust, some willadjust to this.
Some people will adjust to this.
Some organizations will adjustto this.
Some teams will, adjust to thisand some just won't.
And some jobs.
Will disappear and new jobs willbe created, and we just don't
(05:55):
know exactly how.
And we've seen shifts like thisbefore.
So the industrial revolutionbefore, before the Industrial
Revolution, we were a largelyagrarian economy.
And that shifted and everysingle role, every single job,
every single industry changed.
And now we're at the beginningof this cognitive revolution.
(06:17):
But we don't know where it'sheaded.
And when you look back at theindustrial Revolution, it's
almost like it unfolded withthis like choreography that was
so well orchestrated, but ithappened over 80 years.
And now what we're seeing is inthe matter of just a few years,
or even in some cases a fewquarters, it's it's changing
(06:39):
fast.
And so that, that throws peoplefor a loop.
And what I see when I, when I.
Talk to organizations is that noone's figured this out yet.
We're all, figuring this outtogether.
Those that are better equippedto see what's happening at that
front edge of change are thosethat have their hands in it and
(07:00):
are leaping into the unknown.
So I really advocate for thatbecause you need to see change
as it happens.
The best way is to get yourhands in it and really work to
understand it.
Andreas Welsch (07:13):
I love that call to action, right?
A lot of times it's really aboutseeing and feeling so that on
one hand you can either believeor you can also understand.
What does it actually mean?
What does it do?
What are the opportunities?
What are maybe some of thechallenges where this sounds
more like a big promise, but Iknow that here could be some
some holes that we might runinto.
(07:35):
It's also been a couple decadessince we've changed how
switchboards work andswitchboard operators, right,
that were superseded bytechnology or people pressing
the button for you in theelevator.
And must say it was in New YorkCity the other day for a tech
event and there was actually aperson pressing the right button
on the elevator.
So we got off on the rightfloor.
(07:55):
But we know that these are moreexceptions these days than, the
norm.
But I also feel that from theindustrial revolution some of
the robotics in the seventies inmany other evolutions it feels
like it's never been that fastor also it's been so far and so
long ago that very few of usactually relate to this.
(08:16):
So for our generation now in theworkforce in those going into
the workforce, this is reallynew.
It's the first time that thereis such a big monumental change
that's happening with us and tous.
Alison McCauley (08:26):
It's fascinating.
We forget every single timethere's a transformative
technology.
We forget how how much itchanges us and also how every
single change of that magnitudecomes with a combination of fear
and excitement.
So you mentioned elevatorbuttons.
You know when, things were firstelectrified, when electricity
(08:49):
first.
Came to us.
It was met with fear andexcitement.
The president of the UnitedStates, when electricity was
first installed in the WhiteHouse, would not switch the
lights on.
He had his staff do it'cause hewas scared of it.
It's just, it's thatcombination.
It's just that it's hurtlingtowards us so fast.
And that's also because it'schanging so quickly.
(09:11):
That's why it's important to bein it because things change.
Sometimes week to week, butdefinitely quarter to quarter.
And if you're not in it, youdon't see it.
Someone else, your competitormight, that's very true.
Andreas Welsch (09:26):
We're seeing that a lot and even competitors
that are not even born yet arejumping on this.
And, will at some point we'll gointo spaces that are
underserved.
But I'm curious what do yourecommend in addition to getting
hands-on how can leaders supportthe teams and organizations on
this journey?
And, maybe right from a team toorg unit, company level.
(09:47):
There many different layers ofof, that complexity if you will,
how can leaders under supporttheir organizations?
Alison McCauley (09:57):
So that's such a huge question.
I have several differentmethodologies to get at
different angles of that.
And so I'll give some hints onsome of those or over summer of
some of those.
But then I also wanna talkbigger picture about it as well.
'cause there's, a lot ofopportunity to step back and
think about it.
(10:18):
As I mentioned earlier, I havebeen, working in change
management and digital changesince the very beginning of that
profession when it was firstcodified into a formal
profession.
And a lot of the lessons that wedeveloped in some of our first
(10:38):
playbooks are still valid.
And so what's really critical?
Is to meet people where theyare.
So people all across yourorganization are all different
levels of understanding ofwhat's happening in this
organization.
We need to meet people wherethey are.
So you need to understand wherethey are, and you've got people
in your organization who are.
(10:59):
Maybe even using this in theirpersonal lives to do all kinds
of exciting things.
That's incredible expertise thatyou can tap into.
These are passionista that couldbe nurtured into change agents.
And so mapping in yourorganization, who's using what?
Where's the passion, where's theunderstanding is one way to
start to.
Bring your organization to buildthe AI muscle of your
(11:21):
organization.
Another piece that we couldtalk, about a lot more is how
you connect to value.
So we tend to talk about AI astechnology.
Of course it's a technology, butthe real opportunity and where
the unlocks really happen in anorganization are when we start
talking about.
What is the real business needthat you have in your
(11:44):
organization and focus there.
So put aside the technology.
Focus on where the business needare.
What could we do withoutconstraints?
What what would we do if wecould remove blocks and barriers
that we have today?
What would we be able toachieve?
And then start the AIconversation from that focal
(12:05):
point.
So that's about really showingpeople how to get to value in
it.
That changes everything.
And the other piece is aboutreally patiently showing people
the way this always takes longerthan people think.
Once you understand AI, youthink, oh, everybody gets this.
It's so obvious'cause you getbombarded in your echo chamber
(12:27):
around AI.
But.
Truly people need a long time tobe able to understand how to
move in that direction.
And so I emphasize a, wholearsenal of change, manage
techniques around being able tocreate learning circles.
And sharing networks,storytelling, feedback loops.
(12:49):
So there's a whole bunch oforganizational mechanisms that
we can put in place that have ahuge impact.
So anyway, those are some of thelittle summary of some tips and
tricks.
But just to bump it up a level,I'd say that, so when I give
talks, one of the big.
Surprises that a lot of leaderstell, a lot of leaders tell me
(13:11):
they were surprised byafterwards in, the q and a and
the discussions are howimportant expertise is in this
moment.
We're in a world where AI cangenerates a lot of it mixed
things up.
It can, it still hallucinates,right?
And only your experts in theorganization can really
(13:33):
identify.
AI garbage for what it is.
'cause it presents it in a waythat feels really great.
You were talking earlier aboutentry level and some of the
challenges for entry level.
People without the experiencecan't identify AI slop and AI
(13:54):
junk for what it is.
It's your experts that can, soyour experts are the one who can
understand how do we leveragethis technology?
And you have experts all overyour organization at every
single level, every singlefunctional area, every single
department.
And being able to equip yourexperts with the knowledge to
use AI is what unlocks theopportunity.
(14:16):
They're able to navigate thesystems and no matter what
organization at this point intime, you probably could use
more expertise.
And so if you experts understandhow to use AI to amplify the
knowledge they have, if they'reable to really, truly.
(14:36):
Orchestrate these systems tomake it work In that way, you un
you amplify your expertise.
And so that's so much of theopportunity around here.
And then the other thing that Iwould really encourage leaders
to do, and this takes some time,is that we have there's an
opportunity in this moment, notjust to automate.
Today's AI is not just aboutautomation and we have 30 years
(15:01):
of experience.
With automation more than 30years, but like a real focus
around 30 years of, expertisearound automation that works in
a certain way.
This new AI allows us to dothings in a completely different
way, so we need to, dig into ourimagination around reimagine
(15:25):
what we can accomplish and whatwe can achieve as humans in an
organization because we now havethese capabilities, and right
now there's a real.
Deficit of imagination.
We're not tapping into that.
We're in reactive mode.
We're not in, in in, this spacewhere we're really understanding
how could we go next level?
(15:46):
What new products and servicescan we introduce?
What new industries can wecreate?
Because we now have these tools.
And so that's the other pieceis.
To really tap into what's this?
What can we make out of this?
What can we do when we no longerhave the cognitive limitations
(16:08):
that organizations have beengoverned by forever?
Andreas Welsch (16:12):
That's such a great overview.
I've brought generative AI ininto the classroom where I teach
undergrads in business, how dowe actually use these tools?
In last fall, we talked aboutprompting techniques, and we
talked about ChatGPT andAnthropic, and probably half of
the class, maybe a little lessthan half, said yes I've used
these tools before, but I wouldlove to learn more how I use
(16:35):
them properly.
This spring, 95% of students inthe class raised their hand when
I asked who's used it before,and they said can we move on and
not talk so much about promptingtechniques and, what else can I
do with it?
So on one hand right there,there's this incredible
trajectory that even studentsand, younger people are on to
(16:56):
incorporate that into theirdaily work.
And we need to talk a lot aboutresponsible use.
And there's some good studiesabout your brain on ChatGPT,
what do you actually retain andlearn?
But the interesting part therefor me was when I said can you
create, for example a, samplequestions that a recruiter might
(17:16):
ask you about a certain job thatyou might apply for as an
intern?
And, then I asked them, what doyou think about the response?
How was chat, GT's response orcloud's response?
And my students said it wasgood.
And I said what do you mean?
It was good?
Oh, yeah.
It, gave me what I asked.
I got a list of questions.
Okay.
Are the questions specific?
(17:37):
Are they helpful?
Do you think they will ask youand they said I don't know.
Yeah, I think they're good.
So what I realized is similar towhat you shared, that depending
on your expertise and, I'mseeing this in corporate
trainings a lot whereprofessionals are able to
discern, is this good quality?
Is this okay?
Or is it really bad?
Unless you have a rule rubric orsome kind of a reference frame
(17:59):
of what does good actually looklike?
It's really, hard to discern.
Is this actually valuable,useful, good, or is it just
finer total garbage?
So that value of expertise andexperience, what you mentioned,
I think is incredibly important.
And to me that's a starkcontrast with this push that
(18:19):
we're seeing from some companiesand some leaders as well, we
want to be AI first.
We want to lead with AI.
We will do everything with AI.
And if AI cannot do it, onlythen we hire people or we hire
people back.
And you already have people inyour company and they're very
knowledgeable.
They know a lot about yourbusiness.
They have a lot of tacitknowledge.
So to your point, how can youaugment them with the right
(18:40):
tools and leverage theirexpertise?
I think that's criticallyimportant.
And I also feel a lot of timeswe talk so much about
leadership, but sometimes it, onone hand loses the meaning.
Or sometimes we also know thatthey're great leaders and
they're leaders, they're not asgood as they could be.
(19:00):
So specifically looking for teammembers that might need a little
more help or that are on theleading edge of things, how do
you bring them in?
I feel from a leadership pointof view, that changes the game
for you of how you need toassess and, decide again, who.
Should I nurture a little moreand give a little more guidance.
(19:21):
How can team members collaboratewith each other?
Again, who's more leading, whocan bring some information back
to the team?
So a lot of the soft skills andsoft factors I feel, and
interpersonal factors play a lotbigger role when you grow.
Alison McCauley (19:34):
And you know what?
The sort of the pro move herethat's so easy that anyone can
do is and you mentioned it withthe students, is.
Learning how to use AI as athought partner.
So it's the use case that canhelp anybody with any challenges
that they have.
And so even the one that yououtlined for leaders, where do I
(19:55):
start?
How do I understand how toactivate different members of my
team around it?
So if you learn how to use AI asa thought partner, as and you're
really interacting with AI as ifit is a incredible.
Peer or expert in differentareas and you're using it to
push your thinking and you'recontinuing to evolve that you
(20:17):
can unlock all kinds of newlevels of your own brain and
expertise.
You mentioned the studies thatwe're seeing where, AI in some
studies has shown they canbasically dumb you down.
But there's a juncture here.
AI can make you dumber or it canmake you smarter.
It's all about how you use it.
(20:38):
I, yeah, I had an interestingexample with a students.
What I tell them to do whenthey're interviewing for jobs is
go out and upload someinformation, the job
description, your resume.
Upload to AI, ask it to ask youthose hard, develop a bunch of
hard questions to ask you.
Then record yourself using AI.
(20:59):
Record yourself giving theanswers, and then have AI
evaluate that.
Do that three times now, seewhat happens.
So it's that thought partnershipand anyone can apply that to
anything and you build AI musclein the process.
Andreas Welsch (21:12):
I see we're thinking a lot alike that there
was one of the one of theexercises that I gave to my
students as, as well use it as asparing partner as, a coach, as
an interview coach.
So you develop confidence and,you see where are some areas
that you can improve upon.
And by the way what applies to,students.
And early in, in careerindividuals also applies to
professionals and leaders alike,looking to stand out in this
(21:34):
crowded job market.
Alison McCauley (21:35):
Yeah.
And frankly all the way up tothe CEO Yeah.
Andreas Welsch (21:38):
To use this as a thought partner.
Alison McCauley (21:39):
So I have clients that use it to pregame
their board presentations.
Yeah.
It's a fantastic use.
Yeah.
And this one anyone can dotoday.
Andreas Welsch (21:49):
I think that's one of the beautiful things
about it, right?
It's right at the editor orfingertips where you don't have
to be a trained mathmathematician, a statistician.
You don't need to have a PhD touse these tools anymore.
They're on your phone.
Go ahead, use them, obviously,use'em safely, responsibly.
Don't put confidential data inthere.
All the guardrails andboundaries that we need to set,
but it's there.
You can use it.
You can use it at the dinnertable if you want.
Alison McCauley (22:10):
Please do you know there's a flip side to
this.
Yeah.
So when we are confronted withtoo many choices, we tend to
freeze.
Have you ever had that happenwhere
Andreas Welsch (22:19):
Oh yeah.
Alison McCauley (22:20):
Yeah.
So this is called the paradox ofchoice.
And what happens is we actuallyhave this with AI because we are
used to technology.
What it does that's dictated bythe technologist, right?
It's dictated by the app.
All of a sudden you sit in frontof AI, what happens is people
freeze.
They have no, no idea what to,where to start.
And that's part of the challengeis how do we how do we know what
(22:47):
to engage?
How do we know where to start?
And so that's the one of thefirst things to do.
It's really focus in on whereit's gonna make a difference for
You
Andreas Welsch (22:56):
I love how practical your suggestions have
been so far throughout ourconversation.
I want to take us in into anegative rabbit hole, but I'm
looking for, some additionalpractical thoughts from you as
well, because I know a lot ofleaders are, also concerned
about.
What AI or agent AI means fortheir jobs, right?
Will I eventually have a smallerspan of control?
(23:17):
Are we not going to backfillroles with humans?
Am I having, are going to havea, lower personnel budget, but a
larger technology budget in OPEXbudget to, to spend on a
technology?
And, again, what does it mean,right?
When a lot of times I feel,especially in large
organizations.
Influence and status.
So much depends on how manypeople do you manage and do you
(23:40):
lead, do you have 5 50, 500,5,000?
How do you feel that the leaderscan prepare themselves?
Right now, you already gave somegood examples, but what would
you say to leaders who areconcerned about what does all
that AI change mean for me andfor my role, whether I'm at
first level, leadership,mid-level, or even senior
(24:01):
leadership.
Alison McCauley (24:02):
I've heard that concern from several different
areas about how do we measureleaders when it's no longer
about the number of people theymanage?
That's what our structure Yes.
Have long done.
So that's, that is a fear that'sout there.
That is a concern.
And so what I have observed isthat there's, a, what I've
(24:31):
noticed is that people often gointo the conversation about AI.
They're, like, okay, we know weneed to learn about it, but
they're coming in it, at, evenat an executive level with a lot
of fear about true what truly,what does it mean to me that the
emphasis on expertise and theimportance of expertise is a bit
of an unlock because all of asudden people understand that we
(24:52):
can, w we, need our expertise.
Yes, the expertise across myteams, we still need.
The other piece is when you gethands-on and I have a workshop
methodology that I've used thathas worked really well, I.
To help leaders go fromskepticism to actually a path
(25:14):
forward, to navigate the usecase or a perspective on the use
cases that are really gonna makea difference in their business
and how to make those firststeps in just a few hours when
you get to the point whereyou're thinking about your
business problems and how tosolve them with AI, and you can
collaborate as a thought partnerwith AI to do that.
(25:35):
That's where you see the shiftand all of a sudden it's wait a
minute.
I can solve these perennialproblems because of it, and I
can help with my team.
I can reimagine what a role isabout and how I can better serve
my customers or.
To build better products andservices because of this.
(25:56):
I'll give an example.
I was working with a team wherewe were actually the,
organization wasn't aware ofreally the kind of change that
was happening in the middlelevel of their organization with
AI.
And so they decentralizedinnovation.
I recommended a combination ofdecentralized and centralized
innovation around AI.
(26:16):
They'd done the decentralizationwork so people were equipped
with tools.
So one thing that we were doingis mapping out where are the
people who are using it in waysthat are effective, because a
lot of organizations don't evenknow how it's being used.
And I found a woman who hadworked with it was it, they had
(26:37):
a service that was a very costlycustom quote process.
It took weeks of back and forth.
So she created a tool usingClaude that enabled that work to
be done in a matter of hours.
So then I dug into her, with herabout w.
How'd the team feel?
Because all of a sudden thisthis team that had been doing
(27:00):
the custom quotes had beenspending weeks of time, and now
it's just hours.
Yeah.
Their job could disappear.
But of course they were excitedabout it in this situation
because now all of a sudden theycould spend all their time on
developing more strategic Yes.
Relationships.
Yeah.
So that's where that's where wecan start to see these kinds of
(27:21):
differences.
Andreas Welsch (27:23):
I love it.
I love the positive that is inthese transformations as well.
And thinking about the clientthat you mentioned, if you
previously spent weeks creatingthese custom quotes.
Now, it's a matter of hours.
So how many more quotes can youcreate in that same amount of
time?
Meaning how many customers inaddition can you serve or can
(27:43):
you serve more quickly?
Alison McCauley (27:45):
How deeper can you serve those customers?
Andreas Welsch (27:47):
Yeah.
Yes, that too, right?
So it's not just about how canwe now repurpose or reduce the
number of people that we have,because we still plan for that
same volume of custom quotes.
But what else can we do forbusinesses and for leaders like
to suss out what else can we doand, again, what can we deliver
in terms of value in customersatisfaction in that sense.
(28:09):
Now, Alison, we're getting closeto the end of the show and I was
wondering if you could summarizethe key three takeaways for our
audience today.
Alison McCauley (28:15):
Yeah, so I would say very clearly jump in
if you haven't already.
So that's that's number one.
Get hands on.
Really get hands on.
The other thing is really leaninto the expertise in your
organization.
Equip your experts with AI,enable them and help them chart
a path to how they're going toamplify their value through AI.
(28:39):
It's a huge opportunity.
And the next thing is, leadersshould really lean into
imagining and dreaming what isnow possible with these tools.
It's not just about automatingwhat we're already do doing,
it's about rediscovering,reimagining what's possible
(29:02):
because of these tools.
Andreas Welsch (29:04):
I love them, right?
It's all about dreaming big,getting hands on, experiencing
for yourself what it can do, andhelping those around you have
the same en enlighteningexperience as well.
Alison McCauley (29:14):
Yeah, there's a lot here.
There's a huge opportunity herefor those that are ready to jump
in.
Andreas Welsch (29:20):
Perfect.
Alison, thank you so much forjoining us and for sharing your
experience with us.
I've really enjoyed ourconversation.
Alison McCauley (29:26):
I love talking to you.
It's so great.
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