May 30, 2025 • 29 mins
How can leaders foster a true AI mindset among their teams?
In this episode, host Andreas Welsch illuminates this pressing question with guest Matt Lewis, CEO and Chief Augmented Intelligence Officer of LLMental. Drawing from decades in Data & AI leadership roles in healthcare/ life sciences, Matt shares invaluable insights into how a leadership mindset profoundly influences AI adoption within organizations.
Discover why human factors, rather than just technology, play a crucial role in successful AI integration, and learn practical strategies for empowering teams and demystifying AI.
Whether you're a business leader or just curious about the intersection of AI and leadership, this episode is rich with knowledge to help navigate the complexities of AI transformation.
Ready to elevate your organization's approach to AI? Don't miss this enlightening discussion—listen now!"
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 you can successfully
adopt.
When you have the right mindsetas a leader, and who better to
have talked about it thansomeone who's actively
championing that?
Matt Lewis.
Hey Matt.
Thank you so much for joining.
Matt Lewis (00:13):
Andreas, thank you so much for having me back on
the program.
I'm thrilled to be here.
Being on the show last time wastransformative for me and for my
directions.
I'm so happy to be back with youand with the audience.
Thank you for having me, andthanks for the time for everyone
watching.
Andreas Welsch (00:27):
So great.
You're one of the few that haveactually been on, the show for
three times already and it'salways an enlightening
conversation when you're on.
So I'm really excited for whatwe'll cover today.
But for those of our audiencemembers who might not know you,
maybe you can introduce yourselfreal quick, who you are and what
you do.
Matt Lewis (00:45):
Sure.
Happy to do it.
So my name's Matt Lewis.
I'm founder, CEO and Chief AIOfficer at LLMental.
I've been in healthcare and lifesciences for my whole career,
about 27 years.
I started in data science andadvanced analytics at a firm
that is now AbbVie.
It was Proctor Gamble personalhealthcare at the time.
I've been in artificialintelligence for about 18 years.
(01:05):
Most of that time was not nearlyas fun and exciting as it is
now.
Prior to starting LLMental,about two and a half years ago,
I was Chief ArtificialIntelligence Officer at Inizio
Medical, a large private equityowned life sciences consultancy,
and now progressing forward intothe ecosystem in a kind of
general AI native platform asenterprise organization, solving
those problems that need solvingand helping to improve patient
(01:27):
outcomes.
Andreas Welsch (01:29):
I think that's so I important, such a great
mission.
Especially right in these timeswhen people are wondering what
is it with AI?
Is it going to replace me?
I'm feeling a lot of tension andstress and angst.
Championing the mental wellnessaspect is critical.
I think so.
Super excited to see you dothat.
Now maybe in good old fashion,should we play a little game to
(01:52):
kick things off?
Matt Lewis (01:53):
Sure.
Let's do it.
Andreas Welsch (01:54):
So let's do this.
So this one is called in yourown words, when you or when I
hit the buzzer, the wheels willstarts spinning.
You'll see a sentence.
I would love for you to answerwith the first thing that comes
to mind and why, in your ownwords, to make it a little more
interesting.
You only have 60 seconds foryour answer, so should we go?
Let's do it.
(02:15):
All right, so if AI were a book,what would it be?
60 seconds on the clock
Matt Lewis (02:23):
Bible.
Andreas Welsch (02:24):
Okay.
All right.
And why?
Matt Lewis (02:26):
Cause it is that meaningful and means something
different to everyone, and ittouches your heart, mind, and
soul in ways that are possibleto make you be the best version
of yourself.
Andreas Welsch (02:36):
It's super concise and obviously super in
inspiring too.
Wonderful.
And, with Easter just around thecorner and Passover not too long
ago, right?
Super timely now from, that holyscript if, you will, moving on
to another holy and sacred topicwhich is how do you actually
(03:00):
bring AI into a businesssuccessfully?
And I know you've recently helda workshop at the World Economic
Forum for a large number of CEOsto help them better understand
that.
And I'm just curious, what areCEOs asking these days about AI
when it seems like there's somuch talk chatter and so many
different vendors whispering inthe air.
What are they asking about whenit comes to AI?
Matt Lewis (03:21):
Yeah.
First of all, you know thisopportunity to go and speak to
the World Economic Forum's NewChampions program, which I did
last week, was really thehighlight of my professional
speaking career.
I've been in front of theC-Suite and boardrooms, customer
conferences, professionalassociations, medical groups,
patient advocacy, healthcaredelivery, you name it, I've done
it.
(03:42):
But this was really a specialyou opportunity to engage with
this community.
The folks that were in assemblywere world leaders, business
executives some allied closelywith heads of state really
moving the ball of innovationand responsibility up the hill.
And it was a really humblingexperience.
Everyone was there by choice andwas there fully attentive and
(04:05):
engaged and you speak, I knowAndreas at conferences and the
rest.
And it's not always the casethat you're in front of an
audience that's A, payingattention and B actually wants
to take what you're saying backto their place of work and.
Make it help their people andhelp their people do better and
be better as a result.
And being in an environment likethat was really quite wonderful.
(04:27):
I, was fortunate enough to bepart of the program before I was
actually on the stage and,stayed around for what followed,
and it was amazing discussionabout global public health and
global economy, geopolitics.
And the time that we're in rightnow across the.
The world's trajectory is an,interesting one.
Having informed citizensglobally is, critical that we
(04:49):
think about where we are andwhere we're going.
So it was really just a, delightbeing amongst that group.
I think one thing that wasreally interesting is that the,
group there was all like, veryinterested in augmented
intelligence, understandingwhere AI is and where it's
going.
They're all adopting andutilizing artificial
intelligence in their businessesand their places of work.
(05:11):
Many had experience with RPA.
They have a history and a legacywhere they've seen automation be
helpful in some regards and beendoing things like copilot and
other implementations in theircurrent environments right now.
But like many of us maybe notseeing the full benefit of a
full AI transformation that theywould like to see, but not quite
(05:32):
understanding why.
Really a great group to comeacross and, engage directly
with.
The talk that I gave was reallyfocused on mindset and really
thinking about what proportionof the success of an artificial
intelligence transformation isdue to algorithms.
The models, the platforms, thethings that we're talking about.
(05:53):
What is likely to be acontribution of underlying tech
and the considerations of thebroader kind of digital kind of.
Ecosystem that enterprises arecurrently considering, if you
will.
And then what is the balancethat is really contributed by
people, by leaders, byexecutives, by processes, and by
the other human factors withinthe environment.
(06:15):
And I've been talking about thishuman factors consideration for
a long time.
But there, there is a lot ofresearch now that suggests that.
At least 70% of what makes orbreaks an organization with
regards to AI success isactually people driven.
It is not about the platforms,it's not about the models, it's
not about the algorithms.
It's not about whether they havethe right kind of technology or
(06:37):
technologists on board.
It's really about the directexperience with the, technology
and what their disposition,their mindset their mental
wellness, their considerationsare as they progress forward
into the ecosystem and.
This group was quite interestedin, that consideration and had a
number of kind of questions andthoughts around.
How practically they canunderstand where they are on the
(07:00):
kind of mindset continuum, ifyou will.
And then whether those thingsare even amenable to
intervention.
Does someone just show up with afixed mindset, no pun intended,
and stay there forever.
Or are these things that can betrained, can they be taught?
Can take someone into a workshopand change the way that they
think so they can be a betterleader, be a better manager, be
a better.
(07:21):
Colleague and work better withcustomers, and that was most of
the discussion around what arethe kind of facilitators that
enable success versus thosetypes of barriers or things that
kind of frustrate the ability ofan organization to accrue value.
Andreas Welsch (07:34):
In all that you have shared and I always hear
that passion for the topic and,helping others, helping leaders
understand how they can elevatethemselves and their
organization and their people.
I think that's just sofundamental to the things that
you do.
So hearing what you're sharingand what you've shared with
them, I think is a profound andimpactful message, right?
(07:58):
It depends also on yourleadership and your mindset as a
leader.
How you take that to theorganization, how you show up so
that your people can show up astheir true selves as well.
Matt Lewis (08:10):
Yeah that's really critical and I think it really
can't be overstated both thesubject of what augmented
intelligence is able to enhanceand amplify and extend and
optimize is essentially at thecore of it, it's a people
solution.
What we're really doing istransforming humanity.
We're helping to enable andaugment human potential.
(08:32):
That's really what we're doing.
And at the same time, it is alsoboth subject and object.
It's the people that are helpingothers transform.
We're as leaders in the businessas enterprise executives.
We're the ones that are puttingthat into the world.
The way that we show up, the waythat we are authentic and
vulnerable and come to ourcolleagues in the business is
(08:55):
critical.
I get we, when we run largeworkshops or we implement
technology, when we buildplatforms and we design systems,
how we tell teams of what is nowand what is likely to exist in
the near and far future.
Is critical because theyultimately will decide whether
or not they trust us as leaders,whether they want to work with
(09:15):
or for us, whether or not theycan imagine or envisage a role
for themself in theorganization.
In two months, two weeks, twodays as this technology rolls
out.
And if they don't have thattrust and they don't believe
that we're in it for them.
Then no amount of software orsystems is gonna change that for
them.
So it's, really critical thatwhether we're in healthcare like
(09:36):
myself, or life sciences orhuman services, or really any
business, all our businesses arepeople, businesses.
And the most important thing isthat we connect with the people
in our businesses and try to doright by them.
Andreas Welsch (09:48):
Now doing right by our team members.
It starts also with us asleaders.
And there's so much hype and somuch noise in the market about
AI.
How do you recommend leaders,CEOs determine what is actually
factual and what is justfictional?
Matt Lewis (10:09):
Yeah.
Yeah.
I think this is one of thoseperennial topics within the
augmented intelligenceenvironment that you know I,
think we all kind of wish thatit'll go away, but at the same
time we'll be worried when itdoes go away.
I think you it, lives on, alittle bit of a distribution
curve right there, there is alot of hype.
(10:30):
But now also a couple years intothe generative AI wave, there's
also a lot of hope, and I thinkit's not like that the, these
things are on opposite ends of aspectrum there both together
juxtaposed one right on top ofthe other.
It's it might be the case thatin a large enterprise, like a
large life sciences company, forexample.
There could be a division wherethere's still a tremendous
(10:51):
amount of, hype and they haven'tyet seen that hope.
Maybe because within thatdivision, say like within
continuing medical education orwithin customer services or
within supply chain, theyhaven't yet architected a,
strategy for AI, haven't hired aChief AI Officer, haven't built
a POC or project to see thevalue yet.
(11:11):
So for them, it's stillvaporware and like misty, if you
will.
Whereas within another divisionof the same company, they're
quite mature and they're alreadyprogressing towards the hope
side and see more help than theysee hype.
So it's, not like it's eitherfact or it's kind of fiction.
It's really both end all at thesame time.
It's just not evenly distributedto use a William Gibson kind of
(11:32):
expression where the future ishere, it's just not evenly
distributed.
I and I, it is like that in alot of big enterprises where
there, there is a lot of truevalue being accrued, but it's
not evenly distributed acrossthe whole company.
And you, if you look at onepocket, you might see a lot of
bullshit because people justdon't know any better.
But if you look just down thecorridor, you look at a
(11:53):
different business unit, youlook at different.
They're seeing tremendous impactjust because of where they're in
the market and their stage ofmaturity.
So I think it does take a senseof discipline to understand
where there's alignment betweenstrategy and operations and
people and, culture and otherconsiderations, and also to know
what can actually be done inthis environment.
Andreas Welsch (12:14):
Now I've heard different approaches by,
different leaders how they goabout this.
And, some have shared that theyhave started to catalog the use
of AI in the business thatthey've reached out to different
business units.
That they basically put theirears to the ground, where is AI
actually happening?
Where it being implemented inour large enterprise?
(12:35):
And then find these pockets ofinnovation and elevate them and
say, Hey, look.
This is what's happening maybein Portugal.
This is what's happening in in avaccine division.
That's what's happening in,oncology and so on.
What's your recommendationthere?
How do you bring all of thatinnovation that's happening in
different parts of the companytogether?
(12:55):
Isn't, that the, role of theChief AI Officer?
Or are they overstepping if theytry to elevate that?
Matt Lewis (13:02):
Yeah again, it really depends.
It's not a great answer for, a apodcast and for a wide audience
like this, but it really dependson a number of factors like the
stage of maturity of theorganization itself, like what
their disposition is withregards to transformation whole,
or in part like where whatthey're actually.
Doing with regards to buildingtheir own intellectual property.
Are they of a nature wherethey're building a lot of that
(13:24):
own IP in house?
Are they buying or partnering?
And I think we, when we had thisconversation, you and I, maybe
two years ago the, there wasstill a, healthy consideration
out in many large verticalswhere many firms were building
their own models or actuallybuilding them from scratch or
doing a lot of fine tuning andother kinds of considerations.
(13:44):
Now, I think a lot of the,consideration has shifted from
that.
Almost entirely certainly to agreat degree where unless are
born out of Silicon Valley or ycome or type of consideration to
build entirely from scratch anda large enterprise is not
happening nearly to the degreethat it used to.
And if it is happening, it's notgetting much traction.
So it's a very different worldnow than it was even 18 months
(14:08):
ago because like a weakgenerative is like a quarter in
the real world.
So things just move veryquickly.
And if you don't have the kindof staying power to really.
Turn that into, value, themarket will tell you where
you're, where you need to be.
So I think it, there isdefinitely a thought towards
cataloging use cases and alsoseeing what's working.
(14:31):
I think some of the recentliterature that suggests the
value of native AI withindifferent environments, like the
study from Procter and Gamble,that was shared just recently
outta the the team at Harvardsuggests that even just very
general purpose.
Generative working in concertwith a single person is more
effective than a team of peopleworking without AI.
(14:54):
And there are a number of caseslike where this is happening
across many large organizationswhere they don't even have a
proof of concept or a pilot inplace that just someone's using
GPT, they have something ontheir phone and they're working
now in concert with AI.
Much more efficiently and muchmore effectively than with a
team that is human onlyessentially.
(15:15):
And a lot of this is notcataloged because it's
essentially like secret cyborgshadow IT activity and, the
business doesn't necessarilyneed to catalog all of this, but
I think they need to cultivateit.
They need to encourage it.
They need to ensure that.
The ways of working in 2025become really the soil in which
future work is, encouraged.
Otherwise, people in thosebusinesses will start feeling
(15:37):
like this type of activity isnot condoned.
And if someone is doing thistype of work at AstraZeneca and
they feel like it's notsomething that is helpful with
an environment, they're a veryinnovative shop.
So it's maybe poor example, butanother organization, they might
feel like another.
Life sciences organization is abetter place for innovation and
they might flee to go therebecause it's that's more likely
(15:57):
to speed, time to value for,patients in this regard.
So I think there is a place forleaders within the business to
identify these kind of pillarsof light, if you will, and cast
a spotlight on them and show theorganization.
What good looks like, not somuch to just put a big
spreadsheet together and say,look, we captured this
somewhere, but to really showpeople what good looks like and
(16:19):
find a way to scale thatbrilliance, if you will.
I.
Andreas Welsch (16:22):
I think that's a very practical suggestion,
practical advice right there.
So find the happy medium as,always, between looking for,
these things or even if, youfind them, elevate them, but
don't just make a spreadsheetexercise.
That's awesome.
Now you mentioned somethingearlier and, obviously it's also
the, title of our episode that alot of it has to do with the
(16:46):
leader's AI mindset, how we showup as a leader.
To this transformation to ourorganization, how we bring our
team members in parts of theorganization along.
But what does it actually mean?
What does it mean to have an AImindset as a leader?
Matt Lewis (17:02):
Yeah, it is definitely an evolving concept.
I think Gartner really is one ofthe forebearers of, this, of
consideration in their digitalthinking, digital mindset,
digital dexterity considerationthat they offered maybe about
eight years ago or so, wheredigital thinking is more than
just like skillset and tool set.
It is also mindset.
And in digital mindset, you needto have a proficiency with the
(17:23):
digital systems and skills ofthe organization.
But it's also a way of workingand a lot of it has to do with
the sense of urgency with whichleadership adopts its tactical
and operational practices andthe agility with which they
operate them and can adjust tochanges within the environment
ecosystem.
One quick example of this isthis thought.
(17:44):
A kind of exercise of how onebecomes proficient in generative
AI.
Even as early as like early2023, there was still a lot of
discussion around for likeprofessional services firms like
the, large holding companies,agencies.
I.
Arms length consultancies.
Does it make sense for firmslike that, for example, to build
their own models?
And there were many groupstrying to do that on their own,
(18:06):
if you will.
And then very quickly it becameresonant that perhaps partnering
or buying with a third partymight make more sense to do that
much faster than say thetechnology advances and
innovations that occurred adecade earlier with cloud or a
generation prior with theinternet.
And I think teams that wereflexible and could adapt
(18:27):
quickly.
Recognizing that the market wasshifting under their feet,
didn't make those large capitalinvestments to build technology
that was quickly obsolete, thatthe market didn't need and still
have the resources to invest inthe future, if you will.
Where groups that kind ofcommitted to a, rapidly eroding
past found that really justwasn't creating the
(18:47):
considerations that they neededout the ecosystem.
And it is that mix of.
Having a sense of urgency tostand up a strategy that
actually is reflective of thecurrent consideration
considerations, but also beingflexible and agile to adopt and
adapt as things move forward.
Coupled with really anunderstanding of, what it
actually takes to accrueexperience on the ground.
(19:08):
And I think this is might be alittle bit controversial, but
the, typical ways in which weupskill in artificial
intelligence it, is.
Probably the, most importantresponsibility that a leader in
the business has in the modernera, but it, often isn't given
the proper time and space andthought before it's actually
(19:30):
rolled out to frontline staff.
And I, the reason I say that isthat, that I, you know, when
we've talked and I've shared outin previous commentary and
publications I, use this.
Albert Einstein quote that theonly source of knowledge is
experience.
You know that just doing adidactic training course where
you share a lot of informationabout how Transformers work and
(19:51):
what GPT is and zero shotlearning and all the rest, and
that's helpful to a point.
But if you don't give staff,frontline staff, especially
actual experience in theworkflows that are gonna be
relevant to their jobs, thetasks they're responsible for.
And all you do is give them lotsof modules of courses that help
(20:12):
them understand what artificialaugmented intelligence is
capable of, and then there's alot of daylight between the time
that you train them and the timethey actually apply it to their
work.
The literature in this is veryclear and has been clear now for
the last nine to 12 months.
All that happens is that theirfear levels go up, way up, their
anxiety goes through the roof,and then productivity plummets
(20:33):
between 30 and 40% within thefirst three of months
post-training, and it ends uphaving the exact opposite effect
that upskilling is desired toproduce, which is instead of
them becoming more competent andproductivity improving, it
actually plummets to the pointthat people that are on the
front lines.
Feel like almost that AI isgonna take their job.
They become like terrified ofit.
And then the AI adoption and thetransformation really can't work
(20:57):
because most of the people thathave to do the work are so
fearful that they can't reallydo the work that's required.
And as leaders, we've almostdone this to them.
So it's like the, antithesis ofwhat we desire.
We want people to be embracingand engaging and running
towards.
The machine, if you will, asopposed to running away from the
danger.
But unfortunately, but by justtelling them, look, this is
(21:19):
amazing, and then not givingthem any direct exposure
experience to it, it has theopposite effect.
And we, create a problem thatthen needs to be solved.
Andreas Welsch (21:28):
So two thoughts here.
One is I'm thinking about ananalogy and something like
driving a car comes to mind,right?
You show somebody this is a car.
Here's the steering wheel.
Here are the pedals.
Maybe you shift manually orautomatic, doesn't matter, but
you don't actually let them sitin the car or have them driving
have them have driving lessons.
(21:48):
So you tell'em about driving acar, maybe even a race car.
But by the time that theyactually get to sit in the car,
they're so afraid.
Although they know everythingabout physics and combustion
engines and acceleration andwhatnot did.
They're too afraid to actuallytake the wheel, right?
Matt Lewis (22:03):
Yeah.
It'll be the same type of thing.
If you, if say you rewind backto 1906 and do that exact
demonstration at the same time,you take away their horse and
buggy and you prevent them fromdoing anything in that similar
reign, you, you don't let thembuy another horse.
There's no way that they canproduce they can't do anything
on the farm.
They can't get to town, but youtold'em that the automobile is
(22:25):
coming.
They know that it's gonna takeaway their horse and any mode of
transportation they have.
But they don't actually haveaccess to it.
So all they have is the fearthat everything they have known
since they were a child isdisappearing.
But the new thing isn't thereyet.
So the natural reaction for mostpeople is just to be terrified.
And then in most businesses, youdon't have leaders standing up
and saying, look like I don'thave a crystal ball.
(22:46):
Augmented intelligence is likelyto produce significant value.
The roles might shift, theorganization might evolve.
But it's likely to create newopportunities for everyone here.
And here are some of the thingsthat it might mean for you in
your job in the near future.
And here's the first way ofstarting.
Here's this pilot project thatwe're gonna pull you into, and
we'd love to get your feedbackand perspective, but a lot of
people don't do that in aninterim, you just have people
(23:07):
coming home and they're quitescared.
And as a result that, that fearturns into lots of negative
outcomes for people and forprofessionals.
Andreas Welsch (23:16):
I think all the things that you mentioned that,
we need to do are, then the onesthat help leaders promote that
mindset in the organization.
Be vulnerable to some extent,right?
This is new for pretty much anyleader and very few have the
answers if, anybody even has theanswers.
So I think I there's no shame insaying, Hey, look, we are going
through this transformation,this is what it will eventually
(23:39):
bring.
But there's some interim stepsand maybe there's also some
uncertainty where we need tofigure this out together or
where I'm available.
For, your questions and,concerns.
Matt Lewis (23:49):
Definitely.
And I think also it, the earlierpart of what we were discussing
is also resonant, where iforganizations recognize that AI
can potentially provide a lot ofconsideration of value to them
as an enterprise.
They, might need to crawl beforethey can walk, before they can
run.
And you know that, that mightbe, for example, the first thing
they might need to do is tobring someone into the
(24:10):
organization as the head of AIor chief AI officer, and it,
might be prudent for them tohave that person be enrolled for
a period of time, three to sixmonths before they start
figuring out, are we gonna buildthis technology ourselves, which
is probably unlikely in 2025/6,are we gonna partner with the
third party firm?
Are we gonna work with a startupin the ecosystem?
And then are we gonna startdoing real upskilling and
(24:32):
strategic enablement with ourteams the right way?
To think about how we work inpartnership with our teams,
which, because it is a peopleoriented consideration to
progress forward rather than tryto do everything all at once and
then find that they, the resultsare less than what they had
desired.
Andreas Welsch (24:49):
Now you've, shared so many great insights
from on one hand your session atthe World Economic Forum the
other week, but also generallyhow leaders can build this AI
mindset.
And I was wondering if you cansummarize the key three
takeaways for our audiencetoday.
Matt Lewis (25:04):
Yeah I think everyone's walking this path
like at their own pace, so thereisn't like one overarching
consideration that everyoneneeds to do identically.
But I think based upon the stageof maturity that, that
everyone's at, I think AI isstill one of those things that
I.
Reflects back to the personwhat's best for them and their
own strategy.
(25:25):
Un understanding for theorganization at the enterprise
level, where the organizationis, what its strategy is, what
they hope to achieve and, whatparts of the business are best
optimized or enhanced byartificial intelligence is the
best place to start.
Because knowing where there isfriction, where there are
opportunities for improvement isa good consideration to then
determine what makes sense inthe external environment to
(25:48):
partner and to progress forward.
Whether that means identifyingadditional leadership in house
or whether it looks moreexternally from partners and
those considerations.
The, mindset piece is reallycritical and from a, time and a
capital standpoint should beprobably three quarters of the
total investment.
And thinking about not just whatthe organization looks like in
(26:09):
spring of 2025, but what is itgoing to look like in the winter
of 2030?
And getting from here to thereis, not just a matter of taking
some chairs to the table andchanging them around.
It's a, real kind oftransformation of what the
enterprise looks like today to amoderate enterprise as roles and
skills and tasks evolve.
(26:29):
And it is changing thedisposition from like the late.
Legacy approaches to more of anagile, urgent sense of, action
across the business.
And thinking about if we do apilot or a POC in late 25, how
will it scale across theenterprise?
Can we even take this into anorganization of multiple
billions of dollars of revenue?
(26:49):
And is this something we want tobe doing as a firm as we evolve
into the future?
Can we be competitive in thisway?
And then mostly in the thingthat's most critical really is
like thinking about it from.
The perspective of, our staff,our frontline colleagues, people
that are on the front lines thatare talking to customers.
Maybe if it's patient facing orclinical facing how, is this
(27:10):
going to be received?
How does it complement andenhance the work, the knowledge
work of the people that reallyare using our products and
developing or, supporting ourservices.
And if we were with them acrossthe table and they saw what we
were doing.
How does this enable them tomake better decisions in a
faster way that speeds time tovalue?
And if it's not doing that, thenwe need to rethink how we're
(27:32):
both either expressing it orconsidering it because perhaps
it's not really truly supportinghuman potential.
We just we're thinking that itshould, but it's not quite
there.
And until it's, fullysynergistic, it might need a
little bit more work because we,should always be thinking about
it with the human at the centerand that idea of it.
(27:53):
Artificial intelligence plushuman intelligence really equals
brilliance.
Andreas Welsch (27:58):
Wonderful.
I love that.
Such a powerful message, right?
We need both technology and,humans, but put humans in the
center of what we do, because atthe end of the day that's where
the value and where the capitalis.
So Matt, thank you so much forjoining us and for sharing your
experience with us.
It was a pleasure having you onagain and hearing how your
(28:18):
advice leaders built at AImindset.
Matt Lewis (28:21):
Thanks Andreas.
Again, thanks for everyone forthe time.
Much appreciate it.
Today we'll talk about how you can successfully
adopt.
When you have the right mindsetas a leader, and who better to
have talked about it thansomeone who's actively
championing that?
Matt Lewis.
Hey Matt.
Thank you so much for joining.
Matt Lewis (00:13):
Andreas, thank you so much for having me back on
the program.
I'm thrilled to be here.
Being on the show last time wastransformative for me and for my
directions.
I'm so happy to be back with youand with the audience.
Thank you for having me, andthanks for the time for everyone
watching.
Andreas Welsch (00:27):
So great.
You're one of the few that haveactually been on, the show for
three times already and it'salways an enlightening
conversation when you're on.
So I'm really excited for whatwe'll cover today.
But for those of our audiencemembers who might not know you,
maybe you can introduce yourselfreal quick, who you are and what
you do.
Matt Lewis (00:45):
Sure.
Happy to do it.
So my name's Matt Lewis.
I'm founder, CEO and Chief AIOfficer at LLMental.
I've been in healthcare and lifesciences for my whole career,
about 27 years.
I started in data science andadvanced analytics at a firm
that is now AbbVie.
It was Proctor Gamble personalhealthcare at the time.
I've been in artificialintelligence for about 18 years.
(01:05):
Most of that time was not nearlyas fun and exciting as it is
now.
Prior to starting LLMental,about two and a half years ago,
I was Chief ArtificialIntelligence Officer at Inizio
Medical, a large private equityowned life sciences consultancy,
and now progressing forward intothe ecosystem in a kind of
general AI native platform asenterprise organization, solving
those problems that need solvingand helping to improve patient
(01:27):
outcomes.
Andreas Welsch (01:29):
I think that's so I important, such a great
mission.
Especially right in these timeswhen people are wondering what
is it with AI?
Is it going to replace me?
I'm feeling a lot of tension andstress and angst.
Championing the mental wellnessaspect is critical.
I think so.
Super excited to see you dothat.
Now maybe in good old fashion,should we play a little game to
(01:52):
kick things off?
Matt Lewis (01:53):
Sure.
Let's do it.
Andreas Welsch (01:54):
So let's do this.
So this one is called in yourown words, when you or when I
hit the buzzer, the wheels willstarts spinning.
You'll see a sentence.
I would love for you to answerwith the first thing that comes
to mind and why, in your ownwords, to make it a little more
interesting.
You only have 60 seconds foryour answer, so should we go?
Let's do it.
(02:15):
All right, so if AI were a book,what would it be?
60 seconds on the clock
Matt Lewis (02:23):
Bible.
Andreas Welsch (02:24):
Okay.
All right.
And why?
Matt Lewis (02:26):
Cause it is that meaningful and means something
different to everyone, and ittouches your heart, mind, and
soul in ways that are possibleto make you be the best version
of yourself.
Andreas Welsch (02:36):
It's super concise and obviously super in
inspiring too.
Wonderful.
And, with Easter just around thecorner and Passover not too long
ago, right?
Super timely now from, that holyscript if, you will, moving on
to another holy and sacred topicwhich is how do you actually
(03:00):
bring AI into a businesssuccessfully?
And I know you've recently helda workshop at the World Economic
Forum for a large number of CEOsto help them better understand
that.
And I'm just curious, what areCEOs asking these days about AI
when it seems like there's somuch talk chatter and so many
different vendors whispering inthe air.
What are they asking about whenit comes to AI?
Matt Lewis (03:21):
Yeah.
First of all, you know thisopportunity to go and speak to
the World Economic Forum's NewChampions program, which I did
last week, was really thehighlight of my professional
speaking career.
I've been in front of theC-Suite and boardrooms, customer
conferences, professionalassociations, medical groups,
patient advocacy, healthcaredelivery, you name it, I've done
it.
(03:42):
But this was really a specialyou opportunity to engage with
this community.
The folks that were in assemblywere world leaders, business
executives some allied closelywith heads of state really
moving the ball of innovationand responsibility up the hill.
And it was a really humblingexperience.
Everyone was there by choice andwas there fully attentive and
(04:05):
engaged and you speak, I knowAndreas at conferences and the
rest.
And it's not always the casethat you're in front of an
audience that's A, payingattention and B actually wants
to take what you're saying backto their place of work and.
Make it help their people andhelp their people do better and
be better as a result.
And being in an environment likethat was really quite wonderful.
(04:27):
I, was fortunate enough to bepart of the program before I was
actually on the stage and,stayed around for what followed,
and it was amazing discussionabout global public health and
global economy, geopolitics.
And the time that we're in rightnow across the.
The world's trajectory is an,interesting one.
Having informed citizensglobally is, critical that we
(04:49):
think about where we are andwhere we're going.
So it was really just a, delightbeing amongst that group.
I think one thing that wasreally interesting is that the,
group there was all like, veryinterested in augmented
intelligence, understandingwhere AI is and where it's
going.
They're all adopting andutilizing artificial
intelligence in their businessesand their places of work.
(05:11):
Many had experience with RPA.
They have a history and a legacywhere they've seen automation be
helpful in some regards and beendoing things like copilot and
other implementations in theircurrent environments right now.
But like many of us maybe notseeing the full benefit of a
full AI transformation that theywould like to see, but not quite
(05:32):
understanding why.
Really a great group to comeacross and, engage directly
with.
The talk that I gave was reallyfocused on mindset and really
thinking about what proportionof the success of an artificial
intelligence transformation isdue to algorithms.
The models, the platforms, thethings that we're talking about.
(05:53):
What is likely to be acontribution of underlying tech
and the considerations of thebroader kind of digital kind of.
Ecosystem that enterprises arecurrently considering, if you
will.
And then what is the balancethat is really contributed by
people, by leaders, byexecutives, by processes, and by
the other human factors withinthe environment.
(06:15):
And I've been talking about thishuman factors consideration for
a long time.
But there, there is a lot ofresearch now that suggests that.
At least 70% of what makes orbreaks an organization with
regards to AI success isactually people driven.
It is not about the platforms,it's not about the models, it's
not about the algorithms.
It's not about whether they havethe right kind of technology or
(06:37):
technologists on board.
It's really about the directexperience with the, technology
and what their disposition,their mindset their mental
wellness, their considerationsare as they progress forward
into the ecosystem and.
This group was quite interestedin, that consideration and had a
number of kind of questions andthoughts around.
How practically they canunderstand where they are on the
(07:00):
kind of mindset continuum, ifyou will.
And then whether those thingsare even amenable to
intervention.
Does someone just show up with afixed mindset, no pun intended,
and stay there forever.
Or are these things that can betrained, can they be taught?
Can take someone into a workshopand change the way that they
think so they can be a betterleader, be a better manager, be
a better.
(07:21):
Colleague and work better withcustomers, and that was most of
the discussion around what arethe kind of facilitators that
enable success versus thosetypes of barriers or things that
kind of frustrate the ability ofan organization to accrue value.
Andreas Welsch (07:34):
In all that you have shared and I always hear
that passion for the topic and,helping others, helping leaders
understand how they can elevatethemselves and their
organization and their people.
I think that's just sofundamental to the things that
you do.
So hearing what you're sharingand what you've shared with
them, I think is a profound andimpactful message, right?
(07:58):
It depends also on yourleadership and your mindset as a
leader.
How you take that to theorganization, how you show up so
that your people can show up astheir true selves as well.
Matt Lewis (08:10):
Yeah that's really critical and I think it really
can't be overstated both thesubject of what augmented
intelligence is able to enhanceand amplify and extend and
optimize is essentially at thecore of it, it's a people
solution.
What we're really doing istransforming humanity.
We're helping to enable andaugment human potential.
(08:32):
That's really what we're doing.
And at the same time, it is alsoboth subject and object.
It's the people that are helpingothers transform.
We're as leaders in the businessas enterprise executives.
We're the ones that are puttingthat into the world.
The way that we show up, the waythat we are authentic and
vulnerable and come to ourcolleagues in the business is
(08:55):
critical.
I get we, when we run largeworkshops or we implement
technology, when we buildplatforms and we design systems,
how we tell teams of what is nowand what is likely to exist in
the near and far future.
Is critical because theyultimately will decide whether
or not they trust us as leaders,whether they want to work with
(09:15):
or for us, whether or not theycan imagine or envisage a role
for themself in theorganization.
In two months, two weeks, twodays as this technology rolls
out.
And if they don't have thattrust and they don't believe
that we're in it for them.
Then no amount of software orsystems is gonna change that for
them.
So it's, really critical thatwhether we're in healthcare like
(09:36):
myself, or life sciences orhuman services, or really any
business, all our businesses arepeople, businesses.
And the most important thing isthat we connect with the people
in our businesses and try to doright by them.
Andreas Welsch (09:48):
Now doing right by our team members.
It starts also with us asleaders.
And there's so much hype and somuch noise in the market about
AI.
How do you recommend leaders,CEOs determine what is actually
factual and what is justfictional?
Matt Lewis (10:09):
Yeah.
Yeah.
I think this is one of thoseperennial topics within the
augmented intelligenceenvironment that you know I,
think we all kind of wish thatit'll go away, but at the same
time we'll be worried when itdoes go away.
I think you it, lives on, alittle bit of a distribution
curve right there, there is alot of hype.
(10:30):
But now also a couple years intothe generative AI wave, there's
also a lot of hope, and I thinkit's not like that the, these
things are on opposite ends of aspectrum there both together
juxtaposed one right on top ofthe other.
It's it might be the case thatin a large enterprise, like a
large life sciences company, forexample.
There could be a division wherethere's still a tremendous
(10:51):
amount of, hype and they haven'tyet seen that hope.
Maybe because within thatdivision, say like within
continuing medical education orwithin customer services or
within supply chain, theyhaven't yet architected a,
strategy for AI, haven't hired aChief AI Officer, haven't built
a POC or project to see thevalue yet.
(11:11):
So for them, it's stillvaporware and like misty, if you
will.
Whereas within another divisionof the same company, they're
quite mature and they're alreadyprogressing towards the hope
side and see more help than theysee hype.
So it's, not like it's eitherfact or it's kind of fiction.
It's really both end all at thesame time.
It's just not evenly distributedto use a William Gibson kind of
(11:32):
expression where the future ishere, it's just not evenly
distributed.
I and I, it is like that in alot of big enterprises where
there, there is a lot of truevalue being accrued, but it's
not evenly distributed acrossthe whole company.
And you, if you look at onepocket, you might see a lot of
bullshit because people justdon't know any better.
But if you look just down thecorridor, you look at a
(11:53):
different business unit, youlook at different.
They're seeing tremendous impactjust because of where they're in
the market and their stage ofmaturity.
So I think it does take a senseof discipline to understand
where there's alignment betweenstrategy and operations and
people and, culture and otherconsiderations, and also to know
what can actually be done inthis environment.
Andreas Welsch (12:14):
Now I've heard different approaches by,
different leaders how they goabout this.
And, some have shared that theyhave started to catalog the use
of AI in the business thatthey've reached out to different
business units.
That they basically put theirears to the ground, where is AI
actually happening?
Where it being implemented inour large enterprise?
(12:35):
And then find these pockets ofinnovation and elevate them and
say, Hey, look.
This is what's happening maybein Portugal.
This is what's happening in in avaccine division.
That's what's happening in,oncology and so on.
What's your recommendationthere?
How do you bring all of thatinnovation that's happening in
different parts of the companytogether?
(12:55):
Isn't, that the, role of theChief AI Officer?
Or are they overstepping if theytry to elevate that?
Matt Lewis (13:02):
Yeah again, it really depends.
It's not a great answer for, a apodcast and for a wide audience
like this, but it really dependson a number of factors like the
stage of maturity of theorganization itself, like what
their disposition is withregards to transformation whole,
or in part like where whatthey're actually.
Doing with regards to buildingtheir own intellectual property.
Are they of a nature wherethey're building a lot of that
(13:24):
own IP in house?
Are they buying or partnering?
And I think we, when we had thisconversation, you and I, maybe
two years ago the, there wasstill a, healthy consideration
out in many large verticalswhere many firms were building
their own models or actuallybuilding them from scratch or
doing a lot of fine tuning andother kinds of considerations.
(13:44):
Now, I think a lot of the,consideration has shifted from
that.
Almost entirely certainly to agreat degree where unless are
born out of Silicon Valley or ycome or type of consideration to
build entirely from scratch anda large enterprise is not
happening nearly to the degreethat it used to.
And if it is happening, it's notgetting much traction.
So it's a very different worldnow than it was even 18 months
(14:08):
ago because like a weakgenerative is like a quarter in
the real world.
So things just move veryquickly.
And if you don't have the kindof staying power to really.
Turn that into, value, themarket will tell you where
you're, where you need to be.
So I think it, there isdefinitely a thought towards
cataloging use cases and alsoseeing what's working.
(14:31):
I think some of the recentliterature that suggests the
value of native AI withindifferent environments, like the
study from Procter and Gamble,that was shared just recently
outta the the team at Harvardsuggests that even just very
general purpose.
Generative working in concertwith a single person is more
effective than a team of peopleworking without AI.
(14:54):
And there are a number of caseslike where this is happening
across many large organizationswhere they don't even have a
proof of concept or a pilot inplace that just someone's using
GPT, they have something ontheir phone and they're working
now in concert with AI.
Much more efficiently and muchmore effectively than with a
team that is human onlyessentially.
(15:15):
And a lot of this is notcataloged because it's
essentially like secret cyborgshadow IT activity and, the
business doesn't necessarilyneed to catalog all of this, but
I think they need to cultivateit.
They need to encourage it.
They need to ensure that.
The ways of working in 2025become really the soil in which
future work is, encouraged.
Otherwise, people in thosebusinesses will start feeling
(15:37):
like this type of activity isnot condoned.
And if someone is doing thistype of work at AstraZeneca and
they feel like it's notsomething that is helpful with
an environment, they're a veryinnovative shop.
So it's maybe poor example, butanother organization, they might
feel like another.
Life sciences organization is abetter place for innovation and
they might flee to go therebecause it's that's more likely
(15:57):
to speed, time to value for,patients in this regard.
So I think there is a place forleaders within the business to
identify these kind of pillarsof light, if you will, and cast
a spotlight on them and show theorganization.
What good looks like, not somuch to just put a big
spreadsheet together and say,look, we captured this
somewhere, but to really showpeople what good looks like and
(16:19):
find a way to scale thatbrilliance, if you will.
I.
Andreas Welsch (16:22):
I think that's a very practical suggestion,
practical advice right there.
So find the happy medium as,always, between looking for,
these things or even if, youfind them, elevate them, but
don't just make a spreadsheetexercise.
That's awesome.
Now you mentioned somethingearlier and, obviously it's also
the, title of our episode that alot of it has to do with the
(16:46):
leader's AI mindset, how we showup as a leader.
To this transformation to ourorganization, how we bring our
team members in parts of theorganization along.
But what does it actually mean?
What does it mean to have an AImindset as a leader?
Matt Lewis (17:02):
Yeah, it is definitely an evolving concept.
I think Gartner really is one ofthe forebearers of, this, of
consideration in their digitalthinking, digital mindset,
digital dexterity considerationthat they offered maybe about
eight years ago or so, wheredigital thinking is more than
just like skillset and tool set.
It is also mindset.
And in digital mindset, you needto have a proficiency with the
(17:23):
digital systems and skills ofthe organization.
But it's also a way of workingand a lot of it has to do with
the sense of urgency with whichleadership adopts its tactical
and operational practices andthe agility with which they
operate them and can adjust tochanges within the environment
ecosystem.
One quick example of this isthis thought.
(17:44):
A kind of exercise of how onebecomes proficient in generative
AI.
Even as early as like early2023, there was still a lot of
discussion around for likeprofessional services firms like
the, large holding companies,agencies.
I.
Arms length consultancies.
Does it make sense for firmslike that, for example, to build
their own models?
And there were many groupstrying to do that on their own,
(18:06):
if you will.
And then very quickly it becameresonant that perhaps partnering
or buying with a third partymight make more sense to do that
much faster than say thetechnology advances and
innovations that occurred adecade earlier with cloud or a
generation prior with theinternet.
And I think teams that wereflexible and could adapt
(18:27):
quickly.
Recognizing that the market wasshifting under their feet,
didn't make those large capitalinvestments to build technology
that was quickly obsolete, thatthe market didn't need and still
have the resources to invest inthe future, if you will.
Where groups that kind ofcommitted to a, rapidly eroding
past found that really justwasn't creating the
(18:47):
considerations that they neededout the ecosystem.
And it is that mix of.
Having a sense of urgency tostand up a strategy that
actually is reflective of thecurrent consideration
considerations, but also beingflexible and agile to adopt and
adapt as things move forward.
Coupled with really anunderstanding of, what it
actually takes to accrueexperience on the ground.
(19:08):
And I think this is might be alittle bit controversial, but
the, typical ways in which weupskill in artificial
intelligence it, is.
Probably the, most importantresponsibility that a leader in
the business has in the modernera, but it, often isn't given
the proper time and space andthought before it's actually
(19:30):
rolled out to frontline staff.
And I, the reason I say that isthat, that I, you know, when
we've talked and I've shared outin previous commentary and
publications I, use this.
Albert Einstein quote that theonly source of knowledge is
experience.
You know that just doing adidactic training course where
you share a lot of informationabout how Transformers work and
(19:51):
what GPT is and zero shotlearning and all the rest, and
that's helpful to a point.
But if you don't give staff,frontline staff, especially
actual experience in theworkflows that are gonna be
relevant to their jobs, thetasks they're responsible for.
And all you do is give them lotsof modules of courses that help
(20:12):
them understand what artificialaugmented intelligence is
capable of, and then there's alot of daylight between the time
that you train them and the timethey actually apply it to their
work.
The literature in this is veryclear and has been clear now for
the last nine to 12 months.
All that happens is that theirfear levels go up, way up, their
anxiety goes through the roof,and then productivity plummets
(20:33):
between 30 and 40% within thefirst three of months
post-training, and it ends uphaving the exact opposite effect
that upskilling is desired toproduce, which is instead of
them becoming more competent andproductivity improving, it
actually plummets to the pointthat people that are on the
front lines.
Feel like almost that AI isgonna take their job.
They become like terrified ofit.
And then the AI adoption and thetransformation really can't work
(20:57):
because most of the people thathave to do the work are so
fearful that they can't reallydo the work that's required.
And as leaders, we've almostdone this to them.
So it's like the, antithesis ofwhat we desire.
We want people to be embracingand engaging and running
towards.
The machine, if you will, asopposed to running away from the
danger.
But unfortunately, but by justtelling them, look, this is
(21:19):
amazing, and then not givingthem any direct exposure
experience to it, it has theopposite effect.
And we, create a problem thatthen needs to be solved.
Andreas Welsch (21:28):
So two thoughts here.
One is I'm thinking about ananalogy and something like
driving a car comes to mind,right?
You show somebody this is a car.
Here's the steering wheel.
Here are the pedals.
Maybe you shift manually orautomatic, doesn't matter, but
you don't actually let them sitin the car or have them driving
have them have driving lessons.
(21:48):
So you tell'em about driving acar, maybe even a race car.
But by the time that theyactually get to sit in the car,
they're so afraid.
Although they know everythingabout physics and combustion
engines and acceleration andwhatnot did.
They're too afraid to actuallytake the wheel, right?
Matt Lewis (22:03):
Yeah.
It'll be the same type of thing.
If you, if say you rewind backto 1906 and do that exact
demonstration at the same time,you take away their horse and
buggy and you prevent them fromdoing anything in that similar
reign, you, you don't let thembuy another horse.
There's no way that they canproduce they can't do anything
on the farm.
They can't get to town, but youtold'em that the automobile is
(22:25):
coming.
They know that it's gonna takeaway their horse and any mode of
transportation they have.
But they don't actually haveaccess to it.
So all they have is the fearthat everything they have known
since they were a child isdisappearing.
But the new thing isn't thereyet.
So the natural reaction for mostpeople is just to be terrified.
And then in most businesses, youdon't have leaders standing up
and saying, look like I don'thave a crystal ball.
(22:46):
Augmented intelligence is likelyto produce significant value.
The roles might shift, theorganization might evolve.
But it's likely to create newopportunities for everyone here.
And here are some of the thingsthat it might mean for you in
your job in the near future.
And here's the first way ofstarting.
Here's this pilot project thatwe're gonna pull you into, and
we'd love to get your feedbackand perspective, but a lot of
people don't do that in aninterim, you just have people
(23:07):
coming home and they're quitescared.
And as a result that, that fearturns into lots of negative
outcomes for people and forprofessionals.
Andreas Welsch (23:16):
I think all the things that you mentioned that,
we need to do are, then the onesthat help leaders promote that
mindset in the organization.
Be vulnerable to some extent,right?
This is new for pretty much anyleader and very few have the
answers if, anybody even has theanswers.
So I think I there's no shame insaying, Hey, look, we are going
through this transformation,this is what it will eventually
(23:39):
bring.
But there's some interim stepsand maybe there's also some
uncertainty where we need tofigure this out together or
where I'm available.
For, your questions and,concerns.
Matt Lewis (23:49):
Definitely.
And I think also it, the earlierpart of what we were discussing
is also resonant, where iforganizations recognize that AI
can potentially provide a lot ofconsideration of value to them
as an enterprise.
They, might need to crawl beforethey can walk, before they can
run.
And you know that, that mightbe, for example, the first thing
they might need to do is tobring someone into the
(24:10):
organization as the head of AIor chief AI officer, and it,
might be prudent for them tohave that person be enrolled for
a period of time, three to sixmonths before they start
figuring out, are we gonna buildthis technology ourselves, which
is probably unlikely in 2025/6,are we gonna partner with the
third party firm?
Are we gonna work with a startupin the ecosystem?
And then are we gonna startdoing real upskilling and
(24:32):
strategic enablement with ourteams the right way?
To think about how we work inpartnership with our teams,
which, because it is a peopleoriented consideration to
progress forward rather than tryto do everything all at once and
then find that they, the resultsare less than what they had
desired.
Andreas Welsch (24:49):
Now you've, shared so many great insights
from on one hand your session atthe World Economic Forum the
other week, but also generallyhow leaders can build this AI
mindset.
And I was wondering if you cansummarize the key three
takeaways for our audiencetoday.
Matt Lewis (25:04):
Yeah I think everyone's walking this path
like at their own pace, so thereisn't like one overarching
consideration that everyoneneeds to do identically.
But I think based upon the stageof maturity that, that
everyone's at, I think AI isstill one of those things that
I.
Reflects back to the personwhat's best for them and their
own strategy.
(25:25):
Un understanding for theorganization at the enterprise
level, where the organizationis, what its strategy is, what
they hope to achieve and, whatparts of the business are best
optimized or enhanced byartificial intelligence is the
best place to start.
Because knowing where there isfriction, where there are
opportunities for improvement isa good consideration to then
determine what makes sense inthe external environment to
(25:48):
partner and to progress forward.
Whether that means identifyingadditional leadership in house
or whether it looks moreexternally from partners and
those considerations.
The, mindset piece is reallycritical and from a, time and a
capital standpoint should beprobably three quarters of the
total investment.
And thinking about not just whatthe organization looks like in
(26:09):
spring of 2025, but what is itgoing to look like in the winter
of 2030?
And getting from here to thereis, not just a matter of taking
some chairs to the table andchanging them around.
It's a, real kind oftransformation of what the
enterprise looks like today to amoderate enterprise as roles and
skills and tasks evolve.
(26:29):
And it is changing thedisposition from like the late.
Legacy approaches to more of anagile, urgent sense of, action
across the business.
And thinking about if we do apilot or a POC in late 25, how
will it scale across theenterprise?
Can we even take this into anorganization of multiple
billions of dollars of revenue?
(26:49):
And is this something we want tobe doing as a firm as we evolve
into the future?
Can we be competitive in thisway?
And then mostly in the thingthat's most critical really is
like thinking about it from.
The perspective of, our staff,our frontline colleagues, people
that are on the front lines thatare talking to customers.
Maybe if it's patient facing orclinical facing how, is this
(27:10):
going to be received?
How does it complement andenhance the work, the knowledge
work of the people that reallyare using our products and
developing or, supporting ourservices.
And if we were with them acrossthe table and they saw what we
were doing.
How does this enable them tomake better decisions in a
faster way that speeds time tovalue?
And if it's not doing that, thenwe need to rethink how we're
(27:32):
both either expressing it orconsidering it because perhaps
it's not really truly supportinghuman potential.
We just we're thinking that itshould, but it's not quite
there.
And until it's, fullysynergistic, it might need a
little bit more work because we,should always be thinking about
it with the human at the centerand that idea of it.
(27:53):
Artificial intelligence plushuman intelligence really equals
brilliance.
Andreas Welsch (27:58):
Wonderful.
I love that.
Such a powerful message, right?
We need both technology and,humans, but put humans in the
center of what we do, because atthe end of the day that's where
the value and where the capitalis.
So Matt, thank you so much forjoining us and for sharing your
experience with us.
It was a pleasure having you onagain and hearing how your
(28:18):
advice leaders built at AImindset.
Matt Lewis (28:21):
Thanks Andreas.
Again, thanks for everyone forthe time.
Much appreciate it.
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