February 19, 2025 • 45 mins
Welcome to The Inner Game of Change, the podcast that explores the evolving landscape of change management, leadership, and transformation.
In today's episode, I am joined by Lisa Carlin, a strategy execution expert, to dive into one of the biggest conversations in business today; AI strategy and adoption. With the AI hype everywhere, how can organizations separate signals from the noise and make smart strategic decisions?
Lisa brings her deep expertise to help us cut through the noise, focus on what matters and harness AI for real impact. We will explore practical adoption strategies, leadership's role in driving AI success and the mindset shift needed to embrace this powerful technology.
I am grateful to have Lisa chatting with me today.
About Lisa
Hi, I'm a Strategy Execution Specialist. I work with leaders who want to leave a legacy of change and innovation. I help them to plan and execute their strategic projects when stakes are high. They have ambitious goals, and are faced with major risk, tough cultures or likely resistance.
My clients love having an independent sounding board and expert advice, so they can deliver their plans with confidence.
After 50+ implementations, I've learned that traditional strategy approaches alienate staff and hinder implementation. Over this time, I’ve pioneered a culture-friendly, human-centered approach that speeds up change momentum. AI is now a major part of my focus: developing effective AI strategies to fast track success.
My career includes roles at McKinsey and Accenture, then running my own business since 1999. When I’m not at work, I’m gardening with the dogs.
***
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Lisa (00:00):
Look, I think there is a lot of noise and there is a lot
of hype and really it is quitesimilar to, like you said, the
introduction of the Internet,and in many ways, because it's
allowing folks to use such newtools that they haven't had
before.
But I think, if you break itdown into the three elements of
(00:23):
AI this is the way I look at itright, so you can integrate AI
functionality into the productsand services that we offer.
Okay, so that's one aspect.
The second aspect, which isbuilding on other types of
products and services that we'veoffered in the past, then
there's internal efficiencies,which we've been able to do over
(00:45):
the years, process improvement,process automation waves and
this is yet another wave ofoffering more functionality.
And then the third one is thepersonal productivity, which
really is where the generativeAI comes in.
Ali (01:05):
Welcome to the Inner Game of Change, the podcast that
explores the evolving landscapeof change management, leadership
and transformation.
I am your host, ali Jamal.
In today's episode, I am joinedby Lisa Carlin, a strategy
execution expert, to dive intoone of the biggest conversations
in business today AI strategyand adoption.
(01:28):
With the AI hype everywhere,how can organizations separate
signals from the noise and makesmart strategic decisions?
Lisa brings her deep expertiseto help us cut through the noise
, focus on what matters andharness AI for real impact.
We will explore practicaladoption strategies,
(01:50):
leadership's role in driving AIsuccess and the mindset shift
needed to embrace this powerfultechnology.
I am grateful to have Lisachatting with me today.
Well, lisa, thank you so muchfor joining me in the Inner Game
of Change podcast.
I'm eternally grateful for yourtime.
Lisa (02:08):
Thanks for having me here, Ali.
Ali (02:10):
Thank you so much, Lisa.
Today we are covering animportant topic around AI, most
importantly around AI strategy.
I'm going to jump straight intoit, Lisa.
What is the hype about AI?
Straight into it, Lisa.
What?
Lisa (02:24):
is the hype about AI?
Well, ali AI has actually beenaround for quite some time, and
generative AI is, I think, whereall the hype is, because it's
really doing things that andoffering the ability to do
things that are very human-like,that we've never had access to
before.
So it's really been chat GPT,and that was late 2022.
(02:47):
And some of us saw it early2023.
And so, if you think you knowhow quickly they've managed to
chat, gpt has managed to reach amillion users and is just
growing at an outstanding ratebecause it's enabling us to do
things that we couldn't dobefore.
You know from all the differenttypes of modes of content that
(03:11):
it's able to generate, and it'sbeen likened to the new
electricity, which I think isnot far wrong.
Ali (03:20):
Yeah, I like the idea that, yeah, the new electricity.
I haven't really heard aboutthat.
I actually think it's the newinternet, and when the internet
happened in the early 90s, I wasone of those people that
completely ignored it, althoughmy friends were completely into
(03:43):
it and really understand, try tounderstand it.
And I never thought in mylifetime that I will have
another inflection point likegenerative AI and it's happening
now.
But this time I'm not lettinggo.
I'm really just into it and tryto understand how it can help
me be a better value add to mystakeholders, to my clients and
(04:06):
also a personal life.
There's a lot of noise in themarket.
This is how I think about it.
There's a lot of noisehappening in there.
What could be some of thestrategies the organizations can
look at to differentiatebetween what is a noise and what
is a signal?
Lisa (04:26):
Yeah, that's an interesting question.
Look, I think there is a lot ofnoise and there is a lot of hype
, and really it is quite similarto, like you said, the
introduction of the internet inmany ways, because it's allowing
folks to use such new toolsthat they haven't had before.
(04:47):
But I think, if you break itdown into the three elements of
AI this is the way I look at itright, so you can integrate AI
functionality into the productsand services that we offer.
Okay, so that's one aspect.
The second aspect, which isbuilding on other types of
(05:07):
products and services that we'veoffered in the past, then
there's internal efficiencies,which we've been able to do over
the years, process improvement,process automation waves and
this is yet another wave ofoffering more functionality.
And then the third one is thepersonal productivity, which
really is where the generativeAI comes in.
And so I think, if peoplereally think about it from those
(05:29):
three elements, rather thanthis big amorphous AI bundle of
things which I don't reallyunderstand, if they look at it
at that more granular level,they can then differentiate
between just the general noiseand height and the true signal
around.
What can be done in those threeareas?
What are the use cases in thosethree areas.
Ali (05:51):
Deciding the use cases for an organization is a tricky
business because it's got a lotof applications.
If your stakeholder is askingyou for an advice around where
do I start?
What would be your sort ofgeneral counsel to them?
Lisa (06:13):
Yeah, well, the first thing about where to start is
really where I always start istalking to stakeholders and
understanding their goals, andyou know and that's what you
would do in any change project,I'm sure, ali.
So it's really looking at, youknow, understanding the broader
strategy of the organisation,understanding the needs of the
(06:34):
stakeholders and the goals ofwhat they want to get out of it.
And then, once they'veidentified those, you go from
there and do some researchreally into the different use
cases.
So, for example, if a costreduction or cost efficiency
those, you go from there and dosome research really into the
different use cases.
So, for example, if a costreduction or cost efficiency is
a major drive in the industry,okay, then there are some
fabulous ways that you can useAI to reduce costs.
(06:58):
So let's look at the financefunction, for example.
There's been a whole history ofautomation in finance through
ERPs, and then the next wave ofAI just allows much easier
automation and much moreautomation of things that we
weren't previously able toautomate, because AI can just
(07:18):
link between the differentprocesses, which are very
structured data, which we'vealways had, and now we can also
process unstructured datathrough the use of AI.
So it gives us more options.
So by speaking withstakeholders, initially
understanding the goals and thenworking through the use cases.
From there, I think, yeah,that's where I would guide folks
(07:40):
to start.
Ali (07:42):
The way I look at it, Lisa, and feel free to challenge me
if you like.
In my head, anyway, it's notquite about cost-cutting.
There's a focus on this isgoing to improve or enhance my
productivity and the other thing.
So that's one.
The other thing I actually do,especially generative AI, I do
(08:05):
look at it as a capabilityrather than a feature, and this
is not playing, you know, beingsmart with words.
This is I am a user myself andI've been using it since, you
know, the start of 23 withChatGPT, so it's become part of
(08:26):
my workflow and therefore, forme, that is a capability.
I built a capability to be ableto collaborate with the
generative AI.
Am I being too optimistic orromantic about it?
Lisa (08:41):
Well, if you look at previous waves of technology and
what they've done, there'salways been this fear that it's
going to take jobs.
If you think about costreduction, it's going to reduce
the number of headcounts and itdoes in some respects, but it
creates other jobs, and I thinkthat's exactly where we're going
(09:04):
to be with AI.
It's most certainly acapability, as you've said,
because the folks that have thecapability to use AI are able to
we're able to be much moreproductive.
Mckinsey's suggested it's inthe range of about 30%,
depending on the industry andfunction.
(09:24):
So it's like having, you know,up to potentially 30% even more
additional productivity to liftwhat we can do.
So many people are excited bythis because they know that it
means they can have a betterlifestyle.
So and that's certainly whathappened with the first
industrial revolution and youknow folks being able to work
(09:48):
less time than they used to withthe use of technology.
So, in that sense, definitelywill improve productivity, but I
think it can also be used fortargeted cost reduction because
in particular processes, it caneliminate the amount of human
resource needed.
It's not to say that it won'tcreate jobs in other areas,
(10:11):
though.
Ali (10:12):
So the overarching sort of theme and sentiment that I'm not
shy from saying it will impactpeople's jobs Absolutely, and
some of us will, like I'vealways considered, continuously
considered, how, you know, someof my processes can be automated
(10:35):
.
I am thinking with it right now, but then that will allow me
time in my practice forcreativity, allowing me time in
my practice for creativity, andso that freeing of the time
doesn't mean that I'm going tolose my job.
It just means that I canprobably add more value.
We all talk about stakeholderengagement, understanding
(10:57):
people's needs and all of that,but then if you really come down
to the details and thepracticality of it, most of us
will complain I don't have a lotof time in the day, and so I
think that can help.
So it's definitely going toimpact.
What you're saying and this iswhat I hear you say is that
that's okay because it will openup other opportunities the
(11:22):
usual cause and effect for anytechnology, exactly.
Lisa (11:27):
That's exactly right.
The World Economic Forum hassome very interesting data that
last year they predicted that43% of our skill set will be
obsolete and disrupted withinthe next five years, and if they
were to update that researchtoday, I reckon that percentage
would go up.
So at least you know close to50%.
(11:49):
Whatever you want to argue thepercentage is, it will be
different for different people.
But of our skills, you know,around half of our skills are
easily being disrupted, and sofor folks who like to be
productive and creative, like Ido and you nailed it when you
said creativity it just offerssuch a tremendous asset if we
(12:12):
actually take the time, likeyou've done and like I've done,
to experiment and to teachyourself and learn.
So, for example, I'm hopeless atdrawing.
So, for example, I'm hopelessat drawing, I just cannot draw.
But I use DALI, which is a toolin OpenAI, tool in the ChatGPT
(12:34):
paid version, and DALI draws methe most amazing, little
interesting, funny diagrams anddrawings that I use in my
newsletter, which is TurbochargeWeekly, and I can put these
drawings in and, you know, lookpretty cool, even though I
haven't got an artistic bone inmy body.
(12:56):
So you know, that's just onesmall way in which we're able to
, as human beings, do thingsthat we couldn't do before, but,
but it really does take that, Iguess, being brave enough, in a
sense, to put yourself outthere and try things.
Ali (13:14):
One of the things, lisa, that I've been sort of
streamlined the way I thinkabout generative AI is that
every opportunity that I comeacross or a problem, I ask
myself how can generative AIhelp me with this?
And I find this, when I askmyself this question, it will
(13:35):
force me to explore what elsecan a generative AI tool do for
me?
And the other thing is thatwhen I talk about creativity,
one of the greatest things thatare happening to me when I have
an idea in my mind istraditionally, you know, like in
(13:57):
the last few years beforeChatGPT, I would need to spend
hours researching the topiconline and just to put a
one-pager to convince mystakeholders for something.
This process now is such anenjoyable process.
(14:18):
If I've got an idea, Icollaborate with generative AI
and I reckon within an hour Ican put something reasonable for
the executive to look at.
So it helps me articulate mythoughts way faster than the
past, and I find that really,really helpful in my practice
(14:41):
anyway.
Lisa (14:42):
Yeah, I definitely use it in that way to help complement
my thinking.
So if I'm drafting something,it will help me pull together
some dot points and then I cancompare it with the things I've
thought through and it mightidentify different you know
different dog points, differentyou know objections if I'm going
(15:04):
into a meeting that I hadn'tthought of, critical questions
that I hadn't thought to askwhen starting out a new project.
So it's useful in a number ofthose ways.
I think the CEOs and leadersthat I'm seeing who are using it
in that way are, you know, arereally making a difference in
(15:27):
the organization, the ones thatare really open-minded and
innovative and that are usingthose tools themselves.
I see them making a bigdifference as well.
Ali (15:38):
We're going to touch on that leadership aspect of it.
But before I get into that, Iwant to ask you if the majority
of people right now, as inemployees, have kind of
reservation around it.
Probably not fear, but it's thereservation around the unknown.
(15:58):
There's a lot of hype that thismay take over jobs, so
naturally we will have atendency to walk away from this
or have complete apathy towardsit.
What would be your counsel oradvice to organizations about
(16:20):
how to manage that, because it'salready in the public arena?
Lisa (16:26):
Yeah, really good question .
It's really interesting thekinds of sources of resistance
that I'm seeing.
Some of it is just thisreaction to the hype of it all
and the intimidation that peoplefeel, where they just try and
downplay the importance or theusefulness of it and, just you
(16:48):
know, hone in on the fact thatit's overhyped and it's often
wrong and they're deep fakes.
And there's all these you know,and then they would go through
all the you know, the privacyconcerns and all of that.
I think it very much depends onwhere people are at, and if
they are at that point wherethey've got these fear-based
(17:09):
concerns or some very legitimateconcerns about things like data
privacy, it needs to beaddressed and forums need to be
opened up for people to be ableto voice those concerns.
So one of the things I've beendoing with clients, for example,
is running short workshopswhere I go through the three
(17:30):
different types of AI and thensome use cases within that,
depending on the group, andwithin a couple of hours we do
some brainstorming around how itcan be used and get people to
try some things.
And then that starts breakingthe ice, because then people see
that they don't need to be IT,digital specialists, technology
(17:51):
specialists, to be able to usethis, that it's not as hard and,
yes, it actually can add value.
So it's giving people thatopportunity to understand what
it means for them and get theirhands on the tools and start
experimenting.
That really helps.
And the other is I always focuson the culture of the business,
(18:13):
so that's an important part ofmy work as a strategy execution
specialist is to think broaderthan the change, broader than
the project management, broaderthan the strategy.
Think about how all of thatfits into the culture.
And by understanding theculture in that way, then you
(18:34):
know we can modify the approachto suit the culture.
So, for example, if it's veryoppositional and people you know
tend to their reaction to fear,tends to be very active and
they like to voice theirconcerns, right, then give them
an opportunity to do that.
That's what I would do, and andI often do that in the format
(18:57):
of let's think of all the thingsthat could go wrong and all the
things that we don't like aboutit, and then, okay, now let's
look at all the positives andhow we could actually get some
value from it, and that way itgives people a chance to offload
their biggest concerns and tobe able to think about some of
the positives and practicalapplications.
Ali (19:19):
Some of the positives and practical applications.
That idea of creating anawareness about what the
technology is really about andthe capability is such an
important piece.
I focus a lot on two things inmy practice, lisa.
One is the AI.
Literacy, which is basicallythe unknown, can be scary.
(19:43):
Once you, as you mentioned that, break the ice with it, they
think, oh, is that it?
It's actually fun to do that.
And the second thing is thatyou know that I focus on,
instead of focusing on theactual capability and the tool,
I focus on the mindset.
We all want to do a good job, weall want to improve, and even
(20:08):
if you don't want to improve,you still want to do a good job.
Then, if that is your intentionand if you want to progress in
the organization, surely youwant to come up with new
strategies and new ways ofworking Wherever you sit, this
capability can help, and so Ifocus on the mindset, and I know
(20:28):
it's a long-term game, but Ithink that feeds into what you
just talked about, rightly.
So is the culture.
Unless, with this particulartechnology, this is not a
feature, microsoft feature thatyou're just going to have in
there and you're going to forgetabout it.
It's actually there and it willbe a missed opportunity for
(20:49):
people to actually even overlookit.
I mean, why would you not do it?
Let's talk about the leadershippart of it and I think you just
you mentioned before thatleaders adopt first, and
probably not as typical users,because the majority of leaders
have their EAs and everybodyelse around them, but at least
(21:11):
in my opinion, if theyunderstand the potential, they
can be advocates for it.
Be advocates for it.
Lisa (21:18):
Exactly.
That is exactly what I think isneeded.
It's been interesting, ali,this particular digital change
compared to many others, in thata lot of it has been driven
from the grassroots up.
So if I look at the stats ofusers of CHAT-GBT, 65 percent of
(21:40):
them are 35 or 18 years to 35years.
So that cohort and so they'vebeen a big driver of that in
organizations and I do a lot oftalking to the ceo circuits.
You know the round tables andother sorts of mastermind groups
, roundtable development groups,and I go in and one of the
(22:04):
biggest well, apparently this isthe number one topic that
they're thinking about at themoment because they and they
really so they asked me to comein and talk to them about.
You know, what do they need toknow?
Where should they start thosesorts of questions?
And when I started this lastyear, you can see the
(22:24):
development.
So I used to ask for a show ofhands who's using any form of
generative AI, and there werevery few hands going up.
It's getting more and more.
So now we're getting to a pointwhere, you know, I'd say
roughly over 70% of the CEOs Imeet are using or have used
something at least once or againOne of these tools like ChatGPT
(22:48):
, and the folks that are usingit the most, though, are really
role modeling it in theorganization, and they are
sending such a strong signalthat they agree on the
innovation.
You know that they support theinnovation.
And then I look at some folkswho have put blanket bans in
(23:09):
their organizations.
We will not allow use of chatGPT because of the privacy
concerns, and I'm sure you'veseen some organizations like
that, ali, and doesn't that senda very different signal?
Ali (23:22):
I've noticed three types of organizations.
These leaders over the lastthree years is that there are
some who are early adopters,very advocates, they're close to
the technology, they usuallycome from a good technology
background, their CIOs are veryactive and therefore that all
(23:46):
influences their leadershipmindset.
And they've got the last group.
I'm going to talk about that ina second.
The last group do not touch itor say nothing until we sort it
out.
It's quiet.
And therefore ChatGPT andMicrosoft, by the way, with
(24:08):
CoPilot, they're a clevercompany, so they gave you the
technology and you adopted it atno cost.
Actually, copilot, they putthat in in edge, which is their
own browser that is a free tothe organization.
The same with chat, gpt.
In fact, both of thesecompanies did a brilliant job in
(24:29):
creating adoption with theminimum effort, which is
basically they gave you the tooland you had no option but to
use it.
And then you've got the groupin the middle which I think
they're the smart group, they'rethinkers, but they are not
gun-how going that the firstgroup.
They are not sitting and hidinglike the last group.
(24:50):
They do say we're going to startsomewhere.
We understand there areconcerns around the privacy and
security and all of those things.
We are looking at all of thosethings.
We are looking at all of thosethings and we have plans, but
the overarching mentality andthe mindset is that we do
believe that there is somethingin this technology that can help
(25:12):
us and therefore we're takingsome steps, and here are some of
the steps that we're taking.
I think that's probably areasonable approach to the
Australian workplace, whereas inAmerica and Canada from my
experience and talking tocompanies and leaders in there,
especially in America it'shappening.
(25:33):
You're going to have to use it,but we are a different culture
here in Australia.
Lisa (25:39):
Yeah, yeah, we are a different culture here in
Australia.
Yeah, yeah, we are.
And so, look, I agree with youwith those three different areas
.
So they are definitely, youknow, different groups and
people will adopt it at theirown pace.
But there are things that theorganisation can do and the
leaders can do to nudge themforward.
(26:01):
And that's really up to theorganization and how they want
to introduce it and how fastthey want to encourage usage.
Ali (26:09):
Yeah, what industries do you think in Australia, Lisa,
that will highly likely be theearly adopters in this.
They're already happening.
But what's your observation?
Lisa (26:23):
Well, it's been quite interesting.
I've seen the banks andfinancial services do a lot of
work in the space because theywere working on it anyway.
So you know, even years agothere there was a product I saw
which was a humanoid or human AIbot that folks could talk to on
(26:50):
a product like a videoconferencing product, to ask
about their financial servicesneeds.
And this particular product wasbuilt around the culture of the
typical customer profile, whichwas a Eurasian woman.
And that person, that woman,that humanoid, had the ability
(27:13):
to using sentiment analysis tounderstand the expressions on
the person the customer's face,so they could escalate, for
example, the call to a realhuman if the person the
customers face.
So they could escalate, forexample, the call to a real
human if the person was angry,for example.
So that kind of technology hasbeen in place for a while and
some of the financialinstitutions have been using it,
but it's been very expensivetechnology like projects that
(27:36):
would cost at least $100,000plus one off to just get it set
up, never mind the ongoing usagecosts.
Now the price has come down sothat other organisations that
maybe don't have the financialbacking can use it as well.
What I find most interesting.
I don't know that there are anyparticular industries that have
(27:57):
stood out, but the one that'smost surprising to me is law
firms.
So some of the big law firmshave been adopting AI, and why
that surprises me is becauselawyers are particularly
risk-averse, because that'stheir job, and they are
particularly cautious aroundthings like privacy because
they've got to be concernedabout their clients' privacy.
(28:19):
Yeah, that is so important, andyet we've seen some of the
large law firms just race ahead,implementing AI models, taking
in, you know, customized AI botsin-house to be able to deliver
legal advice to clients andlegal precedence to their
lawyers, and I think that's beenquite interesting.
Ali (28:42):
That is very interesting.
That's their first sort of lineof advisory group and they can
get the lawyers to focus on thecomplex cases.
Exactly.
My observation, lisa, is that,talking about lawyers, I worked
with a group of lawyers andthey're very protective.
They don't want to use it foranything lawyer stuff.
(29:05):
However, they think it's anamazing piece to help them do
the research way faster at anexceptionally low cost.
They see that as a huge enablerfor them to be able to provide
comprehensive advice faster totheir clients.
Lisa (29:26):
Some of the consulting firms are also adopting it for
that reason, and I particularlylike.
I don't know if you've seen theReid Hoffman YouTube where he's
created a likeness of himselfand he interviews himself.
I don't know if that one.
Ali (29:39):
Yes, yes, yes, I've read about it.
I don't know if that one yes,yes, yes, I've read about it.
I haven't watched it, yeah.
Lisa (29:43):
It's quite interesting because sometimes I pop it up on
the screen and people guesswhich one's real and which one
isn't.
And you know he's done itreally really well and when you
see how he's.
So the AI version of Read hasbeen trained on Read's IP so
(30:06):
that it can answer the questionsthat somebody would ask you
know about any of the researchand IP that REIT has.
So, you know, in a very nice,in a nice interactive format.
So when you think of that inthe future for training purposes
(30:29):
, for advisory purposes, for youknow, anything from consulting
organisations to training andmaybe even coaching, there's
quite a lot of potential usecases there for those types of
organisations.
So yeah, I think you know itjust automates the kind of lower
(30:53):
level information sharing partof what a consultant or an
advisor, a professional servicesadvisor, would provide.
Ali (31:06):
I recently was thinking about how this capability can
help make better decisions, andthen I was thinking well, it's
already happening in industrieslike stock market and all of
that.
That's already a live decisionmaking process happening through
(31:27):
technology based on theinformation.
Can you see that beingtranslated into the traditional
workplaces?
Lisa (31:36):
Yes, yes, absolutely.
I think people get more andmore comfortable with it.
It will grow.
What I find particularlyinteresting and I'm sure you've
experimented with this as wellis advice around change
management itself, and forproject managers and managing
projects, change projects.
(31:57):
Managers and managing projectsand change projects, you know,
and asking it for advice aroundhow to influence other human
beings, and that's you know thatcan be really, really powerful.
So we're actually usingmachines to advise us, as humans
(32:17):
, in how to relate to otherhumans.
Ali (32:21):
Which is really a fantastic thing.
It's one of the things that Iused way early in the piece and
I experimented with it and I'vebecome better at it.
Now is I gave it and this is askewed source in CorePilot I
gave it access to well, it's gotaccess to all the emails from
the clients, all my chats withthem, and I asked it to analyze
(32:46):
how they accept communicationand messages, what is the best
way to communicate with them,and I took all of that insight
and then I, when I created mychange engagement plan, I
embedded that insight into itand it gave me a complete
picture of the stakeholders.
When I looked at it, some of itdid not surprise me, but some
(33:09):
of it also validated that Ihaven't thought about a lot of
other things that the machinecan help me think about.
Literally, you can askgenerative AI.
Is there anything else that Ihaven't thought about?
Literally, you can askgenerative ai.
Lisa (33:22):
Is there anything else that I haven't thought about?
Ali (33:23):
as simple as that.
As simple as that.
It's like you've got your owncoach with you, you know, giving
you insight.
In fact, as an aside, I givechat gpt photos of my golf swing
.
I took photos from the videoand and I asked chat giti to
analyze my swing based on on thepictures.
(33:45):
It's quite amazing.
So, which means my coach may nothave a job, but I did say to
the coach I still need the human, I still need somebody to say
to me hey, well done, ali.
This is really quite animprovement.
But because I can't pay for thecoach twice a week, I'm
thinking maybe I pay for thecoach once a week, and then I
(34:06):
ask Chad GPT to do the rest forme as a training partner.
And so it's quite fascinating,you know, and Chad GPT knows
about three personas about me.
I am in the business ofchanging comms, I'm a and I'm a
golf player, so it's gotdifferent personas and therefore
(34:26):
it can customize the insightsfor me.
It's quite amazing technology.
I am so happy that I'm actuallyliving in this age, lisa, so
put it that way.
Lisa (34:36):
Oh yeah, me too.
Can you imagine missing out onall of this?
I know.
Ali (34:39):
I know and I want to go back to you mentioned something
around the age group between 20sand 30s.
I was reading something and Ihaven't really read the whole
piece.
I only read the headline in theEconomist just yesterday
talking about the differenceadoption between males and
(35:02):
females in generative AI.
It looks like in the majorityof categories, males are using
it way more, and it's quitesurprising to see jobs like HR,
which is more populated byfemales than males, not using it
(35:22):
, and I think that's a missedopportunity, because generative
AI is actually very capable tohelp with all of those.
You may not have seen this, butwhat's your general take on
that, or is it still too earlyto even look at that?
Lisa (35:41):
Yeah, I haven't actually seen the data on that, ali, so I
couldn't comment on the usageby gender.
But what I do agree with you isthat HR, you know, have a huge
opportunity here to step up anduse generative AI.
I actually did a presentationfor a senior HR audience two
(36:04):
weeks ago and it's such a hugeopportunity for HR to use AI to
completely revolutionize howthey deliver value and partner
with the business, that theydeliver value and partner with
the business.
So, you know, we had a reallyinteresting conversation around
(36:25):
how HR and OD folks learningfolks, talent, folks can use AI
for such an important number ofuse cases and one of them
besides, you know, specializedfunctionally based HR
applications or use cases.
There's also that space ofbeing able to advise
(36:47):
strategically and reallyunderstand the business Because,
as you say, you know, there'sresearch that you can do really
quickly.
You can go in and prepare for asenior meeting and help, and AI
can help.
You know those people reallythink strategically about the
issues that the business isfacing and then tailor their HR
(37:08):
advice around that.
So I'd highly encourage folkswho are in HR to start if they
haven't already startexperimenting.
Ali (37:20):
Yes, I completely agree.
You know capability and culture, HR delivery groups, strategy
group, marketing, media andcomms.
I mean, the list goes on and onand on.
Exactly, yeah, Sorry, Lisa.
Lisa (37:40):
Yeah, I think it also provides so much more value for
your clients, ali, because iffolks you know that are in
change management like yourself,I mean, who can deeply use the
tools for such a wide variety ofuse cases that it's inbuilt
into your processes, as you saythen your clients are.
You know, most contractors likeyourself.
(38:02):
You know they pay us by the dayand then you can just get so
much more done in a day that youknow it's like having two
change managers on the groundinstead of one.
Ali (38:12):
Oh, yes, yes yes, absolutely, that's a reality.
So for anybody listening tothis and they think this is not
reality, think again and maybehave a go.
Another use case that I've beenthinking about and I've read
about like there are hundredsand hundreds of use cases.
There's some unique ones.
(38:33):
I'm helping a client with arestructure and I'm using
co-operative capability to helpthe new people going into in a
restructure.
There are new people going intodifferent jobs.
Some jobs change, some peoplewill get new jobs, new people
joining the organization, and Ifind that generative AI
(38:57):
capability can help fast forwardand accelerate that embedding
of the new structure.
And so that was the idea.
And then I researched the wholepiece over the weekend.
There are not a lot of usecases out there in the world,
however, I'm happy to be numberone, so that's okay in that
space.
So if somebody is not an SMEbut they have working knowledge,
(39:22):
having a capability of agenerative AI capability can
really fast forward them intheir expertise to become a
specialist in their own areas.
I am aware of time.
I'm thoroughly enjoying thisconversation.
You are the author of theTurbocharger Weekly, or
Turbocharge Weekly, where youprovide fast track strategies
(39:47):
for leaders.
What are some of the quick,actionable steps for leaders can
take today when they thinkabout their adoption of
generative AI or AI in general.
Lisa (39:58):
So thanks, ali, for asking that.
I love writing TurboChargeWeekly.
We've now got over 8,000business leaders that read
TurboCharge Weekly every weekand we have an edition.
Actually that's just on tipsfor starting AI which folks can
find on my website.
So the turbochargerscom forwardslash resources.
(40:21):
So if I give you a quick peekinto that for some quick tips to
understand what those threetypes of AI are that I spoke
about in the beginning theproducts and services, internal
efficiency and for personalproductivity, understanding how
to go about experimenting,because that's really where the
(40:42):
best value is and it's how folkslike yourself have really
learned how to use AI.
And to put together across-functional team.
So I'm a big fan ofcross-functional teams.
I teach about cross-functionalteams in my strategy execution
boot camps.
I you know we use those teamsto affect change in
organizations.
So putting together an AI teamin the organization to champion
(41:07):
AI would be another quick tipthat I'd give folks who are
interested in collaborating withothers in the business and
seeing some real change indelivering AI.
Ali (41:17):
Double click, Lisa, on the idea of cross-functional teams.
Lisa (41:22):
Sure.
So what I do usually isunderstand the cultural nuances
of the organization and wheresome of the resistance is likely
to come from.
So, for example, in a culturewhere it's highly siloed, where
each business unit thinks ofthemselves almost as a whole
(41:43):
business with a very differentmindset, I would then be looking
to get representation from eachof those business units or each
of those demographics orwherever the silos are coming
from, and then get thoserepresented onto a
cross-functional project team.
So one of my modules in theTurbochargers Hub, which is my
community, a developmentcommunity for folks who want to
(42:06):
learn all of this stuff iscalled the power of community,
because we talk about howworking together across those
cross-functional teams cancreate huge amounts of momentum
in change projects.
So, yeah, happy to talk aboutit more, ali.
Maybe that's a topic foranother day.
Ali (42:26):
Absolutely.
That sounds good.
The power of the community andcreating that momentum is such
an important piece and I alreadyknow and you've already touched
on that that adoption isalready happening organically in
an organization, whether theleaders like it or not.
In fact, probably some of theleaders are way behind the
(42:47):
employees already using chat,GPT and I think, according to
the stats, about 65% because ofthat adoption and that awareness
(43:07):
that the resistance may not beas tragic and negative as they
expect it to be.
It's been a pleasure having youin my Inner Game of Change
podcast, Lisa.
I really thoroughly enjoyedthat and you made me think.
The reason why I asked aboutthe cross-functional team is
just an idea that I've beenthinking about and expanding on
(43:30):
the principle of the networkchampions and all of that using
generative AI to help me withthat.
How would people connect withyou, Lisa?
Oh, I'd love for people toconnect with me with that.
How would people?
Lisa (43:43):
connect with you, lisa.
I'd love for people to connectwith me on LinkedIn.
You can bypass the follow andactually click on the connect,
so we can connect both ways andalso find me at
theturbochargerscom.
Ali (43:58):
I like that.
Bypass the follow and justconnect with me.
That can be your next articletitle Lisa.
Lisa (44:07):
I really like that.
Ali (44:09):
Yeah, hopefully I'll get you back in the future and we go
into another avatar around AI,but until then, stay well and
stay safe, lisa.
Lisa (44:19):
You too, Ali.
Thanks for having me.
Ali (44:20):
Thank you very much.
Thank you for listening.
If you found this episodevaluable, remember to subscribe
to stay updated on upcomingepisodes.
Your support is trulyappreciated and, by sharing this
podcast with your colleagues,friends and fellow change
(44:42):
practitioners, it can help mereach even more individuals and
professionals who can benefitfrom these discussions.
Remember, and in my opinion,change is an enduring force and
you will only have a measure ofcertainty and control when you
embrace it.
Until next time, thank you forbeing part of the Inner Game of
Change community.
(45:03):
I am Ali Jammah and this is theInner Game of Change podcast.
Look, I think there is a lot of noise and there is a lot
of hype and really it is quitesimilar to, like you said, the
introduction of the Internet,and in many ways, because it's
allowing folks to use such newtools that they haven't had
before.
But I think, if you break itdown into the three elements of
(00:23):
AI this is the way I look at itright, so you can integrate AI
functionality into the productsand services that we offer.
Okay, so that's one aspect.
The second aspect, which isbuilding on other types of
products and services that we'veoffered in the past, then
there's internal efficiencies,which we've been able to do over
(00:45):
the years, process improvement,process automation waves and
this is yet another wave ofoffering more functionality.
And then the third one is thepersonal productivity, which
really is where the generativeAI comes in.
Ali (01:05):
Welcome to the Inner Game of Change, the podcast that
explores the evolving landscapeof change management, leadership
and transformation.
I am your host, ali Jamal.
In today's episode, I am joinedby Lisa Carlin, a strategy
execution expert, to dive intoone of the biggest conversations
in business today AI strategyand adoption.
(01:28):
With the AI hype everywhere,how can organizations separate
signals from the noise and makesmart strategic decisions?
Lisa brings her deep expertiseto help us cut through the noise
, focus on what matters andharness AI for real impact.
We will explore practicaladoption strategies,
(01:50):
leadership's role in driving AIsuccess and the mindset shift
needed to embrace this powerfultechnology.
I am grateful to have Lisachatting with me today.
Well, lisa, thank you so muchfor joining me in the Inner Game
of Change podcast.
I'm eternally grateful for yourtime.
Lisa (02:08):
Thanks for having me here, Ali.
Ali (02:10):
Thank you so much, Lisa.
Today we are covering animportant topic around AI, most
importantly around AI strategy.
I'm going to jump straight intoit, Lisa.
What is the hype about AI?
Straight into it, Lisa.
What?
Lisa (02:24):
is the hype about AI?
Well, ali AI has actually beenaround for quite some time, and
generative AI is, I think, whereall the hype is, because it's
really doing things that andoffering the ability to do
things that are very human-like,that we've never had access to
before.
So it's really been chat GPT,and that was late 2022.
(02:47):
And some of us saw it early2023.
And so, if you think you knowhow quickly they've managed to
chat, gpt has managed to reach amillion users and is just
growing at an outstanding ratebecause it's enabling us to do
things that we couldn't dobefore.
You know from all the differenttypes of modes of content that
(03:11):
it's able to generate, and it'sbeen likened to the new
electricity, which I think isnot far wrong.
Ali (03:20):
Yeah, I like the idea that, yeah, the new electricity.
I haven't really heard aboutthat.
I actually think it's the newinternet, and when the internet
happened in the early 90s, I wasone of those people that
completely ignored it, althoughmy friends were completely into
(03:43):
it and really understand, try tounderstand it.
And I never thought in mylifetime that I will have
another inflection point likegenerative AI and it's happening
now.
But this time I'm not lettinggo.
I'm really just into it and tryto understand how it can help
me be a better value add to mystakeholders, to my clients and
(04:06):
also a personal life.
There's a lot of noise in themarket.
This is how I think about it.
There's a lot of noisehappening in there.
What could be some of thestrategies the organizations can
look at to differentiatebetween what is a noise and what
is a signal?
Lisa (04:26):
Yeah, that's an interesting question.
Look, I think there is a lot ofnoise and there is a lot of hype
, and really it is quite similarto, like you said, the
introduction of the internet inmany ways, because it's allowing
folks to use such new toolsthat they haven't had before.
(04:47):
But I think, if you break itdown into the three elements of
AI this is the way I look at itright, so you can integrate AI
functionality into the productsand services that we offer.
Okay, so that's one aspect.
The second aspect, which isbuilding on other types of
(05:07):
products and services that we'veoffered in the past, then
there's internal efficiencies,which we've been able to do over
the years, process improvement,process automation waves and
this is yet another wave ofoffering more functionality.
And then the third one is thepersonal productivity, which
really is where the generativeAI comes in.
And so I think, if peoplereally think about it from those
(05:29):
three elements, rather thanthis big amorphous AI bundle of
things which I don't reallyunderstand, if they look at it
at that more granular level,they can then differentiate
between just the general noiseand height and the true signal
around.
What can be done in those threeareas?
What are the use cases in thosethree areas.
Ali (05:51):
Deciding the use cases for an organization is a tricky
business because it's got a lotof applications.
If your stakeholder is askingyou for an advice around where
do I start?
What would be your sort ofgeneral counsel to them?
Lisa (06:13):
Yeah, well, the first thing about where to start is
really where I always start istalking to stakeholders and
understanding their goals, andyou know and that's what you
would do in any change project,I'm sure, ali.
So it's really looking at, youknow, understanding the broader
strategy of the organisation,understanding the needs of the
(06:34):
stakeholders and the goals ofwhat they want to get out of it.
And then, once they'veidentified those, you go from
there and do some researchreally into the different use
cases.
So, for example, if a costreduction or cost efficiency
those, you go from there and dosome research really into the
different use cases.
So, for example, if a costreduction or cost efficiency is
a major drive in the industry,okay, then there are some
fabulous ways that you can useAI to reduce costs.
(06:58):
So let's look at the financefunction, for example.
There's been a whole history ofautomation in finance through
ERPs, and then the next wave ofAI just allows much easier
automation and much moreautomation of things that we
weren't previously able toautomate, because AI can just
(07:18):
link between the differentprocesses, which are very
structured data, which we'vealways had, and now we can also
process unstructured datathrough the use of AI.
So it gives us more options.
So by speaking withstakeholders, initially
understanding the goals and thenworking through the use cases.
From there, I think, yeah,that's where I would guide folks
(07:40):
to start.
Ali (07:42):
The way I look at it, Lisa, and feel free to challenge me
if you like.
In my head, anyway, it's notquite about cost-cutting.
There's a focus on this isgoing to improve or enhance my
productivity and the other thing.
So that's one.
The other thing I actually do,especially generative AI, I do
(08:05):
look at it as a capabilityrather than a feature, and this
is not playing, you know, beingsmart with words.
This is I am a user myself andI've been using it since, you
know, the start of 23 withChatGPT, so it's become part of
(08:26):
my workflow and therefore, forme, that is a capability.
I built a capability to be ableto collaborate with the
generative AI.
Am I being too optimistic orromantic about it?
Lisa (08:41):
Well, if you look at previous waves of technology and
what they've done, there'salways been this fear that it's
going to take jobs.
If you think about costreduction, it's going to reduce
the number of headcounts and itdoes in some respects, but it
creates other jobs, and I thinkthat's exactly where we're going
(09:04):
to be with AI.
It's most certainly acapability, as you've said,
because the folks that have thecapability to use AI are able to
we're able to be much moreproductive.
Mckinsey's suggested it's inthe range of about 30%,
depending on the industry andfunction.
(09:24):
So it's like having, you know,up to potentially 30% even more
additional productivity to liftwhat we can do.
So many people are excited bythis because they know that it
means they can have a betterlifestyle.
So and that's certainly whathappened with the first
industrial revolution and youknow folks being able to work
(09:48):
less time than they used to withthe use of technology.
So, in that sense, definitelywill improve productivity, but I
think it can also be used fortargeted cost reduction because
in particular processes, it caneliminate the amount of human
resource needed.
It's not to say that it won'tcreate jobs in other areas,
(10:11):
though.
Ali (10:12):
So the overarching sort of theme and sentiment that I'm not
shy from saying it will impactpeople's jobs Absolutely, and
some of us will, like I'vealways considered, continuously
considered, how, you know, someof my processes can be automated
(10:35):
.
I am thinking with it right now, but then that will allow me
time in my practice forcreativity, allowing me time in
my practice for creativity, andso that freeing of the time
doesn't mean that I'm going tolose my job.
It just means that I canprobably add more value.
We all talk about stakeholderengagement, understanding
(10:57):
people's needs and all of that,but then if you really come down
to the details and thepracticality of it, most of us
will complain I don't have a lotof time in the day, and so I
think that can help.
So it's definitely going toimpact.
What you're saying and this iswhat I hear you say is that
that's okay because it will openup other opportunities the
(11:22):
usual cause and effect for anytechnology, exactly.
Lisa (11:27):
That's exactly right.
The World Economic Forum hassome very interesting data that
last year they predicted that43% of our skill set will be
obsolete and disrupted withinthe next five years, and if they
were to update that researchtoday, I reckon that percentage
would go up.
So at least you know close to50%.
(11:49):
Whatever you want to argue thepercentage is, it will be
different for different people.
But of our skills, you know,around half of our skills are
easily being disrupted, and sofor folks who like to be
productive and creative, like Ido and you nailed it when you
said creativity it just offerssuch a tremendous asset if we
(12:12):
actually take the time, likeyou've done and like I've done,
to experiment and to teachyourself and learn.
So, for example, I'm hopeless atdrawing.
So, for example, I'm hopelessat drawing, I just cannot draw.
But I use DALI, which is a toolin OpenAI, tool in the ChatGPT
(12:34):
paid version, and DALI draws methe most amazing, little
interesting, funny diagrams anddrawings that I use in my
newsletter, which is TurbochargeWeekly, and I can put these
drawings in and, you know, lookpretty cool, even though I
haven't got an artistic bone inmy body.
(12:56):
So you know, that's just onesmall way in which we're able to
, as human beings, do thingsthat we couldn't do before, but,
but it really does take that, Iguess, being brave enough, in a
sense, to put yourself outthere and try things.
Ali (13:14):
One of the things, lisa, that I've been sort of
streamlined the way I thinkabout generative AI is that
every opportunity that I comeacross or a problem, I ask
myself how can generative AIhelp me with this?
And I find this, when I askmyself this question, it will
(13:35):
force me to explore what elsecan a generative AI tool do for
me?
And the other thing is thatwhen I talk about creativity,
one of the greatest things thatare happening to me when I have
an idea in my mind istraditionally, you know, like in
(13:57):
the last few years beforeChatGPT, I would need to spend
hours researching the topiconline and just to put a
one-pager to convince mystakeholders for something.
This process now is such anenjoyable process.
(14:18):
If I've got an idea, Icollaborate with generative AI
and I reckon within an hour Ican put something reasonable for
the executive to look at.
So it helps me articulate mythoughts way faster than the
past, and I find that really,really helpful in my practice
(14:41):
anyway.
Lisa (14:42):
Yeah, I definitely use it in that way to help complement
my thinking.
So if I'm drafting something,it will help me pull together
some dot points and then I cancompare it with the things I've
thought through and it mightidentify different you know
different dog points, differentyou know objections if I'm going
(15:04):
into a meeting that I hadn'tthought of, critical questions
that I hadn't thought to askwhen starting out a new project.
So it's useful in a number ofthose ways.
I think the CEOs and leadersthat I'm seeing who are using it
in that way are, you know, arereally making a difference in
(15:27):
the organization, the ones thatare really open-minded and
innovative and that are usingthose tools themselves.
I see them making a bigdifference as well.
Ali (15:38):
We're going to touch on that leadership aspect of it.
But before I get into that, Iwant to ask you if the majority
of people right now, as inemployees, have kind of
reservation around it.
Probably not fear, but it's thereservation around the unknown.
(15:58):
There's a lot of hype that thismay take over jobs, so
naturally we will have atendency to walk away from this
or have complete apathy towardsit.
What would be your counsel oradvice to organizations about
(16:20):
how to manage that, because it'salready in the public arena?
Lisa (16:26):
Yeah, really good question .
It's really interesting thekinds of sources of resistance
that I'm seeing.
Some of it is just thisreaction to the hype of it all
and the intimidation that peoplefeel, where they just try and
downplay the importance or theusefulness of it and, just you
(16:48):
know, hone in on the fact thatit's overhyped and it's often
wrong and they're deep fakes.
And there's all these you know,and then they would go through
all the you know, the privacyconcerns and all of that.
I think it very much depends onwhere people are at, and if
they are at that point wherethey've got these fear-based
(17:09):
concerns or some very legitimateconcerns about things like data
privacy, it needs to beaddressed and forums need to be
opened up for people to be ableto voice those concerns.
So one of the things I've beendoing with clients, for example,
is running short workshopswhere I go through the three
(17:30):
different types of AI and thensome use cases within that,
depending on the group, andwithin a couple of hours we do
some brainstorming around how itcan be used and get people to
try some things.
And then that starts breakingthe ice, because then people see
that they don't need to be IT,digital specialists, technology
(17:51):
specialists, to be able to usethis, that it's not as hard and,
yes, it actually can add value.
So it's giving people thatopportunity to understand what
it means for them and get theirhands on the tools and start
experimenting.
That really helps.
And the other is I always focuson the culture of the business,
(18:13):
so that's an important part ofmy work as a strategy execution
specialist is to think broaderthan the change, broader than
the project management, broaderthan the strategy.
Think about how all of thatfits into the culture.
And by understanding theculture in that way, then you
(18:34):
know we can modify the approachto suit the culture.
So, for example, if it's veryoppositional and people you know
tend to their reaction to fear,tends to be very active and
they like to voice theirconcerns, right, then give them
an opportunity to do that.
That's what I would do, and andI often do that in the format
(18:57):
of let's think of all the thingsthat could go wrong and all the
things that we don't like aboutit, and then, okay, now let's
look at all the positives andhow we could actually get some
value from it, and that way itgives people a chance to offload
their biggest concerns and tobe able to think about some of
the positives and practicalapplications.
Ali (19:19):
Some of the positives and practical applications.
That idea of creating anawareness about what the
technology is really about andthe capability is such an
important piece.
I focus a lot on two things inmy practice, lisa.
One is the AI.
Literacy, which is basicallythe unknown, can be scary.
(19:43):
Once you, as you mentioned that, break the ice with it, they
think, oh, is that it?
It's actually fun to do that.
And the second thing is thatyou know that I focus on,
instead of focusing on theactual capability and the tool,
I focus on the mindset.
We all want to do a good job, weall want to improve, and even
(20:08):
if you don't want to improve,you still want to do a good job.
Then, if that is your intentionand if you want to progress in
the organization, surely youwant to come up with new
strategies and new ways ofworking Wherever you sit, this
capability can help, and so Ifocus on the mindset, and I know
(20:28):
it's a long-term game, but Ithink that feeds into what you
just talked about, rightly.
So is the culture.
Unless, with this particulartechnology, this is not a
feature, microsoft feature thatyou're just going to have in
there and you're going to forgetabout it.
It's actually there and it willbe a missed opportunity for
(20:49):
people to actually even overlookit.
I mean, why would you not do it?
Let's talk about the leadershippart of it and I think you just
you mentioned before thatleaders adopt first, and
probably not as typical users,because the majority of leaders
have their EAs and everybodyelse around them, but at least
(21:11):
in my opinion, if theyunderstand the potential, they
can be advocates for it.
Be advocates for it.
Lisa (21:18):
Exactly.
That is exactly what I think isneeded.
It's been interesting, ali,this particular digital change
compared to many others, in thata lot of it has been driven
from the grassroots up.
So if I look at the stats ofusers of CHAT-GBT, 65 percent of
(21:40):
them are 35 or 18 years to 35years.
So that cohort and so they'vebeen a big driver of that in
organizations and I do a lot oftalking to the ceo circuits.
You know the round tables andother sorts of mastermind groups
, roundtable development groups,and I go in and one of the
(22:04):
biggest well, apparently this isthe number one topic that
they're thinking about at themoment because they and they
really so they asked me to comein and talk to them about.
You know, what do they need toknow?
Where should they start thosesorts of questions?
And when I started this lastyear, you can see the
(22:24):
development.
So I used to ask for a show ofhands who's using any form of
generative AI, and there werevery few hands going up.
It's getting more and more.
So now we're getting to a pointwhere, you know, I'd say
roughly over 70% of the CEOs Imeet are using or have used
something at least once or againOne of these tools like ChatGPT
(22:48):
, and the folks that are usingit the most, though, are really
role modeling it in theorganization, and they are
sending such a strong signalthat they agree on the
innovation.
You know that they support theinnovation.
And then I look at some folkswho have put blanket bans in
(23:09):
their organizations.
We will not allow use of chatGPT because of the privacy
concerns, and I'm sure you'veseen some organizations like
that, ali, and doesn't that senda very different signal?
Ali (23:22):
I've noticed three types of organizations.
These leaders over the lastthree years is that there are
some who are early adopters,very advocates, they're close to
the technology, they usuallycome from a good technology
background, their CIOs are veryactive and therefore that all
(23:46):
influences their leadershipmindset.
And they've got the last group.
I'm going to talk about that ina second.
The last group do not touch itor say nothing until we sort it
out.
It's quiet.
And therefore ChatGPT andMicrosoft, by the way, with
(24:08):
CoPilot, they're a clevercompany, so they gave you the
technology and you adopted it atno cost.
Actually, copilot, they putthat in in edge, which is their
own browser that is a free tothe organization.
The same with chat, gpt.
In fact, both of thesecompanies did a brilliant job in
(24:29):
creating adoption with theminimum effort, which is
basically they gave you the tooland you had no option but to
use it.
And then you've got the groupin the middle which I think
they're the smart group, they'rethinkers, but they are not
gun-how going that the firstgroup.
They are not sitting and hidinglike the last group.
(24:50):
They do say we're going to startsomewhere.
We understand there areconcerns around the privacy and
security and all of those things.
We are looking at all of thosethings.
We are looking at all of thosethings and we have plans, but
the overarching mentality andthe mindset is that we do
believe that there is somethingin this technology that can help
(25:12):
us and therefore we're takingsome steps, and here are some of
the steps that we're taking.
I think that's probably areasonable approach to the
Australian workplace, whereas inAmerica and Canada from my
experience and talking tocompanies and leaders in there,
especially in America it'shappening.
(25:33):
You're going to have to use it,but we are a different culture
here in Australia.
Lisa (25:39):
Yeah, yeah, we are a different culture here in
Australia.
Yeah, yeah, we are.
And so, look, I agree with youwith those three different areas
.
So they are definitely, youknow, different groups and
people will adopt it at theirown pace.
But there are things that theorganisation can do and the
leaders can do to nudge themforward.
(26:01):
And that's really up to theorganization and how they want
to introduce it and how fastthey want to encourage usage.
Ali (26:09):
Yeah, what industries do you think in Australia, Lisa,
that will highly likely be theearly adopters in this.
They're already happening.
But what's your observation?
Lisa (26:23):
Well, it's been quite interesting.
I've seen the banks andfinancial services do a lot of
work in the space because theywere working on it anyway.
So you know, even years agothere there was a product I saw
which was a humanoid or human AIbot that folks could talk to on
(26:50):
a product like a videoconferencing product, to ask
about their financial servicesneeds.
And this particular product wasbuilt around the culture of the
typical customer profile, whichwas a Eurasian woman.
And that person, that woman,that humanoid, had the ability
(27:13):
to using sentiment analysis tounderstand the expressions on
the person the customer's face,so they could escalate, for
example, the call to a realhuman if the person the
customers face.
So they could escalate, forexample, the call to a real
human if the person was angry,for example.
So that kind of technology hasbeen in place for a while and
some of the financialinstitutions have been using it,
but it's been very expensivetechnology like projects that
(27:36):
would cost at least $100,000plus one off to just get it set
up, never mind the ongoing usagecosts.
Now the price has come down sothat other organisations that
maybe don't have the financialbacking can use it as well.
What I find most interesting.
I don't know that there are anyparticular industries that have
(27:57):
stood out, but the one that'smost surprising to me is law
firms.
So some of the big law firmshave been adopting AI, and why
that surprises me is becauselawyers are particularly
risk-averse, because that'stheir job, and they are
particularly cautious aroundthings like privacy because
they've got to be concernedabout their clients' privacy.
(28:19):
Yeah, that is so important, andyet we've seen some of the
large law firms just race ahead,implementing AI models, taking
in, you know, customized AI botsin-house to be able to deliver
legal advice to clients andlegal precedence to their
lawyers, and I think that's beenquite interesting.
Ali (28:42):
That is very interesting.
That's their first sort of lineof advisory group and they can
get the lawyers to focus on thecomplex cases.
Exactly.
My observation, lisa, is that,talking about lawyers, I worked
with a group of lawyers andthey're very protective.
They don't want to use it foranything lawyer stuff.
(29:05):
However, they think it's anamazing piece to help them do
the research way faster at anexceptionally low cost.
They see that as a huge enablerfor them to be able to provide
comprehensive advice faster totheir clients.
Lisa (29:26):
Some of the consulting firms are also adopting it for
that reason, and I particularlylike.
I don't know if you've seen theReid Hoffman YouTube where he's
created a likeness of himselfand he interviews himself.
I don't know if that one.
Ali (29:39):
Yes, yes, yes, I've read about it.
I don't know if that one yes,yes, yes, I've read about it.
I haven't watched it, yeah.
Lisa (29:43):
It's quite interesting because sometimes I pop it up on
the screen and people guesswhich one's real and which one
isn't.
And you know he's done itreally really well and when you
see how he's.
So the AI version of Read hasbeen trained on Read's IP so
(30:06):
that it can answer the questionsthat somebody would ask you
know about any of the researchand IP that REIT has.
So, you know, in a very nice,in a nice interactive format.
So when you think of that inthe future for training purposes
(30:29):
, for advisory purposes, for youknow, anything from consulting
organisations to training andmaybe even coaching, there's
quite a lot of potential usecases there for those types of
organisations.
So yeah, I think you know itjust automates the kind of lower
(30:53):
level information sharing partof what a consultant or an
advisor, a professional servicesadvisor, would provide.
Ali (31:06):
I recently was thinking about how this capability can
help make better decisions, andthen I was thinking well, it's
already happening in industrieslike stock market and all of
that.
That's already a live decisionmaking process happening through
(31:27):
technology based on theinformation.
Can you see that beingtranslated into the traditional
workplaces?
Lisa (31:36):
Yes, yes, absolutely.
I think people get more andmore comfortable with it.
It will grow.
What I find particularlyinteresting and I'm sure you've
experimented with this as wellis advice around change
management itself, and forproject managers and managing
projects, change projects.
(31:57):
Managers and managing projectsand change projects, you know,
and asking it for advice aroundhow to influence other human
beings, and that's you know thatcan be really, really powerful.
So we're actually usingmachines to advise us, as humans
(32:17):
, in how to relate to otherhumans.
Ali (32:21):
Which is really a fantastic thing.
It's one of the things that Iused way early in the piece and
I experimented with it and I'vebecome better at it.
Now is I gave it and this is askewed source in CorePilot I
gave it access to well, it's gotaccess to all the emails from
the clients, all my chats withthem, and I asked it to analyze
(32:46):
how they accept communicationand messages, what is the best
way to communicate with them,and I took all of that insight
and then I, when I created mychange engagement plan, I
embedded that insight into itand it gave me a complete
picture of the stakeholders.
When I looked at it, some of itdid not surprise me, but some
(33:09):
of it also validated that Ihaven't thought about a lot of
other things that the machinecan help me think about.
Literally, you can askgenerative AI.
Is there anything else that Ihaven't thought about?
Literally, you can askgenerative ai.
Lisa (33:22):
Is there anything else that I haven't thought about?
Ali (33:23):
as simple as that.
As simple as that.
It's like you've got your owncoach with you, you know, giving
you insight.
In fact, as an aside, I givechat gpt photos of my golf swing
.
I took photos from the videoand and I asked chat giti to
analyze my swing based on on thepictures.
(33:45):
It's quite amazing.
So, which means my coach may nothave a job, but I did say to
the coach I still need the human, I still need somebody to say
to me hey, well done, ali.
This is really quite animprovement.
But because I can't pay for thecoach twice a week, I'm
thinking maybe I pay for thecoach once a week, and then I
(34:06):
ask Chad GPT to do the rest forme as a training partner.
And so it's quite fascinating,you know, and Chad GPT knows
about three personas about me.
I am in the business ofchanging comms, I'm a and I'm a
golf player, so it's gotdifferent personas and therefore
(34:26):
it can customize the insightsfor me.
It's quite amazing technology.
I am so happy that I'm actuallyliving in this age, lisa, so
put it that way.
Lisa (34:36):
Oh yeah, me too.
Can you imagine missing out onall of this?
I know.
Ali (34:39):
I know and I want to go back to you mentioned something
around the age group between 20sand 30s.
I was reading something and Ihaven't really read the whole
piece.
I only read the headline in theEconomist just yesterday
talking about the differenceadoption between males and
(35:02):
females in generative AI.
It looks like in the majorityof categories, males are using
it way more, and it's quitesurprising to see jobs like HR,
which is more populated byfemales than males, not using it
(35:22):
, and I think that's a missedopportunity, because generative
AI is actually very capable tohelp with all of those.
You may not have seen this, butwhat's your general take on
that, or is it still too earlyto even look at that?
Lisa (35:41):
Yeah, I haven't actually seen the data on that, ali, so I
couldn't comment on the usageby gender.
But what I do agree with you isthat HR, you know, have a huge
opportunity here to step up anduse generative AI.
I actually did a presentationfor a senior HR audience two
(36:04):
weeks ago and it's such a hugeopportunity for HR to use AI to
completely revolutionize howthey deliver value and partner
with the business, that theydeliver value and partner with
the business.
So, you know, we had a reallyinteresting conversation around
(36:25):
how HR and OD folks learningfolks, talent, folks can use AI
for such an important number ofuse cases and one of them
besides, you know, specializedfunctionally based HR
applications or use cases.
There's also that space ofbeing able to advise
(36:47):
strategically and reallyunderstand the business Because,
as you say, you know, there'sresearch that you can do really
quickly.
You can go in and prepare for asenior meeting and help, and AI
can help.
You know those people reallythink strategically about the
issues that the business isfacing and then tailor their HR
(37:08):
advice around that.
So I'd highly encourage folkswho are in HR to start if they
haven't already startexperimenting.
Ali (37:20):
Yes, I completely agree.
You know capability and culture, HR delivery groups, strategy
group, marketing, media andcomms.
I mean, the list goes on and onand on.
Exactly, yeah, Sorry, Lisa.
Lisa (37:40):
Yeah, I think it also provides so much more value for
your clients, ali, because iffolks you know that are in
change management like yourself,I mean, who can deeply use the
tools for such a wide variety ofuse cases that it's inbuilt
into your processes, as you saythen your clients are.
You know, most contractors likeyourself.
(38:02):
You know they pay us by the dayand then you can just get so
much more done in a day that youknow it's like having two
change managers on the groundinstead of one.
Ali (38:12):
Oh, yes, yes yes, absolutely, that's a reality.
So for anybody listening tothis and they think this is not
reality, think again and maybehave a go.
Another use case that I've beenthinking about and I've read
about like there are hundredsand hundreds of use cases.
There's some unique ones.
(38:33):
I'm helping a client with arestructure and I'm using
co-operative capability to helpthe new people going into in a
restructure.
There are new people going intodifferent jobs.
Some jobs change, some peoplewill get new jobs, new people
joining the organization, and Ifind that generative AI
(38:57):
capability can help fast forwardand accelerate that embedding
of the new structure.
And so that was the idea.
And then I researched the wholepiece over the weekend.
There are not a lot of usecases out there in the world,
however, I'm happy to be numberone, so that's okay in that
space.
So if somebody is not an SMEbut they have working knowledge,
(39:22):
having a capability of agenerative AI capability can
really fast forward them intheir expertise to become a
specialist in their own areas.
I am aware of time.
I'm thoroughly enjoying thisconversation.
You are the author of theTurbocharger Weekly, or
Turbocharge Weekly, where youprovide fast track strategies
(39:47):
for leaders.
What are some of the quick,actionable steps for leaders can
take today when they thinkabout their adoption of
generative AI or AI in general.
Lisa (39:58):
So thanks, ali, for asking that.
I love writing TurboChargeWeekly.
We've now got over 8,000business leaders that read
TurboCharge Weekly every weekand we have an edition.
Actually that's just on tipsfor starting AI which folks can
find on my website.
So the turbochargerscom forwardslash resources.
(40:21):
So if I give you a quick peekinto that for some quick tips to
understand what those threetypes of AI are that I spoke
about in the beginning theproducts and services, internal
efficiency and for personalproductivity, understanding how
to go about experimenting,because that's really where the
(40:42):
best value is and it's how folkslike yourself have really
learned how to use AI.
And to put together across-functional team.
So I'm a big fan ofcross-functional teams.
I teach about cross-functionalteams in my strategy execution
boot camps.
I you know we use those teamsto affect change in
organizations.
So putting together an AI teamin the organization to champion
(41:07):
AI would be another quick tipthat I'd give folks who are
interested in collaborating withothers in the business and
seeing some real change indelivering AI.
Ali (41:17):
Double click, Lisa, on the idea of cross-functional teams.
Lisa (41:22):
Sure.
So what I do usually isunderstand the cultural nuances
of the organization and wheresome of the resistance is likely
to come from.
So, for example, in a culturewhere it's highly siloed, where
each business unit thinks ofthemselves almost as a whole
(41:43):
business with a very differentmindset, I would then be looking
to get representation from eachof those business units or each
of those demographics orwherever the silos are coming
from, and then get thoserepresented onto a
cross-functional project team.
So one of my modules in theTurbochargers Hub, which is my
community, a developmentcommunity for folks who want to
(42:06):
learn all of this stuff iscalled the power of community,
because we talk about howworking together across those
cross-functional teams cancreate huge amounts of momentum
in change projects.
So, yeah, happy to talk aboutit more, ali.
Maybe that's a topic foranother day.
Ali (42:26):
Absolutely.
That sounds good.
The power of the community andcreating that momentum is such
an important piece and I alreadyknow and you've already touched
on that that adoption isalready happening organically in
an organization, whether theleaders like it or not.
In fact, probably some of theleaders are way behind the
(42:47):
employees already using chat,GPT and I think, according to
the stats, about 65% because ofthat adoption and that awareness
(43:07):
that the resistance may not beas tragic and negative as they
expect it to be.
It's been a pleasure having youin my Inner Game of Change
podcast, Lisa.
I really thoroughly enjoyedthat and you made me think.
The reason why I asked aboutthe cross-functional team is
just an idea that I've beenthinking about and expanding on
(43:30):
the principle of the networkchampions and all of that using
generative AI to help me withthat.
How would people connect withyou, Lisa?
Oh, I'd love for people toconnect with me with that.
How would people?
Lisa (43:43):
connect with you, lisa.
I'd love for people to connectwith me on LinkedIn.
You can bypass the follow andactually click on the connect,
so we can connect both ways andalso find me at
theturbochargerscom.
Ali (43:58):
I like that.
Bypass the follow and justconnect with me.
That can be your next articletitle Lisa.
Lisa (44:07):
I really like that.
Ali (44:09):
Yeah, hopefully I'll get you back in the future and we go
into another avatar around AI,but until then, stay well and
stay safe, lisa.
Lisa (44:19):
You too, Ali.
Thanks for having me.
Ali (44:20):
Thank you very much.
Thank you for listening.
If you found this episodevaluable, remember to subscribe
to stay updated on upcomingepisodes.
Your support is trulyappreciated and, by sharing this
podcast with your colleagues,friends and fellow change
(44:42):
practitioners, it can help mereach even more individuals and
professionals who can benefitfrom these discussions.
Remember, and in my opinion,change is an enduring force and
you will only have a measure ofcertainty and control when you
embrace it.
Until next time, thank you forbeing part of the Inner Game of
Change community.
(45:03):
I am Ali Jammah and this is theInner Game of Change podcast.
Host
Ali Juma
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