Leadership in an AI-Enabled World
Summary
TLDRIn this insightful session, Sanman and Professor Linda Hill explore the challenges and strategies of leading in an AI-enabled world. They discuss the importance of adaptability, continuous learning, and data-informed decision-making for executives. With real-world examples and research, they emphasize the need for a new leadership mindset that embraces digital transformation and the cultural shifts it entails, encouraging leaders to reimagine their roles and organizations to thrive in the digital era.
Takeaways
- 😀 The speaker emphasizes the importance of engaging and interactive sessions for learning and discussion, especially in the context of digital transformation and AI leadership.
- 👥 The speaker, Sanman, along with Professor Linda Hill and executive fellow An Lam, teaches a program called 'Leading in the Digital Era', highlighting the need for constant reinvention due to rapid changes in technology.
- 🔧 Sanman's background is in engineering and he has spent the last 20 years helping companies grow digital businesses, indicating the practical experience that informs his perspective on AI and leadership.
- 📈 The script discusses the concept of 'generative AI', showing that AI concepts have been around for a long time but are evolving, especially since the advent of platforms like Chat GPT in 2022.
- 🌐 The research conducted by the speakers involved global roundtables and a survey of over 6,500 executives, providing a broad perspective on leadership in the digital era.
- 📊 The survey results indicate that while many companies have started their digital transformation, a significant portion still feel they have a long way to go, with only 30% of those in the first five years feeling they've made significant progress.
- 🤖 AI usage is growing, with half of the companies surveyed using AI in some capacity, and 87% expecting to use it in some form in the next three years.
- 🛠️ There is a noted resistance to adopting AI, particularly in production, due to the difficulty in finding tangible benefits and the challenge of integrating AI into existing workflows.
- 💡 The discussion suggests that companies are still in the testing phase with AI, and there is a need for better understanding and training on how to effectively use AI tools.
- 🔑 The speaker suggests that leadership in the AI-enabled world requires a different mindset and behaviors, including being data-informed, customer-focused, and adaptable.
- 🚀 The importance of having a bold vision and the courage to embrace exponential changes in technology is highlighted, as is the need for leaders to be catalysts for change within their organizations.
Q & A
What is the main focus of the program 'Leading in the Digital Era'?
-The program 'Leading in the Digital Era' is an executive education program focused on leadership in the context of digital transformation and AI, rather than the technical aspects of these technologies.
What is the background of the speaker Sanman?
-Sanman is an executive fellow at the business school who has spent the last 20 years helping companies create and grow digital businesses, data analytics, and AI-enabled solutions. He has a technical background, having trained as an engineer and worked on optimal control theory, a form of generative AI from 30 years ago.
What is the significance of the speaker's old thesis on optimal control theory?
-The significance of the speaker's old thesis on optimal control theory is that it represents an early form of generative AI, illustrating that the concepts of generative AI have been around for a long time, albeit in different forms.
What was the speaker's role at the software company PTC?
-At PTC, the speaker was involved in the SAS transformation of the company and also worked with generative design, a type of AI that provides different solutions for mechanical equipment based on given prompts and specifications.
What are the key leadership implications of being in the digital era according to the speaker?
-The speaker suggests that the key leadership implications of being in the digital era include the need for a different mindset, set of behaviors, and capabilities to understand and navigate the leadership challenges presented by rapid technological advancements.
How did the speaker and his team conduct their research on leadership in the digital era?
-The speaker and his team conducted their research by working with HBS Global Research centers to set up roundtables, speaking to almost 250 senior executives worldwide, and administering a survey to over 6,500 executives from more than 100 countries.
What is the difference between 'digital maturity' and 'digital transformation' as discussed in the script?
-Digital maturity refers to an ongoing process of adapting to and integrating digital technologies into an organization's operations, recognizing that the goalposts are always moving due to rapid innovation. In contrast, digital transformation often implies a specific, often large-scale change process, with the implication of reaching a final state or 'enlightenment'.
What percentage of companies surveyed are currently using AI in some form or fashion, according to the script?
-According to the script, approximately 50% of the companies surveyed are currently using AI in some form or fashion.
What is the projected percentage of companies that will be using AI three years from now, as per the executives surveyed in the script?
-The executives surveyed in the script project that 87% of companies will be using AI in some form or fashion three years from now.
What are the main functions where companies are currently using AI, as discussed in the script?
-The main functions where companies are currently using AI, as discussed in the script, include customer service, finance and accounting, and production.
What challenges do executives face in terms of AI usage and implementation, as mentioned in the script?
-The challenges executives face in terms of AI usage and implementation include resistance to change, difficulty in prompting AI effectively, lack of understanding of how to integrate AI into existing workflows, and the struggle to comprehend exponential growth in AI capabilities.
Outlines
😀 Introduction to the Digital Era Leadership Program
The speaker, Sanman, introduces the session focused on leadership in the digital era, specifically in an AI-enabled world. He mentions his background in engineering and experience in digital businesses, data analytics, and AI. Sanman highlights his involvement in teaching an executive education program at a business school alongside Professor Linda Hill and fellow executive, Lam. The program, 'Leading in the Digital Era,' is constantly evolving due to the rapidly changing landscape of technology. The speaker also shares his previous work with a software company, PTC, and his experience with generative AI in the form of optimal control theory and generative design.
🔍 Research Insights on Leadership in the Digital Age
The speaker discusses the research conducted to understand the leadership implications of modern technology, which has become mainstream only in the past few decades. The research involved digital natives and roundtable discussions with nearly 250 senior executives worldwide, excluding Antarctica, and a survey of over 6,500 executives from more than 100 countries. The aim was to identify the characteristics leaders and organizations need to survive and thrive in the digital era. The speaker shares insights from the executives on their digital transformation and AI enablement journeys, noting the varying perceptions of progress.
📊 Analysis of Digital Transformation Progress
The speaker presents data from the survey, showing the self-assessed progress of companies in their digital transformation. Only 2% of companies haven't started, while 50% have been working on it for less than 5 years, and over a third have been at it for more than 5 years. Interestingly, 70% of those who have been on the journey for over 10 years feel they are making significant progress. The speaker notes the dynamic nature of goals in digital transformation, as the field is constantly evolving, and the difficulty in feeling a sense of completion.
🤖 AI Usage in Businesses Today and Predictions for 2027
The speaker delves into the current usage of AI within companies, with about half of the companies surveyed using AI in some capacity, particularly in customer service. The expectation is that by 2027, 87% of companies will be using AI. However, there is skepticism about the actual implementation in areas like production and product management, where the benefits of AI are less clear. The speaker suggests that the real innovation potential of AI might be in areas that are not yet fully explored or understood by executives.
💡 The Importance of Organizational and Leadership Adaptability
The speaker emphasizes the need for organizations to be data-informed, to collaborate across functions, and to focus on continuous learning. These characteristics are seen as crucial for thriving in the digital era. The speaker shares anecdotes from various companies, highlighting the cultural challenges and the importance of having the right data and infrastructure in place. The conversation also touches on the concept of 'digital maturity' rather than 'digital transformation,' indicating an ongoing process rather than a destination.
🚀 The Exponential Growth of AI and its Impact
The speaker discusses the exponential nature of AI development, using the example of the game Go and the AI program developed by Deep Mind. The program's rapid improvement and defeat of the world's top Go player illustrate the speed at which AI can advance. The speaker suggests that executives are struggling to comprehend this exponential growth and its implications for their businesses, highlighting the need for a shift in mindset to adapt to these changes.
🛠️ The Role of AI in Job Functions and Strategic Planning
The speaker explores the integration of AI with job functions, suggesting that executives should reimagine roles as a combination of human and robot capabilities. There is a call for strategic planning that focuses on how companies will change due to AI, rather than just the technology itself. The speaker also addresses the challenges of governance and the need for boards to understand the disruptive potential of AI on business models and services.
🏢 Organizational Characteristics for Thriving in the AI-Enabled World
The speaker outlines the key organizational characteristics identified by executives as crucial for thriving in the AI-enabled world. These include data-informed decision-making, cross-functional collaboration, continuous learning, customer focus, and comfort with change. The speaker also discusses the importance of having the right data and infrastructure, as well as the cultural shifts necessary for successful digital transformation.
🛑 The Challenges and Resistance to AI Integration
The speaker discusses the challenges and resistance faced by organizations in integrating AI, including difficulties in prompting AI effectively and cultural resistance to change. The speaker shares experiences from various companies, emphasizing the importance of training and executive support in overcoming these challenges. The conversation also touches on the need for companies to balance innovation with maintaining financial stability and meeting quarterly earnings reports.
🌐 The Importance of Ecosystem Partnerships and Leadership Mindset
The speaker concludes by emphasizing the importance of ecosystem partnerships and the need for leaders to embrace a new mindset that includes continuous learning, adaptability, creativity, and courage. The speaker challenges the audience to consider what they will do differently as a result of the conversation and invites them to share their thoughts and experiences, highlighting the ongoing nature of the research and the evolving landscape of leadership in the digital era.
Mindmap
Keywords
💡Digital Transformation
💡AI-Enabled World
💡Generative AI
💡Data Analytics
💡Digital Strategy
💡Leadership Implications
💡Digital Maturity
💡Exponential Growth
💡Cross-Functional Collaboration
💡Data-Informed Decision Making
💡Adaptability
💡Cultural Change
Highlights
The session aims for an engaging and interactive experience focused on leadership in the digital era.
The speaker, Sanman, introduces himself as an executive fellow at a business school, alongside Professor Linda Hill and executive fellow An Lam, teaching a program called 'Leading in the Digital Era'.
The program is constantly reinvented due to the rapidly changing landscape of digital technologies, including AI.
Sanman's background in engineering and experience with generative AI, such as optimal control theory from his 1994 thesis, is highlighted.
Different forms of generative AI, such as generative design, are discussed, showing the evolution of the concept over time.
The impact of AI, particularly since the release of Chat GPT in November 2022, on leadership and organizational strategies is a key topic.
The importance of having the right data and infrastructure as prerequisites for digital transformation is emphasized.
A survey of over 6,500 executives from more than 100 countries reveals insights into the characteristics needed for leaders and organizations to thrive in the AI-enabled era.
Only 2% of executives report that their companies have not started digital transformation, while over 50% have been at it for less than 5 years.
There is a perceived 'moving goal post' in digital transformation, with 70% of companies that have been on the journey for over 10 years claiming significant progress.
Cultural change is identified as a significant barrier to digital transformation, particularly in more traditional industries.
The concept of 'digital maturity' is introduced as an ongoing process rather than a destination, reflecting the continuous nature of technological change.
AI usage in customer service is highlighted, with 50% of executives reporting its use in some form, projected to increase to 87% in three years.
The potential for AI in areas beyond the current 'low hanging fruit' of customer service and finance is discussed, suggesting a need for further innovation.
The exponential nature of AI development is illustrated through the example of the game Go and the rapid advancement of AI players.
The importance of company culture in the adoption and integration of AI is underscored, with examples of digital natives and traditional companies.
Leadership characteristics for the AI-enabled world are outlined, including adaptability, creativity, and a customer-centric approach.
The need for leaders to embrace a mindset of continuous learning and adaptability in response to exponential technological changes is stressed.
A final challenge is issued to participants to consider one actionable change they will implement in their organizations based on the discussion.
Transcripts
[Music]
afteron um did everyone have a good
lunch this
is Dred afternoon time slot the one
straight after lunch so I had to get
some advice as you can tell from a
couple of different
sources and uh I think they some pretty
good advice I would say I'm not going to
do I'm going to do a lot of it but I'm
not going to do all of it for example
I'm not going to ask you to move around
and ask people to take one to two minute
break for
L but I think uh what I'm hoping for is
an engaging uh session an interactive
session we're going to be talking a lot
we're going to be learning from each
other a lot um and uh and I'd love to
take it from there so um my name is uh
San man
and together with I'm an executive
fellow here at business school and so
together with Professor Linda Hill and
with another executive fellow called an
Lam uh I teach a program called leading
in the digital era uh it is an executive
education program and we've been doing
it for the past three years and every
year I feel like we are constantly
Reinventing because things keep changing
all the time um but uh when we're not
teaching this program we're also
researching the subject as well and
that's what we're the topic of this
conversation is going to be about uh
today's topic is leading in an AI
enabled world and uh as I said it's
um you know it the the program itself
and what we've been talking about is
leadership oriented it's not a technical
program having said that my background
is technical uh I spent the last 20
years helping companies
create and grow digital uh businesses
data analytics and now increasingly AI
enabled um I trained as an engineer um I
dug up my old thesis and so what you see
over here actually is a form an old form
of generative AI it was optimal control
theory so you can tell that was from 30
years ago 1994 wow so so as you can tell
generative AI the concepts of gener AI
was were existing for quite some period
of time in a different form so to speak
um I trained this engine for 5 years
worked as an engineer for five years yes
did
you more why why you you you make the
par well at the same time with when you
when you use optimal control um what
you're doing is you are giving prompts
and you're saying this is what my end
conditions should be and therefore using
these constraints and these and
conditions what is the best way to get
there that was the case in the thesis
work that I've done over there now at
the same time as as early as uh as late
as 2019 2020 I also was working with a
software company called PTC where I was
doing the SAS transformation for the
company but one of the things there was
also we had another type of generative
AI called generative design where you
actually gave prompts for what type of
mechanical equipment you wanted to
actually build and out would come a
number of different solutions and you
choose based on what your specifications
were as well so there are different
forms generative AI that we've sort of
known about but it hasn't been anything
near to what we've experienced ever
since November 2022 when chat GPT came
out open AI came out open as well so
anyways um my my sort of work over these
past 20 years was really um helping you
know I was I was I was the Thompson
ruers for 10 years and uh building data
analytics businesses I ran three of
their digital businesses um when I was
running new Ventures as well and while I
was doing this also for other companies
later on I noticed that um you know you
would end up creating a digital strategy
you would end up creating an
implementation plan where you do the
technology you build the infrastructure
you develop the different uh business
models and so so forth as well and then
when you're running it over a period of
time you suddenly realize that the
aspirations you had for where you wanted
to grow weren't sometimes fulfilled and
in a lot of those when you do the sort
of a postmortem that a lot of those
happen to be leadership or organization
related so not technology
related and so with that in mind when
Professor Linda Hill asked me and an to
come and join her to do some research
because we really wanted to understand
the leadership implications of what it
means to be in this day and age because
if you think about this look at all of
these look at all of these Technologies
here they've really only come to the
mainstream in the past 20 30 years or so
and it's something that certainly when I
was an MBA student here in CL of 2001 I
think I have a few of my section mates
here as well already um these are the
kind of things that we didn't really
sort of learn about from the leadership
perspective and so the way to lead is
actually different and our thesis was
it's a different mindset different set
of behaviors and different set of
capabilities that we should be
investigating and so that was really the
impetus for us to do our
research and we did the research in
conjunction with you know the team that
I mentioned before but we also brought
in some digital natives uh uh in our
team who can really help us with the lay
of the land and sort of reverse Mentor
as well
and we worked with the HBS Global
Research centers there are so many of
these centers all around around the
world and what they helped us with was
setting up these roundtables as you see
over here we spoke to almost 250 senior
Executives all around the world
basically every continent except
Antarctica
um and it was across all of the major
industrial sectors um we also
administered now in its third year a
survey again to senior Executives and
this now survey is more than 6 and a
half thousand Executives from over a 100
countries and that gave us sort of a
view of what you feel might be the
relevant characteristics that leaders
need to have and organizations need to
have in order to really survive and
thrive in this uh digital era in this
particularly AI enabled era so what I'm
going to talk to you about um today is
uh first give you sort of a lay of the
land of you know where these folks think
they are in their digital transformation
journey and their AI enablement journey
and then we'll double click into the AI
element of it which is you know what are
they actually doing where are they
actually using it and what are they
thinking about they're going to be using
going forward uh and then finally we'll
translate that into what do we think are
the the relevant organizational and
Leadership
implications uh as we think about
surviving and going and really thriving
surviv and Thrive is something you'll
hear from me a lot all right um actually
before I go to the next stage I want to
show of hands how many of you are in the
earlier stages of a digital
transformation process it could be AI
enablement it could be something more
digital data analytics oriented uh let's
say um 5 years in up to 5 years in just
raise a show
hands all right how many of you have
been doing this for more than five so
between five to 10
years your organizations are in the
digital transformation Journey so you're
working with a company and the company
is now implemented Data Systems has
Implement testing out AI systems and all
those types of things how many people
been doing it for longer than five years
but less than 10 years
mulle companies yeah yes multiple
companies okay and how many of you have
been doing it for more than 10
years okay there's a handful over here
so when we ask these Executives this is
what we
heard right so only 2% haven't started
yet which is
great
um 50% have been doing this more than
50% have been doing this for less than 5
years right so it's actually in the
earliest stages of uh doing this here's
the interesting part over a third have
been doing this longer than five years
which I thought was pretty pretty
awesome right I mean there's 15% have
been doing it for more than 10 years um
now we asked the same question but we
asked them in a different way was how
much progress do you
think want to venture a guest OPP
what do you
do like reverse where it
shows. interesting so here's what they
being snarky but so interesting here
here's what they said which is actually
quite interesting so to give you a
little bit of a context blue here means
those companies who feel like they're
making a great deal of progress we asked
them to do it on a on a range of you
know zero one to six or or and five and
six were a great great deal of progress
so those who said five and six it's
these ones now a little caveat here when
we talk about all of this right we're
talking about Executives perceptions I'm
talking a round table it's their
perception of how they're doing I'm
asking in a survey it's their perception
of how they're doing right so one
company's perception of their progress
relative to their goals may be very
different to another company's
perception of their relative their goals
but having said all that when you put it
all when you put it all together we
still see some trends that are notable
and that's what we're kind of talking
about here so the the trend we see here
is those who are one to five years in
the in the in in into the journey over
here which is more than half the
people but only about 30% feel like they
made a significant amount of progress
you know if you're in one year it's even
less right but those who've been doing
it for longer
I mean look at this the folks who've
been doing it for more than 10 years
there's only 15% of them who have been
doing it for more than 10
years but 70% of that 15 say that
they're making a great deal of
progress
so what do you make of
that my colleague here says that the go
is sorry you going to speak louder the
go by my colleague here says that the go
is moving all the time and I have to
agree so you're Co calling your
[Laughter]
colleague I I tell you something at a
more than 20 years ago it was about um
getting processes and data model and and
and implementing in in automated
automated systems uh and then data
governance uh so there's there's many
many different things that you do at the
time at the time there was no AI of
course so you do what it's in the menu
so so your colleague is very very
astute thank you so I mean that it it
takes a long time there's a lot of
processes and so forth as well which
which uh which you have to go through as
one of the uh prerequisites we heard
just this morning in that that major
session the amount the of importance
that that's attached to having the right
data and the right infrastructure and
everything in place as well so that's
something that's certainly one that you
wanted to say well I think that the
difference too is that uh less than one
year you've got the Revolt of the
experts right and if you're born digital
you've been making new decisions with
data from day one so I think there's
just a lot of change management or a lot
of
scaffolding against adop I like that I
might use that at some point the Revolt
of the experts so you're saying here
there's a lot of resistance well yeah
because prediction and judgment hasn't
been decoupled yet it's just still exist
in a person that's got experience but up
above prediction and judgment was
decoupled from day one
yeah yes it just makes me wonder if the
B it for 10 plus years have they created
a whole bunch of technical debt to be
disrupted in the you know with what's
happening now yeah that's that's that's
also possible so leading on from what my
colleague here said I think it's a
culture thing like if it's a company if
you're Amazon or something you yeah I
mean maybe born digital is a bit
pretentious right but it's normal it's
part of it I'm work in financial
services where some specifically
insurance which is kind of slow to
change so I think part of it is those
companies you know everyone and a bit
also what you're say that people have
got used to it that's part of it you
join you know Google and Amazon and
whatever even Walmart is pretty good at
this stuff as far as I know right um
because you that's part of it and that's
what you want to do whereas you don't
necessarily um I don't know doing an
insurance broker because you really want
to do um you know digital transformation
so
I I I think a lot of it is is about the
company culture and I'm I'm a board
member now so that's something we think
about a lot well so we are going to
spend a bit of time on uh on company
culture uh um so I will uh I'll ask
you one question what have you
experienced that explains this as well
company culture was one that you talked
about yes um data processes and the
cleanliness of the data from one server
to the next and not having
infrastructure put into place you're
you're cleaning a lot of data up front
so you're doing a lot of work right away
and then you're starting to see a gain
so you're not going to get a big gain
until until you're further down the road
and one of the things we've also noted
that's very right I mean one of the
things we've also noted is that uh one
second is that many of these Executives
were saying that it's like a moving goal
poost things keep changing all the time
and so you're never ever feeling like
you reached your goals you're getting
close to it and when something changes
and then you know you come to November
2022 and all of a sudden you have to
reevaluate everything else because
everyone's are jumping on the AI
bandwagon so to speak so we call this we
like to call this digital maturity as
opposed to digital transformation
because it's not like you go you know
I've reached Enlightenment and I don't
need to do anymore it's never going to
be the case soor you wouldn't think yeah
well my I've been at this sort of
company's transformation for about 50
years and the B the basic rule of thumb
is any major transformation takes 10
years and all companies have to be
reinvented after about a decade so your
your finding is just
consistent it big organizations
particularly if they're
successful indeed indeed and in fact
what we're realizing also is while these
systems need time to
change the pace of innovation is going
faster than we're able to change as well
so we have to struggle with that and
it's causing us I mean you saw
everything that Ethan was showing were
like blown away I mean it's like that's
the kind of stuff that we have to deal
with all right so let me let me jump in
now to when you do a little double click
because one one thing we did this year
was We we really wanted to understand
the AI uh usage and this is what we
asked very basic question to start
things off which is how many of you are
actually using AI in some form or
fashion and what we see here is about
half of them half of the companies this
is
2341 half of them are using it in some
formal fashion and when you when we ask
them to project how many of them are
going to be using it 3 years from now
it's I'm surprised it's not 100% but
it's okay it's 87% which is a not huge
amount in some some form or fashion and
then we ask them where exactly will you
be using this right which of your
functions do you think you'll be using
this and this is what they told us right
so just to give you a l this is 2024 and
we're saying this because we did this
earlier on this
year customer
service out of the
2341 Executives that we spoke to from
over 100
countries 50% of them are using Ai and
customer service in some form or fashion
and you know you've just heard about the
types of things you can do um and then
the same
thing 15% are using them in production
or not even 20% of are using them in
Finance and Accounting so
does that seem does that seem right does
that seem
intuitively okay to you no so when you
asked the first question I'm in
production so it's it's hard to I apply
into production right it's very labor
intensive I don't place the customer I
can make processing more efficient but
if I still need x amount of people to do
manual work where do I actually find
benefit right of using you know you use
a task manager stuff like that or slack
or whatever okay that helps a little bit
in efficiency in terms of data the
operations but where can I actually find
something exponential in terms of
efficiency So you you're you're
saying I've got all these people I've
got all these processes I need to find
something which is tangible which is
going to really move the dial for me and
I haven't found anything so far yeah
interesting anyone else yes like the way
I read this is like those four
categories were no hanging fruits every
even grab them the real Innovation is
going to come in the categories that you
don't see there which is like sales
product management Edgar like I've seen
people talking about these things but
there is more Innovation needs to happen
there is the and those are the groups
that were never talking to technology
teams ever before so are you are you are
you in a l here by the way no because
you would have been one of those weakest
colors from from my experience working
clients this feels overstated which what
feels over the customer service yeah the
whole thing oh interesting tell me more
well couple a couple of observations
what we see with clients is is they go
through a life cycle of generative AI a
lot of clients are in testing phase at
this point they haven't been able to
figure out how to roll it out at
production and scale the second thing is
maybe see the executives are answering
it's because of its personal
productivity use as opposed to changing
the workflows because it there's no
barriers to trying this stuff out in the
organization it's it's a valid point uh
we did ask them um not you know don't
don't you don't you don't use it for you
know making poems or anything like that
birthday things it's got to be for work
so that's for sure but I think you're
right in that everyone's still in
testing phase right they're still trying
to understand and process what's going
on but how do I use this how do I try
this and by the way I see uh I'm going
to co Call Tuck here tuck I see the
the Russell Reynolds guys have come up
with a um a report which I thought was
really great which was they actually
looked at asked a bunch of Executives
and asked them how are you using it
which phase are you using it and so you
can see that some are test in testing
phase some are in U sort of production
phase and so forth as well so there's
there's a whole gamut of all those
things which I think is is useful now
here's what we when we ask them how's it
what's it going to look like three years
from now this is what they told us right
so in the red is
2027 what do you make of
that I'm got to pick someone in the
middle here because they Haven
mid oh I kind of wonder if that's
aspirational or if there's a road map to
that I'm sure there's a lot of those
that it's like I'd love to automate and
use AI for more Finance and Accounting
but I see no road map for it there's not
a lot of technology or anything even
coming out to that gets that so it's
it's used that much more so I this sort
of like
a i me I'm not sure I understand because
if I look at production and product ma
product management staying the lowest
like isn't AI in robotics and that's
going to be like a huge growth area like
I don't understand why it's so low it's
it's it's funny you say this because
this is sort of the the the thinking
process that we had when we were
analyzing all this later on um so a
couple of things that we've noticed
first of
all without a doubt everyone's saying
yeah I I use AI a little bit and I'm
testing it and experimenting a little
bit and I'm sure I'm going to use it a
lot more and that's why all the reds are
pretty much High then there's I know my
business and remember these are SE Suite
Executives so a CFO may not necessarily
know what the applications are in
production right so there's a little bit
of that that we have to try and
understand as well and then there's
actually one other aspect
which I think is is a contributor to
this which is actually bigger than we
think it is um now you just saw azim uh
in in that conversation he talks about
the exponential view we have a professor
here at HBS called shag go some of you
may know him he teaches a program called
fre technologies that will change the
world by 2035 right um one of them was
actually spoken up very poorly today
blockchain we have ai blockchain and
synthetic biology right but the whole
concept of exponential change is
something that is actually really tough
for anyone to understand right we are so
used to thinking things in a linear
fashion right what happened before is
what's going to happen going forward I
maybe it's going to go a little bit
faster oh look at the internet I know
since 1994 or 1993 when uh when I had
Netscape and it was um it before yeah
Mosaic when Mosaic came out uh and and I
know what the trend is I know Amazon
came at this time and therefore I I can
project the same thing going forward and
now with AI maybe it's going to go a
little bit faster but actually all of
those Technologies in many cases are
exponential and certainly AI in itself
is exponential so he spends a lot of
time
telling people to imagine what an
exponential growth is looking like uh
with a a bunch of different examples one
example that I really love and I can
relate to is uh anyone know the game
go strategy g go right who knows what it
is yeah just explain very quickly what
it is it's I did that for my daughter's
High School application video I have a
script so it's the old Chinese game it's
like 2,000 years old I think it's 18
line by 18 line so it's a bunch of uh
300 Crossing and one player has red
uh yellow oh sorry Black Stone PS one
has the white one and then you place one
the other place one the the objective
the game is to if you Circle the other
side then all that get limited way and
the eventual game is you want more than
half of the 361 dots so it's a strategy
game
it's been around 2 and a half thousand
years we still play it and over those
years we have improved it's been passed
down strategies have been passed down
and we're improving improving improving
2014 um a startup called Deep Mind which
is now owned by Google says I'm going to
build a program that is going to really
Challenge and really try and learn how
to play go and be the best
in 2016 it learned from all of these
games from the that humans have played
in 2016 it played against the world
number one Lisa doll two years beat him
hands
down so this computer program which
learned through all these algorithms in
two years beat the world's number one
player and then what do you do what do
you do after that how do you improve
something after that play against
yourself play against yourself right so
they built another another program which
is even more fast and more higher
computation played against itself how
long did it
take 20 minutes 3
days 3 days before it beat that version
that beat Lisa doll and then they said
okay let's build another one which is
even more popular which is even more
complex and uh and
computational that took eight hours of
trading Data before it beat the pre the
version that beat Lis so two and a half
thousand
years 2 years 3 days eight hours that's
exponential and that's something that we
absolutely are not able to comprehend
until we hear these types of examples
and I think that's what a lot of our
executives are struggling with these
really smart people right say oh I think
I'm going to double my use of AI because
I I can see one or two applications I
think it's going to really change
dramatically now a show of hands oh tuck
go ahead I I was just going to add to
that I think the spot we are now the use
cases might be obvious but we're asking
Executives who don't know what this
is what might happen like the business
we're in now we're saying well you
should actually reimagine every one of
the job specs for these functions as a
person plus a robot and who would be
qualified to run that new position then
ask them the questions so we're in a
point here now where the seite jobs are
not properly scoped from personal robot
and the people in them are the old model
right so I think it's going to be really
interesting to challenge each of your
functions and figure out which ones at
most risk and how do I reinvent it we're
early on that I think so and his his
really really funny one on this because
we are talking about cwis but then we
have the long-term persons in the
company in the boards that even know
less to talk about is
that so how do you create so my point is
that maybe many of the companies that
said that they are not going to use AI
they will not exist in three years and
and so and I think that the problem
starts at the top of the pyramid right
now which is with governence and how do
you bring this knowledge to discuss how
your business will be disrupted because
maybe for me the most important point
there is connected it strategic planning
is how your company will change it's not
about technology how the business the
the solutions that you're providing the
services so and I think that's more than
really just if you are tackling sales or
marketing is the overall concept of your
kind so hold that B can I just add one
thing since you've attacked the board
members in the
room it's it's often the board members
that who may not know AI but ask the
really tough questions because they're
not going to lose budgets or people yes
I when I look at that I say yeah it's a
little bit like this but also it's
interesting the loow hanging fruit seems
to be the first thing in any technology
Wave It's low hanging fruit it's
incrementalism and then the fear is if I
touch the core what's going to happen
with the business while I'm going
through the transformation because I got
to report my earnings every quarter so
there's that there's something about the
risk Dynamic that really has to change
as well yes so that you can see the
other side of the valley that you're
trying to get to and have the ability to
go through the ups and downs to get
there I mean I wonder in your first
chart if some of those people that
didn't see prog ress is because in the
first few years they had a bunch of
projects that got funded and defunded
and they didn't show progress so they
lost the leader the board decided they
didn't want to fund it anymore and how
many of those had consistent support
financially and and peoplewise to work
through it to get to where they wanted
to the board perspective there but but I
think I think the the idea of boldness
that you're talking about is something
which is very very important that's
something that we've we've heard as well
I'm just going to go very quickly
through this because I wanted to spend a
bit more time on this I realize got you
know we've only got an hour and we can
go on for ages um when we asked whether
was substitutive or complimentary this
is the answer that we got so there's a
couple of things I I'll go through this
quite quickly but there's a couple of
things that stuck which is and I'm sure
you can see it actually I you know what
I'm GNA ask you what two things do you
see
here sorry your other category is
gone and
delusional I mean it's not popular I
mean sorry to be political but Hillary
Clinton and the coal miners right if you
say people are going to lose their jobs
which they are but I'm not a politician
but they I don't think people want to
think about that so I feel like so
Martin sorl was quite bold when yeah
yeah I agree and and I do think in
certain
areas we really have to think about that
right because that combination of that
exponential growth in Ai and and the
possibilities together with
robotics um that could change
substantially right in other areas it
may be less but I think Point here is
everyone's in this magic 8020
Rule and and I think it's going to be
varying a lot more so what I'm going to
give you guys a little bit of a time now
I'm going to give you maybe three four
minutes I want you to just gather
amongst your neighbors here's what we're
going to do little little exercise uh
this is what happens when you have an
afternoon session by way um think about
get three of you together just Bunch up
and think about in your organizations
where you've been using and how you've
been using it what have been what what
has worked what hasn't worked and
particularly think about it from two
perspectives organizational perspective
and Leadership perspective so I'm going
to give you a couple of minutes to just
to talk about it and I'm going to ask
for some brave souls to raise their hand
and give give their experience
[Applause]
of
[Applause]
I'll give you an example I'll give an ex
up
F fin
of
that's
[Music]
to preservation
oration as it is
[Music]
you should replicate your
intern
[Music]
[Applause]
[Music]
like flash the lights right you
know what Happ sit right fr
[Music]
go ahead all right so um we have two two
Consulting companies here and one SAS
company um and so we talked about are we
really using llms right now and we're
just starting to think about them and so
then from our my company that's using
classic oldfashioned AI machine learning
to do predictions uh We've started one
to build our own GPT because what we've
been doing is scraping the web and then
trying to get the you know regular GPT
to score training and education how well
it fits to the factors that are driving
predictions doesn't fit at all well so
the difficulties have been that my folks
don't it's very hard so they they want
to revert back to doing it themselves
and using their own brains as the GPT
and when we dug resistance then yeah so
when we dug underneath it um I think one
of the issues is they don't know how to
prompt so we need to do more training
and I think the second issue is the only
reason that we're doing we're continuing
on the GPT path is because I have made
the I'm the CEO I have made the
executive decision that we will do it we
are going to figure out how to
any other
team I I heard a lot of
noise I I um so for us the commonality
with us had to do with culture I work in
healthcare and we are so slow we have so
much data but there's this whole privacy
issue so culture has just been a well wi
I just joined my organization a year and
a half ago so I come in the disruptor
and trying to change the culture we're
still working the culture part and
trying to get them to um even look at
systems right but then you have to also
I'm in operations so you have to make
sure it's not disruptive I think
somebody said it it's not disruptive
enough that it's impacting financial and
you know um we have to look at Health
outcomes and be efficient and and still
produce that value right so you got to
have to juggle both and how to figure
out that balance she's a financial
services and same thing she she said
from the higher level all um they all
they've all drunk the Kool-Aid but then
trying to get the lower managers to them
Buy in and then he goes where he's in
Tech and you think everybody should be
using the technology but it's sort of
like a it's not really spread out people
might be using chot GPT on the side but
not really broadcasting so you could
tell that it's still a whole cultural
bottom line culture Chang cult it's hard
yeah yeah so anyone else yep
so now he's speaking for
himself um I work for SNP we are the
providers of the data to no I used to
work for Reuters we were competitors oh
good nice job we can talk a lot um so we
have a lot of vendors uh we get crappy
data pardon my friend um and then
there's a lot of problem for us because
for me my team is the gatekeeper of all
the data that comes for an companies
Securities and Market data which is like
you know which goes to Dow Jones and
ratings and things like that um coming
back to the where we we are using
generative the answer is we have start
so you're absolutely right that we in
the testing phase are we have we been
using AI yes to what she said machine
learning yes to an extent not completely
but to an extent so that's my answer to
first question um second is advantages
it has given us tremendous this it has
shown tremendous progress and at the
face of it the difficulty is I do not
know how to validate
that and the fourth perspective to that
is organizational perspective yes we
want to use uh AI we want to use
everything that is at the suite that's
at our disposal the problem is we have
to keep exploiting what we have but we
have to keep looking at what's there in
the future for us so that we can pull
that back into our mean stream work
that's we interesting so it's it's I'm
going to just move quickly ahead because
I want us to you know we've talked about
the issues with making that
change we're in testing phase we want to
make the changes there's a little bit of
resistance all these things when we
asked the folks what is really important
in order to be able to have all of these
Technologies at the disposal and the
organization
actually working together to be able to
do this what are the characteristics
from an organizational perspective to be
able to survive and thrive this is what
they told us so this is organizational
characteristics data informed decision
making and cross functional
collaboration came up tops right closely
followed by continuous learning you we
talked about the difficulty you have to
train everyone and so forth the custom
Focus always stays it's as long as you
are actually implementing it with the
customer in mind and you're not just
doing some sort of mindless T testing
and then the Comfort will change these
are all
things and just to give you some backr
we we asked them about a whole bunch of
different factors and these were the
ones that they R rated as time does that
does that does that resonate does that
surprise
you no no some instances I think that uh
there's more emphasis on customer
customer focus versus versus just
handling the data uh but I think they're
they both go together because uh data
informed decision making will will serve
the customer uh directly and indirectly
so so I think the I'm surprised by the
the low 41% there interesting by the way
the when I say data informed decision-
making do you do you see the distinction
between data informed and datadriven
yes right so data
driven is the data is telling us we need
to do this let's do this marketing
analytics is a great example of that
right yeah it's just huge volume we know
how to how to uh to work with that data
informed on the other hand is that there
is an element of human interaction there
well it's a human in the loop whatever
you want to call it it it is there's
constant checking and iterations that go
on with it as well and uh I was talking
to a
the head of digital at a major Asian oil
and gas company and he had his mandate
was I need to increase revenue from my
refineries and I'm going to focus on my
distillation cost for those of you who
you
know distillation column is a very
important piece of equipment in the oil
refining process and he had his OT
people and he had his it people the
operational folks who know the process
and the engineering and the and the
equipment really well and the data
scientists who know all their models and
who can build algorithms and everything
and he asked them to work together
crossfunction collaboration
supposedly the data science folks went
off and created these models and they
came up with this presentation this
wonderful presentation that had a
scatter plot which was tightly aligned
and he was like wow this is I've never
seen a scatter plot like this before and
it was totally wrong because because
what he what they told them was you know
what if you you increase the temperature
of the distillation column you will get
more bottom product and so anyone who's
a chemical engineer I I trained as a
chemical engineer so I started laughing
when I heard that right anyone who's a
chemical engineer or a chemistry major
will know that that's physically not
possible right it's against physics it's
against chemistry it's against all and
he basically said you have to be God if
you right but the reason was that they
looked at the data sets in in isolation
and they and they chose the wrong data
sets right so I think the lesson here is
that data informed is really important
they need to make sure that they get the
experts together talk about this and we
we've heard about this not just from a
Senior Management context but also more
from a line manager context as well so
these are the ones which really came out
as uh as important and question oh sorry
go
ahead um were were there any
correlations between the results you're
seeing here in the cost centers so I I
from the last
one that I saw I'm looking and I see
okay this is around revenue and profit
that's where the sees are looking at
it's revenue and profit generation and
and and now we come here and I thinking
to myself okay the last few customer
focus the last one was customer service
where can I spend less money so I'm
really kind of concerned in this
situation that they're actually taking
the customer out um of the of the
picture um and then data inform cost of
decision- making is is high right so if
I make better decisions and it cost me
less so I'm just curious if if you saw a
correlation there uh well so the example
I gave you was the revenue generation uh
example right but I don't think there
was any correlation with that but that's
a good question to ask actually yeah
this I mean think about this this is you
know two and a half thousand people
almost and that's just from this year
it's actually very similar over the past
few years let me just show you this this
is 2022 in Gray and this is
2024 in uh in red
very very similar very similar and the
reason why things like de de and
transparent communication ethical
governance of data the reason why when
we asked because we went back to the to
the uh executive panels and and asked
them why is that so low I
mean and and really what they said was
we feel like we're actually doing a good
job we have systems and processes in
place and we feel we can fathom what we
could do with it whereas in these other
areas we're not quite sure and I see it
in my management that we're not actually
doing this a lot of it is based on
intuition the decision making or we're
not getting enough collaboration it's
those silos that everyone's talking
about and so forth as well so that
that's really what uh was sort of
generated um soon so I think what struck
me right now like looking at this one is
that we were talking about exponential
Grove exponential changes and yet the
reasons or the things that needs to be
in there inorder order to compete are
the same reasons for like many many many
we know that and still that still has to
exist and then some of the new things
that are popping up are the ones that's
also going to go down I just don't um
see that and I guess I now reflect on
what you said a while ago dear colleag
from around is that from a leadership
perspective are you actually wired to be
able to compete now in this day and age
with this because it's the
same so things it's surprising that you
know this is I can look at it also from
another perspective which is pre-chat
GPT post chat
GPT still quite similar but what you
said like what they responded as most
important to compete in gen
a between 22 and 24 they all dropped in
importance so the most important thing
to compete in gen is data informed
decision making digital to compete in
this digital era so it's not just gen
it's together but it dropped off an
importance in the last two years how do
we read
that if they're saying that's the most
important thing to compete in the
digital to the point I was trying to
make earlier the customer uh Focus drops
significantly there from 22 to 24 and I
cannot really validate that in my mind I
can't can't see so so I I would look at
this as so these are not significantly
different enough I mean custom Focus may
be to a certain degree but they're not
significantly different enough that it's
it's that you're saying that it's uh
it's a it's there's a cause and effect
there's no real cause and effect that we
can see but they're Outsourcing it to
strategic Partners right because that's
gone from nothing
to one of the things one of the things
that we did hear a lot about was if you
don't have a lot of competence yourself
in certain areas and you know for
example if someone's closer to your end
user than you are then there's you can
there's things you can do from a
strategic partnership view as well um I
want to quickly now just actually ask
you
your thoughts
on the leadership characteristics
because these are all things that
ultimately when we ask them what is it
really important from a Leader's
perspective if you are in a business or
in an
organization what are those
characteristics that are most important
to thrive going forward this is digital
and AI enabled
world that's what came out yeah right
and I know that we've talked a lot it's
funny Mary talked
about curiosity right
um we also had a a type of was it was
agility but adaptability is sort of all
encompassing a Beyond agility as well so
there's a few of these things creativity
we talked about that as well so I think
there are you know a lot of these
similarities that we've heard already
from the previous P discussions you see
it here as well um is there anything
that you was surprising it should have
been that just curious connected the
previous slide also did you see anything
about hierarchy or the need to do with
hierarchy yes so um the funny thing is
the one of the concepts of data informed
decision making is that the the
information and the decision making is
done at the level where the expertise is
so I loved what was said before about
having the traditional 10 to 12 direct
reports now being 40 direct reports
right because a lot of organizations
particularly the more Innovative
organizations are having that type of
lack of hierarchy or less hierarchy and
so you have and and in many cases when I
when I think about the adaptability part
here part of that is because we're
getting a lot of digital natives that
are coming into the organization reverse
mentoring the more senior Executives
because most of them are senior
Executives right now and therefore
there's a lot of knowledge transfer
that's going ahead um which is
facilitating that so you know who was it
that said it' be great to have a 27y old
on on the on the board right next to the
yeah exactly I mean that's the kind of
thinking that people are experimenting
with now yes I'm curious it seems like
most of your research is with fairly
large companies it's actually uh that's
a great question there is there is a
broad spectrum uh I don't have that here
with me but it's you know when you think
about it it's over 100 countries and
it's uh Executives all around uh there's
a pretty decent amount of folks who are
sub you know 100 million sub 10 million
revenues as well so did you cut the data
because I'm really curious about those
companies that are sub 100 million if
the if the data looks
different we haven't done it yet so we I
think that's a good idea we had actually
done it by geography I don't have that
either um but I think by by revenue is
another way we could do it as well so
that's that's helpful right because the
smaller company I mean they don't have
some of the things you're talking about
are Irrelevant in a company in these
smaller sizes and I'm just really
curious particularly from a leadership
perspective where we're there's not the
same amount of legacy and hierarchy and
I mean not like there's none um I'd love
to hear
your philosophy on what does leadership
look like in those companies yeah so I
I'll give you a personal anecdote okay
so um as I said I've worked with a lot
of different companies different sizes
for the last couple of years I was
working with a company which is a risk
management company series B
funded series B level I was running
product and strategy and m&a on the
product
side um we were using we were using uh
llms to actually create our own QA
process because we didn't actually have
well I came I grew up in the PNG world
where we had a three-letter acent for
everything so p& current best approach
we didn't have a current best approach
for which we could do for our
application so we built one ourselves
and it was done just by rolling up the
sleeves and doing it ourselves that is
the level of adaptability we're we're
talking about here as well my team well
all over the world I had them you know
some of the the digital natives who were
working with me one of them was you know
actually um in in a different country
and a climbing wall and still being able
to do his work and so forth as well so
there's a there's a whole bunch of these
things that we see and even in the
smaller companies that we've spoken to
in our roundt for example our Africa
Round Table we had um one company who
was in HBS Alum actually who was in that
round table and he had all of his um
board members be communicating on
WhatsApp and and being agile in that in
that respect because you know they
didn't go through the the large
processes and so forth as well so there
are examples of these types of situation
now I want to quickly just very quickly
go we have a couple more minutes
um very similar type of profile here
again um and everything that we've done
by the way and it's not and it's not
that there is not enough delegation
going on it's just like we don't
emphasize that because we already have a
lot of those uh um processes in place we
don't have too much here from a process
perspective or from a you know bringing
people along perspective and that's why
the focus is is is over there
um everything that we've sort of done
and even when we're doing our program uh
is through this framework which is the
no dob framework right what do I need to
know in order to understand what a
digitally mature organization is and
truly Ai and a organization what do I
need to do in order to actually build
and Lead it and then finally who do I
need to be myself in order to transform
myself as well as my organization
because that involves a lot of change on
everyone's part and we about a year and
a half ago or so wrote three pieces and
published three pieces in uh in HBS
working knowledge so it's freely
available if you go to HBS wk.com or
whatever it is you'll be able to see
these pieces and we wrote them in that
framework which
is no do B so each one of those three
articles is in that and what you see is
this is really a summary of that right
in our program I actually make a
laminated card and give it to every
partici um but what you see there is you
know these are the qualities that you
need to be thinking about right we
talked about the importance of data in
formed culture we talked about
distributed decision making but think
about the hierarchy
right continuous experimentation and
learning these are all things that you
need to be consistently doing and we
don't see that in many organizations
where it's consistently being done and
then when you actually are in the due
phase what do I need to do you really
have to be prepared for that Journey
because it's a it's a lot of hard work
to bring everyone in the organization
along with you to be able to do this
right and so you need to be able to
upscale that Talent you need to be able
to bring in new digital natives who are
going to help reverse Mentor you and
also take you take you forward and show
you all the new possibilities that are
out there as well and and then we talked
about Partnerships the ecosystem
Partnerships which is really uh crucial
as well um and then finally about being
yourself right it's back to you cannot
you can be a CEO and do top down on
certain things like culture change I
think that's really important
but all the other things that we are so
used to doing from a from a top down uh
command and control perspective that
doesn't really fly anymore in this day
and age right because people have more
information than you and so you have to
be trusting and let go your job as a
leader is a catalyst to help them
actually go and do all of these things
and your job as a leader is to be
courageous to know that oh there's all
these technologies that could
completely uproot everything that we are
doing and we need to be able to kind of
figure out which one of these are really
going to be useful and and then employ
them as quickly as possible so that we
don't lose that Competitive Edge and
that's really the uh the essence of uh
what we're doing so if there's I feel
like there there may be a few takeaways
for you for you but if there's three
things that I want you to really focus
on is that now more than ever
organizations that are going to succeed
have to embrace very D much more data
informed culture and much more cross
functional collaboration that's one of
the one of the keys uh for Success here
and then today's leaders really have to
have a different mindset it's really
about mindset and behavior change and
that's really around continuously
learning continuously adapting staying
curious I'm glad that curious was was
used as as as an important factor and
being very data Savvy being able to
understand that and then at the same
time you got to be really have that
courageous mindset which is to prepare
yourself because it is exponential we
have to keep in imagining these
exponential changes and rely and and and
and really make use of that so we can go
forward so with all of that I'm going to
give you a little challenge a friendly
challenge as you go back to your
organizations what one thing are you
going to do differently as a result of
today's conversation right and and feel
free that's my I LinkedIn QR by the way
feel free to just send me through the
emails or through the QR and I'd love to
hear from you because obviously we're
always looking for folks to work with
and learn from and perhaps be part of
the roundtables and so forth as well so
you know this research continues I'm
sure that our program next year is going
to be very different again because there
going to be all these new de
developments and with that thank you
very much
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