Leadership in an AI-Enabled World

Summary

In 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

00:00

😀 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.

05:00

🔍 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.

10:03

📊 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.

15:05

🤖 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.

20:06

💡 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.

25:08

🚀 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.

30:12

🛠️ 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.

35:24

🏢 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.

40:26

🛑 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.

45:26

🌐 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.

Keywords

💡Digital Transformation

Digital Transformation refers to the integration of digital technology into all areas of a business, fundamentally changing how an organization operates and delivers value to customers. In the video, the concept is central as the speaker discusses the varying stages of digital transformation that organizations find themselves in, with a focus on how AI is reshaping business strategies and operations.

💡AI-Enabled World

An AI-Enabled World denotes a scenario where artificial intelligence is pervasive and integral to various aspects of life and business. The script explores this concept through the lens of leadership, examining how executives are navigating the challenges and opportunities presented by AI in their respective industries.

💡Generative AI

Generative AI is a subset of artificial intelligence that focuses on creating new content, rather than just analyzing existing data. The script mentions generative AI in the context of the speaker's past work in optimal control theory, as well as its modern applications in areas like chatbots and design, highlighting the evolution of the concept over time.

💡Data Analytics

Data Analytics is the process of examining data sets to draw conclusions about the information they contain. In the video, the speaker's background in data analytics is discussed, emphasizing its importance in building digital businesses and the connection to the current wave of AI adoption in various sectors.

💡Digital Strategy

Digital Strategy involves the development and implementation of initiatives that leverage digital technologies to meet business goals. The script touches on the speaker's experience in creating digital strategies and the realization that leadership and organizational factors often play a critical role in the success of these initiatives.

💡Leadership Implications

Leadership Implications refer to the consequences or effects that a particular situation or trend has on the way leaders operate and make decisions. The video delves into the implications of AI and digital technologies for leadership, suggesting that a new mindset and skill set are required to succeed in the digital era.

💡Digital Maturity

Digital Maturity is a measure of an organization's ability to effectively and efficiently use digital technologies to achieve its goals. The script contrasts digital maturity with the idea of digital transformation as a journey with no endpoint, emphasizing continuous evolution and adaptation to technological advancements.

💡Exponential Growth

Exponential Growth describes a rapid increase in a value or quantity, often associated with technological advancements. The speaker uses the example of AI's development in the context of the game Go to illustrate the concept of exponential growth, pointing out the difficulty in predicting and adapting to such swift changes.

💡Cross-Functional Collaboration

Cross-Functional Collaboration is the process of working with people from different areas of an organization to achieve a common goal. The script highlights the importance of this approach in leveraging AI and digital technologies effectively, as it fosters innovation and ensures a holistic understanding of business challenges and opportunities.

💡Data-Informed Decision Making

Data-Informed Decision Making is the process of using data to inform and guide decision-making processes. In the video, this concept is emphasized as a key organizational characteristic for thriving in the digital era, with the speaker noting the importance of combining data insights with human expertise to drive better outcomes.

💡Adaptability

Adaptability is the ability to adjust and respond effectively to change. The script discusses adaptability as a crucial leadership trait in the AI-enabled world, where the pace of innovation is rapid and constant, requiring leaders to be flexible and open to new ways of working.

💡Cultural Change

Cultural Change refers to the process of modifying the shared values, beliefs, and behaviors that characterize an organization. The video addresses the difficulty of cultural change in the context of digital transformation, noting that even within organizations that are technologically advanced, there can be resistance to adopting new ways of working.

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