0:01

This will be like domesticating

0:03

animals was over the history

0:05

of humanity. We've created something

0:08

extremely powerful and yes, your

0:10

horse can kick you and kill you or

0:12

you can ride it. And all of a sudden you

0:14

don't have to use your own feet. You need to

0:16

go a long distance. These tools

0:18

will help us think differently as leaders.

0:21

And I think the workforce will start to embrace

0:24

it a bit versus being afraid of it.

0:26

They'll see the power and you'll see more

0:28

daily use. You'll see more creative aspects coming

0:30

from people that didn't really maybe have that

0:32

creative brain before. What

0:35

can you now use the machine to do that you

0:37

use to use a human to do? And

0:39

that is going to disrupt industries and

0:41

some industries more than others. But

0:44

we've been through this before. The Internet

0:46

disrupted almost every industry. From

0:51

PwC's management publication, Strategy and Business,

0:53

this is Take On Tomorrow, the

0:55

podcast that brings together experts from

0:57

around the globe to figure out

0:59

what business could and should be

1:01

doing to tackle some of the

1:03

biggest issues facing the world. I'm

1:06

Lizzie O'Leary, a podcaster and journalist

1:08

in New York. And I'm Ayesha

1:10

Hazarika, a broadcaster and writer in

1:12

London. Today

1:15

we're talking all about the jobs

1:17

of the future and specifically how

1:19

artificial intelligence is going to reshape

1:21

our careers. Across

1:23

all industries, AI is

1:25

moving fast. Progress in

1:27

generative AI has been so dramatic

1:29

that in some areas its output

1:31

has become indistinguishable from that of

1:33

humans. From screenwriters to insurance

1:36

underwriters, many people are asking a

1:38

question that until recently would have

1:40

sounded like science fiction. Can

1:42

an algorithm do what I do? And if

1:44

so, what does that mean for me? enough

2:00

to create many good jobs while

2:02

reinventing how current jobs are being done.

2:05

In this episode, we'll be asking

2:08

how AI is likely to transform

2:10

different sectors, and in what way,

2:12

and how can leaders of today

2:15

prepare for all the changes, challenges,

2:17

and opportunities this new era brings?

2:20

To find out more, we'll be

2:23

talking to Jerry Kaplan, an

2:25

AI expert, author, and Silicon Valley

2:27

veteran. But first, let's bring

2:29

in PwC's global AI and innovation

2:32

technology leader, Scott Lykken. Scott,

2:34

welcome. Thanks for joining us. Thank

2:36

you so much for having me here. Very excited

2:39

about the conversation. Now,

2:42

Scott, AI has been around for

2:44

a long time, but today we're

2:46

talking about a particular kind of

2:48

AI, generative AI, and I think

2:51

it would be useful for you

2:53

to just give us a clear

2:55

definition of what that is. I'm

2:57

glad you opened up with the fact

3:00

that it's been around a long time.

3:02

People forget there's been over seven decades

3:04

of research into artificial intelligence. Machine learning

3:06

for the past decade has been something

3:08

businesses have been investing in, and

3:11

we've seen value. But about five

3:13

years ago, when the transformer was created, there

3:15

was something different happening, and really, it's a

3:17

deeper set of machine learning. So neural nets

3:20

and deep learning. So

3:22

the generative AI wave that we're seeing

3:24

that everyone is excited about is

3:26

taking us into this new world where

3:28

the machines and the AI can actually

3:31

create new content, or augment content we

3:33

have. And that content could be text,

3:35

it could be visuals, pictures,

3:37

video, it could be audio. So

3:40

instead of just using machine learning and these

3:42

neural nets to predict an outcome, a single

3:44

outcome, we're seeing generative AI

3:47

give us the ability to create brand

3:49

new creative ideas. And

3:51

I think the other piece of this

3:53

is this massive amount of training. So

3:55

the GPT, the pre-training, having

3:58

the machines look at the entire internet. or

4:00

a lot of the internet, let's say, and

4:02

understand connections that humans just could

4:04

never fathom. And being able

4:06

to use that to generate new ideas, it's

4:09

really amazing. Well, that must

4:11

be coming up in boardrooms a lot right

4:13

now. What are the questions

4:16

you are hearing from business leaders

4:18

right now? It

4:20

is pretty amazing to see the broad interest.

4:22

And boardrooms are one of them. I'd

4:25

say we went through this first phase. The questions

4:27

were, what is it? Is it real? Is it

4:30

just a flash? Is it the shiny object? So

4:33

there was this educational wave. I'd

4:35

say the summer was more of an experimental

4:37

wave. So we're starting to experiment with this

4:39

in our organization. So the boards were asking,

4:41

how do we start to dip our toe?

4:44

Where do we start? A

4:46

lot of the questions were, tell me

4:48

a use case, right? Very tactical,

4:50

tangible, practical. We always step

4:52

back and say, stop thinking about individual

4:54

use cases. And think about the power

4:56

of creation, of generation, of

4:58

pressure organization. And now I think

5:01

it's about enabling. How do I

5:03

look at my workforce and actually use this, either

5:05

myself as an executive on a board or a

5:07

CEO or a CIO? But

5:10

how do my people use this? We're in that

5:12

enablement phase, which is exciting. Well,

5:15

thank you for those thoughts, Scott. We

5:17

will come back to you very soon.

5:19

But first, Lizzie, you spoke recently with

5:21

Jerry Kaplan, who's been working in this

5:23

field for longer than most. Yeah,

5:27

Jerry is a serial Silicon

5:29

Valley entrepreneur. He's an

5:31

adjunct lecturer on the social and

5:33

economic impact of artificial intelligence at

5:35

Stanford University. And he's

5:38

also the author of Generative

5:40

Artificial Intelligence, What Everyone Needs

5:42

to Know. I

5:44

began by asking him for the long

5:46

view. You

5:50

have been thinking about the social,

5:52

economic, and workforce impacts of technology

5:54

for a long time. And your

5:56

latest book deals with generative AI,

5:58

a tech. technology that some

6:01

people liken to the invention of fire.

6:04

So I guess I wonder how

6:06

disruptive does generative AI have the

6:08

potential to be, especially when compared

6:11

to other technologies you've looked at

6:13

in the past? Well,

6:15

I wasn't around during the invention of

6:17

fire, so I can't really make that

6:19

comparison. But I think that of

6:22

all of the inventions in history that

6:24

I think are most closely analogous to

6:26

generative AI, I would

6:28

say it's the domestication of electricity.

6:31

If you think about in the late 1800s,

6:33

before that there was no use of electricity.

6:35

It was known as a natural phenomenon. And

6:37

then we began to harness it first for

6:39

the electric light bulb and on and

6:42

on and on and all the way through modern computers.

6:45

In fact, this may be much

6:47

more than an analogy because I

6:49

think there's an argument that generative

6:52

AI is part of a century-long

6:54

exploration of what we

6:56

actually can do with electricity and what

6:58

power it's going to have for society.

7:01

When you say that, you know,

7:04

you are painting a picture of

7:06

something that is truly transformative. And

7:08

one of the places that that gets talked about

7:11

the most is on the workforce. You

7:13

have people saying generative AI is going to steal

7:15

our jobs or it will make them completely different.

7:18

What about how you see its potential impact

7:20

on how we work? Well, sometimes when

7:22

you hear people talk about artificial intelligence,

7:25

there's a tendency to anthropomorphize it and

7:27

to say there's us and there's them

7:29

and they are coming for our jobs.

7:32

And that's not a productive or inaccurate way to

7:35

think about it. Generative

7:37

artificial intelligence and artificial

7:39

intelligence in general is really a new

7:42

wave of automation. Automation

7:44

is the substitution of

7:46

capital for labor. We've

7:49

been through many waves of automation and this one

7:51

will be no different. So to

7:53

understand its impact, all you need to

7:56

do is to understand how previous waves

7:58

of automation have affected our lives

8:00

and our jobs. To give

8:02

you a very short summary of that, it

8:05

makes us more productive, and

8:07

therefore it makes us wealthier. That

8:10

wealth will create new kinds of opportunities

8:12

because it's going to get spent, and

8:15

that eventually picks up slack in the

8:17

job market, either to the expansion of

8:19

markets or new markets that

8:21

did not exist prior to the

8:23

technology that it enables. And

8:27

so in the short term, when we think

8:29

about the changes that we'll see rippling through

8:31

the workforce, is that this

8:34

person is not needed because AI

8:36

can do their job, or this

8:39

person's job changes? Well, it's

8:41

going to change a wide variety of types

8:43

of jobs, and it's going to create nuance.

8:46

Again, I come back to the analogy of

8:48

what has electricity done for us? What jobs

8:50

involved or benefit from the use of electricity?

8:52

Obviously, an awful lot of them do. I

8:55

think we're going to see the same thing here.

8:57

The first phase is always substitution. What can you

9:00

now use the machine to do that you use

9:02

to use a human to do? And

9:04

that is going to disrupt industries and

9:06

some industries more than others. But

9:09

we've been through this before. The internet

9:11

disrupted almost every industry. Are

9:14

there particular sectors that you have thought

9:16

about that are likely to see the

9:18

biggest changes? The most

9:20

obvious ones, because it's immediate and we're

9:22

already beginning to see the effects today,

9:25

are on what I might loosely call

9:27

the creative industries. Because it

9:29

becomes possible for a person to utilize

9:31

a computer or work in conjunction with

9:33

a computer to generate the kinds of

9:35

creative outputs that previously can only be

9:37

done by hand by

9:40

human beings. That's

9:42

why we're seeing the impact first

9:44

in those particular areas. And I'm

9:46

talking about things like graphic artists,

9:48

people who develop brochures or design

9:50

logos. And obviously, writers

9:52

of just about every variety, their

9:55

work can be accelerated, I wouldn't

9:57

say supplanted, but accelerated by proper

9:59

and appropriate. use of these new

10:01

tools. One of

10:03

the most surprising areas where we're going to

10:05

see significant disruption is in the

10:08

practice of software engineering. The

10:11

increase in productivity that's being seen

10:13

among people who do programming is

10:16

astonishing. And at first you

10:18

might think, well, we don't need as many programmers. Not

10:21

so. What's going to happen is it's

10:23

going to be economically viable

10:26

to build programs to

10:28

do all kinds of things that just

10:30

wouldn't have paid to do in the

10:33

past. You know, I

10:35

would imagine if you were listening to this and you're an

10:37

executive in a company, when

10:40

do you need to be thinking, I've

10:42

got to incorporate this into what my company

10:44

does? In a year,

10:46

two years, five years, 10 years, it's going

10:49

to be all manner of systems that are

10:51

going to be much easier to use and

10:53

much more targeted for specific kinds of purposes.

10:55

So it's easy today to think that what

10:58

we're seeing is, my God, we've

11:00

taught this bear to ride a bicycle. You

11:02

know, look, it can do a picture. Look,

11:05

it can generate a report. Oh, that's silly.

11:07

Look, it made a mistake. What a dopey

11:09

bear on the bicycle. It fell over. But

11:12

that's not really where it's going to go. What's

11:15

really fundamentally happening here is

11:17

that we need to change the way

11:19

we view our use of computer technology.

11:23

People have whole departments of people inside

11:25

most big organizations that will

11:27

curate the data and decide exactly what should

11:29

be fed in. So data

11:31

curation is going to be very

11:33

important. The process of training these

11:35

systems to behave in ways that

11:37

we find socially acceptable is going

11:40

to be another major profession, whatever

11:42

that's going to be called. They

11:44

go through a period of socialization.

11:46

No, you shouldn't answer questions like

11:48

that. You need to tell it

11:50

this way. And that

11:52

is very similar to the way in

11:54

which we train our children or ourselves.

11:57

And I Think that will be a major profession. The

12:00

machines. Will. Be profession very

12:02

much like teaching kids. Let's

12:06

talk a little. Bit about guard rails now.

12:09

When. We are thinking about Ai

12:11

through the lens of the. Workforce:

12:13

What are we need To be

12:15

aware? us? What? We

12:17

need to be thinking about is not how

12:19

to regulate technology. But. How do

12:22

I regulate the uses so that. We

12:25

judges society be bad uses.

12:27

It either outlawed or are minimized

12:30

in some particular weight and without

12:32

holding back the tremendous benefits to

12:34

society is going to get. From.

12:37

A technology that is just

12:39

so incredibly powerful. So.

12:41

Unfortunately, it's. Take.

12:43

Your time, but keep your eyes open. So.

12:45

There's some things we already

12:47

know: Our problems: Effects on

12:50

that: misinformation. Disinformation. propaganda. That.

12:52

Are created by this technology for great well.

12:54

Let's. Go to work on trying to see

12:57

how and what we want to do to

12:59

contain that. When. I don't think we

13:01

need to be worried about. Is. There's

13:04

a lunatic fringe in this

13:06

field. They are. There. Has

13:08

warned for a long time and is. Very

13:11

vociferous right now that these machines

13:13

are somehow going to come alive.

13:15

Rise. Up and Swinton. Humanity

13:18

and make Humanity Exchange. My.

13:20

Personal view is. That's

13:22

nonsense. I think it's exceptionally

13:25

unlikely. I'm. Not even sure how it

13:27

would occur if he wanted to do that. These

13:29

are tools plain and simple. We can argue

13:31

either that or Classes Serves whatever it might

13:33

be are they don't have any goals and

13:35

aspirations. They're not going to be drinking or

13:37

fine line and buying up all the beach

13:40

for property. It's in marrying our our children.

13:42

You know that's not the kind of since

13:44

we need to be wearing about and they

13:46

have no desire to wipe us out. If

13:48

we build a machine using this technology, wipe

13:50

us out. There will be somebody. The

13:53

human. Designing and building that

13:55

in making their happening we just need

13:57

to try to make sure that that's

13:59

is hop. Is possible to do

14:01

thinking about the future. I

14:03

have a three year olds and I

14:06

wonder all the time when the world

14:08

is kinda look like when he's a

14:10

team, when he's in college, when he

14:12

joins the workforce. I

14:14

wonder how you think a

14:16

generative A I. Might.

14:19

Change his reality, You.

14:21

Know fifteen years from Now Twenty years from

14:23

now. Your three year old is

14:25

going to grow up in a very different

14:27

world. Than. we have today

14:29

is going to be a world

14:32

where humans are not the only

14:34

intelligent thing. In the Universe.

14:37

This. Will be like domesticating animals

14:39

was over the history of humanity.

14:42

You know we've created something extremely

14:44

powerful. And yes, your horse can

14:46

kick you in, kill you, or you to

14:48

riders him all the sudden. You don't have

14:50

to use your own feet, do not need

14:52

to go a long distance. That's with

14:54

this will be like but know how are

14:57

very different view of the the place of

14:59

humans in the world. This. Is

15:01

gonna be a shift the focus from

15:03

humans to machines. In the

15:05

future when you wanna get the

15:07

objective. Accurate. Sensible

15:10

and wise advice. You're

15:12

not gonna turn to him being. You're

15:14

going to go ask him Seem. To

15:16

Chaplin. Thank you so much for talking with

15:19

me. Or thank you very much So

15:21

he's been been a pleasure. To

15:25

start, let's start with what Jerry

15:27

was saying about the potential impact

15:30

on the workforce. He was relatively

15:32

optimistic that deploying a I will

15:34

replace tasks but not remove jobs.

15:36

How does that tally with your

15:39

experience on the ground working with

15:41

clients? I tend to take

15:43

a similar view or like to step back

15:45

and sick about. We've been through these cycles

15:48

before they just taken longer. I saw the

15:50

birth of the Internet working on the first

15:52

browser in the nineties, but it took decades

15:54

for that to be infused into businesses. so

15:57

i sing here we're seeing a piece of innovation

15:59

has to But the

16:01

fact is it's going to enable us as humans to

16:03

do our jobs better if we embrace it and we

16:05

create a responsible way to use it. Being

16:08

positive around this is important, but being

16:10

responsible around this is more important. Thinking

16:12

about what guardrails to put in place

16:15

so that we do use this in a good way

16:17

for society, of course, and for business. Scott,

16:20

you're talking about this pace of

16:22

change and this, frankly, exponential pace

16:24

of growth. I wonder

16:27

if there are lessons that have

16:29

been learned or that you have seen from

16:31

early adopters about harnessing the

16:33

power of AI and how that

16:35

has changed a workforce, a company,

16:37

kind of what you've seen in

16:40

this rapid transformation.

16:43

I do see the early

16:45

adopters finding value and then reinvesting it

16:47

in a bigger way. So a lot

16:49

of them started in small business units

16:52

and now they're rolling out across finance

16:54

and other areas just beyond IT.

16:58

I think the next wave is that product development. We're

17:00

already starting to see it and being able to turn

17:03

around products much faster, which is great. I

17:05

think others that are waiting, they're waiting for

17:07

that magical use case. That's just not how

17:09

this happens. You have to infuse it into

17:12

your day-to-day and transform big parts

17:14

of your organization. This is not the days

17:16

of machine learning where you solve one problem

17:18

better. This is the days

17:20

of generative AI that's solving a lot

17:22

of problems better all at once. Unfortunately,

17:25

we're always trying to go back to patterns we know and

17:27

this is not a pattern we know. We've

17:29

never seen it before. So we have to take some risk and I think we

17:31

have to reinvest that in as we

17:33

see success. And I

17:36

know you've deployed this technology

17:38

inside PwC, Scott. What is

17:40

your experience of the impact

17:43

on people and on your own

17:45

productivity? We went down the

17:48

road of let's give you a safe, secure

17:50

environment to use it for work. Do

17:52

not use the open public models. Use

17:54

the secure private model that we're giving

17:57

you And think about how to

17:59

change the tasks. Today today that name

18:01

the think about the future transformation opportunities.

18:03

So as you're working with clients, think

18:05

about father Business could change by using

18:07

this tool. You can advise them if

18:09

you're not using your sense. So we

18:11

want people to learn that way. We

18:13

want to enable them in a safe

18:15

and responsible environment and we want them

18:17

to enemy. I think system and innovation

18:20

and just the grassroots innovation is really

18:22

important, but then again, translating and on

18:24

into business transformation. Her business reinvention is

18:26

a big task and we need a

18:28

lot of people to think about. It. You

18:31

recently published research showing workers were

18:33

more likely to be optimistic than

18:36

pessimistic about Ice, but that they

18:38

do have significant concerns around how

18:40

they acquire the right skills, what

18:42

it means for their future. So

18:45

how should employers address those. Fears.

18:47

So think as an employer you

18:49

should embrace. Of school near full

18:52

workforce you can't just creep pockets of

18:54

capability. The should be for everyone to

18:56

do their jobs better. And find

18:58

ways to be more efficient A

19:00

free meal productivity. Instead of

19:02

just looking out the efficiencies, let's

19:04

look at the ups and revenue

19:07

opportunities. The profitability opportunities, new products

19:09

opportunities. If the depends on the

19:11

entire with for syphilis, it's about

19:13

reasons for for everyone digitally upskilling

19:15

an ai upskilling everyone so that

19:17

there's this bigger greater capacity to

19:20

use technology across the entire workforce.

19:22

And. Some of it as as easy as

19:24

to starting and just prompting some of these

19:26

models to see how they can help you.

19:30

And. Following on from that high

19:32

so it worked as an

19:34

employee as be thinking about

19:36

skills and needs as ten

19:39

a eyes and whose responsibility

19:41

is set to train employees

19:43

on this newly developing pat.

19:45

Is moving so fast. I think some of the challenges what

19:47

do you even train on? again

19:50

no matter when you hear this something

19:52

will have tapes because things are changing

19:54

almost daily the technology so part of

19:56

the challenges having a really flexible training

19:58

curriculum so i think it's the responsibility

20:00

of employers to enable this, that's

20:03

also the responsibility of employees to be curious.

20:06

Instead of just looking at it as a negative, it's gonna

20:08

take away parts of all of my job, think

20:10

about it as a positive. We're gonna enable

20:12

our employees to have access to the right

20:14

tools to learn, and then

20:17

responsibly push them along this journey

20:19

together. Over the

20:21

last few months, there have been

20:23

a number of international events, summits,

20:27

gatherings, occasions where

20:29

governments across the

20:31

world are coming together with tech

20:34

giants to discuss the advancements in

20:36

AI, but also to discuss regulation.

20:38

How important do you think it

20:41

is to have these big

20:43

gatherings on an international level? Yeah,

20:46

I feel even weird saying this as a technologist, but

20:48

this is an area I think some regulation

20:50

is needed. Some technologists say the robots are gonna take

20:52

over the world, and some say, no, no, no, it's

20:55

fine, it's no big deal, but

20:57

this is an area I think we need to get ahead of.

21:00

I do think there's different perspectives around the

21:02

world. So the EU has a different perspective

21:04

than the US, than Asia Pacific. There's still

21:06

a bigger problem to solve, but I think

21:08

it's the first step is getting some of

21:11

that together within regions. But

21:13

I hope it's done right. I hope it's done in

21:15

a way that creates that innovative spark, gives

21:18

some autonomy, creates that

21:20

innovation platform, and so far

21:22

we're seeing some of that. If

21:24

you have a business leader who comes to you

21:26

and says, I want to upscale my workforce, I

21:29

wanna harness the benefits of AI, but I don't

21:31

know where to start, where

21:33

should they start? I always

21:35

start with the strategy around a secure

21:37

environment and a way to upscale your people

21:39

responsibly. How do you bring this tool into

21:41

your enterprise? You have to think through this.

21:43

So there's ways to do that with partners,

21:45

there's ways to do it yourself. But

21:48

if you don't have that, experimentation becomes

21:50

dangerous because you don't control the

21:52

risks. So I say start with that secure

21:54

area and the responsible strategy of

21:56

where you're gonna implement this in your business.

21:59

The enable... and looks at the

22:01

patterns of ways to use

22:03

generative AI, because it doesn't solve every problem. Where

22:06

is there an area I can augment or

22:08

create new content or help my teams do

22:11

that faster? And finding

22:13

ways to test that out quickly, I think

22:15

is really important. So I say start small,

22:17

but with a strategy around responsible and secure

22:20

way to use this technology. So

22:22

Scott, can you look into

22:25

your crystal ball and

22:27

give us an idea of where you

22:30

think AI adoption by business will be

22:32

in let's say 12 months from now. I'm glad

22:34

you didn't say five years because I could

22:36

never answer that. 12

22:39

months from now, I think every business

22:41

will be dabbling to some degree

22:43

in generative AI amongst different areas

22:45

of their business. I think large

22:47

portions, probably 50% or so, will

22:51

be implementing transformational generative AI. There's no

22:53

barrier to using it anymore. Again, if

22:55

you do it securely and responsibly, let

22:58

me restate that, but absolutely, this will

23:00

be infused across businesses. These

23:03

tools will help us think differently as

23:05

leaders. And I think the workforce

23:07

will start to embrace it a

23:09

bit versus being afraid of it. They'll see

23:11

the power and you'll see more daily use.

23:13

You'll see more creative aspects coming from people

23:15

that didn't really maybe have that creative brain

23:17

before. They'll be using this to really extend

23:19

their own skills. So I'm excited. I'm a

23:21

little bit frightened about how fast it's working

23:24

or moving, but I love technology, so I'll

23:26

roll with it. Well, Scott, it's

23:28

been such a pleasure speaking with you. Thank you

23:30

so much for your insights. Thank you.

23:32

It was fun. Aisha,

23:36

I am struck by something

23:39

both Scott and Jerry talked about,

23:41

which is the speed of this

23:43

transformation, that this technology

23:46

has been developed for decades and

23:48

decades, and yet we have had

23:50

this exponential

23:53

explosion of

23:55

AI tools being deployed

23:57

and AI in the workforce and

23:59

AI. within different aspects

24:01

of companies. Like it's all finally

24:03

happening, it's all coming together. I

24:05

think that's both why there is

24:07

such excitement and among some people,

24:10

such trepidation about how

24:12

quickly all of this technology is rolling

24:14

out. Listening to

24:16

Scott and Jerry, the big takeaway

24:18

is, look, you have to be

24:20

positive about this because it is

24:22

coming down the track. Whether you're

24:24

a CEO, whether you're a tech

24:27

expert, everybody is dealing

24:29

with AI in some way.

24:31

So you have to be positive, but

24:33

you have to be responsible. We

24:36

do have to innovate, but we also

24:38

need the right regulation and we actually

24:40

do need the right guardrails. And I

24:42

think that's really fascinating to hear that

24:45

from this very innovative community

24:47

of people. Well,

24:54

that brings us to the end of this episode. Next

24:57

time on Take On Tomorrow, we're headed

24:59

to Davos and the World Economic Forum's

25:02

annual meeting. Join us

25:04

for a special episode where we'll be

25:06

asking how businesses can take action on

25:08

their energy demand and thrive in the

25:10

energy transition. We'll also

25:12

be releasing the findings of PwC's

25:15

27th Global CEO Survey, which

25:17

provides key insights from thousands of

25:19

CEOs around the world on issues

25:22

facing business, society, and the global economy.

25:28

Take On Tomorrow is brought to

25:30

you by PwC's strategy and business.

25:33

PwC refers to the PwC network

25:35

and or one or more of

25:37

its member firms, each of which

25:39

is a separate legal entity.