0:00

Call them changemakers. Call them

0:02

rule breakers. We call them redefiners.

0:05

Join us in conversation with daring

0:07

leaders who are creating extraordinary impact

0:09

and driving change from around the

0:12

globe. Each episode gives you

0:14

a fresh perspective on your leadership and

0:16

career journey. I'm Hoda Tahun,

0:18

a leadership advisor at Russell Reynolds.

0:20

I'm Clark Murphy, the former chief

0:23

executive officer and a leadership advisor.

0:25

And this is Redefiners. Hi,

0:29

everyone, and welcome back to Redefiners.

0:31

I'm Hoda Tahun, a leadership advisor

0:33

at Russell Reynolds Associates, and I

0:35

am here with my phenomenal co

0:37

-host, Simon Kingston. Hi, equally

0:40

phenomenal. Hoda, great to be with you. Before

0:42

we get started, just a quick

0:44

reminder to our listeners that you

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can find all episodes of Redefiners

0:48

and the Leadership Lounge on YouTube.

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And if you're currently watching Redefiners on

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an episode. And for our audio listeners,

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don't forget to rate redefiners wherever you

1:01

get your podcasts. We absolutely

1:04

love to get your feedback. Simon,

1:06

today's conversation focuses on a key

1:08

topic that we've been covering that

1:11

is the potential to continue to

1:13

redefine and at least impact every aspect

1:15

of our lives, business and society. AI.

1:18

Yes, soda AI. It's a subject

1:21

that must be on every leader's

1:23

mind as they try and wrestle

1:25

with the implementation of the technology,

1:27

both to gain efficiencies, to enhance

1:29

the quality of their business and

1:31

ultimately to grow revenues. A

1:34

few leaders, I think it's fair to say,

1:36

have jumped in with both feet and are

1:38

making it work for them. But I think

1:41

a greater number in the work that we've

1:43

done are still working out what it means

1:45

for them, testing and in the experimental phase

1:47

and working out where they can get most

1:50

bang for the buck. And I

1:52

think we saw a very similar adoption

1:54

curve with the digital transformation about a

1:56

decade ago where some leaders quickly figured

1:58

out the process and value of digitizing

2:00

their businesses while others were a bit

2:03

stuck in maybe more traditional workflows and

2:05

processes, right? And I'm sure you've seen

2:07

that with your clients. I

2:09

certainly have seen quite a bit of

2:11

that in the hospitality world with crews

2:13

and hotel companies that are perhaps figured

2:15

out how to use the AI and

2:17

the technology to scan through and scour

2:19

through customer feedback forms, or maybe others

2:21

are still doing it the old fashioned

2:23

way. Yeah, and we're seeing it in

2:25

social impact too, where they're thinking both

2:27

about the way in which they can achieve

2:29

even better value for the scarce resources that they've

2:32

got, but also thinking about the ethical. dimensions

2:34

of this, which loom large for quite a lot of

2:36

social organizations. Yeah, and I think we're going to dive

2:39

in quite a bit today on the ethical piece. So

2:41

today's guests can hopefully help us better

2:43

understand how leaders can harness the power

2:45

of AI in their business, especially when

2:47

it comes to creating better experiences for

2:50

their customers and employees. That's

2:52

right, Hoda. Our guest today is

2:54

a serial entrepreneur. He's led companies

2:56

both in the digital transformation

2:58

and now in AI -led

3:01

change. is

3:03

the chairman and CEO of Coveo,

3:06

which is a global provider of

3:08

artificial intelligence -powered business solutions for

3:10

e -commerce, customer service, and workplace

3:12

applications. Before that, he

3:15

co -founded and served as chairman and CEO

3:17

of Teleo, which delivers cloud

3:19

software for talent and human

3:21

capital management, and was

3:24

acquired by Oracle for $1

3:26

.9 billion in 2012. Louis

3:28

serves on the board of

3:31

Alimentation Custard, Inc. which

3:33

owns and operates 16 ,000

3:35

Cushar and Circle K convenience

3:37

stores in 26 countries across

3:39

the world. And he

3:41

also, as if that wasn't enough, sits on

3:44

the board of Petal MD, a leading cloud

3:46

applications provider in the medical sector. Louis,

3:49

welcome to Redefiners. Thank

3:51

you, Hoda. Thank you, Simon. Great to be with you

3:53

today. So, Louis, when most people think

3:55

of AI companies, they typically think of

3:58

the big tech hubs like Silicon Valley

4:00

or Seattle in the United States. And

4:02

your previous company, Teleo, is based in

4:04

San Francisco. But Coveo is based in

4:06

Quebec, Canada, which is quite a bit

4:08

away from Silicon Valley. Do you see

4:10

that as an advantage or a disadvantage

4:13

being outside the typical tech hubs? Well,

4:15

first of all, Teleo was founded

4:17

also in Canada. had a majority

4:19

of its 1 ,500 employees in

4:22

Canada. But if you look at

4:24

whether it's Thaleo or Coveo today,

4:27

if you think about Coveo specifically, yes,

4:30

we are a Canadian company, but we

4:32

do 98 % of our revenue outside

4:34

of Canada. What I think is noteworthy

4:37

here is that a lot of the

4:39

AI you know, not all of it,

4:41

but a lot of the AI you

4:44

know actually was invented in Canada. If

4:46

you look at The recent

4:48

Nobel Prize in physics is

4:50

Jeff Hinton from the University

4:53

of Toronto and Joshua Benjo

4:55

at the Montreal Institute of

4:57

Learning algorithms. It was actually

5:00

also nominated three years

5:02

ago. And so there's

5:04

a lot of AI talent here in the

5:06

country. And more importantly is

5:09

we've been in the application of

5:11

AI. in the

5:13

case of Coveo since 2012. That's

5:15

when we started adopting machine learning

5:18

in our platforms, in

5:20

our search platforms, and personalization platforms

5:22

for digital experiences. So this is

5:24

where we do a lot of

5:27

our research and development. We have

5:29

closed a lot of people working

5:31

at Coveo. We are a Canadian

5:33

public company. But again,

5:35

we do it for large enterprises across

5:37

the world. A lot of the brands

5:39

you know, Leo

5:41

technology under the hood. So

5:44

we have established that AI is really Canadian.

5:47

Good. I did

5:49

not quite say it exactly like

5:52

that. Talking about you

5:54

though, Louis, you've been a leader,

5:56

a senior leader in the businesses

5:58

that you've helped lead for quarter

6:00

of a century. And on the face

6:02

of it, you move into those leadership

6:04

roles very quickly after graduation. Was

6:07

there a moment that impelled you?

6:09

into that kind of leadership and to

6:11

find you what we call on this

6:13

podcast a redefiner moment for you that

6:15

shaped who you became as a leader.

6:18

I think the defining moment for

6:20

me and you know might

6:22

sound a bit like cliche.

6:24

I was probably raised by

6:26

a mom and dad who

6:29

taught me at an early

6:31

age that happiness is reality

6:34

minus expectations when while

6:36

frustration is probably expectations

6:38

minus reality. And

6:40

I don't aspire as a leader

6:43

as being a very notorious person

6:45

or whatever. I really believe in

6:47

the power of teams. And I

6:50

know it might be cliche to

6:52

say that, but I do have a

6:54

framework for who I surround myself with.

6:56

I like grit, I like

6:59

curiosity, I like

7:01

rigor and engagement. I

7:04

think there are many things that We can

7:06

do. I could be doing something else. But,

7:09

you know, I'm someone who's been

7:12

married 34 years and who's

7:14

been pretty loyal to my

7:16

partners over the years. And

7:18

I really believe in the

7:20

stick -to -itiveness of teams

7:22

and, you know, having a

7:24

common mission and being very

7:26

resilient. You know, most companies, most

7:29

people are not resilient. And

7:31

I think we can take advantage of that

7:33

as entrepreneurs, always be

7:35

the last one standing. So it's

7:37

probably a combination of those

7:40

moments and some core

7:42

beliefs that took us to

7:44

where we are. And then again, you tell

7:46

me what the definition of success is, I'm

7:48

still trying to find it. I think

7:50

there's a wide body of thought that would suggest

7:52

you're pretty successful. But

7:54

what's intriguing in these

7:57

conversations that and Clark and I

7:59

have the privilege of having is how often

8:01

leaders refer to their families, refer to

8:03

the foundation years in terms of

8:05

the values that help shape them.

8:07

So it's interesting that you reach for that so

8:09

naturally. I think fundamentally it

8:12

starts with values, just like when

8:14

you build a business. Business has

8:17

a spine. A business has, yeah,

8:19

a mission and a vision and

8:21

a mission, but fundamentally

8:23

it is about creating

8:26

a spinal system that

8:29

people adhere to. In

8:32

our case, I believe in

8:34

three core fundamental values, which

8:36

is everything in a business is designed

8:39

to ensure that customers succeed every

8:41

time. And I

8:43

think that's the externally facing value without

8:45

customers. Businesses are about revenues

8:48

and customers. Everything else is a proxy

8:50

to achieve that. And I

8:52

think that's really, really fundamental.

8:55

Customers must succeed. The

8:57

second value to serve that is that

8:59

you only earn trust when you deliver

9:01

value. And then from

9:03

an internal perspective, which applies both

9:05

externally and externally. And internally, you

9:08

just hire great people. I've mentioned

9:11

that before. And you just tell

9:13

them to do the right thing

9:15

and help the team. You

9:18

know, I always tell people, you know, if you want

9:20

to go fast, you go alone. If you want to

9:22

go far, you need a team. And

9:24

in order to achieve that, you need

9:26

to be always learning, always listening. You

9:28

need to elevate others, embrace

9:31

differences, because if you bring people in

9:33

a room that, you know, people talk

9:35

about diversity these days, it's

9:37

interesting. It's intriguing to me that,

9:39

you know, we've took diversity

9:41

down to Excel

9:43

metrics and all of that

9:46

diversity should be a goal

9:48

because only in diversity you

9:50

find innovation you don't

9:53

find innovation and creativity

9:55

and new solutions to problems by

9:58

putting in the room people who.

10:00

Think think the same look

10:02

the same act the same you

10:04

you know it comes from human

10:06

collision so embracing others differences

10:08

and really then it's

10:11

about. getting people to

10:13

take ownership, getting things done and

10:15

engaging and cultivating excellence. And

10:17

if you just, you know. I've

10:20

just described what 70 % of my

10:22

job is. The

10:24

rest is talkative people like you. You've

10:28

given us a whole set of threads which

10:30

are going to draw out over the course

10:32

of the next 25 or 30 minutes. But

10:35

just in terms of locating where you are

10:37

now, you were right at the forefront of

10:39

the digital transformation when you co -founded Teleo.

10:42

That gives you an amazing

10:44

ability to compare how leaders

10:46

were prepared for that wave

10:48

of technology -driven change with how

10:51

they are now as they face

10:53

into AI. And

10:55

you're obviously part of that with

10:57

Caveo. But as you think about those

10:59

two waves of change and transformation, how

11:03

well -prepared do you think leaders are

11:05

for AI relative to how they were then?

11:08

Not well, but more and more. I

11:12

think AI, first of all, AI is not new. I

11:14

wasn't the founder, contrary to Tileo,

11:17

where I was the co -founder.

11:19

I wasn't the founder of Coveo.

11:21

I was the angel investor. And

11:23

when I was at Tileo, we were

11:26

public on the NASDAQ back then and

11:28

so on. So I was still there.

11:30

And I met Laurent, my partner today,

11:32

the founder of Coveo in 2008. who

11:35

was a search guy who was

11:37

very strong in search and natural

11:40

language processing and delivering large -scale

11:42

search experiences and so on. And

11:44

in 2008, he told me, he said,

11:46

look at this technology. It's called machine

11:48

learning. And Netflix uses

11:51

that. And Amazon uses

11:53

that. And Wayfair uses that.

11:55

And they're going to revolutionize

11:57

the furniture industry. And

12:00

so we'll Spotify and et cetera.

12:03

because that was the very

12:05

defining technology that turned digital

12:08

experiences from content -centric to

12:10

person -centric. This is

12:12

your Netflix experience, right? You know, who's watching is

12:14

the first question. And once they know that they

12:17

assemble content for you, you can search Meryl Streep,

12:19

you don't need to, because they do

12:21

a better job, right? They knew the entire repertoire

12:23

and so on. So it was really a revolution

12:25

in that space. Our

12:28

thesis in 2012 was

12:30

that corporates whether it's

12:32

corporate America or the corporate world would

12:34

wake up within about

12:37

five years. And that

12:39

by 2017 -18, every

12:42

enterprise would adopt AI to deliver

12:44

their digital experiences the same way

12:46

Netflix does it for you. We

12:49

were wrong. It took

12:51

chat GPT. If you look at

12:53

the big picture, chat GPT wasn't just

12:55

the launch of Generative AI

12:57

of course it was and it was

13:00

a major event took the world by

13:02

storm, but it was way more than

13:04

that It literally woke up the world. It

13:06

was the very defining galvanized moment where people

13:08

woke up and said well wait a second

13:11

I can write a poem on

13:13

my iPhone and And and and I

13:15

could get it to you know, this

13:17

is different right? It's it's a different

13:19

paradigm I don't think

13:21

companies, and it's very, to

13:23

this date, it's very intriguing to me. If

13:25

you think about the retail industry, they

13:29

essentially witnessed Amazon

13:31

using machine learning takeover

13:33

the world for 15

13:35

years. And honestly, they did nothing,

13:38

aside from a few

13:40

larger retailers, Walmart did, et cetera.

13:42

But if you look across the board,

13:45

the adoption of AI, albeit

13:47

so logical, in an

13:50

area such as commerce

13:52

didn't hit the imagination. Now

13:55

it is, obviously, and

13:58

it's going to revolutionize the world, the

14:00

world of knowledge. I always

14:02

say that the transformation of

14:05

technology over 30 years was

14:07

about efficiency gain, using

14:09

software to do faster, better,

14:12

more systematic processes, essentially what

14:14

was essentially what software was

14:16

designed for. We build data

14:18

models, we program rules on these data

14:20

models. AI finds the rules.

14:24

That's a different thing. And

14:26

then suddenly, now we're in the world

14:28

of proficiency gains, not efficiency. So if

14:30

you have 10 ,000 employees, what happens

14:32

when every employee can handle 30 %

14:34

more complexity, 50 % more of the

14:36

time, 90 % faster? That's

14:39

what we're talking about. And so the

14:41

world is going to be divided between

14:43

the AI adopters and non -AI adopters.

14:45

And I always say AI or die. It's

14:47

going to be the greatest competitive divide

14:49

in business that we will have ever seen.

14:52

Why did it take some

14:54

people so long to spot that potential?

14:56

And what can we learn from that

14:58

delay, as it were,

15:01

in advising leaders on how to respond

15:03

now? i think in general

15:05

there's always a lag in

15:08

in technology adoption and look

15:10

particularly in uh in canada

15:12

i would say but also the

15:15

fact that it was it's hard uh

15:17

you know a company like coveo

15:19

build we are we built one

15:21

single platform coveo is one

15:24

big platform we didn't do

15:26

custom code that applies intelligence

15:28

into digital experiences

15:30

in commerce and customer

15:32

service websites or workplace

15:34

applications and but it's one single platform

15:36

but it took us 15 years. To

15:40

build all the indexing the search

15:42

the semantic layer the relevance layer

15:44

and now all the grounding and

15:47

the generative ipod and so on

15:49

and now we're moving beyond

15:51

that to being able for instance

15:53

to optimize margins in real time

15:56

and all that. Back to

15:58

your question, Simon, I think it's the

16:00

obscure aspect of AI

16:03

that probably people didn't

16:05

grasp. Or most people

16:07

didn't understand that the

16:09

very experiences that as

16:12

consumers, we go

16:14

through all day every day, from,

16:17

again, Netflix to Uber to our powered

16:19

by AI. There are videos

16:21

of Jeff Bezos talking about machine

16:23

learning in 2006. As

16:27

I said earlier, it's very

16:29

interesting that it took Chad GPT

16:31

as the catalyst, but I

16:33

guess now it went the other

16:35

way. I think it went way

16:38

beyond hype, and I think we're

16:40

entering, in a way, a little

16:43

bit of a phase of disillusionment

16:45

as the dust settles, typically

16:47

reality stands. And

16:49

now you sort of

16:52

realize that markets and

16:54

people are far more

16:56

educated because some of them

16:58

tried and failed and experimented and

17:00

so on. And so

17:02

people are far more now

17:04

knowledgeable about what it takes

17:06

to make this all work,

17:09

property. And that's

17:11

obviously a big opportunity

17:13

for applied AI companies

17:15

like Covell. And Louie,

17:17

on this topic of where the

17:19

value is going to be created

17:21

as companies and executive leadership teams

17:24

and board directors are thinking about

17:26

the next 10 years, what should

17:28

they be thinking about? And

17:30

what advice would you give to leaders so that

17:32

they don't maybe make mistakes that have been made

17:34

over the last 10 years? The

17:37

advice I would give is

17:39

there are a number of

17:41

known use cases in the

17:44

area of digital experiences. you

17:46

will not be able to

17:49

compete in areas such as

17:51

retail, commerce, business

17:53

to business commerce, in areas

17:55

such as customer service, when an

17:57

advisor at a bank can ask a

17:59

very complex question

18:02

such as, you know, for my client,

18:04

what are the tax implications of a

18:06

mortgage on a second home in northern

18:08

Wisconsin, given the change of regulation by

18:11

the city of XYZ and blah, blah,

18:13

blah, press return and get that answer.

18:17

That's game changing

18:19

and you cannot

18:21

underestimate the human

18:23

augmentation associated with

18:26

that ability. Of

18:29

course, it's hard to do

18:31

and companies like us know how to execute

18:33

on that, but you should not

18:35

underestimate the ability that this

18:38

will create. Again, I

18:40

come back to my previous statement. What

18:42

happens? when suddenly

18:45

people online can handle 30 %

18:47

more complexity, 50 % or of

18:49

the time, 90 % faster. That's

18:51

what we're talking about. It's

18:53

the age of proficiency, not the

18:56

age of efficiency again. And that's

18:58

really, really, really profound.

19:01

And so my advice is

19:03

embrace it quickly. And

19:05

as a follow -up to this

19:08

part of the conversation, what about

19:10

responsible AI and ethics? We would

19:12

love your perspective on this piece.

19:15

And what should leaders keep in mind around the ethical

19:17

piece as it comes to AI? First of

19:19

all, thou shalt not use third -party data.

19:22

Netflix uses your data, uses

19:25

what you click on, the trailers you watch,

19:27

what you start watching, what you drop, what

19:30

you browse, and et cetera. And they

19:32

use the sum total of all the

19:34

other 100 million users and et cetera.

19:36

And that's where they find the patterns

19:39

using machine learning. to figure out what

19:41

you're going to enjoy next. But if

19:43

you want to opt out, you opt

19:45

out. So they're never going to go

19:47

behind your back and et cetera. And

19:50

so I think this is ethics. And

19:52

I think it's designed for people. And

19:55

again, it uses data that you can

19:57

control. And you're

20:00

agreeing to that. People want that

20:02

experience and so on. And that's

20:04

a great use of technology. I

20:07

think in this day and age,

20:09

what people expect from companies is

20:11

one very simple thing. Don't

20:13

waste my time. Because time is

20:15

the most precious thing we all have. If

20:18

they use technology to

20:20

help me be more efficient

20:22

with my time, I think I really

20:25

appreciate that. If

20:27

they do that now in

20:29

a manner that if they

20:31

try to do it to

20:33

influence me in other ways,

20:35

or go figure out things

20:37

that reach my privacy

20:39

and etc. I think I'm

20:41

personally, I'm violently against that.

20:46

We'll be right back with Louis

20:48

Tatou. But first we'll hear from Harpreet

20:50

Karana, our Chief Digital and Data Analytics

20:52

Officer. Harpreet will discuss

20:54

why it's so important that organizations

20:56

commit to using AI responsibly. It's

20:59

clear that artificial intelligence offers

21:01

amazing opportunities to innovate. Yet,

21:03

it can introduce significant risks

21:05

if left unchecked. That's

21:07

why it's important for organizations to

21:10

put proper safeguards for AI development

21:12

and use. In fact, many

21:14

will be legally required to do

21:16

so through regulations like the EU

21:19

AI Act. Yet, our

21:21

research reveals a concerning gap. Only

21:23

27 % of leaders feel their

21:25

organizations provide adequate guidance on ethical

21:28

use of AI, and just 24

21:30

% believe they have sufficient protections

21:32

against AI misuse. So

21:34

what's the solution? Especially in an

21:37

environment where the underlying technology is

21:39

moving so quickly. One important

21:41

first step is to develop and

21:43

implement responsible AI principles that guide

21:45

organizations on ethical uses of AI.

21:48

At Russell Reynolds Associates, we've implemented

21:50

six core principles. grounded in a

21:53

people -first approach. What

21:55

this means is that we want to

21:57

ensure human oversight remains front and center

21:59

in AI development, and we consistently

22:01

look out for impacts of AI

22:03

adoption on people. Want to

22:06

learn more about our responsible AI principles

22:08

and our people -first approach? Check

22:10

out the full details, including resources

22:12

that you can use to create

22:15

your organization's responsible AI initiatives in

22:17

the show notes or visit RussellRenals.com.

22:20

Now back to our conversation with Louis. Louis,

22:27

let's talk about customer and

22:29

employee experience. You've already mentioned

22:31

the first of your values

22:33

was to be dedicated to

22:35

customer success. You'll

22:38

know better than we do how fickle customers can be.

22:41

One bad experience is

22:43

enough to turn 50 %

22:45

of customers off straightaway and onto

22:47

other brands. the most

22:49

recent polling that we've seen by

22:51

Gallup suggests that employee engagement is

22:53

low in the US and even

22:55

lower internationally. So thinking

22:58

about those two things, customer

23:00

success and engagement and employee

23:02

engagement, what for you are

23:04

the great advantages, the great

23:06

potentials of AI and Gen

23:09

AI and improving those results

23:11

for companies? Right. AI

23:14

has the power And

23:18

that's been demonstrated

23:20

in spade to

23:22

essentially create experiences

23:24

that are extremely

23:27

individualized. That are

23:29

prescriptive in nature and now

23:31

thanks to generative a i

23:34

advisory what i mean by

23:36

advisory is. Well we

23:38

understand personalization but actually

23:40

i often talk about

23:42

individualization because. Madison

23:44

Avenue has been using personalization for

23:47

more than two decades, and it

23:49

really meant persona. What I mean

23:51

here is moving from persona to

23:53

person. So if you

23:55

have a million consumers, you should run

23:57

a million stores, is what I'm saying.

24:00

That's number one. AI has

24:02

the power to drive prescriptive experiences.

24:05

So not only catering

24:07

to your needs, but

24:09

anticipating what you might

24:11

need. and driving recommendations

24:14

and et cetera, and

24:16

really suggesting alternatives and et

24:18

cetera, maybe just like Uber

24:20

does and et cetera. And

24:24

then AI has the power

24:26

now to create advisory experiences,

24:28

particularly generative AI. So

24:30

prior to generative AI,

24:33

you could go online and say,

24:35

what is A? What is B?

24:38

What is C? very

24:40

profound content or knowledge

24:43

or answers to that.

24:46

Now with generative AI, you can go

24:48

online and say, what is the difference

24:51

between A, B, and C, comma, dot,

24:53

dot, dot. And given that my context

24:55

is XYZ, which one would you

24:57

recommend? Now, if you turn

25:00

it around on the business side, AI

25:02

also has the ability not

25:05

only to individualize, experiences

25:07

that are prescriptive and advisory but it has

25:09

the ability to do that in real time

25:12

so as to maximize business outcomes in

25:14

real time. So I can for

25:16

instance not only give you what you want

25:18

and predict what you will want and give

25:20

you advice and a really rich experience. But

25:23

I can do it in a

25:25

way that perhaps you know will

25:27

will maximize my margin for each

25:29

and every consumer a million times

25:31

a day and that's the future

25:33

of business. The future of business

25:35

is a business of one, and

25:38

the future of business is

25:40

the ability to optimize to

25:42

maximize margins at every interaction.

25:44

That's something that is not

25:47

even humanly possible, which is

25:49

why it's going to create

25:51

such a competitive divide between

25:53

the adopters and the non

25:56

-adopters. Do you think that

25:58

AI is owned by a

26:00

specific leader in an organization?

26:03

Every company needs to build the competence

26:05

and the muscle. You need

26:07

a core competence, a core group

26:09

of people in my opinion in

26:11

every organization that understands AI. If

26:14

only to understand where to apply

26:16

it and how to prioritize and

26:19

then how to manage compliance costs,

26:22

ROI and understand use cases

26:24

and all of that. But

26:27

other than that, I think it

26:29

will permeate everyone who's responsible for

26:31

the internet today within companies. Is

26:34

there a chief internet officer? Not

26:36

to my knowledge. Not to my

26:38

knowledge. Yeah. If you look on

26:40

the vendor side right now, every

26:43

big vendor is trying to own

26:45

AI, right? My AI is Salesforce.

26:47

My AI is better than Microsoft

26:49

and is better in my opinion.

26:52

It's much more a spinal ability.

26:56

Across if you think about an

26:58

enterprise There are applications everywhere. There's

27:01

data everywhere and you need a

27:03

spinal ability in fact both from

27:05

a talent and technology perspective to

27:08

drive AI across Your organization and

27:10

you just need people who understand

27:13

the engineering side of things to

27:15

understand just like you have an

27:17

engineering department that can understand how

27:20

to apply physics principles

27:22

and energy and electricity and

27:24

all the rest. So AI

27:26

is like electricity. What

27:29

do you make of it? So

27:31

that's how I would fry it.

27:33

Louis, that's a very powerful account

27:35

of what's going on. And

27:37

the implication of most of our

27:39

questions so far has been asking

27:41

your viewers and executive. But

27:44

you've sat on multiple boards.

27:47

You've moved from board into the executive role

27:49

and back again. What for you? Makes a

27:51

great board. How do you go about thinking

27:53

about its composition and how to define its

27:56

success? I love the question. I

27:59

think boards are effective when,

28:01

first of all, when they

28:03

work together. And

28:05

number two, when there's

28:08

true synergy with the

28:10

executive leadership team. And

28:12

number three, when both teams

28:15

agree on a common set

28:17

of facts and the company's

28:20

strategy. When boards try to

28:22

run the company or get

28:24

forensic or think that they

28:27

can show up every month

28:29

or every quarter and understand

28:32

as much as management does,

28:34

that's when you start seeing

28:37

problems. And I think it's

28:39

really important for board members to understand that. People

28:42

think... It

28:45

goes with the general statement that, I'm

28:47

a firm believer with this as a

28:49

preface maybe that says, what's

28:51

dangerous is when you know enough

28:53

about something to think you're right,

28:55

but not quite enough to think

28:57

you could be wrong. And

28:59

I've seen board members behave

29:01

that way because they understand

29:03

98%. And I didn't say

29:06

90. They understand 98 %

29:08

of the business. But

29:10

you know what? Every business is built

29:12

in the long tail. in the understanding

29:14

of the last 2%. Everybody can grasp

29:16

98 % of a business if you're

29:18

at it. The winning

29:20

businesses understand the last 2%.

29:22

I believe that all through

29:24

my career, I've seen that

29:26

true excellence happens in the

29:28

long tail. And

29:31

it's in the intricate moments that

29:33

you win. We talked about customer

29:35

satisfaction. It's not about satisfying 90

29:38

% of your customers. Actually,

29:40

in customer service, It's actually easy. People

29:42

now talk about chatbots for AI and

29:45

etc. And then the examples we see

29:47

is, how do I change my password? Well, you know what?

29:49

That's not where you make your money. You

29:51

make money. Your cost

29:54

in customer service is not serving

29:56

the first 90 % of the

29:58

question. That's easy. Where

30:00

you lose customers is in the long tail.

30:02

It's in the complex situation. You

30:05

need to be there for the

30:07

tough circumstances, not for the easy

30:09

ones that are high -volume. 90

30:11

% of your customer service cost

30:13

is for less than 10 %

30:15

of the customers, the issues. Actually,

30:18

I would argue 95 % and five.

30:21

But these 5 % of customers

30:23

are the ones giving you the

30:25

most money, and they're also the

30:27

ones that will give you the

30:29

most effort, trouble, work,

30:32

and they're the ones that will

30:34

churn. Not the

30:36

ones that you're trying to answer with a

30:39

chatbot, how do I change my password? That's

30:41

easy. And that's what

30:43

more sophisticated companies understand. So

30:45

back to the board, I

30:48

think when board members really understand that,

30:50

when board members are humble and they

30:52

understand that, no, they probably don't know

30:54

as much as management, I work for

30:57

a board. Their prerogative is to fire

30:59

me tomorrow. I've always, and

31:01

you know what? I'm only as good as my last

31:03

quarter anyway, so I'm not naive. But

31:06

that's the way it works.

31:09

So when you pick board members

31:11

that really work together as a

31:14

team, are constructive and

31:16

are humble and yet super

31:18

competent that have the background

31:20

and the broad perspective and

31:23

can work with management, that's

31:25

where magic happens. Louis, are those

31:28

sorts of effective boards? Are they

31:30

born or are they made? By

31:32

which I mean, do you see

31:34

a click early on? of complimentary

31:36

skills and experience. Honestly,

31:38

I've churned board members not because they

31:40

were bad individuals, but because they weren't

31:43

catalysts for the magic. As

31:45

a CEO, and maybe words are cheap,

31:47

right? It's easy to say, but I

31:49

generally feel that way. I don't look

31:51

for a board that necessarily agrees with

31:53

me or won't ask challenging questions because

31:55

I want to be the first one

31:57

to ask the challenging questions and I

32:00

welcome them. But again,

32:02

it always has to be constructive

32:04

because we're in this together. You've

32:06

led three companies to either acquisitions

32:08

or IPO. You were president and

32:10

CEO of the clan group, which

32:12

is acquired by Dan in the

32:14

90s. You went on to co

32:16

-found Tileo, which is acquired by

32:18

Oracle. Then you grew Coveo and

32:20

took it public in 2021. Very

32:23

impressive track record. For those

32:25

listening, what advice or

32:27

guidance would you give other

32:29

leaders? who are aspiring for

32:31

similar success. Business is

32:33

challenging. If it's not challenging all the

32:35

everyday, if it were easy, others would

32:38

do it. You have

32:40

to make the difference between unpleasant

32:42

and difficult, right? And you just

32:44

have to, as I said earlier,

32:47

I believe in the word stick

32:49

to itiveness or resilience or persistence,

32:52

but not in a... not

32:54

in a naive way. I

32:57

really believe in the power

32:59

of analysis. I coach businesses

33:01

and I coach entrepreneurs. And

33:04

I find a lot of businesses,

33:07

a lot of entrepreneurs, they tend

33:09

to drink their own Kool -Aid

33:11

sometimes without proper analysis. I

33:14

will say, as a matter of

33:16

background, I grew up as a

33:18

commercial pilot. I learned the difference

33:21

between taking risks versus taking chances.

33:23

Yes, you take risks. My engine,

33:25

I can get a flame out

33:27

on a turbine at 10 ,000

33:29

feet or whatever, but I

33:31

can manage that risk. But

33:34

I don't take chances. We

33:36

have checklists and we do our analysis

33:38

of pre -flight and all of that.

33:40

It's much easier to spend more time

33:42

planning than trying to plan during the

33:44

execution. And I always think that if

33:47

you don't know where you're going, there

33:49

will be a lot of people along

33:51

the way to tell you. So

33:54

this is sort of

33:56

some of the principles.

33:59

But also, the great is the enemy of

34:01

the good. It's

34:03

not about being good enough. You

34:06

just need to be more agile

34:08

and make mistakes fast. It's okay

34:10

to fail as long as you

34:13

fail fast is what we tell

34:15

our employees. and that

34:17

I tell entrepreneurs as well. So

34:19

lots of analysis, not

34:22

analysis paralysis. Do

34:24

it and do deep analysis

34:27

fast. So the cycle time

34:29

should be short. It doesn't mean that

34:31

you're not going to go deep. And

34:33

then act and try, experiment and put

34:35

the customer at the center. Just

34:38

listen to customers. They will tell

34:40

you a lot. Oh, they absolutely

34:42

will. Louis, we've reached a bit

34:44

of the conversation. which we call the

34:47

rapid fire section. So we're going

34:49

to ask you a series of questions

34:51

so that our listeners get to know

34:53

you even better. And your job

34:55

is simply to answer them as quickly as you possibly

34:57

can. Are you ready? I guess I

34:59

have to be. Besides

35:02

mail, phone and

35:05

calendar. What are the

35:07

three apps on your smartphone that you can't

35:09

live without? Perplexity, Slack.

35:14

I love Slack. And

35:16

how about my card game? Louie, who

35:19

is a mentor that had the biggest

35:21

impact on you? Oh, I've

35:23

had I've had several all the

35:25

way back to when we took

35:28

bond public and it said about

35:30

work with executives You know from

35:32

from large tech companies, so I

35:35

won't name a specific person But

35:37

I will just say that people

35:39

who have lived the most intricate

35:41

moments to me are the most

35:44

helpful and the most intriguing and

35:46

I value that a lot. And

35:49

you know, one common characteristic

35:51

between all of them is

35:53

they're all very genuine individuals.

35:56

That's probably the quality I admire

35:59

the most. Do you like

36:01

to focus on the journey or the destination? Oh,

36:04

definitely the journey. I think

36:06

most people focused on the

36:08

destination, unfortunately, I find. And

36:11

the journey is the rewarding

36:14

part. had the

36:16

opportunity to exit my first

36:18

public company at age 33.

36:20

And most entrepreneurs that I

36:22

know that have exited businesses,

36:24

talk much more about the

36:26

journey than they talk about

36:28

that destination. When you're 30,

36:30

Cree, actually, there are not a lot of people to

36:32

play with on Wednesday morning. But

36:35

there is so

36:37

much about keeping

36:39

you alive and

36:41

building and being

36:43

challenged. competing

36:46

in a good way, right? You

36:48

know, why do we compete? Well,

36:50

because it keeps you alert, it

36:53

keeps you engaged, it keeps you

36:55

innovating. Those are all themes that

36:57

pertain to the journey, right? You

37:00

know, what else would we do,

37:02

right? If we

37:05

were engaged in doing something,

37:07

and yes, being challenged every

37:09

day, that's life. So

37:12

I think that's... 100 % the

37:15

journey. Louis, what's the best

37:17

piece of advice you've ever been given? I

37:19

really remembered at one point, one

37:21

of my mentors actually said, he

37:24

said, you know, the one place

37:26

in the world where businesses work

37:28

super well all the time is

37:30

in Excel. And

37:32

he went on to say there are more

37:34

fiction that have been written in Excel than

37:36

in Word. I really

37:38

remembered that because business

37:41

is about adapting. every

37:43

day in changing and innovating and

37:46

delivering value and so on. If

37:48

I had my druthers, we wouldn't

37:50

make annual plans. We would have

37:53

three -year plans and quarterly plans.

37:55

And I think it's amazing how things

37:58

change when you think long -term. What's

38:01

your favorite way to decompress after a long day

38:03

at work? Hiking, skiing,

38:05

flying, and maybe a

38:08

bit of wine. And you

38:10

mentioned that you are a

38:12

licensed helicopter pilot. Where

38:15

is the most interesting or unusual

38:17

place that you have flown to?

38:20

From Montreal to northern

38:22

Quebec. And

38:24

if you think about the territory of Quebec,

38:26

there's only, you know, seven a half million

38:28

people. From Montreal to

38:30

northern Quebec, to north of the

38:33

Bay of Angala is further than

38:35

to go from here to Florida.

38:38

flew to a place named

38:41

the Torn Gap Mountains, but

38:43

all through northern Ontario, north

38:46

of Algonquin Park. And we

38:48

actually went canoeing in the

38:50

Arctic three years ago, which

38:53

was quite interesting as well.

38:55

So there's some fairly pretty

38:58

scenery. Oh, I'm sure it's

39:00

beautiful. And because our listeners

39:02

are going to be enjoying this episode

39:04

early in 2025. Do

39:07

you have any... Year's resolutions

39:09

you're willing to share with

39:11

us. Oh my god, my

39:14

New Year's resolution would be

39:16

that I don't know that

39:19

it's achievable but would be

39:21

to broaden everyone's perspective on

39:23

the world in general. And

39:26

I wish we didn't see

39:29

the polarization and narrowing of

39:31

perspectives that we're seeing right

39:33

now. The world's becoming very

39:35

polarized. I think technology is

39:37

a culprit, but my wish

39:40

would be that people look

39:42

at the world with a

39:44

much more multi -dimension and

39:46

broader perspective, and I think

39:48

it would make the world

39:50

better. Louis, that was a

39:53

fantastic tour d 'horizon of

39:55

a very successful career, but

39:57

also a very interesting mix

39:59

of reflections on what your

40:01

success is consisted in. That

40:04

defining moment early on was

40:06

really interesting, rooted in relationship,

40:08

and that stick -to -itiveness

40:10

that you referred to both

40:12

in the teams around you

40:15

in executive groups, but also

40:17

in the boards that you've

40:19

been part of and helped

40:21

to shape the grit, the

40:24

curiosity, the rigor that ran as a

40:26

thread through a lot of what you

40:28

said. The focus on

40:30

customer success The understanding of that

40:32

as a value as well as

40:35

a set of technology enabled capabilities

40:37

was extraordinarily strong. And the challenge

40:39

that you posed to people in

40:41

almost every sector where customers can

40:44

engage with 30 % more complexity,

40:46

50 % more of the time, 90

40:49

% faster. That's an incredible thing to

40:51

absorb. as

41:02

the focus of customer need and

41:04

a real understanding of that need

41:06

as a leader to take risks, but

41:08

not chances. And last but not

41:10

least, AI tastes of maple syrup.

41:12

Louis, thank you so much for

41:15

the wonderful insights and the incredible

41:17

knowledge that you've shared with us.

41:19

We've so much enjoyed having you

41:21

on Rita Finders. Thank you so

41:24

much for joining us. Well, thank

41:26

you, Hodha. Thank you, Simon.

41:28

It's been a very pleasant

41:30

conversation. I'll

41:32

see you in minute. Thanks for

41:35

joining us on this episode of

41:37

Redefiners. For more compelling insights from

41:39

leaders across industries and around the

41:41

world, listen to redefiners wherever you

41:44

get your podcasts. And to learn more

41:46

or to get in contact with us,

41:48

visit our website at Russell reynolds.com, find

41:50

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41:54

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