Fireside with Founders & Leaders

In this episode of "Fireside with Founders & Leaders," host Rupert McSheehy sits down with David Burns, the CTO of TLC Worldwide. David shares his extensive journey through the technology landscape, from his early days as a developer on PlayStation games to advising private equity and venture capital firms on transformative technology strategies. With a rich background spanning Europe, the US, and Asia, David provides valuable insights into the challenges and nuances of leading tech transformations across diverse cultures.

The conversation delves deep into key aspects of leadership in tech, particularly how effective communication and understanding of cultural differences shape successful organizational dynamics. David emphasizes the importance of aligning technology with business objectives and how a well-structured approach can elevate organizational performance. They also explore the current landscape of AI, discussing its potential to drive innovation and the importance of having a strategic roadmap to integrate AI technologies effectively into business processes.

What is Fireside with Founders & Leaders?

In this podcast, we talk to some of the greatest founders and leaders about their journey to where they are as well as discuss their companies and many other subjects depending on the guest.
We are aiming to create meaningful content that everyone can get value from. We hope you enjoy 😁

you're listening to the Far Side

with founders and Leaders Podcast

the podcast that gives you a behind the scenes

look of some of the world's most

amazing founders and leaders

looking at their journeys

and how they got to where they are today

David welcome to the podcast

thank you very much Rupert

so for people that don't know

give us a bit more in terms of your broader background

and a bit more about the business today

and what you guys do over at um

at TLC I don't know

well I'm just in from myself

from my own experience so I've

one of those kind of very fortuitous

career paths over the years

I actually started off as a developer many

many years ago on the initial PlayStation games

and I was doing that also whilst in university as well

and that was a real kind of hot bed of activity

and you were it was very much a focus on delivery

and getting things over the line

and you get a real insight as to how teams work

and how you need to collaborate

to be able to generate success

particularly in those types of environments later um

as I moved on in my career

I went into the more broader

technology transformations

and worked for some very large organizations

including the likes of CGI

and also Hula Packard as well

and we were dealing with global

technology transformations

these were transformations which are

in some cases

were in the hundreds of millions of dollars

if not the kind of billion dollar type of accounts um

those huge

monolithic accounts don't tend to exist these days yeah

but certainly that was kind of the background

on which I was brought up on um

through the industry and what that really

embedded into me is

a real strong sense of good practice

of having a process and a way of working

and I think that's

that's really served me well throughout my career

because you're always

you always step forward from that foundation

and an actual fact I was watching a

a podcast a few weeks ago and it was Jeff Bezos

and Bezos was saying

one of the things he would always advise founders to do

is actually have that

that kind of bedding in an organization

where you learn best practice

really well yeah

because then you can step forward from there

understanding what good should look like

and that served me really well throughout my career

so as I've moved into the more private equity VC space

and work with companies who are

clearly of a much smaller scale than the likes of HP

and some of the others I've worked with

I've been able to

identify the best practices and the ways of working

and how we can generally improve the business

whether that be from a point of view of sales activity

and pipeline generation

whether that's back office transformation

or whether that's actually core product development

because I've got that kind of grounding in real good

solid processes and ways of working

and all that training which is associated with that

yup and that really helps me get some quite valuable

or bring forward some very valuable insight

which I think

sits well with private equity organizations as well

because they're always constantly looking for that

kind of expertise that insight

which is going to be the differentiator

for them and their businesses

and how do you um

I suppose sort of put the value on on good right

because it can be quite subjective

like good to one person is

very different to good to another person

so what does good look like

oh that you

and again you're absolutely right

everyone has their own perspective on that

and I think that's really

that's one of the tricks in this whole process

you have to understand

what everyone's definition of good

really is yeah

um

and whether or not we think there's a way to actually

get to that position

and what are the compromises as well

that you might need to take on that journey

so to speak but having that ability to communicate

having that ability to uh

kind of articulate the journey

and work with business people

who are not necessarily from a technical background

and don't

maybe understand the challenges of transformation

once you start to fill that in

the definition of good starts to become clear

not just for yourself mm hmm

but also maybe for the CEO of the business

maybe also for the COO or the CFO as well

and also for the investors yeah

because often where that

where you reach there is almost a compromised position

which is okay that's good

this may this view might be good

but to get to that

here's the steps that we've got to take at that point

the business might look at it again and say okay

maybe we can find a different way

a more of the kind of a way with less steps in this

or less challenge and

because you're always looking for the most efficient

the most productive

way to use the resources that you have at hand yeah

to gain the outcome that you need nice

and and in terms of we

we mentioned you've got experience working across

in different locations with companies across

across the world yeah

how do you think that shaped your leadership style

it makes you very attuned to the nuances of culture uh

and also the value of that

within various different work environments

as well and also

just more broadly that

I lived a long time in places like Austria and Germany

and and

you become more attuned to the language

barriers that exist yes

people all speak English um

and you know in some countries

some of the English is really excellent

but

there is nuances in the way that you use your language

and it it makes you understand that

you need to just step back

and make sure that communication is real clear

mm hmm and that then also drives again a

a kind of understanding of

having good documentation in place

having good control in place

making sure that everyone is crystal clear

on what is being asked to them

and what again

good looks like um

so that's that's

something which I've certainly learnt as I've worked

in places like Malaysia also in India as well um

and also not just kind of being there for a week

but actually being within those cultures

for elongated periods of time

sometimes a year two

3 or 2 or three years

and that really serves you well because you can then uh

once you start to understand some of the challenges

of those cultures and those working environments

hmm it becomes easier for

to work with people in those areas as well yeah

I think that's so important because most

most leaders who work in international organizations

they tend to go on a business trip

and they'll go there for a week or two at a time

there's no way

you can get ingrained into the culture and

align yourself with okay

what are the challenges that these people are facing

comparatively to what we're facing

it's a completely different dynamic uh

being somewhere where you're staying in a hotel

and you're basically there for two weeks

is a completely different dynamic

to living and working in those environments

in those countries for two and three years

and you really

you really don't get a sense of the culture

if you're not there for a long period of time

because that's not that's not present

you know

the hotels that people stay in are very Westernized

yup and you're moving from a hotel to an office

which is also very Westernized in its structure

when you actually live in these locations

and you actually see what goes on day to day

and again the challenges that people have

that's when you start to understand the

the cultural nuances yeah

I particularly found this out um

it was quite interesting during my time in Austria

where um

where I it's one of those places that you can

you go skiing

go visit and it's beautiful and it's wonderful

love it um

but different when you're there yeah

yeah and not

not not that it's not good

but just different from maybe the kind of the

the Broken Mountains yeah

yeah so to speak

everyone's wearing their lederhosen with the yodel

and you also get you

you start to get an insight into the mindset

of the people who live in those countries

as well because

you know slightly different

we like to think that we all

and there are some common groundings

amongst people across the world always

but those cultural differences

are what makes it all unique

and really special as well

and it's embracing those

which is really key cause once you understand that

you can also then get the best out of the people

who are working with you as well yeah okay

and that's so key that is so key

what's the thing that surprised you the most about like

all your different sort of

your places that you've you've been in terms of the

that sort of cultural difference

and having to really understand it

where you went oh my God

I didn't expect that I think what I've seen is

some of the things that you take for granted

when you live in a country like the

the UK and you're brought up in the

in and in such a country

when you step out into certain countries

around the world

which are maybe less developed in certain areas um

you see the challenges of them

of people just getting things done

in those environments

uh so it becomes very bureaucratic in certain

in certain countries to just get rather

simple things done mm hmm

um now fortunately

I've always had

support mechanisms around me to help employees

kind of overcome some of those hurdles

but these might be in some cases some private things

yeah OK

that employees have some

just general day to day living challenges

uh and that's

that's where that's where getting involved

and really caring for the employees welfare

really helping and supporting people in the right way

and again that's what really makes the difference get

that's that's where

where

you start to see the change in the mindset of the team

that you're there to actually really support them

and help them

not just from a point of view of their professional

capability

but also as well you're looking out for their welfare

you're looking out for their lives more broadly

and how you can make sure that the

the work life balance

and how work operates around their lives as well

is structured in the right way

unfortunately

it is sometimes the case that when you go into uh

when I've gone into certain countries in the past

some of the employees have come through from

other organizations

who have not really tried to build that type

type of support capability

mm hmm in place

so when they always

when I've brought people into work for me

they often have seen that step change of

you know

I'm genuinely interested in the people who work with me

and work as part of the team

yeah because I'm

I really want to see people succeed and drive

their career forward that's really

you know that

that

for me is the thing which really drives me in terms of

yeah people's performance

yeah nice

and it might sound like a silly question because it

again may seem simple to you

but to other people out there

because as you mentioned there's lots of businesses

that don't have these mechanisms in place

and I can't believe

it's because they're all narcissists

and they don't want to help people right they

they just don't know how to do it or there's blockers

like how do you put these processes in place

is it just putting in like SOS structure

the beginning of this is having a

a form a very formulaic structure

yeah yeah

so that everyone knows where they stand

everyone knows what they're doing um

and everyone knows their responsibilities

and their accountabilities

that's the starting point

because that makes it very clear

to everyone about what what the expectations are

and how to work with colleagues

and so on and so forth

and then you can start to also as well um

align behaviours as well

and make sure that we were all working in the right way

in a very respectful way which really kind of heightens

or gets the best behavior out of people yep

uh so the yeah

the again the

the this always challenges throughout that because

and it's

it's never one unique way of addressing the problem

but getting that kind of structure in place

from the very outset really helps people

and again going back to the early stages in my career

the need for good process

there really helps people as well

yeah because again

people sometimes have come from organizations

where there is less focus on structure and process

and that doesn't really give people

always the foundation that is needed to be successful

yeah so putting that in place often really

and I've seen it myself

I've seen people who come in and they start off

and they're kind of you know

they're not a great performer

they're fairly solid

but you put that structure in place

you put that foundation in place

you invest in them and you work with them

and you be honest

and truthful and transparent with them

you can change people into real star performers

yep really get the best from them

and that's a reciprocal thing as well

because then they see the growth and the capability

yep that and what they could do

and that sometimes is eye opening for the individuals

as well which is a fascinating journey to be on

with those people it's great

isn't it yeah

to see how people develop is really insightful

it tends to be the enjoyable part of the job

once you get into leadership for

for most not some

but for most is seeing people develop and come

through and being able to help them to

to sometimes even light a bit of a fire to go right

this is exciting it is and

and you can you can see as you say the

the the

the the fire is kind of on the

the shine in their eyes so to speak

yep um

because they're doing the thing that they love

hmm

and this is also another thing which I think I've uh

Learned throughout my career

is give people the opportunity

to do the thing that they love

really and to that extent

give them the right support and guidance and to

to a degree get out of their way

mm hmm as well yeah

because if people love what they're doing

they will invest the time

they will kind of coach themselves as well they

they you know

they will do a lot of that themselves

yep um

and they will go out and try to learn more

around the subject

and I see that a lot with the team which I've got now

and teams which I've had previously as well

nice and and you've done

you know lots of advisory workers you said for P firms

vcs on strategy yes

solving some of their problems

like what are the typical

things that they're asking you to solve

like what are the

the problems that they're tending to have

from a tech perspective I mean

to it general themes which come across

because every every business is different

and every private equity has somewhat different focus

but generally it is

it is a real need for clarity around vision

strategy and the

the plan that we're gonna execute which supports that

and ultimately

the organization that you need to achieve those

that vision and strategy and that sounds kind of very

kind of like obvious to say

but it's when you start to get into the detail of that

having a strategy that you know

is actually gonna work and actually deliver and the

the plan which supports that

mm hmm

that is not as as easy to execute through yep uh

so it's that so generally what

what I see when I'm speaking with peas

is that need for clarity around that okay

so that they know okay what's coming when it's coming

how does that address on

how does that help enterprise value

how does that grow the value of the business

mm hmm how does that grows from a revenue perspective

how does that grows from an EBITDA perspective

um and how does that

maybe differentiate us away from others in the market

gives us something unique cause again

all these things contribute to enterprise value

which is really helpful for ultimately

an exit for a PA

and but having that

that plan and aligning that to the strategy

and the broader strategy of the business as well yeah

and being able to articulate that on terms

which everyone understands

gets and sees clearly where the value is being created

that is is generally the

the the points which come across yep

um of course as you go through that journey

certain things change

people get more into a little bit more into the detail

yeah um

but you have to build that solid foundation

of a clear picture

and a clear way forward from the outset

and

would you categorize those things under due diligence

or would you separate those two things

so some of it so at

at diligence you can kind of get a view of that

mm hmm but a lot of this comes post the

the deal okay

okay so this is post deal

so rather than yeah

okay post deal

and you will see and you will be familiar with this

a lot of recruitments of Ctos

and also chief product officers and various other uh

key staff is done post a deal

yep because sometimes there is a need for a step change

sometimes the CTO that got you to here is not the CTO

which is gonna get you to there fact

very often that's the case yeah

we know this right

so we know this cause a CTO is not a CTO

so to speak there's different flavours

yeah there is

and they don't want to do that next job

they often go this isn't for me yeah

there there are those

you know the

the the typical founder CEOs

more of of more of that engineering background

hmm as where the

the PE CEOs the more

the more kind of main stage

uh PE CEOs

or

people who've been through that transformation journey

yeah and have the ability and

and can intuitively talk about value

that they're generating and not technology

that they're kind of bringing into the business

because at the end of the day

the technology is always a means to an end yeah

should be and that's

I think always the

one of the challenges which I've always seen

is making sure that if we're gonna do anything

from a technology point of view

if the technology strategy is gonna drive an outcome

that has to be aligned to the business metrics

to the to the

the value of the business

to the revenue to the EBITDA that we're gonna drive

do you think that's an area that

sometimes you've seen people get wrong

I've frequently seen unfortunately

situations where it becomes a

far too technical conversation

or the clarity is not there okay

the and this is where

you know this this

this is where the experience comes into play

you've got to be able to articulate this in terms

which everyone can follow

in terms which everyone can kind of get

because everyone these days

particularly exact teams have a limited um

ability to actually absorb huge amounts of information

they're dealing with so many things yeah

the world moves so fast

they what you need

to do is the CTO

is increasingly take very complex challenges

and crystallize them into

this is what that means and ultimately

that's the outcome that we reach for the business yeah

if you can do that

then you'll find a far easier conversation

always with other exes with peers

but certainly with investors as well yeah

it's about those business outcomes

as you say it's taking it away from everything else is

is ultimately to those people as investors and exes is

is noise I don't really care

they wanna know

what's the return on the investment that I'm making

yeah and and you do uh

from time to time you come across uh

various different investors who are very technically

savvy and they really want to understand the

the the challenges and again

the

a good thing with my experience is I'm able to kind of

if you wanna go into the the the detail

we'll go into the detail yeah

um but generally the conversation is

is much more about what we're trying to achieve

by when that's gonna be achieved

and what the best benefits are for the business

the important thing is alignment yeah OK

everyone has to believe that

everyone has to be assured that that's the right thing

and I spend a lot of time

making sure that we're constantly keeping alignment

on a day to day basis

because it's easy to get for misunderstandings to

to arise it's easy for for transformation

activities to start to not deliver in the right way

yeah so keeping that alignment um

with your peers is so critical these days

because at the end of the day

it's a team effort and it's the team

which achieves the outcome with the business uh

and that that's one of the things which I think

I think it's the biggest transformation for Ctos

yep over the last few years

and particularly over the last 20 years

I've seen a lot of CTOs were the technical gurus

but they almost sat separate outside of the business

yep

now CTOs are an integral part of the team

they have to be

and the technology is an integral part of the business

yeah I

during previous years gone by

I used to rail against this concept of the business

and tech yep

the business is tech tech is part of the business

yep it's all one and the same thing

and they used to often you'd hear this in conversation

which was the kind of like

the tech team

perceived as some sort of addition or some

they just siloed by themselves

renegades doing what they want

exactly yeah

some strange organization which is not

we don't talk to them yeah

yeah don't and

and there wasn't that line

so I always pushed back against that and yeah

I always worked with CEOs and with investors to say

we're core we're absolutely core to the

and let's not talk in those terms

hmm because by talking in those terms

it's

almost becomes a bit of a self fulfilling prophecy

if you talk like that

then you're instantly gonna start to behave like that

yep and it's also not good for the technology

and the product people on the ground as well

they need to know that what they're doing is core

and really drives the value

and that comes back to you know

people at an individual level

want to know that

the things that they're doing as part of a business

really have an impact yeah

and have you seen um

investment firms and companies

miss out on technology opportunities

because they've not been so aligned with the tech

and the the business

they're not as one yeah

absolutely um

and unfortunately I've seen it um quite often yeah

where there isn't an alignment around the

the kind of business strategy and the technology

and often they're

the points that

someone like me is often brought into the whole

conversation but I've frequently

frequently seen it where

the reason that alignment

or the business has this mindset of

tech is something else hmm

and date and to an extent

and to an extent

that's also happened with data and data science

because a very complex

very difficult challenging subject okay

let's keep it at an arms length right

not really engage it

or we need that in far more simplistic terms

and I particularly through

I think there was a period between

I would say 2,010 to 2000

well just pre covid

so that kind of decade

where I was consistently seeing that disconnect

between what tech organizations can achieve

within a broader business

um and also as well

what data organizations can achieve as an outcome

and businesses

weren't leveraging that in the right way

mm hmm uh

the businesses for me

who are really gonna be successful

who are

those who really integrate that

as part of the soul and core of what they're doing

yep if you get that right

then all of a sudden you have products and capabilities

which are differentiating

you have people who are far more actively engaged

and it becomes quite an exciting atmosphere

and that's you know

that's something which I've always pushed for

to achieve within the working environment

people then come along the journey with you

they're as you say

more engaged right

they want to do the work it's

it's a wonderful thing to see when you've got CFO's

CEO's

COO's actively engaged in the conversations around data

yeah and it's

it's actually and I'm not

I'm not saying that the the

it's always completely aligned right right

at least they're talking about it though

but the fact is that they're talking yeah

yeah and that's

that's an exciting thing because then

you start to talk about the art of the possible

and where you can take this

and what new things can be achieved

and that's really you know

that for me

that's the bit which always gets me out of bed

so to speak yeah

um is that level of excitement

is that level of enthusiasm of

what can we achieve today

yeah

it takes it beyond the the baseline

right that everyone's doing

it's great when you get when you're not

and I think that's one of the things which

which I I personally Mark myself um

in terms of my own measurements of success

if I get a business

everyone in the business talking in those terms

I know I'm doing a good job

yeah at that point

yeah because they must have

at some point listened to what I was saying

ha ha ha um

and the fact that they're kind of

relaying things in that way

and understanding not just that this is kind of

magic and smoke and mirrors

and we can all achieve everything

but understanding the practicalities

and the steps that we need to take yeah

if businesses are talking in those terms

then certainly I've had some success as a CEO

yeah good

and we talked a bit about AI

and we can not talk about AI

I'm sorry I have to bring it up again um

but when we previously spoke

you mentioned

you've sort of moved beyond not just building like

predictive models you're looking at like

true agentic AI systems

and some of the work that you're doing

yeah um'cause there's a lot

there's a lot of noise around AI right

everyone's doing something with AI again

we spoke about

I've been to some events recently and there

everyone's talking about AI

which is great I'm very happy to talk about it yeah

now now

95% of any conference that you go to

at this moment in time is AI

and then there's usually a stall somewhere

so where someone's not talking about AI yeah

no one's standing there

no one is so everyone's talking about it right

so it it is and unfortunately we

we do as an industry

we do have this if we do we do it to ourselves um

we are constantly

always kind of bringing forward the next great thing

and so on so yeah

and you could

if you looked over the technology industry

over the last 30 years

you could be critical and say every five

every seven years we're always doing this right

it's something new there's something yeah

something game changing something evolutionary um

but in actual fact this I think is

is different yeah

and it's different because there is firstly

and let's not talk about the levels of investment

which you've gone into it

but the the volume of incredibly bright people

and the structure and the organisations

which should be put around

trying to get more value out of this techno

technological capability is really

really uh

that's really exciting mmm hmm

cause if you start to have organizations like anthropic

like uh

open AI with the resources that they've got

and again I don't just mean the financial resources

but the people the knowledge

the insight

then you're inevitably gonna generate something

which is which is really quite game changing

I think the for businesses

and that that's kind of one end of the scale

because these

kind of trillion dollar valuation businesses

which I'm as I understand

that's where anthropic is gonna be when it uh

floats on the on the stock exchange on the um

it's mad in itself right

yeah exactly

you know they're literally talking about a valuation

which is just short of $1 trillion

so but that is one end of the scale

and the problem is that we can get

quickly absorbed into that type of bubble

the reality for most businesses who are kind of 3

400 people on a certain level of revenue is

how do we get that into our business

how do we adopt that where do we utilize it

what does it mean for us yep

right and are you

when you actually start to have honest conversations

with many other CTOs and CIOs

which I've done

quite frequently over the last two years or so

in actual fact

they're all struggling with the same questions

yeah

some have gone into

what I would refer as pilot purgatory right

where they've got 300 pilots of whatever it is

that's running in the background

burning a huge amount of tokens

yep to um

but these are very disjointed activities

and they're not kind of looking at how you redesign

the ways of working they're just kind of very isolated

very uh reactive

yeah and very tactical actions

which in some ways

do inform a broader knowledge base of what can be done

but you've got to join the pitch together

mm hmm this is a transformation journey

yeah and it's something that we Learned particularly um

18 months ago when we started to really introduce some

really good AI capabilities

into TLC we learn very quickly

that this was about transformation

this was about taking people on the journey

you can't redesign the way that people work

if you haven't included people in that conversation

yeah it's a fundamental part of it right

I I

you know at

at best you're gonna be disjointed

at worst you're gonna get a complete push back yeah

you need uh

people to be part of that conversation

and again it comes back to a little bit of having

process and structure in place

uh because your

if you're gonna restructure your way of working

you actually have to have a baseline

cause otherwise you're investing in AI

but you're if you don't

if you don't know where you're at as a baseline

how can you ever prove the value of the investment

yeah exactly

you'll never know you go

we're not sure if it worked

yeah exactly

maybe it did maybe it didn't

we think it's better you're yeah

it'll be

it becomes a very subjective judgement based call

which was we were there

we're now there and there is better we think yeah yeah

most people will say there is better

because they just will yeah

exactly they won't even say we think you're

you're never gonna say well

we spent six months to trying to do this

and a load of cash and actually millions of dollars

yeah we just kind of gone somewhere else yeah

it has to be you're always gonna stand by the notion

that it's better

so you have to then take a step back and say okay look

what's the transformation that we're on here

what's that

broader processes that we're trying to enable again

align what you're trying to achieve

to the objectives of the business

hmm you know

there's no point in going off and investing

not just again not just financially investing

but people's time and training and insights

into AI capabilities without

really understanding

where you're gonna take the business

with that yeah uh

and that has to be clear again

because I would never step into those journeys

unless my my peers are clear where we're going

cause you know they

I have an obligation to them

to make sure that what I'm suggesting is

what they're aligned with is yeah

and equally with our investors as well yeah

you know going off on random tangents with

just because AI is the kind of flavour of the month

it's not really good but the and again

it's not

it's the whole challenge with AI is not a kind of one

one size fits all type of thing cause of course

you got the and I again

everyone's initial focus was the generative stuff great

but the generative stuff is very reactive

very tactical it's not

gonna really be the thing which moves the needle

in your business the agentic stuff potentially is yup

uh because then you're joining

multiple activities together yep

there's pitfalls in the agentic approach as well

where you've got to really step back and think

about how you're implementing this

mm hmm you know

we were having a debate some time ago about this

and the structure of the agents

and what you want agents to do yeah

and do you want one monolithic agent

yeah or do you want to actually take kind of a

a microservices approach yeah

and have smaller agents with discreet function

yeah okay

and then join these things together well

again horses for courses

it depends right

yeah some people might say actually look

I know this and end to end

and I wanted to do all these steps equally

some other businesses might say

you know what I really want that flexibility

that actually these discreet agents give me

mm hmm so again

you need to look at that overall architecture

of your agentic AI

and what you're trying to achieve as a

business objectives

and make sure that all that's aligned

it's not and that's the bit where

CTOs need to step into that mindset

mm hmm and some are yeah

some are a little bit behind the curve on that yeah

um but you have to absorb this

you have to take it on board and you have to learn it

you have to understand the nuances of things like MCP

you have to understand Langchain

and these types of technologies these days yeah

because they are

in the same way that we used to talk client server

in many many years ago ha ha ha pre cloud doctor yeah

um

you have to have these frames

these terms of reference yeah

and you have to be able to understand

how you can leverage these

and what is appropriate and what is not yeah

that's the role of the CTO

it's just it's just a I was gonna say simple

that's the wrong word'cause nothing's simple

necessarily but it's a transformation in its

in its true core right

so we've had the age of digital transformation

which there are also plenty of organisations

still going through

a traditional digital transformation

by the way as you know um

but now it's looking at OK

well

digital transformation 2.0 or whatever we wanna call it

is is involving AI right

we're taking it to the next level

so

we're gonna go through the same processes to work out

like how this transformation fits

the business bringing experts to help us do it

rather than just trying to figure it out by ourselves

yeah and I

I I think that's where the gap in the knowledge

still exists hmm

is not necessarily

do you understand AI technologies and the capabilities

do the question is more

do you understand how to drive a transformation

with that yeah

capability and most people haven't done this

because that's the thing

so people are still learning as they figure it out

at this was said earlier

everyone's still figuring out how it works

they may have done a

a traditional digital transformation in the past

which is similar

but there's gonna be nuance things and terms and

and that that but that's the

that's the actual

you've hit on one of the key points there

there is a lot of learnings from the

technology and digital transformations

that have been done in the past

and there's a lot

lots of practices that you just need to bring into

an AI based transformation

yep and

but equally as well

you need to start to get your business talking in those

frames of reference as well

you know

we used to have cloud first now we've got AI first okay

well to a certain extent I

it does make me laugh when when we do that as an Indian

yeah um

but there is something in it yeah

which is we need to all think like that

and once you get again

it's not just the CTO function to think like that

once you get the entire business thinking like that

you're then on a really good path

you're then on a path where

it becomes second nature to the business to say

actually you know what if we actually do the following

we can achieve the same outcome

without necessarily having

three times more staff in a certain area yeah um

so yeah there there is lots of potential there

but there is lots of learning and lots of maturing

that needs to happen really quickly

the thing that I will say is

I'll sit here now and I'll say this in 12 months

every that that will have been caught up a lot yeah

and that's what I'm seeing where

whereas if I step back fifteen years ago

technologies used to answer enter into the market

which was sometimes game changing in the approach

and uh let's take cloud as an example yep

cloud took a huge time for businesses to really adopt

yeah of course

there were larger

much bigger scale enterprises who completely got this

right but they had the investment and they could do it

they were more hindered by the legacy

challenge that they had well yeah

taking everything off the prem to the cloud

bunch of prem servers that no one knew exactly what

what these things did right

so um

but I was surprised by the amount of businesses

who were in

that kind of like 100 to kind of thousand headcount

business space

um who still hadn't gone cloud

mm hmm now I think fast majority

eventually organizations have got round the hurdle

and nearly everyone's kind of got

their heads around that problem

what I'm seeing with the AI first approach

if we use that yup

is that

I think people held their ground initially for the

for the last 18 months or so

but now there is a real push yeah

so then that's why I say within the next 12 months

people will have made that transformation

they will have had to do that

they will have had to drive that outcome

and that's what I that's why again I

I say there is something far more tangible here

than the ebbs and flows

of what's happened in the technology market

in the past yeah

people are getting used to the technology now

and they understand it a little better

no one understands it perfectly

I don't think uh well

maybe a few people here and there

but people now start to really

sort of realize the benefits

and they are asking a lot of the right questions

and going okay

this isn't just noise it's not going away

we need to work out how we can harness this yeah

in whatever we're doing I think yeah

and

and I think this is where kind of anthropic and open AI

particularly but even Microsoft and many others now

get it right is

because

employees in the work environment are exposed through

generative AI to the potential power

so

it makes it actually a bit of an easier step for CTOs

when you start to talk about what else you can do

and you introduce concepts of agenic AI yup

then it's not that

it's not so much of a leap for people

it's not a hard sell to your finance team to say

we're gonna use this stuff in AI

and they're not suddenly so scared going yeah

what happened to my job yeah

I look I see as an enabler

I remember in 2012 trying to have

having to explain to our finance teams

why you couldn't capitalize

all the stuff that is now in cloud right right

which was a bit of a shock to them um

so so because of that

the work and the the services that open AI and

and anthropic and many others have

have brought to the market

that has got everyone thinking in those terms hmm

so um

so I'm I'm optimistic and hopefully

you know

I think

our use of this type of technology will rapidly mature

and not we we tend to as humans use this

use these types of technologies for superficial stuff

initially but eventually we get our heads around it

yeah and start to really bring forward some true

game changing business applications

but you know it's

it's it's

it's always the

the nature of these types of advancements

which is the the people

the benefit which is identified comes later

hmm yeah

so great we've got a foundational game changing tech

in what these guys have done um

in these in these organizations

there will be a a next step

a new generation of people who start to build out

really really tangible use cases against this

and you can see this already starting to happen

yeah with more and more kind of agent

agentic capabilities coming online

and some of it is

you now start to look at some of it and go

that's really smart

someone's really thought that through

and when we spoke last time

you mentioned uh

that you guys have been working on building

some recommendation engines

that had yeah

around about 90% 8% accuracy

yeah or over

that's quite smart to me yeah

so that's what how did that

how did that start talk to me about that project

no that this is

and it all starts from the same position of you have

you understand what your market needs

yeah you understand what you can offer

as a potential proposition within that market

so it's not necessarily an instinctive okay

here's what we can do with AI yeah

you're trying to solve a business problem

you're trying to uh

bring something new and exciting

and innovative to your customers

you're trying to get that competitive edge

yeah a little bit

and again you know that

that is the the your your starting point

then you start to look at what you could do with AI

to solve problems because in many cases

what you're able to do is

you knew these problems existed previously

but you could never solve them right

because it was never there

now you've got the opportunity to kind of say right

how do we get to a position where

we can build something where we have a

an engine which recommends

the right type of campaign for our customers

in such a way that it delivers

that with a high level of accuracy

so our customers can be assured

that if they follow the guidance that we're giving

uh they

they're gonna drive the outcome

that they want to achieve

on their side

which you know that might be more brand awareness

that might be an uptick

in the sales that they see of that particular brand

but we want to make sure that we always

get to that place where

we've done all the hard work in the background

where we've got the models in the background

and we can say with a level of credibility

based on our expertise based on our knowledge

here's the best way to go about achieving

your business goals your outcomes

we've got

the AI is operating as part of that to augment the

the whole thinking

but ultimately that takes you as

as a as a provider of these type of services

that takes you into a place where

you're really showing that you've got the

your focus is on the best interests of your customers

and where you can take your customers

and that's really what was driving that is

how can we do something extraordinary for customers

yeah how can I

sit there with a brand manager of a multinational

and say I can within a level of accuracy

guarantee an outcome for you

we gotta be careful with the word guarantee yeah

but um

almost guarantee almost guarantee

but have models in the background

which show

that there is a level of accuracy and predictability

on the outcome could you do that without AI

because could a human

give that level of accuracy in the prediction

do you think

not consistently um

and there are too many variables okay

far too many variables because if you look at

if you look at what you can do with AI

you can bring in literally thousands of variables

including you know

let's say there is a cause

we do a lot of stuff which is kind of days out

offers these types of rewards

okay what happens if you have a really bad summer

right

well actually you can use AI to kind of say right

look what's the long term weather forecast

and that can actually play in

mm hmm potentially yeah yeah

now you could never do that with a human right

they they

for them to be able to do that at any speed

it's not scalable

it's gonna by the time it's some will have passed right

by the time they probably managed to do it

if you have 100 organizations every month

asking roughly those types of questions

yeah

and you need to respond literally in no more than a

a few minutes if not maybe an hour right yeah

maximum yeah

you just couldn't you couldn't do that yeah

um

and that's what really AI gives you is that capability

which is again you know

one of the really strong use cases for AI

is being able to do to get

serve up analytics and insights exceptionally quickly

in ways that we've never had the opportunity to do

now

that is not maybe a direct line sight of cost saving

but it really is right yeah

it really gives

people that decision making capability to act on

almost immediately yeah

and you know

if you can do that if you can do something at pace

then OK that might help our customers in certain ways

well it definitely helps

doesn't it with things like reporting

because think about traditional reports

it takes takes a while for them to be compiled

every all the data to go into it

someone to build something that someone who's see

sweet level

who's doesn't like looking at lots of numbers

they'll go I wanna see the tell me show me the graph

for example simplest form

that's a that's the other shift which I think

which is really this one which is exciting for me

is traditional approach has always been get uh

technology teams or business insight teams

or business intelligence teams

to build out some reports

mm hmm and we kind of go through this kind of

definition process and then eventually we

someone goes off builds these reports and hey

presto four weeks later here's your report right

we don't need to do that anymore

mm hmm forward

now it's about

have we got all the data in the background

is that data of a good quality

and is it all joined together

yeah that's the key right

yup yup

absolutely and we mustn't miss the data part of this

yup because often that gets pushed over with with AI

but the reason why all these

companies need the investment

and the levels of people that they need

is not about the AI capabilities

it's about the data in the background

and how they manage and curate that data

so getting your data in a really fit state

then enables you to basically go back to a customer

and say you want reports

ask the system just type into the system

and it will tell you what data you have available

and then you can ask it to build a report for you

and it will build that report for you within seconds

that completely shifts the dynamic

because it's not about what report do you want right

it's not about a visualization of a report

it's about here's your data

it's structured in this certain type of way

use the AI to interrogate it

and ask the questions that you want

yup and that is empowering people again

yeah and that is what really drives businesses forward

and that's where you get excited

decision making in like seconds

exactly exactly

ultimately rather than having to wait a month

as you say you know

you can imagine

if you've got this wealth of data in the background

and you're and your CFO

or your CEO is asking these questions around

the value of what we're getting from the likes of

you know whatever services that TLC delivers

yeah the wealth of data is there

you can just ask

and you can produce the reports literally in seconds

yeah that is again

a game changer yeah

it's amazing um

and we talked a bit about um

like the use of tokens

and you're spending lots of money on uh

on AI cause it's not this

say the cost saving is is not really the

the thing that's driving it for

for most people these days

I think a lot of people still selling that um

bit bit of snake oil

in my opinion yeah

um should be looking at

the other things that we've been speaking about yeah

um

we talked a bit about about budgets and having budgets

and you need to have budgets for

for AI I

believe

and there's been a lot of people not having budgets

for AI and just throwing money at

at things and having unlimited budgets and just going

yeah just spend

and I know you've been through this scenario for

from other things you've been doing

so I've had unlimited budget to do yeah

but not not particularly with AI

but certainly from a people point of view but no

just to to come back to the AI point

and it's a critical thing

you have to put usage limits into your AI capabilities

and that has to be a default

uh you cannot just leave that open ended

because if you leave AI open

say for example I give data to a

a customer or or give an AI capability to a customer

and data is in the background

and I put no limitation on that in the background okay

they can run run run keep going Gary

and they can potentially

generate a huge amount of cost

really quickly yep

so one of the

the things which I always insist on with all my teams

is anything that we do

which is leveraging large language models

as we build out the kind of

the rag structures

and various other things that we've built out

is we have to have usage limits

and that is monitored um

almost on a daily basis

so that we can see how it's being used

what it's being used for

and that's not necessarily to kind of like

restrict anyone

but it's always to kind of look at what's happening

mm hmm because then you can kind of

proactively address any usage

yeah or those usage patterns

and to a certain extent

you can also reach out to people and say

what is it you're doing

cause you're generating a huge amount of cost here

and sometimes that's that

what they're doing is actually a huge business value

so yeah

yeah and go yeah

it's fine right

can I yeah yeah

but it's like any consumption model

don't leave it untethered

yeah yeah

you suddenly find you've got a huge Bill at the end and

yeah and no value

and there was kind of a bit of a unique

situation in the past where

those consumption models were kind of in the remit

of the the tech teams who understood right

don't do this don't do that

otherwise you'll spend a lot of cash really easily with

particularly with the large language models

and their availability

the opportunity for that to go wrong really quickly is

is there yeah

so you have to put in those limitations

and like this this comes back to something

which I think is

coming a bit more hotly up on the rails

when people talk about AI

is governance structure

a real oversight on what you're doing with that

with that tech yeah

if you don't and it's like anything

it's like any innovation right

all these things all technological innovations

can be used in a very good

positive way which really enhances what we're doing

but can also be very destructive very easily hmm

and we see many examples of that

outside of the work environment yeah

of course but

there are examples where it's becoming deconstructive

inside the work environment as well yeah

so you've got to be able to monitor it and you know

also as well

there is a tendency for people to play with AI yeah

well most people are playing with AI

experimenting at the moment

cause they're getting used to it and they don't know

they want to understand what's happening yeah

yeah and

and you've got to be careful again with that

because there there is a danger that you

you consume a lot of resources in that

in that learning activity um

which is why we try to particularly in TLC

but also as well in other places which I've worked

you try to always align back to

if we're gonna do something in this space

let's make sure that it's gonna

generate the value that we want to

do your leg work do the rigour in the background

before you start committing down these directions

otherwise

you will inevitably end up with a situation where CFO's

if you haven't done that leg work

and all of a sudden you're generating cost

CFO's will come up and then say well

why have we got all this cost all of a sudden yep

and that's again

a responsibility of a CTO in the modern context

is to have got all that level setting done

yep in advance

so that when you start to leverage

AI capabilities at scale and it does come with cost

everyone's okay with that because you can budget for it

yeah and they know that it's offering far more value

yep then it is cost yeah

right you know

no one you're lying it yeah

yeah yeah

many many years ago when I no one used to kind of uh

bat an eyelid at the huge expense

that people used to pay for

SAP

transformations ERP transformations

yep because everyone

CFO's and CEO's and everyone in the business

were completely aligned

to the fact that these types of systems offer

huge value

now

you need to make sure that you're doing that with AI

as well it's the Val

it's spell out the value proposition

spell out where this is going

spell out what this is gonna do for the business

and then everyone becomes fairly

a lot more relaxed

about the cost that it's gonna generate

but you still need to monitor closely in terms of like

the future and what it holds

crystal ball moment but what are the

I suppose like what's the

what's the

give me the one technology trend that you think

people should pay attention to

quantum computing yeah

yeah

seriously it's a great one yeah

um because

and oddly enough this goes back to my university days

I I wrote my thesis on quantum computing

albeit it was very kind of uh high level and um

probably wildly inaccurate at the time

but the

the potential that

that has to do things that we've never even

and it it's really out the

outside of the realms of even speculation

hmm um

but the first type of services are coming online

and you'll see that increasingly

come of influence

over the course of the next 10 years or so

as more and more use cases for that type of capability

start to pull around I'm really

excited to see the intercept point between AI

and quantum computing yes

I agree that will be game changing yep

um it will when that will come

I'm I'm sure who knows yeah

I'm sure that you know Google will probably work

they've they've

probably made the biggest advancements in quantum

computing over the course of the last few uh

months with the stability of qubits

and that's just

you know

that that has gone past thresholds that many uh

researchers in this space

thought were never gonna be achievable

you know the

the actual stabilization that they've now got

in those types of environments is um

something really exciting

that then lays

the foundation for commercial applications

of this type of technology

and you can see now that the universities

are starting to get universities

and various different research organizations

are starting to get access to that for the first time

yep there's teams in various different UK universities

and US universities

who are now signing contracts with Google

and many others

to get access to that quantum computing capability

almost in the way that they kind of like

buy time from the telescopes and stuff like that

they're buying time from these things now

the potential for that is huge

and again

there is a downside to that

which and I I wouldn't kind of panic everyone

but

every cryptocurrency in the world is all of a sudden

at risk

because

there is no way that

those systems can literally go through any type of

cryptography or any type of security that we've got

almost within minutes yep

so there is a downside of that

that's why we have to have the kind of

controls and governance

I think if you look at in the same way

that there is a bit of a battleground emerging

between various different uh

countries around the world around AI

that battleground will increasingly heat up

around quantum computing

well let's see where it goes David

it has been absolutely fascinating talking to you

thank you so much again for taking the time

pleasure I think we've uh

we've set a few things straight today

ha ha ha uh

hopefully given some people

some insight into some things they didn't know

as well uh

I've certainly enjoyed it

so I'm sure the

the listeners and the watchers have as well

thanks Rupert

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