July 8, 2025 • 20 mins
In this episode of CGI’s Energy Transition Talks, host Caroline McNaught speaks with Peter Warren, CGI’s Global Industry Lead for Energy & Utilities, about the transformative role of AI in reshaping the sector. Drawing on insights from CGI’s 2025 Voice of Our Clients research, they explore how AI helps streamline compliance, modernize legacy systems, and address workforce challenges—while enhancing agility and driving sustainable outcomes. Tune in to hear how utility leaders can navigate complexity, embed strategy in innovation, and do more with less in an era of digital disruption
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Caroline McNaught (00:00):
Hello everyone, welcome back to
another episode of our EnergyTransition Talks podcast.
My name is Caroline McNaught,I'm part of the Global Brand and
External Communications teamhere at CGI, and joining me
today is CGI's Vice Presidentand Global Industry Lead for
Energy and Utilities, peterWarren.
Peter, can you introduceyourself and your role here in
(00:20):
energy and utility sector?
Peter Warren (00:21):
Yeah, Hi Caroline.
Thank you very much for thatgreat introduction and thank you
for having me today.
Caroline McNaught (00:29):
Well, today I'm excited because we'll be
discussing the key trendsshaping energy and utilities
organizations and the insightsthat will guide their future.
Based on the newly released2025 CGI voice of our clients
research In energy and utilities, we spoke with 158 executives
to better understand thepriorities and strategic shifts
(00:50):
ahead.
So, with that in mind, peter,what trends stood out to you
this year?
Peter Warren (00:54):
Yeah, it was really an interesting year this
year when we started talking todifferent folks.
Obviously, ai bubbled to thetop, but also the geopolitical
things that are going on aroundthe world bubble to the top.
There were really quite a fewareas where everyone was sort of
looking for how do I do morewith less?
How do I change the world, howdo I deal with the budgets that
(01:17):
I have, and so it was reallyquite a mix of different
functions, but I know there weresome top trends that were there
and do you want to maybe justhighlight them for us, or I can
do that.
Caroline McNaught (01:28):
Sure, I know that for energy and utilities,
we saw a lot around AI that'snot new but in particular, AI
for decarbonization and gridresilience.
Across industries as well,workforce transformation and
talent shortages seemed to be akey issue.
I know in energy and utilitieswe were seeing that quite a bit
Supply chain resilience and risknavigating, regulatory change
(01:49):
and a few others that I'm surewe can drill into, but those
were some top ones that I thinkwe saw across this industry.
Peter Warren (01:54):
Yeah, so maybe taking them on one at a time
with you here.
So decarbonization Initially,when decarbonization sort of
started and moved forward, Iremember one person saying this
is going to ruin us all.
This ESG stuff is going to beterrible for us.
And yes, some of it is mandatedand moving forward.
But companies are still movingforward with not only just
(02:14):
because there are governmentsand mandates to actually
decarbonize and lower things,but the entire economy wants to
decarbonize in lower end and,given that energy of all forms
is the scope one, scope threesorry, scope three input into
every other industry, havingthis decarbonize is a key
component for every othercustomer of these companies.
(02:36):
They also realize that they cansqueeze out inefficiencies,
that when they started to lookat how do I decarbonize things,
they also realized that theycould actually drive out
inefficiencies that they hadn'treally realized before.
So this is not only being donebecause it's mandated, it's
being done because the customerswant it and it's also because
it does drive out inefficiencies.
Caroline McNaught (02:57):
I know AI came up quite a bit this year.
It's hard to avoid it thesedays.
How has AI been playing a rolein helping balance
sustainability with gridreliability?
Peter Warren (03:06):
It's been interesting.
One of the cases that we didwas with one company was looking
at the regulatory compliance.
It's interesting.
Regulations are very tough forevery industry and I had one
client tell me if I comply tothis, I automatically void that
and it's kind of a tough thingfor them to do.
So what we've been able to do isuse AI to help track all of
(03:27):
their compliancy, to look atwhat they're doing, to look at
the forms, look at the functions, and bring this forward to them
as in this very complex form ofdocuments that sometimes are
different formats and differentalignments and actually help
them have a dashboard to say,hey, how am I doing from a
compliancy standpoint and whatshould I move forward?
You know, I remember one clienttalking to us is that every day
(03:50):
is a compliancy day.
Every day is another thing.
When some of these rules firstcame out, people were treating
it like an annual audit and theywould have a bunch of people
get together in a room and theywould all sort of come together
and say this is our best guess.
Now that has become sort of anongoing process, having tools
like AI in all of its formats,scanning documents, compiling
(04:11):
things, pointing out failures,pointing out gaps, pulling out
misses, is something that weneed for a day-to-day purpose.
Caroline McNaught (04:18):
Makes sense.
When you talk about compliance,that sounds like a bit of a
challenge.
What are the biggest challengesutilities face with using AI
for resilience, whether that beintegrating into existing
infrastructure or any otherconsiderations that they may
have when approaching that?
Peter Warren (04:33):
Yeah, that's another good point.
You know, it really comes downto access at data at pace and
scale.
The AI systems are as smart asyou feed them, and we've all
seen or heard of stories wheresomebody does something and it
doesn't really pan out very wellbecause the AI came up with the
decision that it said it wasgoing to do.
(04:54):
I mean, there were some majorplatforms that came out and were
republishing what BBC publishedas a news announcement.
The AI was turning it intosomething else and effectively
creating fake news as it wentforward, and so having reliable
data so that you're not having ahallucination is a key function
.
So this comes down to actuallysome pretty basic organizational
(05:15):
restructuring capabilities,having access to data at pace
and scale, and the silos thatexist in a lot of companies.
Those are restricting thebenefits they're getting out of
AI.
In fact, one of the things wefound out when we compared those
that were happy with theresults what we call digital
leaders and the ones thatweren't, is they're actually
(05:36):
both investing money verysimilarly as each other and
actually in very similar wayseach other.
The difference and actually invery similar ways the difference
was that one is more agile and,as an organization is
responding to the data, dealingwith it, but also more agile in
the way that they free up thedata and don't have the fiefdoms
of saying, no, this is my CISdata or this is my GIS data, and
(05:59):
I have methodologies of findingand correcting that data over
time.
So it's much more of a businesstransformation aspect that we
help people with and work withthan it is really a technical
problem.
Caroline McNaught (06:10):
So interesting.
When you talk abouttransformation, that word seems
to apply across the board thisyear.
When we look at workforcetransformation and talent
shortages, what are we seeingthere?
How are digital technologiesreshaping workforce needs in the
energy sector?
Peter Warren (06:26):
Yeah, that's another great one.
One of our business units partof the Canadian team in Western
Canada has been doing apublishing series on workforce
of the future, specificallybecause their clients in that
part of the world we see this inother parts of the world with
their great example are facing atalent shortage in the oil
industry.
(06:46):
To come into Alberta to takethings on to the point where
some universities have actuallyeither cut back or canceled
courses simply because youngerpeople weren't signing up for
them, and so we've even had tochange how we service these
clients.
So in this particular case, weactually supply that market with
a very popular software to do akey function of accounting
(07:09):
carbon capture and so on and thepeople that run those systems
are going to retire in a fewyears.
So, you know, ai has theopportunity to come in and
systems have new systems havethe opportunity to come in here
and produce the outcomes asthese people move forward.
It's not to replace the people,because the people are going to
leave.
It's replacing the function andwe see this across the industry
(07:31):
is that clients have to startto optimize what they're doing,
have their good people focus inon key, high-value processes.
So this system will then feedthis data up to another
higher-valued person.
They'll say, yes, I agree withthat or I don't agree with that.
And the other one is putting allthe functions and we've done
this in several differentclients and we see other people
(07:53):
doing this consolidating all ofthe knowledge for the employees
into the handheld device thatthe person can have.
You know we've talked about theaging population for 10 years
in this industry, that you knowpeople are retiring and we have
this problem, but up until nowthere wasn't an easy solution to
say how do you get all thatdata into one place?
(08:15):
And AI is actually that answer,as it turns out.
So we can actually scan allthose documents, much like that
earlier example where I talkedabout compliancy for regulations
.
We can scan all the manuals, wecan scan all the best practices
a company has and put that inthe hand of the person, and the
person then can actually notonly have it for their primary
function, but maybe secondary,third functions.
(08:37):
So employees' functionality canactually broaden, they can do
more skills because it's in thepalm of their hand and, by the
way, this starts with health andsafety.
It starts right off.
Are you wearing the right gear?
Are you happy enough to do thisjob today, all of those
compliancy things?
Then it says, okay, nowapproach it from this direction
and do the following.
Caroline McNaught (08:58):
Well, you jumped seamlessly into what was
going to be my next questionaround how roles are evolving
with automation and AI.
I think that looks like it'ssomething that isn't going away.
So it's really about makingsure you know what you're doing
with those tools to enableefficiencies, in that, when we
are looking at operations andhaving these new efficiencies
obviously there we saw a lot ofgeopolitical disruption and
(09:22):
other factors that are shapingthe supply chain.
How are energy leadersstrengthening operations amid
these global disruptions?
Peter Warren (09:29):
Yeah, it gets into all one of our other areas that
you brought up with regulatoryand so on, and we touched a bit
on compliancy earlier.
It's really looking at thetotal operations of the
operations of the company andsaying how do I make it more
efficiency?
It's value for money.
Really.
It comes down to how do I domore with less, how do I get
(09:49):
more of a bang for my dollars?
And looking at the entireoperation.
So you know, for us in I won'tget into product names
necessarily on this call but forus, when we out-task or do a
function for somebody, we'reusing AI to get constant
iterative improvements in theway that we look at this and
people are applying this in avariety of different ways.
But how do I look at what I'mdoing in a process?
(10:13):
How do I optimize that?
Okay, how do I optimize itagain?
How do I make it better?
How do I make it better?
Ultimately, it gets down to, youknow, the last five or 10% that
it's too much cost to squeezethat out.
But then you move to the nextone and look at that and
continually look at how tooptimize the systems.
The next one and look at thatand continually look at how to
optimize the systems, do I?
(10:34):
Maybe if I've got existingchatbots or existing other types
of bots in my system, can I saythat one's not very busy right
now.
I can actually give that onemore work before I go start
buying other stuff and reallylooking at the end-to-end
process in a digital fashion.
Now, and that's the nextevolution of the digitization
process, people have put indigitization in pockets.
Now how do I consider it as anend-to-end?
Caroline McNaught (10:59):
And how are in that role of navigating
regulatory change?
How are utilities adapting tothese fast evolving energy and
AI regulations?
Peter Warren (11:09):
I would say, like the rest of us, they're holding
onto their seats and riding itthrough.
It's an ongoing battle andoften regulation doesn't keep up
with the actual going ons withtechnology.
So in some cases people areleading and well ahead, and
other people you know othergroups are actually racing to
catch up the compliancy of AIwith you know other groups are
(11:33):
actually racing to catch up thecompliancy of AI with you know,
specifically Europe being aleader in that and other people
starting to apply it.
That's a key function.
The NIST 2 securityrequirements that are happening
in Europe and even in the UnitedStates, where you know the
critical infrastructure securityis being pushed down.
They've always had some ofthese things, but it's all being
tightened up both in thegovernments and in the
(11:53):
regulatory area, and it's aconstant challenge.
Going back to that is that, froma project management standpoint
, you can have people looking atthis, but these people can be
also balanced off with an AIsystem that says, hey, this is
about to go into the red or theyellow, this is not going to be
something that you want to miss,and having systems set up to
(12:15):
monitor these processes.
People try to navigate anever-changing world.
This year in our VOC the voiceof the client as well.
It was highlighted tariffs forthe first time.
I mean we're not surprised atthat, but people were saying
they need new digital tools, newdigital products that will help
them manage these.
So they're recognizing the needfor it.
They're just not quite clear ona product that exists, so AI is
(12:38):
actually becoming that product.
Caroline McNaught (12:40):
So interesting.
Peter Warren (12:43):
What can't it do these days, right?
Well, it makes good-lookingchipmunks racing cars in my
backyard.
I did that with it.
Caroline McNaught (12:47):
How can companies build agility into
their operations to respond tothe shifting regulations more
effectively?
Peter Warren (12:54):
Yeah, agility starts, I think, from the top.
You know, it starts from acultural change and this has
been always linked as.
One of the factors that we keepseeing when we start to compare
one factor in our voice of theclients to another factor, is
that we see the ones that aregetting the benefit out of all
(13:15):
of their investments.
The leadership, theorganization is very agile.
There's also an alignment thatgoes on.
So agile doesn't mean chaotic.
Agile means that they'reresponding to what's moving
forward and they're dealing withit in a structured fashion.
Believe it or not, agile can bevery structured, which is
something this industry loves.
If you don't do things in astructured fashion, things catch
(13:37):
fire and blow up.
So you can still have thisstructure, but you can respond
to it in a very different wayand have the people understand
that this is good for them, havean involvement with it, have
the systems being more agile andfreeing up this data.
That then reinforces thisanswer that's moving forward.
So it really comes down from analignment business and IT
(13:59):
actually in sync For companies.
When we interview somebody fromthe business side and then
somebody from the IT and wecompare their answers.
If there's a huge gap, that'snot a good thing.
If they're more or lessswimming in the same direction,
that's a much better story, asyou can imagine, and if the
executives are also sayingsomething different, I mean
(14:19):
that's not good.
So it really comes down toorganizational alignment and
structure and the ability torespond to what's happening.
Caroline McNaught (14:27):
Fantastic.
Well, on that note, that takesus to the last trend that I
think really stood out forenergy and utilities this year,
and that was legacymodernization and innovation.
So we see across the board,modernizing legacy systems is a
major challenge for a number ofbusinesses.
Where should organizationsstart?
Peter Warren (14:44):
Yeah, legacy systems are interesting
Sometimes.
I use an analogy often withpeople of renovating a house
because people understand thatit's a good visual.
I myself am sitting amongst abunch of tools and things
because our house is underrenovation.
When you renovate something,sometimes you leave a temporary
(15:04):
wall in place and that could bea legacy system.
If you think about it, you'regoing to modernize it, you're
going to an open concept, but ifyou take down that wall right
now, the ceiling falls in.
So suddenly you've got abungalow from a two-story, so
you've got to look at it.
That, how do I move thingsforward?
There's also the factor of thepeople that support those
(15:24):
systems.
You don't want to reallyreplace them if they know the
COBOL system or whatever ithappens to be, and that's the
thing that maintains the secondfloor.
And so digitizing, fordigitization's sake, is
something that you strategicallyhave to look at where there's
low-hanging fruit, where there'sthings that are important
things, and where I actuallyhave the people that can
(15:45):
actually want to do it and cando it, and or partner with
somebody that can bring thatthat A want to do it and B can
do it, and or partner withsomebody that can bring that
skill set in.
But look at it from renovatinga house as maybe years before
you take down that temporarywall.
It doesn't mean you're going topaint it.
It doesn't mean you're going tohang pictures on it.
You can de-risk it by usingtools to migrate it maybe off of
an old piece of hardware.
(16:06):
A toy or other systems couldrecompile it and you could now
put it on a lower risk piece ofsoftware.
But it's gonna do the samething it always did If it
printed on purple polka dottedpaper.
It's gonna print on purplepolka dotted paper.
Still.
You're not gonna get newfunction out of it, but it's
still supporting the secondstory until such time as I can
have enough infrastructurearound to take it down.
(16:28):
So I think you have to look atit.
Caroline McNaught (16:34):
I love that analogy.
I'm not sure this wouldnecessarily help a house, but
how would cloud and AI platformsaccelerate innovation in this
area?
Peter Warren (16:46):
Yeah, cloud is a huge one and, of course, most AI
systems are cloud largelanguage models.
We're seeing more and more playin.
Dianne Gushu, our AI VP, doctorof AI wisdom talks about small
language models, and we're usinga lot more small language
models for specific functionswithin a utility or government
(17:07):
or other area.
When you don't necessarily wantto go out to the big external
cloud, you want to do things ina controlled fashion, more
locally.
So if it's a critical thing,you know I love cloud and we
have some clients that havereally gone to cloud, but then,
as the cloud providers continueto raise prices, that's an
ongoing aspect for them.
(17:27):
I think looking at cloud in abalanced way is important.
Where does it offer me a quickacceleration to move forward?
But where should I maybe keepsome things closer to home?
We had this debate with oneclient that's actually very
local to me here years ago.
They had their outagemanagement system and one party
was saying we should put it allin the cloud.
(17:48):
But Canada, where I live, isvery prone to ice, storms and
even hurricanes, believe it ornot, and we get something like
27 tornadoes a year in the areaI live, so weather can come in
and cause major disruption ifyou're not careful.
And so could you imagine if youhad your outage management team
standing there waiting for thenetwork to come back online so
(18:10):
you could actually startrestoring stuff?
Wouldn't be good.
That should be local, at least,even at an ER.
Maybe your Monday to Fridayversion is running on the cloud
for efficiencies and access andso on, but the actual cloud, you
know a local version is veryimportant and something like
that.
So I think it's looking at thefunction of cloud importantly,
but you can still get thebenefits of AI at home on a more
(18:32):
local platform, maybe even asmall language one.
Caroline McNaught (18:35):
Nice.
Well, we've covered almost allthe trends.
If there's one immediate callto action for energy leaders,
Peter, what would you say it isfor this time in the landscape.
Peter Warren (18:46):
Yeah, it's a good one.
I mean, start off with gettingyour compliancy people and
regulatory people everybodyinvolved with this up front.
There's no point in chargingoff and doing something that is
going to get you in trouble froma compliancy standpoint or
regulatory standpoint.
And start with business casesand application use cases that
(19:08):
are business outcome focused,something that's going to drive
a positive outcome.
It's not about doing digitaltwins or digital triplets just
for the sake of doing them.
As Diane has said before, shesays nobody ever comes to us and
says I want an AI thing.
They want an outcome.
So figure out what that outcomeis and then do it in a way that
both your security, yourcompliancy people are all
(19:31):
involved with that, so that youdo it in a way that is
expandable and operational foryou.
It's all about making thingsthat are operational.
Caroline McNaught (19:38):
Makes sense.
Now, Peter, on a lighter note,what's one thing giving you
optimism about where energy andutilities are headed as an
industry?
Peter Warren (19:45):
Wow, that's a great one.
The innovation One reason why Ilove this industry is people do
it because they're passionatefor it, and so the aspect and
the opportunity for thisindustry is great.
There's a lot of today'sexisting leaders moving forward
in it and there's a lot of newentrants in this industry that's
coming forward.
(20:05):
That's both a good thing and abad thing, I guess, but the
industry is changing andevolving, and the movement
towards producing large amountsof consumable energy more at a
local level, amounts ofconsumable energy more at a
local level, more of thediversity of energy sources, the
ability to have people use andconsume their own energy, but
(20:28):
maybe supported by utilities ina function I mean, if you think
about it, I'm not an expert onsolar panels and batteries, but
I do trust my local utility andalways have, so the opportunity
for them to be my serviceprovider for something like that
that still benefits me andgives me reinforcement is a
great idea.
So I think there's going to bea lot of innovation.
(20:48):
There's going to be a lot ofcustomer service movement
forward, and the customercentricity aspect of all of that
I think I'm really most keenabout.
Caroline McNaught (20:56):
Well, peter, is there anything that we
haven't touched on, that you'dlove to leave the audience with
Just?
Peter Warren (21:04):
move forward, get on with the bandwagon.
Start with the use case, startwith your compliancy.
People, what I said before,make it practical.
When you do that, then theC-suite sees benefit in it.
You can start to look at thingsthat actually, with the
generative AI of havingdecisions brought up to you as a
(21:25):
outcome, if I've got three orfour digital twins moving
forward, well that's very nice.
But what does it mean to me asa business operator?
And that's where maybe thetriplet concept of generative AI
can come in and say, well,these are the things you should
consider, given everything elsegoing on, and that's not just
for this industry.
That could be a manufacturing,that could be a variety of
different industries.
Caroline McNaught (21:44):
Well, peter, thank you so much for your time
today.
It's been fun putting you inthe spotlight, as you so
generously do, to your guests onthis podcast and to anybody
listening.
Be sure to subscribe on Spotifyand Apple and stay tuned for
more Energy Transition Talks,episodes in
Hello everyone, welcome back to
another episode of our EnergyTransition Talks podcast.
My name is Caroline McNaught,I'm part of the Global Brand and
External Communications teamhere at CGI, and joining me
today is CGI's Vice Presidentand Global Industry Lead for
Energy and Utilities, peterWarren.
Peter, can you introduceyourself and your role here in
(00:20):
energy and utility sector?
Peter Warren (00:21):
Yeah, Hi Caroline.
Thank you very much for thatgreat introduction and thank you
for having me today.
Caroline McNaught (00:29):
Well, today I'm excited because we'll be
discussing the key trendsshaping energy and utilities
organizations and the insightsthat will guide their future.
Based on the newly released2025 CGI voice of our clients
research In energy and utilities, we spoke with 158 executives
to better understand thepriorities and strategic shifts
(00:50):
ahead.
So, with that in mind, peter,what trends stood out to you
this year?
Peter Warren (00:54):
Yeah, it was really an interesting year this
year when we started talking todifferent folks.
Obviously, ai bubbled to thetop, but also the geopolitical
things that are going on aroundthe world bubble to the top.
There were really quite a fewareas where everyone was sort of
looking for how do I do morewith less?
How do I change the world, howdo I deal with the budgets that
(01:17):
I have, and so it was reallyquite a mix of different
functions, but I know there weresome top trends that were there
and do you want to maybe justhighlight them for us, or I can
do that.
Caroline McNaught (01:28):
Sure, I know that for energy and utilities,
we saw a lot around AI that'snot new but in particular, AI
for decarbonization and gridresilience.
Across industries as well,workforce transformation and
talent shortages seemed to be akey issue.
I know in energy and utilitieswe were seeing that quite a bit
Supply chain resilience and risknavigating, regulatory change
(01:49):
and a few others that I'm surewe can drill into, but those
were some top ones that I thinkwe saw across this industry.
Peter Warren (01:54):
Yeah, so maybe taking them on one at a time
with you here.
So decarbonization Initially,when decarbonization sort of
started and moved forward, Iremember one person saying this
is going to ruin us all.
This ESG stuff is going to beterrible for us.
And yes, some of it is mandatedand moving forward.
But companies are still movingforward with not only just
(02:14):
because there are governmentsand mandates to actually
decarbonize and lower things,but the entire economy wants to
decarbonize in lower end and,given that energy of all forms
is the scope one, scope threesorry, scope three input into
every other industry, havingthis decarbonize is a key
component for every othercustomer of these companies.
(02:36):
They also realize that they cansqueeze out inefficiencies,
that when they started to lookat how do I decarbonize things,
they also realized that theycould actually drive out
inefficiencies that they hadn'treally realized before.
So this is not only being donebecause it's mandated, it's
being done because the customerswant it and it's also because
it does drive out inefficiencies.
Caroline McNaught (02:57):
I know AI came up quite a bit this year.
It's hard to avoid it thesedays.
How has AI been playing a rolein helping balance
sustainability with gridreliability?
Peter Warren (03:06):
It's been interesting.
One of the cases that we didwas with one company was looking
at the regulatory compliance.
It's interesting.
Regulations are very tough forevery industry and I had one
client tell me if I comply tothis, I automatically void that
and it's kind of a tough thingfor them to do.
So what we've been able to do isuse AI to help track all of
(03:27):
their compliancy, to look atwhat they're doing, to look at
the forms, look at the functions, and bring this forward to them
as in this very complex form ofdocuments that sometimes are
different formats and differentalignments and actually help
them have a dashboard to say,hey, how am I doing from a
compliancy standpoint and whatshould I move forward?
You know, I remember one clienttalking to us is that every day
(03:50):
is a compliancy day.
Every day is another thing.
When some of these rules firstcame out, people were treating
it like an annual audit and theywould have a bunch of people
get together in a room and theywould all sort of come together
and say this is our best guess.
Now that has become sort of anongoing process, having tools
like AI in all of its formats,scanning documents, compiling
(04:11):
things, pointing out failures,pointing out gaps, pulling out
misses, is something that weneed for a day-to-day purpose.
Caroline McNaught (04:18):
Makes sense.
When you talk about compliance,that sounds like a bit of a
challenge.
What are the biggest challengesutilities face with using AI
for resilience, whether that beintegrating into existing
infrastructure or any otherconsiderations that they may
have when approaching that?
Peter Warren (04:33):
Yeah, that's another good point.
You know, it really comes downto access at data at pace and
scale.
The AI systems are as smart asyou feed them, and we've all
seen or heard of stories wheresomebody does something and it
doesn't really pan out very wellbecause the AI came up with the
decision that it said it wasgoing to do.
(04:54):
I mean, there were some majorplatforms that came out and were
republishing what BBC publishedas a news announcement.
The AI was turning it intosomething else and effectively
creating fake news as it wentforward, and so having reliable
data so that you're not having ahallucination is a key function
.
So this comes down to actuallysome pretty basic organizational
(05:15):
restructuring capabilities,having access to data at pace
and scale, and the silos thatexist in a lot of companies.
Those are restricting thebenefits they're getting out of
AI.
In fact, one of the things wefound out when we compared those
that were happy with theresults what we call digital
leaders and the ones thatweren't, is they're actually
(05:36):
both investing money verysimilarly as each other and
actually in very similar wayseach other.
The difference and actually invery similar ways the difference
was that one is more agile and,as an organization is
responding to the data, dealingwith it, but also more agile in
the way that they free up thedata and don't have the fiefdoms
of saying, no, this is my CISdata or this is my GIS data, and
(05:59):
I have methodologies of findingand correcting that data over
time.
So it's much more of a businesstransformation aspect that we
help people with and work withthan it is really a technical
problem.
Caroline McNaught (06:10):
So interesting.
When you talk abouttransformation, that word seems
to apply across the board thisyear.
When we look at workforcetransformation and talent
shortages, what are we seeingthere?
How are digital technologiesreshaping workforce needs in the
energy sector?
Peter Warren (06:26):
Yeah, that's another great one.
One of our business units partof the Canadian team in Western
Canada has been doing apublishing series on workforce
of the future, specificallybecause their clients in that
part of the world we see this inother parts of the world with
their great example are facing atalent shortage in the oil
industry.
(06:46):
To come into Alberta to takethings on to the point where
some universities have actuallyeither cut back or canceled
courses simply because youngerpeople weren't signing up for
them, and so we've even had tochange how we service these
clients.
So in this particular case, weactually supply that market with
a very popular software to do akey function of accounting
(07:09):
carbon capture and so on and thepeople that run those systems
are going to retire in a fewyears.
So, you know, ai has theopportunity to come in and
systems have new systems havethe opportunity to come in here
and produce the outcomes asthese people move forward.
It's not to replace the people,because the people are going to
leave.
It's replacing the function andwe see this across the industry
(07:31):
is that clients have to startto optimize what they're doing,
have their good people focus inon key, high-value processes.
So this system will then feedthis data up to another
higher-valued person.
They'll say, yes, I agree withthat or I don't agree with that.
And the other one is putting allthe functions and we've done
this in several differentclients and we see other people
(07:53):
doing this consolidating all ofthe knowledge for the employees
into the handheld device thatthe person can have.
You know we've talked about theaging population for 10 years
in this industry, that you knowpeople are retiring and we have
this problem, but up until nowthere wasn't an easy solution to
say how do you get all thatdata into one place?
(08:15):
And AI is actually that answer,as it turns out.
So we can actually scan allthose documents, much like that
earlier example where I talkedabout compliancy for regulations
.
We can scan all the manuals, wecan scan all the best practices
a company has and put that inthe hand of the person, and the
person then can actually notonly have it for their primary
function, but maybe secondary,third functions.
(08:37):
So employees' functionality canactually broaden, they can do
more skills because it's in thepalm of their hand and, by the
way, this starts with health andsafety.
It starts right off.
Are you wearing the right gear?
Are you happy enough to do thisjob today, all of those
compliancy things?
Then it says, okay, nowapproach it from this direction
and do the following.
Caroline McNaught (08:58):
Well, you jumped seamlessly into what was
going to be my next questionaround how roles are evolving
with automation and AI.
I think that looks like it'ssomething that isn't going away.
So it's really about makingsure you know what you're doing
with those tools to enableefficiencies, in that, when we
are looking at operations andhaving these new efficiencies
obviously there we saw a lot ofgeopolitical disruption and
(09:22):
other factors that are shapingthe supply chain.
How are energy leadersstrengthening operations amid
these global disruptions?
Peter Warren (09:29):
Yeah, it gets into all one of our other areas that
you brought up with regulatoryand so on, and we touched a bit
on compliancy earlier.
It's really looking at thetotal operations of the
operations of the company andsaying how do I make it more
efficiency?
It's value for money.
Really.
It comes down to how do I domore with less, how do I get
(09:49):
more of a bang for my dollars?
And looking at the entireoperation.
So you know, for us in I won'tget into product names
necessarily on this call but forus, when we out-task or do a
function for somebody, we'reusing AI to get constant
iterative improvements in theway that we look at this and
people are applying this in avariety of different ways.
But how do I look at what I'mdoing in a process?
(10:13):
How do I optimize that?
Okay, how do I optimize itagain?
How do I make it better?
How do I make it better?
Ultimately, it gets down to, youknow, the last five or 10% that
it's too much cost to squeezethat out.
But then you move to the nextone and look at that and
continually look at how tooptimize the systems.
The next one and look at thatand continually look at how to
optimize the systems, do I?
(10:34):
Maybe if I've got existingchatbots or existing other types
of bots in my system, can I saythat one's not very busy right
now.
I can actually give that onemore work before I go start
buying other stuff and reallylooking at the end-to-end
process in a digital fashion.
Now, and that's the nextevolution of the digitization
process, people have put indigitization in pockets.
Now how do I consider it as anend-to-end?
Caroline McNaught (10:59):
And how are in that role of navigating
regulatory change?
How are utilities adapting tothese fast evolving energy and
AI regulations?
Peter Warren (11:09):
I would say, like the rest of us, they're holding
onto their seats and riding itthrough.
It's an ongoing battle andoften regulation doesn't keep up
with the actual going ons withtechnology.
So in some cases people areleading and well ahead, and
other people you know othergroups are actually racing to
catch up the compliancy of AIwith you know other groups are
(11:33):
actually racing to catch up thecompliancy of AI with you know,
specifically Europe being aleader in that and other people
starting to apply it.
That's a key function.
The NIST 2 securityrequirements that are happening
in Europe and even in the UnitedStates, where you know the
critical infrastructure securityis being pushed down.
They've always had some ofthese things, but it's all being
tightened up both in thegovernments and in the
(11:53):
regulatory area, and it's aconstant challenge.
Going back to that is that, froma project management standpoint
, you can have people looking atthis, but these people can be
also balanced off with an AIsystem that says, hey, this is
about to go into the red or theyellow, this is not going to be
something that you want to miss,and having systems set up to
(12:15):
monitor these processes.
People try to navigate anever-changing world.
This year in our VOC the voiceof the client as well.
It was highlighted tariffs forthe first time.
I mean we're not surprised atthat, but people were saying
they need new digital tools, newdigital products that will help
them manage these.
So they're recognizing the needfor it.
They're just not quite clear ona product that exists, so AI is
(12:38):
actually becoming that product.
Caroline McNaught (12:40):
So interesting.
Peter Warren (12:43):
What can't it do these days, right?
Well, it makes good-lookingchipmunks racing cars in my
backyard.
I did that with it.
Caroline McNaught (12:47):
How can companies build agility into
their operations to respond tothe shifting regulations more
effectively?
Peter Warren (12:54):
Yeah, agility starts, I think, from the top.
You know, it starts from acultural change and this has
been always linked as.
One of the factors that we keepseeing when we start to compare
one factor in our voice of theclients to another factor, is
that we see the ones that aregetting the benefit out of all
(13:15):
of their investments.
The leadership, theorganization is very agile.
There's also an alignment thatgoes on.
So agile doesn't mean chaotic.
Agile means that they'reresponding to what's moving
forward and they're dealing withit in a structured fashion.
Believe it or not, agile can bevery structured, which is
something this industry loves.
If you don't do things in astructured fashion, things catch
(13:37):
fire and blow up.
So you can still have thisstructure, but you can respond
to it in a very different wayand have the people understand
that this is good for them, havean involvement with it, have
the systems being more agile andfreeing up this data.
That then reinforces thisanswer that's moving forward.
So it really comes down from analignment business and IT
(13:59):
actually in sync For companies.
When we interview somebody fromthe business side and then
somebody from the IT and wecompare their answers.
If there's a huge gap, that'snot a good thing.
If they're more or lessswimming in the same direction,
that's a much better story, asyou can imagine, and if the
executives are also sayingsomething different, I mean
(14:19):
that's not good.
So it really comes down toorganizational alignment and
structure and the ability torespond to what's happening.
Caroline McNaught (14:27):
Fantastic.
Well, on that note, that takesus to the last trend that I
think really stood out forenergy and utilities this year,
and that was legacymodernization and innovation.
So we see across the board,modernizing legacy systems is a
major challenge for a number ofbusinesses.
Where should organizationsstart?
Peter Warren (14:44):
Yeah, legacy systems are interesting
Sometimes.
I use an analogy often withpeople of renovating a house
because people understand thatit's a good visual.
I myself am sitting amongst abunch of tools and things
because our house is underrenovation.
When you renovate something,sometimes you leave a temporary
(15:04):
wall in place and that could bea legacy system.
If you think about it, you'regoing to modernize it, you're
going to an open concept, but ifyou take down that wall right
now, the ceiling falls in.
So suddenly you've got abungalow from a two-story, so
you've got to look at it.
That, how do I move thingsforward?
There's also the factor of thepeople that support those
(15:24):
systems.
You don't want to reallyreplace them if they know the
COBOL system or whatever ithappens to be, and that's the
thing that maintains the secondfloor.
And so digitizing, fordigitization's sake, is
something that you strategicallyhave to look at where there's
low-hanging fruit, where there'sthings that are important
things, and where I actuallyhave the people that can
(15:45):
actually want to do it and cando it, and or partner with
somebody that can bring thatthat A want to do it and B can
do it, and or partner withsomebody that can bring that
skill set in.
But look at it from renovatinga house as maybe years before
you take down that temporarywall.
It doesn't mean you're going topaint it.
It doesn't mean you're going tohang pictures on it.
You can de-risk it by usingtools to migrate it maybe off of
an old piece of hardware.
(16:06):
A toy or other systems couldrecompile it and you could now
put it on a lower risk piece ofsoftware.
But it's gonna do the samething it always did If it
printed on purple polka dottedpaper.
It's gonna print on purplepolka dotted paper.
Still.
You're not gonna get newfunction out of it, but it's
still supporting the secondstory until such time as I can
have enough infrastructurearound to take it down.
(16:28):
So I think you have to look atit.
Caroline McNaught (16:34):
I love that analogy.
I'm not sure this wouldnecessarily help a house, but
how would cloud and AI platformsaccelerate innovation in this
area?
Peter Warren (16:46):
Yeah, cloud is a huge one and, of course, most AI
systems are cloud largelanguage models.
We're seeing more and more playin.
Dianne Gushu, our AI VP, doctorof AI wisdom talks about small
language models, and we're usinga lot more small language
models for specific functionswithin a utility or government
(17:07):
or other area.
When you don't necessarily wantto go out to the big external
cloud, you want to do things ina controlled fashion, more
locally.
So if it's a critical thing,you know I love cloud and we
have some clients that havereally gone to cloud, but then,
as the cloud providers continueto raise prices, that's an
ongoing aspect for them.
(17:27):
I think looking at cloud in abalanced way is important.
Where does it offer me a quickacceleration to move forward?
But where should I maybe keepsome things closer to home?
We had this debate with oneclient that's actually very
local to me here years ago.
They had their outagemanagement system and one party
was saying we should put it allin the cloud.
(17:48):
But Canada, where I live, isvery prone to ice, storms and
even hurricanes, believe it ornot, and we get something like
27 tornadoes a year in the areaI live, so weather can come in
and cause major disruption ifyou're not careful.
And so could you imagine if youhad your outage management team
standing there waiting for thenetwork to come back online so
(18:10):
you could actually startrestoring stuff?
Wouldn't be good.
That should be local, at least,even at an ER.
Maybe your Monday to Fridayversion is running on the cloud
for efficiencies and access andso on, but the actual cloud, you
know a local version is veryimportant and something like
that.
So I think it's looking at thefunction of cloud importantly,
but you can still get thebenefits of AI at home on a more
(18:32):
local platform, maybe even asmall language one.
Caroline McNaught (18:35):
Nice.
Well, we've covered almost allthe trends.
If there's one immediate callto action for energy leaders,
Peter, what would you say it isfor this time in the landscape.
Peter Warren (18:46):
Yeah, it's a good one.
I mean, start off with gettingyour compliancy people and
regulatory people everybodyinvolved with this up front.
There's no point in chargingoff and doing something that is
going to get you in trouble froma compliancy standpoint or
regulatory standpoint.
And start with business casesand application use cases that
(19:08):
are business outcome focused,something that's going to drive
a positive outcome.
It's not about doing digitaltwins or digital triplets just
for the sake of doing them.
As Diane has said before, shesays nobody ever comes to us and
says I want an AI thing.
They want an outcome.
So figure out what that outcomeis and then do it in a way that
both your security, yourcompliancy people are all
(19:31):
involved with that, so that youdo it in a way that is
expandable and operational foryou.
It's all about making thingsthat are operational.
Caroline McNaught (19:38):
Makes sense.
Now, Peter, on a lighter note,what's one thing giving you
optimism about where energy andutilities are headed as an
industry?
Peter Warren (19:45):
Wow, that's a great one.
The innovation One reason why Ilove this industry is people do
it because they're passionatefor it, and so the aspect and
the opportunity for thisindustry is great.
There's a lot of today'sexisting leaders moving forward
in it and there's a lot of newentrants in this industry that's
coming forward.
(20:05):
That's both a good thing and abad thing, I guess, but the
industry is changing andevolving, and the movement
towards producing large amountsof consumable energy more at a
local level, amounts ofconsumable energy more at a
local level, more of thediversity of energy sources, the
ability to have people use andconsume their own energy, but
(20:28):
maybe supported by utilities ina function I mean, if you think
about it, I'm not an expert onsolar panels and batteries, but
I do trust my local utility andalways have, so the opportunity
for them to be my serviceprovider for something like that
that still benefits me andgives me reinforcement is a
great idea.
So I think there's going to bea lot of innovation.
(20:48):
There's going to be a lot ofcustomer service movement
forward, and the customercentricity aspect of all of that
I think I'm really most keenabout.
Caroline McNaught (20:56):
Well, peter, is there anything that we
haven't touched on, that you'dlove to leave the audience with
Just?
Peter Warren (21:04):
move forward, get on with the bandwagon.
Start with the use case, startwith your compliancy.
People, what I said before,make it practical.
When you do that, then theC-suite sees benefit in it.
You can start to look at thingsthat actually, with the
generative AI of havingdecisions brought up to you as a
(21:25):
outcome, if I've got three orfour digital twins moving
forward, well that's very nice.
But what does it mean to me asa business operator?
And that's where maybe thetriplet concept of generative AI
can come in and say, well,these are the things you should
consider, given everything elsegoing on, and that's not just
for this industry.
That could be a manufacturing,that could be a variety of
different industries.
Caroline McNaught (21:44):
Well, peter, thank you so much for your time
today.
It's been fun putting you inthe spotlight, as you so
generously do, to your guests onthis podcast and to anybody
listening.
Be sure to subscribe on Spotifyand Apple and stay tuned for
more Energy Transition Talks,episodes in
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