Latest / Look Forward / Powering the Future: Data Centers at the Crossroads of AI and Sustainability

Transcript

Powering the Future: Data Centers at the Crossroads of AI and Sustainability · Look Forward

0:06
Welcome to the Look Forward Podcast from S&P Global.
0:10
My name is Molly Mintz.
0:12
I'm the lead strategist for research and development at S&P Global Ratings.
0:17
When this podcast originally launched six years ago, I was supporting the show as
0:22
its executive producer behind the scenes.
0:26
Now I'm thrilled to be back in the studio and in front of our audience
0:30
as one of the shows new host.
0:33
In today's rapidly Shifting Markets success depends on anticipating
0:38
what's next on the horizon.
0:41
The experts who excel are professionals who can spot emerging trends
0:45
before they fully materialize.
0:48
With the Look Forward Podcast, you can access the forward-looking intelligence.
0:51
You need to navigate uncertainty with confidence.
0:56
The Look Forward Podcast delivers fresh insights, deeper analyses, and
1:00
innovative approaches that are essential in this rapidly changing world.
1:05
To help you prepare for future risks and opportunities, we bring you specialist
1:10
perspectives on capital markets, trade and supply chains, the multidimensional
1:15
energy transition, sustainability and climate, global realignment technology
1:21
and digital disruption and beyond.
1:24
This podcast connects you with S&P Global's Look Forward Council,
1:29
bringing cutting edge research on long-term trends and transformative
1:34
market shifts, with a sharp focus on what these developments mean for the
1:39
decisions that will shape your tomorrow.
1:42
I'm looking forward to always learning with you.
1:46
Data centers are the factories of the 21st century digital economy
1:51
and essential to artificial intelligence driven transformation.
1:56
The investment boom, powering this revolution is already becoming the
2:00
largest contributor to US growth.
2:02
S&P Global 451 research estimates that US data center capacity represents
2:09
over 40% of the global total, and that figure is projected to continue growing.
2:16
Asia Pacific follows as second with Europe, a distant
2:20
third on the global stage.
2:22
Nations worldwide are engaged in an AI race.
2:26
Determining the future of economic competitiveness, national
2:31
security, and societal paradigms.
2:34
But expansion in the data center industry faces limitations due to ai, significant
2:39
energy consumption, challenges and power demand constraints increased
2:44
competition for opportunities and sustainability concerns over emissions
2:49
and water stress among other risks.
2:53
To discuss the frontier for data centers on the cusp of forthcoming research
2:57
from S&P Global's, look forward council.
3:00
I am thrilled to be joined by two pioneering subject matter experts
3:04
from S&P Globals 451 research.
3:07
Kelly Morgan, research director for data Center infrastructure at
3:11
451 Research and Brian Partridge, head of Research at 451 Research.
3:17
Kelly, Brian, thanks so much for coming on the Look Forward Podcast.
3:21
Let's start off with the fundamentals.
3:25
Would you please explain your roles and share with our audience
3:28
why data centers are such an important focus for your research?
3:33
Uh, I guess I can start.
3:34
So, Kelly Morgan, I head up the data center team at 451, uh, where I've been
3:40
covering data centers for 20 years and they were not that important until Gen AI.
3:45
I mean, they were very important, but nobody knew about them.
3:48
So I like to joke that now, uh, since Gen AI and this kind of massive increase
3:54
in need and, uh, request for data center capacity, my mom knows what I
3:59
do now, so I'll pass it on to Brian.
4:03
Hey Molly.
4:04
Hey Kelly.
4:05
It's great to be with you both.
4:06
So, I'm Brian Partridge.
4:08
Uh, my role is I'm the global Head of research for 451 research.
4:12
I've actually been with 451 for over 10 years, has worked for as
4:16
an IT analyst for over 20 now.
4:18
Um, S&P Global acquired 451 actually back in, uh, late 2019.
4:23
So just a little context about 451.
4:25
So.
4:26
Our analysts have been tracking the evolution of the IT
4:29
market for the past 25 years.
4:32
Our clients tend to be a mix of tech vendors and users, service
4:36
providers, energy companies, um, more recently investors.
4:41
And we are really providing a range of intelligence focused
4:44
broadly on the most disruptive tech innovations across a broad landscape.
4:49
So what we're doing every day is our teams are focused on companies, we're
4:53
focused on trends, demand signals across this broad stack stack of technologies.
4:59
And so why data centers now?
5:01
Well, the first thing to say, and Kelly just said it right, is they've
5:03
always mattered to us, uh, and well before we've entered what we're calling
5:07
the AI era, uh, and these buildings and all the stuff that goes in them
5:12
is really the physical layer of it.
5:14
Um, and I'll say that we've built one of the strongest teams around and data
5:19
sets in the industry centered on data center operators, assets and markets.
5:25
Um, but with AI now in the picture, it really requires a
5:28
fundamental upgrade of the physical infrastructure to run those workloads.
5:34
And we're gonna talk a lot about that today.
5:36
Um, but really what.
5:37
Is so important to know is that this AI boom has created this
5:40
supercycle investment and data centers really sit at the front
5:45
and center to this entire movement.
5:47
Brian on that front, let's unpack how data center investments are
5:52
increasingly moving the macro needle.
5:55
Our latest look forward journal research finds that AI driven data
5:58
center growth added roughly half a percentage point to us GDP in mid 2025.
6:06
What's behind this surge?
6:07
Will these investments translate into lasting productivity gains
6:11
rather than just a construction boom.
6:14
Yeah, I mean it's a lot to unpack, unpack there, but, but fundamentally, it's true.
6:18
You know, data centers and the infrastructure that supports them
6:22
are becoming a critical engine for the US economy and beyond.
6:27
The recent surge investment isn't just about land or buildings, of course, and
6:31
includes the servers, the racks, the cooling systems, the software and the
6:36
r and d that power these facilities.
6:38
So our analysis at S&P suggests that these combined investments added a roughly a
6:43
half percentage point, as you mentioned.
6:45
And that's a clear sign that AI infrastructure is now a major
6:49
economic contributor, not just a tech narrative or story.
6:53
And this shift is transforming the tech sector itself.
6:56
When we think about the public cloud providers, we call them hyperscalers,
7:00
um, in our world, Microsoft, Google, Oracle, AWS, they're now investing.
7:08
With revenue CapEx ratios comparable to like what the telecom operators will do
7:13
during a ma, a major network build phase.
7:16
So that's really creating a high tech capital and energy intensive set of
7:19
facilities, which is really not what they've traditionally done in the
7:23
past, in, in, in a lot of corners.
7:25
So the result of this is big tech is becoming more CapEx heavy, more energy
7:30
intensive, increasingly influential on productivity, um, uh, widely.
7:37
The key question which you raise, right Molly, is where and how?
7:41
And when will this drive lasting productivity gains?
7:46
So it's early.
7:47
Our 451 research demand side data suggests that the expectations for scale remain
7:54
high, but long-term impact here really depends on a number of factors, which is.
7:59
How effectively AI can augment labor, drive efficiency, and
8:04
integrate into business processes.
8:06
And these are complex challenges.
8:08
They require a complete rethink of workflows and the human machine
8:12
interplay and it, that's not easy.
8:15
Um, but essentially where we are today is the infrastructure is being
8:20
ground for these transformations.
8:22
And the translation to sustain economic benefits will vary
8:26
by industry, by company.
8:29
By specific processes, like for instance, in areas like software
8:33
development and customer experience, the impact of AI is already
8:37
pronounced and and producing outcomes.
8:39
Some industries are still trying to figure out what they're gonna do.
8:42
Obviously, capital is continuing to flow into digital infrastructure investments.
8:47
I wanna note that these projects demand an enormous amount of upfront
8:51
capital from a plethora of sources.
8:54
While market fundamentals are healthy, the sector's capital, intensity, and
8:58
reliance and AI could pose risks.
9:01
Given that the ultimate timing of widespread a adoption and
9:04
the eventual size of the overall market are yet to be realized.
9:08
So Brian, how serious are these risks and what should market
9:12
participants be watching for?
9:14
Yeah, I mean, it's a great question.
9:15
It's important question, and I, I would say generally the AI and the, uh, AI
9:21
infrastructure and data center market are a very interesting spot right now.
9:25
So when we think about where we sit today, the fundamentals, I would agree, are
9:29
strong demand is outpacing supply, occup occupancy, and rate rents are rising.
9:36
Pricing power is supporting sort of near term growth.
9:39
At the same time, these projects are incredibly capital intensive,
9:43
often relying on billions of dollars of public and private
9:46
financing to get up off the ground.
9:49
And in the end, success really depends on AI revenue materializing
9:52
at scale, which it has not yet.
9:54
So we really need to watch and understand the demand signal.
9:57
This is something that 451 is, uh, doing every day, especially around inference.
10:03
And what we're looking for is sustained enterprise adoption beyond pilots.
10:08
This is called AI diffusion, and watching this mix from training to inference
10:13
because inference is really where the rubber hits the road for AI monetization.
10:18
Other risks that we're actively monitoring as our clients are as well is are
10:22
things like speculative construction.
10:24
So those are like building projects without committed tenants.
10:28
And if a lot of that happens and we've seen some signs of potentially
10:31
some of that sort of bubbling up, it creates potential for
10:35
oversupply, especially demand slows.
10:38
We're also monitoring structural constraints in policy, tailwinds.
10:42
Things like power, availability on the grid, behind the meter, the permitting
10:47
required to get new power, infrastructure up and running equipment, lead times
10:52
and regulatory signals, whether they be about sovereign compute requirements,
10:56
incentives, sustainability rules.
11:00
All of that will determine.
11:01
You know which regions can best service their AI demand, and which
11:06
projects at the micro level may face execution or stranded asset risk.
11:10
At the same time though, there's tremendous upside here, which is
11:14
why there's so much excitement and momentum in this space, right?
11:17
This isn't just about buildings and servers.
11:20
This is about powering breakthroughs in science technology, accelerating
11:24
things like drug discovery, immense productivity gains.
11:28
The potential here for economic and societal value goes far beyond
11:32
traditional returns, so it's essential to be mindful of the risk factors.
11:38
Also understand that the risks are about transform transformational
11:42
impact across these industries.
11:44
So to summary, right, the takeaway is that strong fund fundamentals exist today.
11:50
Certain companies sectors may get overheated depending on their
11:53
local market dynamics or what's happening within the company.
11:56
This is a highly competitive field, which is actually quite healthy for the
12:00
market, and not everybody's gonna win.
12:03
So what's required for our clients is an active approach to risk management
12:08
and paying close attention to the market signals that are relevant
12:11
to your specific set of exposures.
12:14
Now, Kelly, over to you.
12:16
Let's change gears and look at data centers, energy demands,
12:20
specifically electricity.
12:22
How are data centers impacting the US power grid and what
12:26
challenges does this pose?
12:29
Yeah, well one of the key issues has been the sudden rise in data
12:34
center demand for electricity.
12:36
So in the US data centers were typically growing by about six to 8% a year,
12:41
sort of single digit growth in terms of their demand for electricity.
12:46
And then all of a sudden post ChatGPT as generative AI has taken
12:51
off that demand increase to 19-20%.
12:56
You know, we have it at.
12:57
Anywhere between 15 to 20% over the next few years.
13:01
Uh, and so that was already a huge leap right there.
13:04
And there have been plenty of challenges just with supply chain
13:08
and getting these things built.
13:09
But when it comes to energy, this was a particular challenge because the US
13:14
energy grid was actually used to pretty flat growth for the past, I think decade.
13:19
There's been relatively flat growth in terms of amount
13:22
of energy use, and although.
13:25
There were plans that that would grow due to electric vehicles
13:28
and various other things.
13:29
This pretty much took the industry by surprise.
13:33
Uh, and then, so as a result, there are lots of challenges.
13:37
Getting that kind of newly requested amount of power to the
13:41
right place at the right time.
13:43
And another key challenge here is that the time horizons for data
13:47
centers are very different than the typical time horizons for utilities.
13:51
So a data center can be built in a year to two years, assuming
13:55
all their permitting is lined up.
13:57
Whereas building a new power plant right, is on a much longer timescale.
14:01
And even the transmission lines and getting substations put in and all
14:04
the infrastructure requirements for power that can take, um, anywhere
14:09
from 5 to 10 years in a lot of cases.
14:12
So that means fundamentally we're in a crunch at the moment.
14:16
Uh, where the utilities are, are getting pressure from the data centers.
14:19
The data centers, having always kind of requested data center capacity
14:24
and requested energy and not had to really worry about getting it.
14:29
I mean, in some locations they did, and now all of a sudden that is pretty
14:32
much the key constraint to growth in particular locations around the us.
14:37
So lots going on trying to balance those two aspects out really.
14:43
So in this context, what role do onsite energy solutions play?
14:49
Yes, so that is kind of the hoped for relief valve.
14:53
I would say.
14:54
A lot of data center firms are kind of planning that if they can't get their
14:59
power and time, they could set up their own power behind the meter to either.
15:06
Sort of transition them to an eventual grid connection or perhaps just
15:10
be used to power the data center.
15:12
That of course, adds, um, a huge level of complexity.
15:18
A lot of these data centers are not used to becoming power plant
15:22
operators, so there's that.
15:24
It adds a whole level of CapEx that, folks weren't prepared for necessarily, right?
15:29
You're building your data center, but you also have to build a, a natural
15:32
gas fired power plant and it may not be easy to get everything you need to
15:39
build that behind the meter power either.
15:40
So as a, a company at S&P, we're doing a lot of research on.
15:46
Where might behind the meter power be required?
15:49
Where might it be needed?
15:51
What are the options?
15:52
Uh, you know, I think the preferred option at the moment for a lot
15:56
of data center firms is to use natural gas fired power plants.
16:00
But those turbines, uh, that are required to build, those are all
16:04
sold out for the next few years.
16:06
And also in a lot of locations, the quantity of natural gas
16:10
might just not be available.
16:12
In the next year, right?
16:13
So there, there are all kinds of challenges there and some things that
16:17
might be sort of quick and easy to connect, such as, um, solar power, right?
16:22
Or in some locations, maybe wind power.
16:25
Uh, typically data centers haven't wanted, uh, kind of uneven power, right?
16:30
They want very steady supply that's very reliable.
16:34
They're not used to dealing with supply that might.
16:38
Not be consistent.
16:39
So the industry is looking at options like batteries and various
16:44
ways to, to get around that.
16:46
But it, it's certainly, I would say, pushing the, enter the whole
16:50
industry to become more creative and look at a lot of different
16:53
solutions to try to get around this.
16:56
Okay.
16:56
Kelly, another question for you.
16:58
How can data centers balance growth with sustainability goals?
17:04
Oh yes, that's back to me.
17:06
So part of this challenge with the renewable energy, uh, when we've asked
17:11
most of the big data center consumers, right, the, the firms that want to
17:16
use these data centers to put their AI equipment do still plan to try to meet
17:22
their sustainability targets, so they haven't just thrown those out the window.
17:27
Due to generative AI to meet those sustainability targets, we get
17:31
back to that question of whether you want to connect a solar farm
17:35
directly to your data center, and what kind of issues does that pose?
17:39
Typically, up until now, the data center providers have been, um, paying for
17:45
green energy to be added to the grid, but not directly to the data center.
17:50
I think that will continue the top it firms have been the, essentially
17:55
the top customers for PPAs, for paying for these, um, renewable
18:00
resources to be added to the grid.
18:02
That will continue, but we are also seeing some other efforts, um, to both
18:08
make the data centers more efficient.
18:10
To use less water, for example.
18:12
And the challenge there is that often to use less water, you need to use more
18:15
power, so then you need more green power.
18:18
They're looking at longer term approaches to add more sustainable power, so
18:23
that in some cases could be nuclear.
18:25
They're looking at things like geothermal in certain locations, right?
18:28
So any options.
18:30
And then we are seeing certainly in, in some locations, and this is pretty
18:34
complicated to do, but uh, we're seeing it in Europe for example, quite a lot.
18:38
Um, having the data center become part of a really an energy
18:43
ecosystem so that they're feeding leftover heat from the data center.
18:48
So a lot of energy goes into the data center.
18:51
Comes out as heat essentially.
18:54
And that heat can be used for other things.
18:56
So it's being plugged into heating systems to heat people's homes.
19:00
It can be plugged into industrial systems, um, greenhouses, for example.
19:05
We're seeing that, we're seeing data centers, heat swimming pools, right?
19:09
So there are also ways to become, uh, sustainable in, in sharing
19:14
kind of the output of, of what they're, what they're producing.
19:19
Okay.
19:20
Looking outside of the us, the Middle East is also emerging as
19:25
a global data center force driven by cloud computing and AI demand.
19:30
With Saudi Arabia in particular, experiencing a digital transformation
19:36
as it seeks to diversify its economy.
19:39
Kelly, what's driving this momentum and what unique opportunities and
19:43
challenges are defining this market?
19:47
So on Saudi Arabia, um, essentially what we're seeing for data center growth
19:53
globally is that we're seeing it I think in a similar way to the, the way
19:59
private, uh, public cloud expanded.
20:02
So.
20:04
It initially was launched in the us, got the first start there, and
20:08
that's what we're seeing with AI.
20:10
Um, AI has been kind of kicked off in the US and that's where most of the
20:14
growth comes from initially, but then.
20:17
It, it becomes, it ends up being rolled out around the world.
20:21
And typically, uh, it providers, AI providers would start with
20:26
key hubs in key locations, right?
20:29
So they're looking for one or two hubs in Europe, some hubs in, uh, Asia
20:34
hubs in the Middle East, and we have.
20:37
Quite a few countries around the world now, kind of vying
20:40
to become those main hubs.
20:42
And one of the key issues, uh, one of the ways that determines whether
20:46
you'll become a hub is whether you have energy available and then also to
20:50
a certain degree, government support.
20:52
And that's what we're seeing in Saudi Arabia.
20:55
So I think the kingdom of Saudi Arabia is making an effort to become one of
20:58
those key hubs to serve Middle East.
21:01
I think Africa, possibly part of Europe.
21:04
And the, the benefits that they can offer are, uh, state government,
21:10
uh, kind of approach, you know, a government support system to help data
21:15
centers get permitting, to help align power infrastructure with data center
21:20
infrastructure, where that's needed.
21:22
And then just in general to, uh, provide available power to these things
21:27
and to kind of provide a way of, uh.
21:30
Forward looking planning to make sure there will be enough power
21:34
to support the data center demand.
21:36
So that's what we're seeing there.
21:38
Brian, I'm bringing this back to you.
21:40
Looking forward to 2026, what themes do you expect to change the AI and
21:46
data center narrative, and what trends are you most excited about?
21:52
Yeah, sure.
21:52
Like right now as we speak, we're sort of finalizing the agenda, um, and I'm
21:57
taking an input from a broad swath of stakeholders across S&P on, on the key
22:02
sort of items we're gonna work on as part of the Look Forward Council right now.
22:07
But I'll call out three major trends that we're excited about and we'll be investing
22:11
our time and energy and sort of uncovering and, and, uh, covering next year.
22:16
It has to start on this whole evolution from sort of the training.
22:21
Mode or phase of, of AI, uh, adoption to inference and really understanding
22:28
the implications of what that's gonna look like globally and in and
22:32
in the hot spots of the marketplace.
22:35
Um, that's going to really have a, a great amount of impact on the data
22:40
center footprint that's required.
22:41
How much compute is gonna be required at different locations.
22:45
You can think of it like from the, a very, very large data center all
22:48
the way out to somebody's pocket.
22:50
And AI is gonna actually live in all of these places.
22:53
And the inference phase that are require more far-flung compute,
22:57
which has, um, you know, impact on, on all of these different things.
23:01
So really understanding what are the applications and use cases of AI that
23:06
are gonna, that are gonna drive the architectural requirement and where
23:09
the inference needs to be is something that we're looking at closely.
23:13
Uh, the other thing I would say is sort of compute sovereignty.
23:17
Um.
23:18
And, and overall sort of global strategy around ai.
23:21
So we're already focused on this, but it's interesting and we have plans to
23:24
sort of double click on different, um, countries to understand what are they
23:30
doing to secure their compute capacity, how are they building sustainable, uh,
23:36
and uh, reliable supply chains to actually bring the, the, these ecosystems together.
23:42
And, uh, and speed's the name of the game here.
23:45
How are they dealing with critical minerals and ensuring that they've got
23:49
access to the rare earths and copper and things that they need in order
23:54
to compete to, to do what Kelly said, which is to create their AI hubs.
23:58
And then there's just so much interesting innovation happening
24:02
within the AI stack itself at the data center layer, like in terms of.
24:08
Heating, uh, cooling and efficiency designs.
24:12
I mean, these AI data centers are, are a rethink of how data centers are built.
24:17
So we we're gonna be seeing a lot of innovations in places like liquid cooling.
24:22
Um, Kelly mentioned behind the meter.
24:24
I mean, we see that as a really interesting.
24:26
Opportunity for us to bring value to those ecosystems, but also a place for
24:31
innovation and, and, and potentially even like around the corner, things
24:35
like what's the role for small, uh, modular reactors on the nuclear
24:40
side, uh, down the line to sort of support some of these requirements.
24:44
So there are many, many things that we're focused on, but I, I would call
24:48
out those three as maybe the, the, the most interesting and exciting.
24:53
Kelly, what can we additionally expect for the global energy and resource
24:57
challenges shaping data center expansion?
25:01
Well, as I think Brian was saying, we're trying to figure out what the next likely
25:08
source of energy generation will be, and certainly nuclear is in that conversation.
25:13
Lots of investment being made there.
25:15
The key question there is timeline.
25:18
Uh, but yes, all over the world, I think a lot of countries are looking
25:22
at their plans for growth on both the energy generation side and transmission.
25:31
One of the key issues really everywhere, I think.
25:34
Uh, but we've certainly seen this in places like the UK and China.
25:38
And the US alot of times your key generation hubs, particularly for
25:43
renewables, are not in the locations where either the data centers wanna be
25:48
or certainly where your population is.
25:51
So I think a lot of countries are doing re rethinking about how to get
25:56
that power to the right location.
25:58
Do you bring it from Scotland down to London?
26:00
Do you bring it from Western China to Eastern China or do you try to
26:04
get all the data centers to move to Scotland and Western China?
26:07
So that's all being discussed and debated and I think a lot of government policies,
26:13
you know, government regulators are trying to figure out how to set up policies
26:16
to, to determine this going forward.
26:19
And since we have the crystal ball in our hands, looking into the future, how close
26:25
is the market to seeing quantum computers integrated into traditional data centers?
26:33
What hurdles do we have left to actually overcome?
26:37
Well, yes, that is a great crystal ball question.
26:40
Uh, quantum computers are mostly in the lab.
26:44
They're starting to move out of the lab.
26:45
We are starting to see real compute happening, uh, but they do require very
26:51
specific, uh, setups, I would say so.
26:54
There are various types of quantum computers.
26:57
Some require very cold infrastructure.
27:00
Everything has to be super chilled.
27:03
Others require, or maybe in a way all of them, but some of them are more
27:07
focused on, uh, seismic isolation.
27:10
There can't be any movement.
27:12
Others need protection from, um, electromagnetic rays, for example.
27:18
So they require some very specific things that typically don't
27:21
exist in current data centers.
27:24
So I think as quantum computing grows, we're likely to just see
27:30
continued builds of specific quantum computers rather than seeing them move
27:35
into typical regular data centers.
27:38
Um, interestingly, they're also in slightly different spots than most
27:41
of the mega data center markets.
27:43
There are near where there are labs and research, uh, and advanced.
27:48
You know, work being done on quantum computing.
27:52
Uh, so places like Boston, Silicon Valley is, is a classic.
27:57
Boston isn't known for a huge number of data centers.
27:59
We have a few.
28:00
I live here, but not a lot.
28:02
Uh, but so we are starting to see some expansion of that.
28:05
I think one of the key questions that we're still waiting to figure
28:09
out is whether quantum will disrupt AI and whether actually quantum
28:14
computing could take over some of that work currently expected to be
28:18
done by AI and whether that will kind of impact the energy requirements
28:23
and so far in terms of energy.
28:26
Required for quantum computing.
28:28
It will depend which type we end up sort of seeing used the most.
28:33
Uh, the, certainly the ultra cooled data centers use plenty of energy, so that
28:38
might not end us end up saving energy, but perhaps they'll do a lot more calculations
28:44
in one, sort of using the same amount of energy, uh, than AI computers.
28:48
We're all, that's all still to be determined, but coming soon.
28:53
So of course with all of these dynamics at play, understanding the nuances of
28:58
how rapidly the digital revolution is adapting and advancing is more critical
29:04
and clearly more competitive than ever.
29:07
Brian.
29:08
Where is S&P Global?
29:10
Investing in talent and tools to better crystallize and forecast
29:14
data center and energy demand.
29:19
Yeah, sure.
29:19
So I'll, I'll speak for the, the, um, the parts of S&P where
29:23
Kelly and I are most involved.
29:24
And you know, what I can say is we're investing heavily both in
29:27
talent and tools to really help our clients navigate this fast.
29:32
Fast moving environment and that's across data center, AI, it and energy.
29:38
So things that we're working on is, and I wanna make sure everyone
29:41
understands we already have global coverage, but what we're gonna be
29:44
doing is, is developing even deeper global coverage in hotspot regions.
29:49
And I would call out places like the Middle East, which we've talked
29:52
about, even Africa and India.
29:55
To, to get deeper and broader in the understanding and surfacing for our
30:00
clients, the regional dynamics that are driving the data center growth
30:03
and, and energy dynamics in the market.
30:05
You'll see a lot more, um, quantitative and forecasting
30:10
enhancements coming from our teams.
30:13
We're growing our quantitative modeling team to do, um, forecasts
30:17
and US energy demand by region, by energy, region by state.
30:22
We're extending our planning horizons well beyond what would be traditional
30:25
in the IT world of five years, all the way out to, to what's required
30:29
to energy, which goes out beyond 10.
30:32
You'll see a lot more strategic.
30:34
Um.
30:35
Strategy, uh, strategic modeling from us and scenario modeling.
30:39
So developing a number of ai, uh, driven electric electricity demand scenarios.
30:45
Um, looking at grid constraints and partnership with the power teams,
30:50
tracking the regulatory impacts at the state, local level, federal levels,
30:56
and really just generating the insights that are required to navigate this
30:59
fast moving market for investors, for operators, and for energy ecosystem.
31:04
Participants.
31:06
It's clear that data centers are a critical engine for ai,
31:10
cloud, and economic growth both domestically and globally.
31:15
Thank you, Kelly and Brian, for these essential insights.
31:20
Thank you for listening to the Look Forward Podcast.
31:23
To read the research we discussed, please visit sp global.com.
31:29
I'm Molly Mince and I'm looking forward to advancing essential
31:33
intelligence with you next time.