Live from Morgan Stanley’s European Tech, Media and Telecom
conference in Barcelona, our roundtable of analysts discuss
artificial intelligence in Europe, and how the region could
enable the Agentic AI wave.
Read more insights from Morgan Stanley.
----- Transcript -----
Paul Walsh: Welcome to Thoughts on the Market.
I'm Paul Walsh, Morgan Stanley's European head of research
product. We are bringing you a special episode today live from
Morgan Stanley's, 25th European TMT Conference, currently
underway.
The central theme we're focused on: Can Europe keep up from a
technology development perspective?
It's Wednesday, November the 12th at 8:00 AM in Barcelona.
Earlier this morning I was live on stage with my colleagues, Adam
Wood, Head of European Technology and Payments, Emmet Kelly, Head
of European Telco and Data Centers, and Lee Simpson, Head of
European Technology Hardware. The larger context of our
conversation was tech diffusion, one of our four key themes that
we've identified at Morgan Stanley Research for 2025.
For the panel, we wanted to focus further on agentic AI in
Europe, AI disruption as well as adoption, and data centers. We
started off with my question to Adam. I asked him to frame our
conversation around how Europe is enabling the Agentic AI
wave.
Adam Wood: I mean, I think obviously the
debate around GenAI, and particularly enterprise software, my
space has changed quite a lot over the last three to four months.
Maybe it's good if we do go back a little bit to the period
before that – when everything was more positive in the world. And
I think it is important to think about, you know, why we were
excited, before we started to debate the outcomes.
And the reason we were excited was we've obviously done a lot of
work with enterprise software to automate business processes.
That's what; that's ultimately what software is about. It's about
automating and standardizing business processes. They can be done
more efficiently and more repeatably. We'd done work in the past
on RPA vendors who tried to take the automation further. And we
were getting numbers that, you know, 30 – 40 percent of
enterprise processes have been automated in this way. But I think
the feeling was it was still the minority. And the reason for
that was it was quite difficult with traditional coding
techniques to go a lot further. You know, if you take the call
center as a classic example, it's very difficult to code what
every response is going to be to human interaction with a call
center worker. It's practically impossible.
And so, you know, what we did for a long time was more – where we
got into those situations where it was difficult to code every
outcome, we'd leave it with labor. And we'd do the labor
arbitrage often, where we'd move from onshore workers to offshore
workers, but we'd still leave it as a relatively manual process
with human intervention in it.
I think the really exciting thing about GenAI is it completely
transforms that equation because if the computers can understand
natural human language, again to our call center example, we can
train the models on every call center interaction. And then first
of all, we can help the call center worker predict what the
responses are going to be to incoming queries. And then maybe
over time we can even automate that role.
I think it goes a lot further than, you know, call center
workers. We can go into finance where a lot of work is still
either manual data re-entry or a remediation of errors. And
again, we can automate a lot more of those tasks. That's
obviously where, where SAP's involved. But basically what I'm
trying to say is if we expand massively the capabilities of what
software can automate, surely that has to be good for the
software sector that has to expand the addressable markets of
what software companies are going to be able to do.
Now we can have a secondary debate around: Is it going to be the
incumbents, is it going to be corporates that do more themselves?
Is it going to be new entrants that that benefit from this? But I
think it's very hard to argue that if you expand dramatically the
capabilities of what software can do, you don't get a benefit
from that in the sector.
Now we're a little bit more consumer today in terms of spending,
and the enterprises are lagging a little bit. But I think for us,
that's just a question of timing. And we think we'll see that
come through.
I'll leave it there. But I think there's lots of opportunities in
software. We're probably yet to see them come through in numbers,
but that shouldn't mean we get, you know, kind of, we don't think
they're going to happen.
Paul Walsh: Yeah. We’re going to talk
separately about AI disruption as we go through this morning's
discussion. But what's the pushback you get, Adam, to this notion
of, you know, the addressable market expanding?
Adam Wood: It's one of a number of things.
It's that… And we get onto the kind of the multiple bear cases
that come up on enterprise software. It would be some combination
of, well, if coding becomes dramatically cheaper and we can set
up, you know, user interfaces on the fly in the morning, that can
query data sets; and we can access those data sets almost in an
automated way. Well, maybe companies just do this themselves and
we move from a world where we've been outsourcing software to
third party software vendors; we do more of it in-house. That
would be one.
The other one would be the barriers to entry of software have
just come down dramatically. It's so much easier to write the
code, to build a software company and to get out into the market.
That it's going to be new entrants that challenge the incumbents.
And that will just bring price pressure on the whole market and
bring… So, although what we automate gets bigger, the price we
charge to do it comes down.
The third one would be the seat-based pricing issue that a lot of
software vendors to date have expressed the value they deliver to
customers through. How many seats of the software you have in
house.
Well, if we take out 10 – 20 percent of your HR department
because we make them 10, 20, 30 percent more efficient. Does that
mean we pay the software vendor 10, 20, 30 percent less? And so
again, we're delivering more value, we're automating more and
making companies more efficient. But the value doesn't accrue to
the software vendors. It's some combination of those themes I
think that people would worry about.
Paul Walsh: And Lee, let’s bring you into
the conversation here as well, because around this theme of
enabling the agentic AI way, we sort of identified three main
enabler sectors. Obviously, Adam’s with the software side. Cap
goods being the other one that we mentioned in the work that
we've done. But obviously semis is also an important piece of
this puzzle. Walk us through your thoughts, please.
Lee Simpson: Sure. I think from a sort of a
hardware perspective, and really we're talking about
semiconductors here and possibly even just the equipment guys,
specifically – when seeing things through a European lens. It's
been a bonanza. We've seen quite a big build out obviously for
GPUs. We've seen incredible new server architectures going into
the cloud. And now we're at the point where we're changing things
a little bit. Does the power architecture need to be changed?
Does the nature of the compute need to change? And with that, the
development and the supply needs to move with that as well.
So, we're now seeing the mantle being picked up by the AI guys at
the very leading edge of logic. So, someone has to put the
equipment in the ground, and the equipment guys are being leaned
into. And you're starting to see that change in the order book
now.
Now, I labor this point largely because, you know, we'd been seen
as laggards frankly in the last couple of years. It'd been a U.S.
story, a GPU heavy story. But I think for us now we're starting
to see a flipping of that and it's like, hold on, these are
beneficiaries. And I really think it's 'cause that bow wave has
changed in logic.
Paul Walsh: And Lee, you talked there in
your opening remarks about the extent to which obviously the
focus has been predominantly on the U.S. ways to play, which is
totally understandable for global investors. And obviously this
has been an extraordinary year of ups and downs as it relates to
the tech space.
What's your sense in terms of what you are getting back from
clients? Is the focus shifts may be from some of those U.S. ways
to play to Europe? Are you sensing that shift taking place? How
are clients interacting with you as it relates to the focus
between the opportunities in the U.S. and Asia, frankly, versus
Europe?
Lee Simpson: Yeah. I mean, Europe's coming
more into debate. It's more; people are willing to talk to some
of the players. We've got other players in the analog space
playing into that as well. But I think for me, if we take a step
back and keep this at the global level, there's a huge debate now
around what is the size of build out that we need for AI?
What is the nature of the compute? What is the power pool? What
is the power budgets going to look like in data centers? And
Emmet will talk to that as well. So, all of that… Some of that
argument’s coming now and centering on Europe. How do they play
into this? But for me, most of what we're finding people debate
about – is a 20-25 gigawatt year feasible for [20]27? Is a 30-35
gigawatt for [20]28 feasible? And so, I think that's the debate
line at this point – not so much as Europe in the debate. It's
more what is that global pool going to look like?
Paul Walsh: Yeah. This whole
infrastructure rollout's got significant implications for your
coverage universe…
Lee Simpson: It does. Yeah.
Paul Walsh: Emmet, it may be a bit
tangential for the telco space, but was there anything you wanted
to add there as it relates to this sort of agentic wave piece
from a telco's perspective?
Emmet Kelly: Yeah, there's a consensus view
out there that telcos are not really that tuned into the AI wave
at the moment – just from a stock market perspective. I think
it's fair to say some telcos have been a source of funds for AI
and we've seen that in a stock market context, especially in the
U.S. telco space, versus U.S. tech over the last three to six
months, has been a source of funds.
So, there are a lot of question marks about the telco exposure to
AI. And I think the telcos have kind of struggled to put their
case forward about how they can benefit from AI. They talked 18
months ago about using chatbots. They talked about smart
networks, et cetera, but they haven't really advanced their case
since then.
And we don't see telcos involved much in the data center space.
And that's understandable because investing in data centers, as
we've written, is extremely expensive. So, if I rewind the clock
two years ago, a good size data center was 1 megawatt in size.
And a year ago, that number was somewhere about 50 to 100
megawatts in size. And today a big data center is a gigawatt. Now
if you want to roll out a 100 megawatt data center, which is a
decent sized data center, but it's not huge – that will cost
roughly 3 billion euros to roll out.
So, telcos, they've yet to really prove that they've got much
positive exposure to AI.
Paul Walsh: That was an edited excerpt from
my conversation with Adam, Emmet and Lee. Many thanks to them for
taking the time out for that discussion and the live audience for
hearing us out.
We will have a concluding episode tomorrow where we dig into tech
disruption and data center investments. So please do come back
for that very topical conversation.
As always, thanks for listening. Let us know what you think about
this and other episodes by leaving us a review wherever you get
your podcasts. And if you enjoy Thoughts on the Market, please
tell a friend or colleague to tune in today.
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