In this episode of Lead-Lag Live, I sit down with Kai Wu, Founder and CIO of Sparkline Capital, to break down how the AI investment cycle is evolving as scrutiny rises and market enthusiasm becomes more selective.
From hyperscaler spending and data center economics to market concentration and fading euphoria, Wu explains why investors need to rethink where real AI returns may come from and why the next winners may not be the obvious names.
In this episode:
– Why massive AI capex is starting to worry investors
– How market concentration amplifies downside risk
– The productivity debate behind AI adoption
– Why AI adopters may outperform AI infrastructure plays
– How to position portfolios for the next phase of AI investing
Lead-Lag Live brings you inside conversations with the financial thinkers who shape markets. Subscribe for interviews that go deeper than the noise.
#ArtificialIntelligence #AI #StockMarket #MarketRisk #TechStocks
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Episode Transcript
Explosion innovation in this space has, if anything,
only um accelerated the trendand the value of these sorts of
data.
So, you know, I think I think toyour question, um, what the AI
boo has done is actually kind offull further reinforced my
thesis with regards to, youknow, uh the the belief that uh
you know an even greater shareof corporate value now lies in
(00:59):
these intangible assets, whichof course include intellectual
property, AI, and other um, youknow, AI models and other like
linked ideas.
SPEAKER_01 (01:20):
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(02:03):
No gimmicks, no funnels, and nononsense.
One winner gets the wholepackage.
The rest of you stay f untilnext year.
Happy holidays from the FewCrew.
I'm your host, Melanie Schaefer.
Welcome to Lead Leg Live.
Now, AI investment is stillaccelerating, but the
(02:24):
conversation is starting toshift.
Governments are debating rulesaround AI accountability and
model oversight, whileeconomists question how quickly
AI actually feeds through toproductivity and growth.
At the same time, marketscontinue to reward a narrow
group of companies most exposedto AI capex and data advantages.
My guest today is Kai Wu,founder and CIO at Sparkline
(02:46):
Capital.
Kai, it's always great to haveyou here.
Yeah, thanks for having me back.
So if we start at sort of thehigh level with AI spending
still rising but scrutinyincreasing, how has your view of
the AI opportunity evolved overthe past year?
SPEAKER_00 (03:01):
Yeah, well, I think it's been an interesting year.
Um, for the first six to ninemonths, I'd say the market was
more or less euphoric about theAI boom.
Whenever a company announced anew AI CapEx um plan, their
stock would go up.
I mean, the the bellwether wouldof course be Oracle, whose stock
(03:23):
went up 30% in a single day onthe back of an announcement that
they'd be building data centerson behalf of OpenAI.
Um since then, the um fate hasthe fortunes have sort of
changed for these names.
Um Oracle is stock is down40-50% since that point in time,
um, you know, basically fullyretracing um it its gains and
(03:45):
its CDS.
So the uh credit default swap,um this the credit spread
between their debt and therisk-free one has blown out.
So investors are starting todevelop concern around the
sustainability of the spendingand um in particular um you know
OpenAI as a uh as a credit forOracle.
(04:05):
Um you also saw the uh therecent news this week about um
Blue Owl pulling out of a bigdata center deal um that that um
Oracle was trying to um puttogether, which is you know kind
of rattled markets as well.
Also, Core Weave, which is youknow perhaps one of the few pure
play data center cloud umcompanies, they IPO'd earlier
this year to great fanfare.
(04:26):
Stock was up significantly,they're down over 50% as well
since this point in time.
Um you you look at the thehyperscalers, right?
Um in the last quarter, theythey announced their earnings,
and some companies like Googleand Amazon did quite well, but
others like Meta actually fell asignificant amount um after they
announced earnings, which Ithink signals that the market is
(04:49):
no longer uniformly um euphoricon AI spending, but it's instead
being more discerning around howthat spending will actually be
uh what will it actuallygenerate in terms of RY for
these companies, right?
So clearly the market andinvestors are happy with what
Google's spending their moneyon, while they don't trust
Zuckerberg as much with regardsto how he plans to spend the you
(05:12):
know tens of billions of dollarsum on AI data centers.
SPEAKER_01 (05:17):
Yeah, Kai, so you mentioned Oracle and Meta and
Google, but we continue to see aheavy concentration in this
small sort of group of AI-linkedmegacaps.
Do you see that concentration asa risk factor overall or a
feature of how AI economics uhjust works?
SPEAKER_00 (05:31):
Yeah, I mean, I think this is a unique time
because you know, even beforethe AI boom, right, um, the
magnificent seven stocks, um, sothat's Meta, Google, Amazon,
Nvidia, Tesla, um, Microsoft,Apple, um comprised 30 to 33% of
the index.
Today they're around 33% of theSP 500 index.
(05:52):
So that means as an investor,one third of your money is in
these names.
And it just so happens to alsobe the case that these
Magnificent Seven stocks arealso, in addition to Oracle, the
companies that are investingmost heavily in the uh AI data
center uh boom.
Right.
So the top four names, umGoogle, Amazon, Microsoft, and
(06:12):
Meta, are collectively spendingum, you know, over you know, uh
$400 billion in data centers,um, which is obviously quite
quite a large um expenditure andwith plans to kind of increase
that um over over time.
So this is a huge bet thatthey're making.
And so, yes, I mean, I think youknow, as an investor in even a
(06:34):
passive index, you should beconcerned about the fact that a
third of your money is um in thehands of these big tech CEOs
that are basically betting thefirm on this um platform shift
to AI.
SPEAKER_01 (06:49):
Yeah, and I mean there's there's another bet
because there's debate aroundwhether AI is delivering real
productivity gains, at leastcurrently.
From the data that you look at,are we seeing measurable
economic impact, or is thatstill sort of ahead of us?
SPEAKER_00 (07:03):
So I think that's the that's the trillion dollar
question.
Um so with all the money that'sgoing into building out these
data centers, obviously, youknow, that's that's fine as a
venture bet, right, um, for now,but at some point investors will
want to see a return on theircapital, a return on investment
in these in these things.
And and the challenge is thatthe end users, right, of these
(07:24):
of these AI data centers, likefor example, Meta and well,
Microsoft, for example, willsay, yeah, you know, we're we're
fully utilized.
Um, in other words, when webuild out these this cloud, um,
we're basically unable tofulfill all the demand that the
end users have with regards toum GPUs and AI um inference.
Now, of course they're gonna saythat for now, but the question
(07:46):
is, is that sustainable?
Like who ultimately is the enduser of the Azure cloud with
regards to um you know AI?
And you know, obviously thebiggest um uh user, the biggest
uh you know demand center isOpenAI itself.
Um, ChatGPT has beentremendously successful in
scaling its business to you knowhundreds of millions of users.
(08:07):
Um we have anthropic and theother AI model platforms, as
well as you know, a few cursorand other companies that could
be considered wrappers aroundthat.
Now, the problem is that thiswhole complex of companies has
revenues on the order of$20 to$40 billion.
Um I think it was uh um one ofthe consultant uh companies that
estimated that in order togenerate a sustainable ROI on
(08:31):
these on um a reasonable ROI onthe data center investments,
revenues for kind of pure AIapplications would have to reach
around um$2 trillion on anannual basis by 20 in five
years.
Right?
So from now to five years fromnow, um we effectively get 100x
the um amount of revenue that weearn um on kind of pure AI
(08:54):
applications.
Right.
And that may be sustainable, butthat's that's the the big
question, which is will weactually be able to do that?
Now we we've seen some, youknow, we've seen both kind of
good and bad um data on theside.
To be honest, it's probablystill too early to tell whether
or not um this will transpire.
Um, you know, ChatGPT, forexample, despite not being three
(09:16):
years into existence and havingyou know scaled its free service
tremendously, only about fivepercentage points or so of uh
their users are actuallymonetizing or actually paying
for their service.
Um and and you know, we alsohear mixed re reports around you
know, is the enterprise actuallyadopting and using AI and
(09:36):
finding it to be valuable um intheir processes?
Now, to be fair, um enterpriseadoption is slow to begin with,
whether AI or or any form oftechnology.
So again, that may be still toosoon to tell.
Um but I think that'll be thebig guess for markets as we you
know turn the page to 2026.
Um, you know, are the you knowFortune 500 companies, these um
uh enterprise customers actuallyfinding value in AI and are they
(10:00):
willing to pay for it?
If the answer is yes, thenperhaps the AI boom is um will
continue.
And if the answer is no, then umyou know we may see pain ahead.
SPEAKER_01 (10:09):
Yeah, and so I want to pivot just a little bit and
talk about uh something that wediscussed last time uh you were
on the show, and that wasintangible assets and how
traditional signals can breakdown.
Has the rise in general andgenerative AI changed how you
think about valuing intangibleslike data and algorithms, et
cetera?
SPEAKER_00 (10:26):
No, I mean I think you know, if you step back, the
the reason why um, you know, Iset up my firm and you know all
the research I conduct is aroundthis idea that you know
traditional value investing,they tend to focus too heavily
on tangible and not enough onintangible assets.
In other words, the traditionalvalue frameworks do not put
enough emphasis on the value ofdata and AI and other
(10:48):
technologies.
Now, the explosion in innovationin this space has, if anything,
only um accelerated a trend andthe value of these sorts of
data.
So, you know, I think I think toyour question, um, what the AI
boom has done is actually kindof f further reinforced my
thesis with regards to, youknow, the the belief that you
(11:10):
know a even greater share ofcorporate value now lies in
these intangible assets, whichof course include intellectual
property, AI, and other um, youknow, AI models and other like
linked ideas.
SPEAKER_01 (11:22):
Yeah, and we've talked a little bit about the
the risk involved, but uh forinvestors who are trying to
position across the AI adoptioncurve, where do you think
expectate expectations are themost stretched, which you've
kind of touched upon, but wheremight the market still be
underestimating change?
SPEAKER_00 (11:37):
Yeah, I mean, I think this is a really, really
interesting question andsomething I thought a lot about.
Um, you know, if you step back,I went back, you know, one of my
early research papers went backto the dot-com boom, and I said,
if you had the a crystal balland you wanted to play the
dot-com boom perfectly, howwould you have done that?
Well, what you would have doneis you in the kind of mid-90s,
you would have invested in thehighest beta um names, the kind
(12:00):
of infrastructure players of thetime.
That includes telecoms, whichare basically the same as the
hyperscalers.
They're investing the money intothe CapEx to build out fiber
optic cables, which areanalogous to data centers today.
You would have invested inCisco, which is basically the
NVIDIA of the day, right?
Selling picks and shovels to thedata center builders or the
fiber optic um, the telecoms,those stocks would have done the
(12:23):
best early on.
But then there would havereached a time period where
these names would have wouldhave gone up so much that their
valuations became stretched,right?
You know, Cisco was trading, youknow, was one of the biggest
stocks in the in the stockmarket and traded at very
elevated multiples by 2000.
So at that point in time, again,with a crystal ball, the correct
(12:43):
thing to have done would havebeen to rotate away into less
overvalued names.
Now, one thing you could havedone would have been to sell
everything and just go into buryyour head into the into
non-internet related stocks,which you know may have worked
tactically, but obviously wouldmean that you're kind of giving
up on the internet revolution ifyou're kind of not benefiting
(13:03):
from the technologicaltailwinds.
So, what you could have doneinstead um would have been to
invest in internet adopters,right?
So what I would these are thecompanies that stood to benefit
from the rise of the internet,yet weren't themselves making
huge capital, risky capitalexpenditures into the fiber
optic build-out, um, nor werethey trading at excessive
(13:25):
dot-com style evaluations, sonot the pets.coms of the day.
So these kind of you think ofthese as kind of the early at
early adopters within like theold economy or you know, more
traditional businesses that arejust implementing a uh internet.
I think that's kind of wherewe're starting to reach today in
the AI cycle as well, where youknow, we've seen a huge amount
of um uh returns from NVIDIA,from the Magnificent 7, you
(13:49):
know, in the past few years, andthese stocks have done some done
very well.
I think now is the time to thatwe to start thinking about how
you know the next cycle mightplay out, right?
The the adopters of AI, which asI mentioned, it was stir early
early.
There have been a few companiesthat have reported earnings,
like CH Robinson is a goodexample, um, that have you know
done done really well, theirstocks have done really well on
the back of you know um allegedAI improvements in their in
(14:13):
their businesses.
I think what we'll likely seeover the next year, and again,
this is the big test, but I doexpect it to be the case, that
we'll see more and morecompanies um you know announcing
and talking about how AI isdriving out performance.
And these companies, while theymay be in kind of stodgier
industries, they will be able tothen use that improvement to
(14:34):
outcompete their even stodgierrivals.
Um so I think these companiestrade at you know basically no
premium to the market.
So you're getting kind of freeAI exposure, so to speak.
And they exist not just intechnology and communications,
they exist in all sectors of theUS, as well as internationally,
right?
In Germany and France and Japan,uh countries where you know
(14:55):
maybe their valuations aren't ashigh.
So you get more diversification,you get less capital um
intensity, um, you get less umyou know overvaluation while
still maintaining positiveexposure to AI.
And so you mentioned you askedthe question about what my
signals are telling me.
Um, that's what the signals aretelling me.
So I'm not just like telling youthis is, I think, where we are.
I mean, that's bottoms up, um,just looking at what the models
(15:16):
are doing, is what the mod whatthe models are basically having
us rotate out of the Magnificent7.
So at one point we wereoverweight Magnificent 7.
We were no longer overweight.
We our top position is Google,um, but only have a couple names
in that category.
Most of the weight's nowstarting to shift away into the
kind of adopters away from theinfrastructure plays.
Um, and so that's kind of wherewe think that one should
(15:40):
consider positioning um, youknow, for the next year.
SPEAKER_01 (15:43):
And so you mentioned that you don't have a crystal
ball, but for uh investors andadvisors who want to learn more
about all the research that youdo and uh see more of your
thoughts on AI, where shouldthey go?
Where is the best place tocontact you?
SPEAKER_00 (15:55):
Yeah, um if you want to look at the research I write,
you can just go tosparklandcapital.com.
Um, and I have all my mypublications posted there.
There are probably 24 or so morethan that now on papers.
Um, and then in terms ofcontacting me, you can email me.
My email is you know on thewebsite, or you can contact me
either the form, or I'm also onTwitter and LinkedIn with a
(16:16):
handle CKI W U.
SPEAKER_01 (16:19):
Also, Wilkai, thanks for joining me again, and thanks
to everyone for watching.
Be sure to like, share, andsubscribe for more episodes of
Lead Leg Live.
Always a pleasure, thank you.
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