In the race to dominate generative AI, big tech firms
haven't just been building, they've been buying.
But there's something strange about most of the deals that
they've struck. Companies like Meta, Microsoft,
Amazon, Google and NVIDIA are embedding themselves deep within
the AI ecosystem through strategic investments, exclusive
partnerships, and talent acquisitions with deals that
stop just short of formal takeovers.
But the economic impact of these deals, it turns out, is
indistinguishable from full control.
This new approach, which some analysts are describing as non
acquisition acquisitions, is designed to work around
antitrust law. The idea is to avoid drawing
regulatory scrutiny with deals that allow tech giants to secure
privileged access to foundational by models, critical
data pipelines, and elite research talent.
Despite all the talk of slashing regulation, and despite the
support that Trump has drawn from Silicon Valley so far, the
new administration is showing a surprising degree of continuity
with the Biden era approach to antitrust enforcement,
particularly when it comes to Big Tech and AI related deals.
According to the law firm Goodwin Proctor, US enforcers
are still willing to challenge deals they view as anti
competitive under traditional horizontal theories of harm,
particularly mergers between direct competitors with leading
market positions. So far, there's been no sign of
reduced FTC enforcement. The tactics used by today's tech
giants to quietly consolidate power in the AI sector are not
without precedent. More than a century ago, John D
Rockefeller pioneered similar strategies during the rise of
Standard Oil, where he often acquired companies without
formal legal documentation, using silent partnerships,
verbal agreements, and trusted intermediaries to quietly absorb
competitors. According to his biographer,
Standard Oil executives worried that this secrecy could cause
problems for the firm, as if a seller died unexpectedly, his
heirs might mistakenly claim ownership of a refinery that
Standard Oil had bought and paid for.
To further obscure control of the businesses he had purchased,
Rockefeller created the Standard Oil Trust in 1882, a legal
innovation that allowed him to centralized authority over
dozens of companies without technically owning them
outright. These tactics eventually led to
the 1911 Supreme Court decision that broke up Standard Oil under
the Sherman Antitrust Act. Today, Big Tech's use of non
acquisition acquisitions, exclusive infrastructure deals
and strategic talent consolidation echoes
Rockefeller's playbook. Meadows recently announced $14.8
billion investment in Scale AI, which involved hiring.
The data labeling startup CEO will test how the Trump
administration views Aqua hire deals, where a company buys a
startup as a means of hiring its most important staff, which many
have criticized as an attempt to evade regulatory scrutiny.
Meta executed a $14.3 billion investment in Scale AIA leading
data labeling firm, earlier this month.
On paper, Meta bought a 49% non voting stake in Scale, but in
practice they gained exclusive access to scale's Human in the
Loop data pipeline. The migration of Scale founder
Alexander Wang and key staff to Meta's new superintelligence
unit, and a web of contractual agreements that effectively
embedded Scales capabilities within Meta's AI infrastructure.
The structure of this deal meant that Meta could avoid the
formalities of a merger while achieving many of its strategic
benefits. In an excellent sub stack
article, which I'll link to in the description, Drayton de
Silva described the deal as being like the way medieval
Masons would move entire cathedrals from one side to
another, brick by brick, by numbering each brick,
transporting it to a new site, and then rebuilding the entire
cathedral exactly as before. The reconstructed cathedral, he
says, is in a new location, but in a spiritual and metaphysical
sense, He argues, it's the same cathedral scale.
AI, which was once an independent supplier to the
entire AI ecosystem, once this deal is done, now functions as a
de facto internal division of Mehta.
De Silva argues that there are multiple elements in the deal
structure that make it vulnerable to FTC scrutiny.
From an antitrust perspective, the deal raises red flags across
multiple dimensions. De facto control input
foreclosure, talent consolidation, coordination
risk, and dominance entrenchment.
Even if regulators ultimately blocked the deal, Mehta may have
already achieved A strategic victory by disrupting rival
operations and gaining insight into scales operations.
In a funny piece about Mark Zuckerberg's new bro look in the
FT, Hannah Murphy argues that Facebook feels desperately dated
today. Instagram has been losing ground
to TikTok for quite some time, and the metaverse, after which
Mark Zuckerberg renamed the entire company, is a ghost town,
but without even ghosts. The FTC is already pursuing an
antitrust case against the firm, saying that it's acquisitions of
Instagram and WhatsApp were anti competitive and aimed at
monopolizing the social media market.
The case is currently in trial, with arguments focused on
whether Meta's acquisitions were part of a broader strategy to
eliminate competition and maintain its dominance.
Meta has struggled from the very beginning to innovate internally
and has mostly had to rely on acquisitions for growth.
If Meta loses this antitrust case, the company could be
forced to sell off Instagram and WhatsApp.
They would most likely still be allowed to hold on to the
metaverse. And those creepy AI glasses that
Zuckerberg wears with the built in cameras just because nobody
else actually uses them? Meta has been very aggressive in
its attempts to grow in generative AI.
And the new investments that Meta and almost all of the other
big tech firms have been making in AI startups are not just
financial investments. They're strategic and designed
to secure early access to cutting edge models, proprietary
data, and elite research talent. These deals, it could be argued,
are driven by a belief amongst Big Tech CE OS that the next
wave of AI breakthroughs will be shaped not just by algorithms,
but by control over the infrastructure and inputs that
power them. Data labeling pipelines, cloud
compute access, and model training workflows have become
the new battlegrounds. Microsoft's relationship with
Open AI is a master class in contractual leverage, but the
deal still has its flaws. Since 2019, Microsoft has
invested over $13 billion into Open A is for profit subsidiary,
securing exclusive commercial rights to its models and
integrating them deeply into its Azure cloud platform and
enterprise software products. Yet despite the scale of this
investment, Microsoft holds no formal equity stake in Open AIS
nonprofit parent and no voting control over its board.
This structure was carefully designed to avoid the appearance
of a merger. Microsoft didn't report the
transaction to the FTC at the time because the investment
didn't amount to control of the company.
Under U.S. law, Open AI remains an independent entity, at least
on paper. But in practice, Microsoft has a
level of influence that rivals are exceeds that of a majority
shareholder. The FTC is now investigating
whether this partnership constitutes a de facto
acquisition. A year and a half ago, when Open
A IS board of directors ousted Sam Altman over concerns about
AI safety, Microsoft received just minutes notice of what was
going on and its executives were not consulted in the decision.
At the time, Microsoft offered Altman and the core research
team roles within Microsoft, which would have likely drawn
regulatory scrutiny. The bizarre structure of Open
AI, which includes A nonprofit entity and a capped profit
subsidiary, has caused all sorts of conflicts.
Now that the company is trying to convert into a for profit
company, the FT reports that Microsoft has considered halting
discussions if the two sides can't agree on critical issues
like the size of Microsoft's future stake in Open AI.
If Microsoft was to walk away from these discussions, it could
still rely on the existing commercial contract to retain
access to Open AI's technology until 2030.
The Wall Street Journal recently reported that Open AI executives
have discussed leveling antitrust accusations against
Microsoft as a last ditch option for loosening the firm's control
under their deal. So while Microsoft's deal may
have been structured to avoid FTC scrutiny, the fact that they
don't have full control is still causing them plenty of problems.
Amazon and Google have each invested billions of dollars in
Anthropic, the AI startup behind the Claude family of models.
In return, Claude is hosted on AWS and Google Cloud, raising
concerns about cloud dependency and preferential access.
NVIDIA, meanwhile, has taken equity stakes in dozens of AI
startups, bundling those investments with early access to
hardware developer support and Co marketing opportunities.
In one of the stranger deals, NVIDIA invested in Core Weave, a
business that buys and rents out access to NVIDIA graphics
processing units for training artificial intelligence models.
Nvidia's investment strategy creates a self reinforcing loop.
It funds the companies most likely to buy its products and
in doing so, ensures continued demand for its hardware.
This dual role raises questions about conflicts of interest and
fair market practices. Preferential treatment can
distort competition, not because NVIDIA is denying access
outright to certain competitors, but because it's subtly shaping
the playing field through capital and supply chain
influence. The term Aqua hire is used in
finance to describe the acquisition of a company
primarily to hire its employees rather than for the operating
business. It's a strategy used by larger
companies to quickly acquire specific talent, particularly in
industries where skill teams can be hard to find through
traditional recruitment. The Information reported last
week that Meta is in advance talks to hire the prominent AI
investor, not Friedman and Daniel Gross, to help lead it's
AI efforts, and that as part of those talks, Meta might
partially buy out Friedman and Gross's venture capital fund,
which holds stakes in top AI startups and is worth billions
of dollars on paper. If the talks are successful,
Gross would leave Safe Super Intelligence, which he Co
founded with the former Open AI chief scientist last year, and
work mostly on AI products at Meta.
As part of the deal, Meta could end up owning minority stakes in
the start-ups that the venture capital firm has invested in,
but allegedly won't get information about and control
over these start-ups, according to the article.
Drayton da Silva's Sub Stack article shows how Meta broke its
non acquisition of Scale AI into 4 main parts, each of which
could raise red flags under US antitrust law.
Meta bought 49% of Scale's shares, but with no voting
rights, they got exclusive access to Scale's data labeling
pipeline, a key resource for training AI models.
They hired Scale's CEO and key staff, meaning that competitors
could no longer access them, and they kept Scale CEO on Scales
board while he leads Metas AI Lab.
Each of these moves on its own might seem harmless, but
together they give Meta almost complete control without calling
the deal a merger. Drayton points out the
traditional antitrust enforcement was built around
clear ownership and control, but in the world of technology,
influence can be exerted through contracts, infrastructure and
informal arrangements. The FTC and the Department of
Justice have recently started to adopt A substance over form
approach, focusing on the economic reality of deals rather
than their legal structure. The FTC has published 11 merger
guidelines, and Drayton focuses on Guidelines 3456 and 11 in his
piece, which are most relevant to this structured deal.
Guideline 11 is about how minority stakes can still give
control, and under this deal, Meta owns 49% of scale and might
be able to influence decisions with that leverage.
Guideline 5 is about how blocking rivals from access to
key resources is bad, and under this deal Meta gets exclusive
access to scales data. Guideline 4 is about how hiring
away key people can kill competition, and in this deal
Meta is hiring away scale CEO and other top talent.
Guideline 3 is about how shared board members can lead to
collusion, and in this deal scale CEO is on both sides.
Guideline 6 is about how deals that make a dominant firm even
stronger are risky, and Meta weakens its AI rivals by
disrupting their access to scale.
Drayton argues that even if the FTC or the courts blocked the
deal, Zuckerberg already has a win.
Open AIXAI. Google and Microsoft have
already scaled back or paused their work with Scale AI, citing
data privacy risks and conflict of interest issues.
Anthropic has not yet announced anything publicly, but it also
works with scale. Together, these five labs plan
to spend over $250 billion on AI related CapEx in 2025.
Meta has already induced months long delays and disruptions to
their critical workflows, likely costing them billions.
Drayton estimates that setting up and announcing this deal cost
Meta approximately $40 million across external advisors and
internal resources over six months, which is a very
effective asymmetric attack on their rivals.
He finishes up his piece with an amusing playbook for non
acquisitions for Tech CE OS Hoping to avoid regulatory
scrutiny. I'll leave a link to a sub stack
in the video description. It's worth checking out the
deals being struck by Meta. Microsoft's Open AI partnership
and Nvidia's customer investment loop all challenge regulators to
look beyond formal mergers in assessing competition within an
industry. While the deals that are being
struck might not trigger traditional review thresholds,
their cumulative effect can without a doubt be expected to
reshape competition within an industry.
Big Tech CE OS don't seem to just expect AI to be a
technological shift, but a structural shift too.
They believe that as foundational models become the
engines of the next digital economy, the companies that
control their development, deployment and distribution
could end up wielding extraordinary influence.
Unlike past industrial consolidations, this one is
being shaped less through traditional mergers and more
through strategic entanglements. While regulators may not have
noticed this in the past, the sheer volume of these deals has
brought this issue to their attention.
At present, it would appear that there is plenty of competition
in the AI space. There are a number of
competitors and they're all racing to develop better and
better models. Some of the huge investment in
the space has quite likely been driven by a belief that AI will
have winner take all economics like Internet search did, where
Google built the best search engine many years ago and then
dominated that sector for the next few decades.
Since the DeepSeek breakthrough earlier this year, there's been
growing concern amongst investors that while it might be
extremely expensive to achieve AI breakthroughs, the new models
once built might be quite easy to replicate.
Meaning that there may not be a dominant AI company in the near
future and that the industry could instead remain extremely
competitive with very little pricing power.
Meta, Microsoft, Amazon, Google and NVIDIA are without a doubt
trying to build moats around AI1 contract at a time, but
regulators do appear to already be on to what's going on and
could shut these deals down if they appear to be harming
competition in the industry. We've all seen the sudden
transformation of Mark Zuckerberg from the left-leaning
tech nerd who wrote an open letter to his child about his
goal of building inclusive and welcoming communities while
pouring millions into social justice causes into the gold
chain wearing MMA bro who told Joe Rogan that corporate America
had been culturally neutered and workplaces needed more masculine
energy. This all happened right around
the time of Trump's election victory, and this metamorphosis
could be explained as much by Zuckerberg's need to align
himself with the new administration as an actual
change. In his beliefs, should any of
these deals be deemed anti competitive, being aligned with
the current administration, along with the purchase of the
correct meme coins could solve a lot of Mark Zuckerberg's
problems. As an example, the US Supreme
Court unanimously upheld a federal law requiring TikTok to
either be sold by its Chinese parent company or be banned in
the United States more than six months ago.
But enforcement and has been repeatedly delayed by executive
orders from the US president, who even invited its CEO to his
inauguration. It's not obvious that any of the
big tech firms have anything like a monopoly on AI.
At present, it appears to be an extremely competitive space.
While the technology is driving massive investment and strategic
growth, profitability remains elusive for most AI companies
other than NVIDIA. According to the Wall Street
Journal, Microsoft loses around $20 per user per month on GitHub
Copilot. The expectation for these
companies, whose core businesses are very profitable, appears to
be that long term gains will come as AI becomes more
efficient, cheaper to run, and more deeply integrated into
enterprise workflows. At present they have a lot of
money and are spending some of it on generative AI to make sure
that they are still competitive in the future.
They're also spending this money as a moon shot investment where
maybe they'll develop a dominant product which will matter as
much to the future Internet as search did to the Internet 25
years ago. The Economist made a very good
argument in a recent article that the FTC case calling for
the breakup of Mehta is without merit.
They say that the FTC's argument against Mehta wasn't compelling
when it was launched in 2020, and in the years since the
complaint was filed, it's only become less persuasive. the FT
CS claim in the case is that network effects create
insurmountable barriers to entry.
But The Economist points out that the last few years have
seen a rush of new successful social media start-ups.
Some have fizzled, like Clubhouse and Be Real.
Others remain small, like Blue Sky and Truth Social.
But the arrival of TikTok made a mockery of the idea that the
market was closed to new entrants.
They point out that partially because of TikTok, social media
apps now revolve around short form video, which has put metas,
Instagram and Facebook in competition with YouTube, Shorts
and Twitter, who are all pursuing the same short form
video audience that TikTok drew in.
They highlight that Spotify, which was originally a music
service, is pushing into video too.
Roblox, a gaming platform, acts as a social network for many
teenagers. They say that as competition
spreads across previously separate categories, the FT CS
narrow market definition looks ever sillier.
There's no doubt that all of these AI deals are being
specifically designed to work around the FTC rulebook.
And it does appear that some of the deals are anti competitive
in nature in that they're being done to block access to key AI
services, slowing down competitors.
But this scramble to invest and build better and better models
while keeping prices low doesn't appear to be harming consumers
and reflects how competitive the space is at present.
While these deals are worth keeping an eye on, it's not
obvious to me that they'll be stopped anytime soon.
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