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Meta’s $14.8 Billion Scale AI Deal Raises Regulatory Questions Amid AI Partnership Scrutiny

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Meta’s $14.8 billion investment in data-labeling startup Scale AI, along with hiring its CEO, poses a test of the Trump administration’s stance on so-called “acquihire” deals—arrangements that some critics argue are used to bypass antitrust scrutiny.

The deal, announced Thursday, gives Meta a 49% nonvoting stake in Scale AI, which employs gig workers to manually label data and serves major clients including Meta’s rivals Microsoft and OpenAI. Because Meta does not gain a controlling stake, the transaction avoids mandatory U.S. antitrust review. Still, regulators could investigate if they suspect the deal was structured to sidestep rules or harm competition.

The structure aims to prevent Meta from cutting off competitors’ access to Scale’s services or gaining undue insight into rival operations. Despite this, Reuters reported that Alphabet’s Google has decided to sever ties with Scale following Meta’s investment, while other customers are reconsidering their relationships.

Scale AI stated its business remains strong and that it is committed to protecting customer data. Scale’s 28-year-old CEO Alexandr Wang will join Meta as part of the deal but will remain on Scale’s board with restricted access to sensitive information.

Experts say that while the Trump administration’s antitrust enforcers are cautious of big tech platforms, they generally want to avoid overregulating AI development. William Kovacic, competition law expert at George Washington University, noted regulators will watch these partnerships closely but might not intervene if they do not stifle competition.

Previous FTC inquiries into “acquihire” deals under the Biden administration—including Amazon’s hiring from AI startup Adept and Microsoft’s $650 million deal with Inflection AI—have so far resulted in no enforcement action.

Boston College Law professor David Olson highlighted Meta’s choice of a minority, nonvoting stake as a legal shield, though he acknowledged the FTC could still seek to review the deal.

The investment has drawn criticism from U.S. Senator Elizabeth Warren, who called for scrutiny to ensure Meta does not unlawfully suppress competition or increase monopoly power. Meta is already facing an FTC monopoly lawsuit, but whether regulators will challenge this specific investment remains unclear.

Separately, the U.S. Department of Justice’s antitrust division is probing whether Google’s partnership with chatbot maker Character.AI was structured to evade regulatory review and is seeking advance notice of Google’s AI investments as part of broader efforts to rein in the company’s dominance.

Unglamorous World of Data Infrastructure Drives Surge in AI-Focused Tech M&A

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Despite a slowdown in global dealmaking due to tariffs and geopolitical uncertainty, the data infrastructure sector is booming as legacy tech giants scramble to secure their positions in the AI race. Companies that handle the vast volumes of data required to train advanced AI models have become key acquisition targets for firms like Meta, Salesforce, and ServiceNow, eager to compete with leaders such as OpenAI, Google, and Anthropic.

“AI without data is like life without oxygen, it doesn’t exist,” said Brian Marshall, global co-head of software investment banking at Citi, highlighting how data management has taken center stage in the tech industry’s current moment.

Technology deals have been one of the few bright spots in a subdued M&A market, accounting for $421 billion out of the $1.67 trillion in global deals announced in the first five months of 2025—roughly 25% of total M&A volume. This marks a steady rise from 20% in 2024 and 17% in 2023. Notably, nearly 75% of the value of tech deals involves AI software makers.

Goldman Sachs Managing Director Matthew Lucas described enterprise data as the “most dynamic area in software M&A right now,” emphasizing that speed and being first to market are critical, driving companies to acquire rather than build their own capabilities.

Investment bankers identify companies like Confluent, Collibra, Sigma Computing, Matillion, Dataiku, Fivetran, Boomi, and Qlik as likely acquisition targets. These firms specialize in integrating, analyzing, and managing data on cloud platforms—capabilities essential for effective AI deployment.

Executives from Boomi, Dataiku, Fivetran, and Qlik expressed no surprise at the increased attention. Dataiku CEO Florian Douetteau noted that “messy, siloed data” has long limited analytics potential, but the urgency of AI has made resolving these issues existential for businesses.

Recent multibillion-dollar acquisitions illustrate this trend. Meta’s $14.8 billion deal for a 49% stake in data-labeling company Scale AI, Salesforce’s $8 billion plan to buy data integration firm Informatica, and ServiceNow’s acquisition of data catalog platform Data.world exemplify how legacy tech companies are investing heavily to own the data pipeline critical for AI.

Globally, generative AI spending is forecast to hit $644 billion in 2025, a 76.4% increase from 2024, underscoring the scale and pace of AI investment.

IBM also recently closed its acquisition of data management company DataStax, aiming to improve handling of unstructured data for its AI platform.

However, dealmakers caution that acquiring data infrastructure alone does not guarantee AI success. Proper organization and filtering of data are essential to avoid errors, as seen when Air Canada faced legal issues over bad AI chatbot advice due to poor data input.

“A lot of companies have a huge amount of data, but they’re learning that you can’t just funnel every piece of data you have into an AI engine without organization and expect correct results,” said Brian Mangino, partner at Latham & Watkins.

The rapid pace of acquisitions and the high stakes in AI competition highlight how data infrastructure—though less glamorous than AI algorithms themselves—is becoming the backbone of future tech innovation.

Meta Poaches 28-Year-Old Scale AI CEO in $14.3 Billion Stake Deal

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Meta, the parent company of Facebook, has taken a 49% stake in the data-labeling startup Scale AI for $14.3 billion, valuing the company at $29 billion. As part of the deal, Scale’s 28-year-old CEO Alexandr Wang will join Meta to lead its new superintelligence efforts, marking a major move in Meta’s artificial intelligence strategy.

Meta confirmed plans to deepen collaboration on data production for AI models, but did not disclose financial details publicly. Sources close to the discussions said the primary motivation behind the multibillion-dollar investment was securing Wang’s leadership for Meta’s superintelligence unit.

Wang, a Los Alamos, New Mexico native born to Chinese immigrant physicists, dropped out of MIT to co-found Scale AI. He quickly gained acclaim as one of Silicon Valley’s most promising entrepreneurs, achieving billionaire status in his twenties. His influence extends into Washington D.C., where he has testified before Congress and helped secure government contracts for Scale.

Meta’s AI efforts have faced challenges recently, including staff departures and delays in launching open-source AI models that could compete with Google, OpenAI, and China’s DeepSeek. By recruiting Wang—a business-focused leader rather than a research scientist—Meta CEO Mark Zuckerberg is betting on a new approach to revitalize its AI ambitions.

Scale’s chief strategy officer, Jason Droege, will serve as interim CEO following Wang’s transition. Despite the large investment, Meta does not plan to take a board seat at Scale. A select group of Scale employees will also join Wang at Meta, while Wang will retain his seat on Scale’s board.

The $14.3 billion investment ranks as Meta’s second-largest acquisition after its $19 billion WhatsApp buyout. It remains uncertain whether the deal will face regulatory review amid ongoing antitrust scrutiny faced by Meta, which has been sued by the U.S. Federal Trade Commission for allegedly stifling competition via acquisitions like Instagram and WhatsApp.

Founded in 2016, Scale AI plays a pivotal role in providing accurately labeled data essential for training advanced AI models such as OpenAI’s ChatGPT. The company uses platforms like Remotasks and Outlier to manage gig workers who manually label data. Scale was valued at nearly $14 billion in a May 2024 funding round backed by Nvidia, Amazon, and Meta.

While the deal represents a windfall for early investors like Accel and Index Ventures—who can now sell half their stake—it may raise concerns among Scale’s AI lab clients, who might fear Meta gaining insight into competitors’ data priorities through Wang’s ongoing board membership.