<div id="readability-page-1"><div><p>Nearly a year ago, when Alexandr Wang left Scale AI, the company he founded, it was widely believed that the startup had essentially reached its end. But now, under the leadership of new CEO Jason Droege, Scale AI's revenue has rebounded and is expected to surpass $1 billion this year. Last June, Alexandr Wang slowly walked down the stairs of Scale AI's San Francisco headquarters in the open atrium. Employees were unsure whether he was still the head of the company. Just the day before, this data labeling giant announced a major deal: Meta would acquire a 49% stake in Scale AI for $14 billion, and founder and CEO Wang would be leaving to lead Mark Zuckerberg's newly established SuperAI Lab. The news caused chaos within the company, with many employees believing he had already resigned. Therefore, when Wang appeared, everyone was surprised and applauded, welcoming him to the all-hands meeting. In a recent Forbes interview, Wang confessed: &#34;I burst into tears on the spot. In another parallel universe, I would be more than willing to stay at Scale AI.&#34; He couldn't recall exactly what he said at the meeting, but an attendee revealed that Wang began by reminiscing about his experience founding Scale AI during his freshman year at MIT, before breaking down in tears. This person recalled, “Wang” muttered to himself at the time, “How silly of me, what am I doing?” This exclamation, though directed at his own tears, accurately captured the widespread confusion outside. This major deal, which had been leaked a few days prior, has raised the same question throughout Silicon Valley: At the time, Scale AI was valued at $13.8 billion and was experiencing rapid growth. Why would its founder abandon his own company and join Meta? It's worth noting that in the field of artificial intelligence, Meta has been striving to catch up with Google, OpenAI, and Anthropic. Scale AI was originally a leading company in the field of manually labeled data, bringing together a massive number of crowdsourced labelers and professionals such as PhDs, lawyers, and engineers to provide training data for top AI models such as Google's Gemini and OpenAI's ChatGPT. Since first delivering its large language model technology to the Pentagon in 2020, Scale AI has become a key service provider for the U.S. Department of Defense. This company also once propelled Wang to the top of the list of the world's youngest self-made billionaires. Scale AI's ties to Meta once seemed poised to jeopardize its stable business of providing infrastructure services to leading AI companies. The industry consensus was: which cutting-edge lab would be willing to entrust its core data to a company nearly half-owned by Meta? Wang took about ten core employees from Scale AI to join Meta, and now he believes this collaboration is a &#34;rare opportunity&#34; for both companies. In the latter half of the all-hands meeting, Wang formally introduced his successor, Jason DeRog. DeRog, formerly Chief Strategy Officer of Scale AI, previously worked at Uber and also for Axon, the manufacturer of Taser stun guns. Despite the turmoil of the previous week, the all-hands meeting was concise, lasting only 30 minutes with no Q&amp;A session. Wang and DeRog maintained a succinct tone throughout. DeRog recalled: &#34;We shook hands, hugged, all full of anticipation for the future, and then went our separate ways.&#34; Currently, DeRog still holds the title of interim CEO, but he is tacitly considered the long-term leader within the company. It has been almost a year since the deal was officially announced, and Scale AI has been around for ten years since its founding in May 2016. Unsurprisingly, the company now presents a very different image. Drogue's first move after taking office was to adjust the company's investment direction: no longer relying solely on traditional data labeling business, but instead helping large enterprises such as Ernst &amp; Young, Paramount, and Cisco, as well as public sector clients such as the US military, build dedicated internal AI applications. This strategy appears to be beginning to show results. Scale AI told Forbes that its revenue has increased from $870 million two years ago to nearly $1 billion last year. Since its inception, the company has accumulated total revenue of $2.5 billion. Much of this revenue growth is attributed to its new shareholder, Meta. According to a Forbes report at the time, as part of the cooperation agreement, Meta was to pay Scale AI at least $450 million annually for the next five years, or half a year's worth of AI expenses (whichever is lower). Wang and Drogue declined to comment, but this fee represented almost half of Scale AI's annual revenue. Drogue also did not disclose the revenue breakdown between data services and AI application services. He stated that data annotation is currently the company's main source of revenue, but he expects application service revenue to surpass traditional data service revenue within the next 18 months. Wang, who has already joined Meta, remains deeply committed to the company he founded. He stated: &#34;Some people think that Scale AI has declined and reached its end, but this is completely untrue.&#34; He believes that the resilience shown by Scale AI has completely overturned the market's stereotypical perception. Wang's parents worked at Los Alamos National Laboratory, the birthplace of the atomic bomb. Ten years ago, Wang and co-founder Lucy Guo co-founded Scale AI. Lucy Guo dropped out of Carnegie Mellon University after being selected for Peter Thiel's Thiel Fellowship program, which encourages young people to drop out of school to start businesses. Both had worked at the question-and-answer platform Quora, where they met. Before settling on AI infrastructure, they had considered several entrepreneurial directions. Last year, Guo revealed on entrepreneur Emma Grede's podcast, &#34;Aspire,&#34; that the two later disagreed on the company's future direction. The catalyst for the full-blown conflict was that Guo had confided to someone that she believed Wang &#34;should be fired.&#34; She speculated in the podcast that this person later told Wang these words. “I was very bothered by the person who relayed the message, because I thought there was a basic level of trust between us. I felt betrayed at the time.” Leaving the company and joining Meta. Image source: ETHAN PINES FOR FORBES. Ultimately, Lucy Guo chose to leave the company. When asked about this past experience, Wang smiled slightly awkwardly: &#34;We rarely talk about it. At Y Combinator, people don't tell you how common it is for founders to part ways. But we eventually resolved our differences, and I'm genuinely proud of everyone on the team. Even after such a change, the company continued to steadily move towards success.&#34; Seven years later, it was Wang's turn to leave the company he had founded. He first received an invitation from Zuckerberg last spring, when the Meta flagship model, Llama 4, underperformed, and Zuckerberg began looking for a new AI leader. The two had first met years ago when Wang sought advice from Zuckerberg on running a startup. When asked how Zuckerberg extended the invitation, Wang casually replied: &#34;I don't understand what's so incomprehensible about it. It's simply that Meta has excellent development opportunities in the field of AI, and its prospects are extremely attractive. So we hit it off immediately and explored the possibility of cooperation.&#34; He added that Zuckerberg's own belief in the cause of AI is &#34;very clear and firm.&#34; Subsequently, Wang sought the company's board of directors' opinion to weigh the pros and cons. Investor Mike Volpi stated: &#34;These kinds of blockbuster deals are often only finalized when the pros and cons are roughly balanced.&#34; Volpi became an early investor in Scale AI during his time as a partner at Index Ventures. His discussions with Wang went far beyond the details of the deal itself: &#34;What we discussed more was not the specific process of the transaction, but what Alex ultimately wanted to achieve in his life.&#34; Last June, the $14 billion deal was officially announced, reaping huge profits for both investors and employees. According to sources, the vast majority of employees received dividends equivalent to about half the value of their equity. It's understandable that some employees felt frustrated by Wang's departure. When asked if he felt guilty about leaving the company, Wang said: &#34;Everyone had a lot of emotions when it happened, and I completely understand that. But I always believed that the team was capable of achieving extraordinary results.&#34; The company subsequently initiated layoffs. Two months after the official announcement of the deal, in August, Scale AI announced the layoff of 200 full-time employees, approximately 14% of its total workforce, and the termination of its cooperation with 500 contract workers (these were contract employees, not the same group as data labeling staff on a per-order basis). A Scale AI spokesperson stated that the company currently has approximately 1,300 full-time employees and plans to recruit another 500 by the end of this year. Even before officially signing with Meta, Scale AI had already anticipated that this deal would affect its collaborative relationship with the cutting-edge AI lab. DeRogge stated: &#34;We anticipated this turmoil, without a doubt. After all, the facts are clear: the company founder jumped ship to another AI lab, working for a client's competitor.&#34; He added: &#34;Most long-term clients eventually chose to return to the partnership, but not all.&#34; To allay clients' concerns that Scale AI would be subject to Meta, DeRogge launched a charm offensive, reassuring partners. Some clients wanted to visit the company's offices to communicate face-to-face with management and R&amp;D personnel, while others requested a detailed clarification of the terms of the transaction. DeRog emphasized to clients that Meta would not receive a seat on the company's board of directors; and while Wang would retain his position as a director of Scale AI, neither he nor any other director would have any prior knowledge of the details of Scale AI's collaborations with its clients. Drogue now states: &#34;I am also a shareholder of Scale AI, and my motivation is to provide the best experience for non-Meta clients. I am not a Meta employee.&#34; According to two people familiar with the partnership, the most prominent client lost was OpenAI. Losing this company is a huge blow, not only because of OpenAI's pivotal position in the industry, but also because it was one of the leading labs that first introduced Scale AI into generative AI. Even before ChatGPT ignited the global AI boom in 2022, OpenAI had already invited it to assist in training GPT-3. According to sources familiar with the matter, Google temporarily suspended its data annotation collaboration with Scale AI after news of its investment in Meta broke, but resumed business dealings several months later. Of course, there is one customer it doesn't need to worry about losing: Meta. Scale AI played a crucial role in the training of Muse Spark, the first model it spearheaded after Wang took office. This model was officially released in April. Market reviews were mixed, but overall positive, and it was seen as a comeback success in the Meta competition. Speaking about the new model, Wang said: &#34;This is the result of painstaking effort. Scale AI is a crucial partner. The success of Muse Spark is inseparable from the joint efforts of all partners, and Scale AI is definitely a vital part of it.&#34; Beyond that, Wang declined to elaborate further on his work at Meta. Following the equity investment deal, Scale AI attempted to reshape its business. Drogue explained that before the partnership, 70% of the company's business was data labeling, and 30% was building AI applications for enterprises and governments. The company has now shifted its business focus, and by the end of last year, its annualized revenue from enterprise AI applications had reached $200 million. The company has also added many large enterprise clients, including the Mayo Clinic, BP, and Allianz. For example, Scale AI collaborated with the Mayo Clinic to develop a system capable of reading and parsing fragmented medical records. Tony Qui, Chief Technology Officer of EY's Strategic Consulting Group, stated that EY is leveraging Scale AI to build internal AI agents, one of which assists EY in conducting due diligence for M&amp;A clients. Qui said that EY initially chose Scale AI based on a recommendation from OpenAI. A few weeks later, when news of Meta's investment emerged, the company had reservations, but after meetings with Drogue and other management members, they ultimately decided to continue the collaboration. Scale AI claims that its unique competitive advantage lies in simultaneously serving both enterprise services and data annotation. The company has a long history of training large models for cutting-edge AI labs, possessing a deep understanding of industry technology trends—technologies that major enterprises are eager to deploy. Lucas Swisher, a partner at investment firm Coatue (who led the Series B funding round for Scale AI), commented: &#34;Only Scale AI can truly provide both types of services simultaneously.&#34; Furthermore, it has increased its involvement in US government operations, continuing the development path taken during Wang's tenure. In early May, the US Department of Defense awarded Scale AI a $500 million contract to lead the Thunderforge project, which aims to integrate AI agents into military mission planning. In April, Scale AI, along with Palantir and Anduril, was selected as a contractor for the U.S. Golden Dome defense program. This is a $185 billion missile defense system project under the Trump administration, but both Scale AI and the U.S. Department of Defense declined to disclose details of the company's role in the project. Cameron Stanley, Chief Digital and Artificial Intelligence Officer at the U.S. Department of Defense, stated that Scale AI has demonstrated particularly outstanding performance in data annotation during its service to the Department of Defense; [The text also mentions early involvement in...] When introducing machine learning into military intelligence workflows using Maven, Scale AI's performance in computer vision was remarkable. He praised Scale AI's metadata organization as &#34;top-notch in the industry.&#34; Scale AI's unique advantage lies in its ability to help the Pentagon integrate various fragmented datasets and understand how to align with Department of Defense administrative processes, thereby facilitating the smooth implementation of projects. Stanley told Forbes, &#34;Their ability to aggregate massive amounts of heterogeneous data, understand its logic, and organize it into a structure that can be used to train algorithms is extremely rare.&#34; He declined to reveal whether Scale AI's technology has been deployed in actual combat, and a Scale AI spokesperson did not disclose specific details of the military cooperation. Drogue emphasized that the company's reduction of the weight given to data annotation business was not due to clients' concerns about Meta's equity participation causing Scale AI to reach a business ceiling, but rather because the growth rate of the entire data annotation industry itself had slowed down. Conversely, in the enterprise AI application field, with major giants transforming towards artificial intelligence, the market space is extremely vast. Regardless of the reasons, competitors in the same industry, such as Surge, Mercor, Handshake, and Invisible, have seized the opportunity to grab market share and openly promote themselves to secure contracts. Legal documents show that last year, Mercor poached a former Scale AI employee, who is suspected of stealing strategic trade secrets from the company's clients. The two parties reached a settlement in January of this year. The settlement amount was not disclosed to the public, and there had been no prior media coverage of the matter. The CEO of a competitor company privately admitted that since reaching a deal with Meta, Scale AI has gradually faded from view in large-scale contract bidding in the data annotation field: &#34;In recent months, we've basically heard nothing from them, and they're rarely mentioned when discussing cooperation within the industry.&#34; Meanwhile, Scale AI is actively pursuing a potential IPO. When the deal with Meta was initially finalized, going public was already one of the factors considered. Early investor Mike Volpi stated: &#34;In a sense, this investment could still yield double returns. That is, if the remaining part of the company goes public independently, investors can achieve another round of exit and profit.&#34; Drogue, however, took a conservative approach to the IPO timeline: &#34;Scale AI is very likely to go public in the future, but it is currently in an extremely early planning stage.&#34; Currently, Scale AI is on an unprecedented development path in the industry. In recent years, numerous AI startups have engaged in high-profile acquisition-style talent poaching deals with tech giants. Founders of popular AI companies such as Inflection, Adept, Character, and Windsurf have collectively jumped ship to Microsoft, Amazon, and Google. However, DeRogge firmly disagrees with categorizing Scale AI as such. What is the reason? He explained: &#34;We have a mature business, while those companies don't have a well-established business model; the two are completely incomparable.&#34; This article is translated from: https://www.forbes.com/sites/richardnieva/2026/05/13/scale-meta-deal/</p></div></div>

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<p>Scale AI, sold to Meta for $14 billion, is thriving under new CEO Jason Droege, with revenue expected to surpass $1 billion this year. Following founder Alexandr Wang's departure, the company shifted focus from traditional data labeling to building AI applications for major enterprises and public sector clients. This strategic pivot, along with a significant annual payment from Meta, has contributed to a revenue increase from $870 million to nearly $1 billion in the past year.</p>

- Following the departure of Scale AI founder Alexandr Wang, the company, now led by CEO Jason Droege, is projected to surpass $1 billion in revenue this year, rebounding from uncertainty.  
- The $14 billion deal with Meta, which allowed Wang to transition to a new role, initially caused turmoil within Scale AI but has since led to significant collaboration and growth in AI applications.  
- While Scale AI focuses on expanding its enterprise AI services, it faces challenges and competition in the evolving market, with plans for a potential IPO on the horizon.

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After being sold to Meta for $14 billion, Scale AI is actually thriving.