Meta's $14B AI gamble with Alexandr Wang falls short as developers turn skeptical

A year after Meta tapped Alexandr Wang to build a new AI model, Zuckerberg has to sell it

But the stock is underperforming every other tech megacap, and developers are skeptical of whether Meta can be a real player in a market dominated by OpenAI, Anthropic and Google. A year after spending over $14 billion to bring in Alexandr Wang and a group of his top Scale AI engineers to revamp its artificial intelligence efforts, Meta is at least back on the map in AI, though it's still far behind OpenAI, Anthropic and Google in the market. Wang's big accomplishment was the delivery of the Muse Spark AI model in April, marking Meta's first jump into proprietary foundation models and away from a strict adherence to open source, or open weight as it's more commonly called in AI. The group Wang leads -- Meta Superintelligence Labs -- was established to give the company some sizzle in the hottest corner of the tech industry. Now that CEO Mark Zuckerberg has his new model, it's on him to make it a financial success. That means showing the company can attract paying users for its AI tools, rather than just using the technology to enhance and bolster its core advertising business. "Meta needs to provide more proof points of both adoption and commercialization," said Ralph Schackart, an analyst at William Blair who recommends buying the stock. "Investors are looking for Meta to monetize a new AI-first product, beyond the substantial positive impact AI is having on enhancing the advertising models." Wall Street, at least so far, is unimpressed. Meta's stock is down 18% over the past 12 months, the worst performer in the megacap group, along with Microsoft, which has its own challenges in AI. That's even after Meta reported 33% revenue growth in the first quarter, the fastest rate of expansion for any period since 2021. For Meta, the problem started with what some industry experts called, in hindsight at least, a strategic blunder. The company jumped into AI with its Llama family of models, offering an open-source approach that allowed developers to freely tinker, while the other big model makers charged for access. In April of last year, Meta's release of Llama 4 fell flat, failing to captivate developers and leading Zuckerberg to reconsider his company's approach to AI development. Two months later, Zuckerberg shocked the tech world, announcing his company's $14.3 billion investment for roughly half of Scale AI and, more importantly, bringing over Wang and his top lieutenants. Wang's development and rollout of Muse Spark in April of this year got the ball rolling. Instead of focusing on third-party developers, the new model was designed to easily plug into Meta's apps like Facebook and Instagram as well as AI-powered devices like the Ray-Ban Meta glasses, said Thomas Randall, an analyst at the Info-Tech Research Group. That's on top of the standalone Meta AI app and site. "There'll be a lot of these frontier model providers that will fundamentally change in lots of different ways, and Meta needs to have a consistent, reliable proprietary model that they themselves own," Randall said. He added that Meta would be "lost" if Zuckerberg didn't open his wallet for Wang and other big-name AI hires over the past year, in what Randall called a "strategic rebuild" for the company. Randall said Meta hasn't taken the "most optimized route," but at least "I can now see a vision for what they're trying to achieve and what Wang has been trying to achieve," he said. Since the release of Muse Spark, Meta has unveiled new AI and business-related subscription plans as part of an effort to expand its business beyond online ads. Historically, it hasn't worked. Meta still counts on ads for 98% of revenue. Schackart said he wants to see "tangible evidence of a growing list of new, AI-first products created by Muse Spark, even if monetization lags." He said that's "what investors are looking for." No matter how good Wang's model may be, Zuckerberg has a high hill to climb with developers coming off the Llama debacle. "I think the AI community largely ignores Meta at this point," said Rob May, CEO of the startup Neurometric, which works in the realm of token engineering. May said it's hard to gauge how much success Wang has had leading MSL, because the company has thus far only released one AI model, which he characterized as a "yawn" among the AI community since the technology is not widely accessible. Although Meta was heavily courting third-party developers with Llama, May said the company's efforts under Wang seem geared toward internal uses. May said he used to be in regular touch with Meta for Llama-related issues, but now said he "can't get them to return messages." May admits that it makes sense for Meta to focus on AI for its core ad products, because the company has a $200 billion a year business to protect. "That company has built the machine," he said. Andrew Moore, the CEO of enterprise startup Lovelace and former Google Cloud AI chief, said it's not too late for Meta to find a lane. Meta has focused on making its models more efficient through training techniques. Moore said that could be a major differentiator among developers worried about the rising costs of foundation models. "If they do proprietary, computationally efficient models, that will be so different from what's happening in this death match between the big guys," Moore said. "They might really benefit." Moore added that Meta has to show an advantage somewhere, whether it be on cost, latency or other technical nuances that matter to developers. Krish Subramanian, the CEO of consulting firm KOI AI and former product head at IBM Consulting, said developers are more excited about Google's AI models than what Meta is offering. The appeal of Llama was that it specifically targeted developers wanting open-weight alternative models, while with Muse Spark, Meta has made little effort in that direction, he said. "The lack of developer trust will come back to hit them if they don't focus on third-party developers," Subramanian said, noting that it took years for Microsoft to regain trust from open-source coders during the early days of Azure. "To just focus on a walled-garden kind of an ecosystem and ad revenue as the main source of income, they probably will never become the big player," he said. A Meta spokesperson pointed to Wang's recent comments about the company's continued support for the open-source ecosystem, and said Meta still plans to offer outside developers access to Muse Spark's underlying technology via an API, as it previously announced. "We're already testing with some early partners, and look forward to releasing it this month," the spokesperson said. In addition to the challenges with developers, there's slumping morale. Meta has been slashing jobs throughout the year, and in May fired about 8,000 workers. The cuts spanned departments, including teams working in roles related to trust and safety, which has raised concerns about potential problems that can arise in AI development, according to people familiar with the matter who asked not to be named in order to speak candidly on the subject. Meta declined to comment about the layoffs. Regarding safety-related issues, the spokesperson pointed to comments from Wang on the matter. He told the Core Memory podcast last month that, "One of the things that is very important to me is safety for these models." There's also tension at the top of the AI organization. Although the Muse Spark release received high marks internally, there's pressure on Wang along with former GitHub CEO Nat Friedman, who also joined last summer as part of the AI spending spree, to deliver meaningful revenue growth from the model and future releases, sources with knowledge of the matter said. Meta tech chief Andrew Bosworth, a 20-year company veteran, is a close confidant of Zuckerberg's and someone the CEO could turn to for a bigger role in AI if the newcomers are perceived as failing, the sources said. On the May podcast, Wang dismissed any reported internal conflicts. Wang has called Muse Spark an "appetizer" for what's to come, and said there will be more powerful, "larger models." But the AI community is used to a steady stream of updates and new features. That's what they get from OpenAI, Anthropic and Google. "What I care about is the frequency of the launches and the cadence," said Howard Yu, a business professor at the International Institute for Management Development in Switzerland. "When you launch something, can you build upon that momentum?" Randall of the Info-Tech Research Group said it's ultimately up to Zuckerberg to determine that strategy and to show "how much of a superpower they are now with all of their products." Yu agreed. "This is really about leadership, right?" he said, noting that at tech companies in particular, the CEO defines and articulates the vision, especially when it involves spending billions of dollars. That Zuckerberg's metaverse and virtual reality ambitions have generated over $80 billion in total losses since late 2020 makes the AI pitch a tougher sell, Yu said. "He's running out of the space for his credibility to last," Yu said. "I think the virtual reality foray may have burned up a lot of his goodwill in front of investors." 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Meta Facing Pressure to Show It Can Monetize AI Creations | PYMNTS.com

One year later, the company is facing substantial pressure to prove it can monetize the resulting tools such as its Muse Spark model as its stock continues to underperform compared to other tech giants, CNBC reported Sunday (June 14). "Meta needs to provide more proof points of both adoption and commercialization," Ralph Schackart, a William Blair analyst who recommends buying the stock, told CNBC. "Investors are looking for Meta to monetize a new AI-first product, beyond the substantial positive impact AI is having on enhancing the advertising models." Unlike its predecessors, Muse Spark is a proprietary foundation model created for internal integration across Meta's ecosystem, which includes social media platforms like Facebook and Instagram, as well as hardware like its Ray-Ban Meta glasses. "There'll be a lot of these frontier model providers that will fundamentally change in lots of different ways, and Meta needs to have a consistent, reliable proprietary model that they themselves own," said Thomas Randall, an analyst at the Info-Tech Research Group, per the CNBC report. He added that Meta would be lost if CEO Mark Zuckerberg hadn't shelled out to hire Wang and other high-profile AI figures, calling it a "strategic rebuild" for the company. Randall said that while Meta hasn't taken the "most optimized route," he could at least "now see a vision for what they're trying to achieve and what Wang has been trying to achieve." This is happening amid in-house instability, following the layoff of 8,000 workers last month. Sources familiar with the matter told CNBC Meta is dealing with tension at the top of the AI organization, noting that Wang and other big name hires are under severe pressure to provide meaningful growth to justify the company's massive spending. The news follows reports from earlier this month that Meta had postponed plans to share its latest AI models with developers with no schedule for a release of the new model. The delay, which has stretched almost two months since Meta told developers a release was coming "soon," is leading to questions about how fast the company can monetize its vast spending on AI development, according to a report from The Wall Street Journal.

Meta's $14B AI Bet Falls Short as Engineers Turn to Rival Claude

The company earlier built its AI reputation through open models like Llama. The release of Llama 4 failed to excite developers, which pushed Meta to change direction. The shift toward proprietary AI now defines its strategy. Safety also plays a major role in decisions. Wang confirmed that Muse Spark showed risk signals during testing, especially in sensitive areas. Meta chose to keep the model private to control these risks more effectively. Limited access has slowed adoption. Muse Spark mainly works inside Meta's own apps, while outside developers have very little access. This approach creates challenges in building trust among the wider developer community. Investors remain cautious. Meta continues to earn most of its revenue from advertising. are growing, but clear returns have not yet appeared. The company has started testing subscription services to create new income sources. The competition in AI continues to grow stronger. Firms like Anthropic gain attention by offering reliable and widely used tools. Meta must match this trust while improving performance.