By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panel is divided on Meta's AI cloud and model licensing strategies. While some see potential in becoming the 'OS for AI' or monetizing excess compute capacity, others caution about execution risks, fierce competition, and unproven monetization strategies. The key debate centers around whether Meta can successfully pivot from its ad-reliant model and generate sustainable growth from AI initiatives.
Risk: Fierce competition in the cloud infrastructure market and unproven monetization strategies for AI models.
Opportunity: Potential to become the 'OS for AI' and create a moat that makes ad-spend stickier.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
This has been a forgettable year for Meta Platforms (NASDAQ: META) investors so far. Shares of the tech giant are down 5% as of this writing, underperforming the tech-laden Nasdaq Composite index that has logged 11% gains in 2026.
Concerns about Meta's aggressive capital spending on artificial intelligence (AI) projects and the potential returns of these investments have weighed on its stock price this year. However, the Magnificent Seven stock jumped nearly 9% on July 1 after a report emerged that it may be entering the lucrative AI cloud market.
Where to invest $1,000 right now? Our analyst team just revealed what they believe are the 10 best stocks to buy right now, when you join Stock Advisor. See the stocks »
Let's see what this potential move may mean for Meta stock.
According to Bloomberg News, Meta Platforms is planning to sell its excess AI cloud computing capacity to customers. It was easy to see why this report gave Meta stock a big boost. The company is on track to spend $135 billion in capital expenditure this year at the midpoint of its guidance range, up significantly from $72.2 billion last year.
Meta has been spending heavily to integrate AI tools across its applications and advertising offerings, as well as to build frontier AI models (the most advanced kind of foundational AI models) through its Superintelligence Labs division. The good news is that these investments are driving tangible gains for Meta.
The company's Muse Spark advanced AI model, which is the first one to be launched by Meta Superintelligence Labs and powers the Meta AI assistant, has led to a double-digit percentage increase in user sessions on Meta AI. Additionally, the Meta AI business assistant is resolving its clients' issues at 20% faster, while the number of advertisers using the company's generative AI creative tools now stands at more than 8 million.
Meta is also pushing the envelope in AI wearables. The daily users of its AI glasses doubled year over year in Q1. Still, the toll that Meta's heavy spending may take on its bottom line has got the market worried. So, when reports emerged that this tech giant would start selling its AI cloud excess capacity, investors heaved a sigh of relief.
This will allow Meta to monetize the unused cloud computing capacity in its inventory, mitigating Wall Street's worries that it is overspending on AI infrastructure. This could be a smart move if Meta indeed decides to rent out excess infrastructure. Also, Bloomberg News reports that Meta will offer access to its AI models to customers renting AI compute capacity, in addition to raw compute capacity to run their own models and applications.
Meta, therefore, could be poised to enter the massive AI cloud market that's expected to generate $267 billion in revenue in 2030, according to Gartner. Entering this market will supercharge Meta's already impressive growth. The company's Q1 revenue increased 33% year over year to $56.3 billion. However, aggressive capital spending resulted in a smaller 14% increase in its adjusted earnings per share (after excluding the one-time income tax benefit of $3.13 per share).
However, as Meta's investments in AI infrastructure start paying off, its bottom-line growth should also accelerate, following an estimated 8.5% jump in 2026.
Also, if Meta enters the cloud AI market like other Magnificent Seven companies, it could clock faster growth than Wall Street's expectations.
Meta's underperformance this year explains why the stock is trading at attractive levels. It has a trailing earnings multiple of 21, a significant discount to the Nasdaq Composite's earnings multiple of 39. Of course, Meta's tepid earnings growth explains why it is cheap right now. However, a potential acceleration in growth could eventually lead the market to reward it with a higher valuation, resulting in more upside.
On the other hand, Meta is trading at 7 times sales, a slight premium to the Nasdaq Composite's average sales multiple of 5.3. The gains that Meta's AI tools are bringing for advertisers, along with its reported entry into AI cloud infrastructure, could help it exceed Wall Street's growth estimates over the next three years.
Analysts are anticipating a 26% jump in Meta's revenue this year. That's expected to be followed by healthy double-digit growth in 2027 and 2028, albeit at a slower rate.
Meta could exceed those numbers, especially given its growing share of the digital ad market. According to eMarketer, Meta's digital ad market share could hit 27% in 2026, surpassing Google. This indicates that the integration of AI tools into Meta's advertising platform is paying off. Given that the digital ad market's revenue is expected to surpass $1.5 trillion in 2030, there is a strong likelihood of Meta cruising past consensus revenue estimates.
But even if it generates $354 billion in revenue in 2028 and maintains its 7x sales multiple, its market cap could jump to $2.5 trillion. That suggests a potential 60% upside over three years, which is why investors should consider buying this AI stock while it trades at attractive levels.
Before you buy stock in Meta Platforms, consider this:
The Motley Fool Stock Advisor analyst team just identified what they believe are the 10 best stocks for investors to buy now… and Meta Platforms wasn’t one of them. The 10 stocks that made the cut could produce monster returns in the coming years.
Consider when Netflix made this list on December 17, 2004... if you invested $1,000 at the time of our recommendation, you’d have $407,651! Or when Nvidia made this list on April 15, 2005... if you invested $1,000 at the time of our recommendation, you’d have $1,252,823!
Now, it’s worth noting Stock Advisor’s total average return is 922% — a market-crushing outperformance compared to 208% for the S&P 500. Don't miss the latest top 10 list, available with Stock Advisor, and join an investing community built by individual investors for individual investors.
**Stock Advisor returns as of July 9, 2026. *
Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends Meta Platforms. The Motley Fool recommends Gartner. The Motley Fool has a disclosure policy.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"Meta's transition to a cloud infrastructure provider is a high-risk operational pivot that must prove it can generate meaningful margins without cannibalizing the core advertising business."
Meta’s pivot toward selling excess AI compute capacity is a classic 'infrastructure-as-a-service' play that aims to turn a massive cost center—$135 billion in projected capex—into a revenue stream. While the article highlights the potential for a $2 trillion valuation, it ignores the operational friction of becoming a cloud provider. Scaling infrastructure for external enterprise clients requires a level of reliability, SLAs, and technical support that Meta hasn't historically prioritized. If they succeed, they optimize utilization rates; if they fail, they are left with depreciating hardware and bloated opex. At a 21x forward P/E, the market is pricing in skepticism regarding their ability to pivot from a pure social-ad model to a diversified cloud player.
Meta’s core competency is social engagement, not enterprise cloud; attempting to compete with AWS or Azure could dilute focus and lead to margin compression if they are forced to engage in a price war to attract cloud tenants.
"Meta's ad-tech AI traction is real and underpriced, but the cloud infrastructure story is pure speculation being used to justify aggressive capex that hasn't yet proven its ROI."
The article conflates two separate narratives: Meta's proven ad-tech AI wins (33% revenue growth, 8M+ advertisers using gen-AI tools) versus speculative cloud infrastructure upside. The cloud story is entirely Bloomberg rumor—no guidance, no customer commitments, no timeline. Meanwhile, the math is aggressive: $135B capex this year on 14% EPS growth (excluding one-time tax benefit) suggests ROI remains unproven. The 21x P/E 'discount' to Nasdaq 39x is justified if growth stays 8.5% in 2026. The $2.5T market cap thesis requires *both* cloud entry *and* sustained 26%+ revenue growth through 2028. That's two bets, not one.
If cloud infrastructure monetization fails to materialize or takes 5+ years to scale, Meta remains a 21x stock on mid-single-digit earnings growth—a value trap, not a bargain. The capex could crater returns for years.
"N/A"
[Unavailable]
"Meta's upside depends on a scalable, margin-boosting AI cloud monetization that remains uncertain; without it, the cheap stock thesis is at risk of disappointment."
META trades at a seemingly cheap 21x trailing earnings and 7x sales, but the real test is whether its AI cloud monetization effort pays off at scale. The article glosses over execution risk: renting out excess compute from a position of heavy capex, potential margin compression from infrastructure investments, and fierce competition from AWS, Google Cloud, and Azure. Ad-reliant revenue remains exposed to regulatory shifts and iOS changes. The 2030 Gartner-documented AI cloud market assumes significant monetization of Meta’s model outputs and cloud services, which is far from guaranteed. If cloud upside slows or margins stay under pressure, the assumed rerate may never materialize.
Bullish counterpoint: Meta could monetize excess capacity efficiently, win licensing deals for its models, and ride AI-driven ad productivity to a meaningfully higher multiple as AI becomes core to its moat; the market often underpricing optionality in large platform ecosystems.
"Meta's long-term value lies in Llama's ubiquity as an industry standard, not in competing with hyperscalers for raw cloud compute revenue."
Claude is right to call out the 'cloud' narrative as speculative, but both Gemini and Claude miss the real play: model licensing via Llama. Meta isn't building another AWS; they are commoditizing the infrastructure layer to make their open-source models the industry standard. By winning the developer ecosystem, Meta creates a moat that makes ad-spend stickier and infrastructure costs a tax on competitors. The valuation isn't about cloud margins; it's about becoming the OS for AI.
"Llama dominance ≠ revenue; open-source moats are notoriously weak on monetization."
Gemini's Llama-as-OS thesis is seductive but conflates developer mindshare with monetization. Meta's open-source strategy *commoditizes* AI models—the opposite of margin expansion. If Llama becomes the standard, Meta captures ecosystem lock-in but *not* direct revenue. The ad-stickiness argument assumes developers who use free Llama spend more on Meta ads, which is unproven. This is optionality theater masking that core ad growth (33% YoY) already prices in AI productivity gains. The $135B capex ROI still hinges on either cloud revenue or ad ARPU expansion—neither guaranteed.
[Unavailable]
"Monetizing Llama-as-OS hinges on uncertain licensing and governance revenues, with margin risk if open-source ecosystem costs rise and capex remains high."
Gemini’s Llama-as-OS thesis sounds compelling, but monetization hinges on licensing models, support costs, and governance with open-source communities. Developer adoption may boost ad visibility, but that path is uncertain and could be margin-dilutive if Meta must subsidize tooling, security, and compliance. Until licensing yields durable revenue streams beyond optionality, the idea risks valuation compression if capex remains high while cloud-adjacent revenue underwhelms.
The panel is divided on Meta's AI cloud and model licensing strategies. While some see potential in becoming the 'OS for AI' or monetizing excess compute capacity, others caution about execution risks, fierce competition, and unproven monetization strategies. The key debate centers around whether Meta can successfully pivot from its ad-reliant model and generate sustainable growth from AI initiatives.
Potential to become the 'OS for AI' and create a moat that makes ad-spend stickier.
Fierce competition in the cloud infrastructure market and unproven monetization strategies for AI models.