Key Points

• The chip industry is booming thanks to AI.

• Advanced Micro Devices is seeing margins and earnings soar as its data center business expands.

• Broadcom is meeting insatiable demand for custom AI chips and networking solutions for advanced AI workloads.

Artificial intelligence (AI) is impacting every sector of the economy, so there are several ways investors can profit from this opportunity. But recent earnings results show that top semiconductor companies are still well positioned to deliver outstanding returns for long-term investors.

The AI chip market is expected to grow at an annualized rate of 24% through 2029 to reach $311 billion, according to MarketsandMarkets. If you have $3,000 you’re looking to invest right now, here are two chip stocks to consider buying and holding for the long term.

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1. Advanced Micro Devices

Advanced Micro Devices(NASDAQ: AMD) has become a widely used brand of chips in the consumer PC market. Its Ryzen processors have taken significant market share from Intel. But it’s also one of only two suppliers, along with Nvidia, of general-purpose graphics processing units (GPUs) that are used for AI workloads.

While Nvidia has a commanding lead in GPUs, it’s not going to control 100% of the market. This leaves a substantial opportunity for the runner-up in this market to do well. AMD’s data center business is booming, with segment revenue up 57% year over year in the first quarter.

AMD is meeting demand for cost-effective alternatives in the chip market. Oracle is experiencing tremendous growth in its cloud infrastructure business right now, and it’s a key partner for AMD. Oracle’s cloud infrastructure will offer up to 131,072 AMD Instinct MI355X GPUs for AI. AMD has already announced the MI400 series for launch next year, which will enable even better performance for AI training and inferencing.

As data center sales make up a larger mix of AMD’s total revenue, it is pushing margins up. Higher margins drove a 55% year-over-year increase in adjusted earnings last quarter. Given the long-term opportunity in the AI chip market, which AMD estimates at $500 billion, investors are undervaluing AMD’s future earnings.

The stock is trading at a forward price-to-earnings (P/E) multiple of 38 on 2025 earnings estimates. But this multiple drops to 25 on 2026 estimates. As AMD continues to expand margins from growth in its data center business, the stock could offer significant upside over the next few years and beyond.

2. Broadcom

Beyond the surging demand for general-purpose chips that AMD supplies, there is growing demand for chips designed for specialized tasks. Broadcom(NASDAQ: AVGO) is one of the best stocks to profit from the demand for custom chip solutions.

Broadcom has been a top-performing semiconductor company for years, supplying components for many markets, including Apple‘s iPhone. But demand for its application-specific integrated circuits (ASICs) for AI is off the charts.

The company’s AI chip revenue grew 46% year over year in the most recent quarter. As demand for custom ASICs grows, it also fuels demand for networking products that can handle faster data transfer, which is needed for next-level AI performance.

Broadcom’s new Tomahawk 6 Ethernet switch has enough data capacity to support 100,000 AI chips working together to train the next-generation AI models. The company’s networking business posted revenue growth of 170% year over year last quarter, representing 40% of its AI-related revenue.

However, management sees the demand for its custom AI chips outpacing sales of its networking products over time. It’s a huge opportunity, as evidenced by Broadcom’s momentum. Management expects its AI growth to remain steady through fiscal 2026, which could support new highs for the stock.

Broadcom earns very high margins, so the favorable demand outlook points to robust earnings over the next year. The stock trades at 41 times this year’s consensus earnings estimate, but that multiple drops to 33 on next year’s estimate. These are not cheap valuation multiples, but the investment in AI technology is pointing to substantial growth in the coming years for leading chipmakers, and that should support excellent returns for investors.

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Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. John Ballard has positions in Advanced Micro Devices and Nvidia. The Motley Fool has positions in and recommends Advanced Micro Devices, Alphabet, Apple, Intel, Microsoft, Nvidia, and Oracle. The Motley Fool recommends Broadcom and recommends the following options: long January 2026 $395 calls on Microsoft, short August 2025 $24 calls on Intel, and short January 2026 $405 calls on Microsoft. The Motley Fool has a disclosure policy.

Investors may be generally tracking the artificial intelligence wars (AI), with most of the “Magnificent Seven” companies spending hand over fist in a race to be the first to crack AI — and all the financial benefits that come with it.

But over the last couple of weeks, Meta Platforms (META 0.37%) CEO Mark Zuckerberg has made truly massive moves, committing huge amounts of dollars to both talent and computing infrastructure that dwarf even the current super-expensive standard of today’s AI leaders.

The implications of the moves may have been comprehended by some, but may still be underestimated by the larger investment community.

Zuck throws down the gauntlet

Over the past month or so, Zuckerberg has:

1. Purchased 49% of data-labeling leader Scale AI at a $28 billion valuation, bringing in Scale’s CEO Alexandr Wang and top leadership.
2. Hired top AI talent in addition to Wang to create a “Super-Intelligence Team” from several leading AI and tech rivals, totaling about 50 researchers, by offering multiples more than other companies, with some offers rumored to be as much as $200 million or more.
3. Notable poached talent includes Nat Friedman, the former GitHub CEO; Daniel Gross, who was CEO and co-founder of SSI, Ilya Sustkever’s current start-up (Sustkever was a co-founder of OpenAI); Ruoming Pang, the head of Apple‘s AI division; as well as Lucas Beyer, Alexander Kolesnikov, and Xiaohua Zhai from OpenAI.

On infrastructure investments, Zuckerberg also shed light on massive upcoming projects:

1. In a Threads post, Zuckerberg said Meta was going to invest “hundreds of billions of dollars” in AI superclusters.
2. This includes the industry’s first 1GW supercluster, which Meta is calling Prometheus and should come online in 2026.
3. Zuckerberg also said this will be just the first of multiple GW-plus superclusters, including Hyperion, which will eventually scale up to 5 GW over several years, and encompass a data center almost the size of Manhattan.

How does all this spending pay off?

One might wonder what spurred this spending binge from Zuckerberg, and whether it was an offensive or defensive move. The answer, perhaps not surprisingly, is likely both.

Zuckerberg now says Meta is aiming for “super intelligence,” which could be somewhat akin to what was formerly referred to as artificial general intelligence (AGI). The concept of super intelligence, and whether AI is capable of reaching such a thing, has been hotly debated. However, it appears that Zuckerberg now believes super intelligence is achievable, and may be reached within the next few years. 

In a recent interview with tech magazine The Information, Zuckerberg said:

There is this big debate in the industry today. All right, is super intelligence going to be possible in three years, five years, seven years? But I don’t think anyone knows the answer. I just think that we should bet and act as if it’s going to be ready in the next two to three years.

Zuckerberg also believes “super intelligence” may mean different things to Meta than it does to more enterprise-oriented Mag Seven companies. Whereas, say, Microsoft might use AI to automate many enterprise functions, leading to an increase in productivity, for Meta, Zuckerberg apparently has a vision of giving consumers “super intelligence” related to their everyday lives, the media they consume, and their social connections.

Zuckerberg also made an interesting note in the interview that the high salaries are worth it, since the ultimate team will likely be small, between 50 and 70 people:

I think that the physics of this is, you don’t need a massive team to do this. You actually kind of want the smallest group of people who can fit the whole thing in their head. So there’s just an absolute premium for the best and most talented people.

This makes sense. The architecting of AI systems is very complex, and if a technician makes a wrong architectural choice along the way, that can affect the performance of the entire model. According to AI chip blog Semianalysis, Meta’s recent large language model Llama 4 has been a disappointment, and the reasons were partly due to poor data labeling — which the Scale AI acquisition should help with — and a few poor architectural choices.

Thus, it’s perhaps no surprise that Zuckerberg feels investing in a smaller number of high-caliber engineers is the best path. The difference between a winning model and a disappointing model may come down to a few high-level decisions, so it makes sense that Zuckerberg would pay up for quality over quantity for Meta’s new AI efforts.

Another offensive aspect of this is that Meta has arguably more financial resources than its rivals, especially OpenAI, which is considered a start-up and losing tens of billions at the moment. Last year, Meta’s “core” social media advertising business brought in a whopping $87.1 billion in operating income, somewhat offset by a $17.7 billion loss in its Reality Labs division. And that $87 billion is probably on track to reach close to $100 billion this year.

Therefore, Meta has the ability to pay as much or more than its rivals, and by paying these types of astronomical salaries, it’s raising the costs of employment for everybody — OpenAI included. Zuckerberg continued:

… one of the benefits of reinforcement learning is it gives you a venue to, you know, potentially convert very large amounts of capital into a better and better service, and potentially a better service than other less well-funded or less bold competitors will be able to do so… I view that as a competitive advantage. If we can get this to work well, and that’s why we are basically all in on this. We’re building, you know, we’re building multiple, multi-gigawatt data centers, and we can basically do this all funded from the cash flow of the company.

But the move may also be defensive, and isn’t without risks

While the “all-in” spending binge from Zuckerberg is exciting, investors should also be wary of a few things. First, it appears Meta’s AI super intelligence dream team will be essentially starting from scratch. This is likely due to Meta’s recent efforts on its Llama 4 LLM coming up short of expectations, or at least falling further behind its other competitors than Zuckerberg would like. So, it appears Meta’s latest attempt at leading AI is a bit of a bust, raising questions about the need to put all its chips into the pot, so to speak, at this moment.

It has also been reported that Zuckerberg wasn’t able to successfully acquire all the companies and talent that he wanted. In addition to Scale AI, Zuckerberg reportedly also wanted to acquire Mira Murati’s Thinking Machines and Ilya Sustkever’s SSI, but was rebuffed in both cases. It was also reported Zuckerberg extended billion-dollar offers to some of OpenAI’s leadership team, but was also rebuffed. So, while Meta now has perhaps the most formidable AI “dream team” around, it isn’t a “full” dream team necessarily.

Finally, Meta has a history of throwing money at certain far-off ventures, without immediate tangible outcomes. Look no further than the Reality Labs segment, which is basically Zuckerberg’s gambit to create the “next computing platform” of virtual reality goggles or glasses. Meta even changed its name from Facebook to Meta Platforms in 2021 to show its commitment to the effort. However, in 2024, three years later, that segment lost $17.7 billion, up from a $16.1 billion loss in 2023.

Finally, Zuckerberg didn’t really spell out what he exactly meant by an everyday consumer “super intelligence.” While both the Reality Labs division and the concept of consumer super-intelligence may one day come to fruition, it’s not assured — even with Zuckerberg assembling an AI “dream team.” So while this past month’s spending is exciting, look for investors to get impatient if Meta’s spending goes up without a corresponding growth in revenue.

And yet, the spending makes Meta a must-own stock

If one of today’s current tech leaders reaches “super intelligence” before the others, it has the potential to disrupt the balance of power among today’s Magnificent Seven. That’s why any young person or growth investor should have exposure to Meta and its rivals, in spite of their massive AI spending today.

If and when one of these companies “cracks the code” before others, it’s possible the Magnificent Seven could become the Magnificent Three, Two… or even One. With his moves over the past month, Zuckerberg is investing heavily to make sure Meta is one of the leading candidates to become that “one.”

Investors should keep their ears out for more information when Meta reports earnings at the end of the month on July 30.

The market has returned to its highs, along with many top artificial intelligence (AI) names. However, another market dip could always be around the corner.

Let’s look at three top AI stocks that have made strong runs that would be good buys on a pullback.

1. Palantir

With a high valuation but attractive growth opportunities, Palantir Technologies (PLTR -0.34%) is a stock that would be attractive on a dip. The company has emerged as one of the market’s most compelling AI growth stories, and its momentum has been gaining speed.

In the first quarter, Palantir posted its seventh consecutive period of accelerating growth, with revenue up 39%. The rise is being led by its U.S. commercial segments, which saw sales jump 71% and the value of future deals soar 127%.

While there is a lot of talk about which company is building the best AI model, Palantir is focused on something far more practical: making AI useful. Its Artificial Intelligence Platform (AIP) uses AI models to help solve real-world problems.

AIP does this by gathering data and then connecting it to physical assets and operational workflows, allowing companies to make AI more useful. As a result, the platform is being used for a growing list of purposes, including hospitals monitoring for sepsis, insurers using it in their underwriting, and energy companies optimizing their pipeline infrastructure.

The company’s largest customer is the U.S. government, which is starting to embrace AI to become more efficient. Last quarter, Palantir’s government revenue climbed 45%.

The company also recently landed a major deal with NATO, expanding into international defense just as Europe ramps up military spending. That gives it three potential growth engines: domestic commercial enterprises, the U.S. government, and now the international public sector.

Yes, the stock is expensive by traditional metrics, but Palantir looks like it’s laying the groundwork to become one of the next megacaps. As such, any pullback could be a great buying opportunity.

2. Nvidia

Nvidia (NVDA -0.42%) has once again been helping lead the market higher. The company recently got good news when the Trump administration said the U.S. would ease chip export controls, allowing the company to resume selling its H20 chips to China. This will add billions in revenue.

Nvidia remains the undisputed champion of AI infrastructure, with its graphics processing units (GPUs) the backbone of this build-out due to their fast processing speeds. And the company has sped up its development cycle to ensure it remains on top.

Over the past two years, data center revenue has exploded from $4.3 billion to more than $39 billion — incredible growth for a company the size of Nvidia. It held a 92% share in the GPU market in the first quarter.

Its chips drive sales, but its secret weapon is its CUDA software. The company created the free platform in 2006 as a way to expand the use of GPUs beyond their original purpose of speeding up graphics in video games.

While it was slow to play out in other end markets, Nvidia smartly pushed CUDA into academia and research labs, where early AI research was being done. That led developers to build directly on CUDA, leading to a growing collection of tools and libraries designed to maximize GPU performance for AI workloads.

If shares of Nvidia dip, be ready to pounce. Data center spending continues to ramp up, and the company has a big opportunity in the automotive market, too, as autonomous and smart vehicles start to become more prevalent.

3. Microsoft

Another company that has seen its stock run up in price is Microsoft (MSFT -0.32%). It dominates the enterprise software space with its Microsoft 365 suite of worker productivity products and has one of the leading cloud computing companies in Azure.

The cloud remains the company’s fastest-growing business, with the unit producing revenue growth of 30% or more each of the past seven quarters. Azure revenue jumped 33% last quarter (35% in constant currency), with nearly half of that coming from AI services. Growth could have been even higher, but Microsoft has been hitting capacity constraints.

As such, it plans to ramp up capital expenditures (capex) in fiscal 2026 with a focus on adding GPUs and servers. It said those assets are more directly tied to AI revenue than buying the buildings that house them. That’s a smart move that should support continued cloud computing momentum.

Microsoft’s $10 billion investment in OpenAI gave it an early AI lead, especially with Azure initially being granted exclusive access to its leading large language models (LLMs). Companies continue to be attracted to OpenAI’s popular AI models, and Azure gives its customers direct access to them.

It has also embedded OpenAI’s models throughout its ecosystem to run its Copilot, which is gaining popularity with businesses. At $30 per enterprise user per month, it offers a lot of strong upside.

That said, the OpenAI partnership is getting complicated. The exclusivity deal is over, and the two sides are reportedly negotiating new terms as the AI provider looks to restructure. Still, Microsoft remains entitled to 49% of OpenAI Global’s profits up to a tenfold return on its investment — potentially a huge payday.

Microsoft remains in a strong long-term position. The stock’s recent run-up makes it an attractive candidate to buy on any pullback.