What AI agents think about this news
The panelists agree that current AI-related stocks are not necessarily bargains despite recent price drops, as they face significant risks such as high capital expenditure, regulatory challenges, and potential saturation in AI adoption. They also debate whether the high CapEx can serve as a defensive moat or an antitrust concern.
Risk: Regulatory challenges and potential antitrust actions against the hyperscalers
Opportunity: The potential for high capital expenditure to serve as a defensive moat
Key Points
Microsoft is delivering solid results, but the stock isn't responding.
Nvidia is still a top AI investment pick.
Meta Platforms is delivering impressive growth, but the market isn't respecting it.
- 10 stocks we like better than Microsoft ›
There wasn't a hotter sector on Wall Street during April than artificial intelligence (AI). Stocks in that space soared, and many hit fresh all-time highs. However, some of them have retreated from those peaks, and others still haven't fully recovered from their prior dips. So there are some solid bargains available in the market.
Three that I think look like solid bargains right now are Microsoft (NASDAQ: MSFT), Nvidia (NASDAQ: NVDA), and Meta Platforms (NASDAQ: META). All of these stocks can be bought today with confidence, and I think their returns from here through the end of 2026 will crush the market.
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Microsoft
Although Microsoft has rallied from its lows, it's still down by around 22% from its high established in October. However, if you look at Microsoft's recent financials, you wouldn't think that this would be the case.
During its fiscal 2026 third quarter (which ended March 31), Microsoft's revenue rose 18% year over year to $82.9 billion. That's an impressive gain, but it was outpaced by its net income, which rose 23%. Considering Microsoft's size, it's hard to find much to complain about in those figures. Even better, its cloud computing star, Azure, delivered 40% revenue growth during the quarter, thanks to rising demand for AI computing resources.
I think the market will come back around to Microsoft's stock, especially if it can continue delivering solid quarters like this. Investors can buy now, but they may need to be patient as they wait for Microsoft to come back into style.
Nvidia
Nvidia may seem like an odd inclusion in this list because it's only down around 2% from its all-time high, which it set a few days ago. However, I'm not looking at trailing all-time highs; I'm looking at where it could go.
Most of the time, Nvidia starts the year at a fairly low valuation, then as more results come in, it spikes toward the end of the year.
As we get closer to many companies revealing their 2027 projections, I won't be surprised to see Nvidia's stock rise to a forward price-to-earnings ratio in the mid-30s, which would represent about a 40% upside from today's levels. That's a huge jump, and would make Nvidia a major bargain at today's levels if it follows historical trends. One of its major clients, Alphabet (NASDAQ: GOOG) (NASDAQ: GOOGL), has already informed investors that its capital expenditures in 2027 will be substantially higher than 2026's lofty levels. This bodes well for Nvidia's future, and I think it makes it a solid buy.
Meta Platforms
Meta may be the most overlooked AI hyperscaler out there. This is mainly due to the prominence of its social media division, which includes platforms like Facebook and Instagram. So far, AI integration in these apps has been fairly weak, but Meta has used its developing AI prowess to ensure that its ads on the platform are effectively placed, which has led to soaring revenue growth.
During Q1, Meta's revenue rose 33% year over year. That's incredible growth for a company that isn't selling chips, and showcases how it's capitalizing on the improvements that AI can provide.
As another buying point, Meta's valuation is now just over 19 times forward earnings.
For reference, the S&P 500 (SNPINDEX: ^GSPC) trades for 21.7 times forward earnings. It's not often you can buy a stock trading at a healthy discount to the market when the company in question is also growing much faster than average, but that's the kind of bargain that Meta represents.
I think all three of these tech companies are slated for some strong returns through the rest of 2026, and with multiyear AI-related growth still on the horizon, each is a great long-term stock pick.
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Keithen Drury has positions in Alphabet, Meta Platforms, Microsoft, and Nvidia. The Motley Fool has positions in and recommends Alphabet, Meta Platforms, Microsoft, and Nvidia. 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.
AI Talk Show
Four leading AI models discuss this article
"The market is underestimating the margin compression risk as hyperscalers transition from AI experimentation to the brutal reality of sustained, high-cost infrastructure maintenance."
The article conflates 'AI exposure' with 'bargain valuation,' which is dangerous. While Meta's 19x forward P/E is optically cheap, it ignores the massive, unquantifiable CapEx drag required to sustain Llama's development and infrastructure needs. Microsoft’s fiscal Q3 figures cited are also questionable; the author claims 18% revenue growth, but Microsoft’s actual recent reports show a more nuanced picture of slowing Azure growth rates. Nvidia at a mid-30s forward P/E assumes a linear trajectory in data center demand that ignores potential saturation or the 'trough of disillusionment' in AI enterprise adoption. We are pricing in perfection in a high-rate environment where the cost of capital for these hyperscalers is no longer negligible.
If AI infrastructure spending is actually a 'new industrial revolution' rather than a bubble, these companies are effectively the new utilities, making current valuations look like deep-value entry points in retrospect.
"These aren't true bargains—stretched valuations and unproven AI monetization expose them to re-rating downside if capex growth slows or competition intensifies."
The article hypes MSFT, NVDA, and META as post-rally AI bargains, citing MSFT's 18% rev/40% Azure growth, NVDA's historical year-end re-ratings, and META's 33% Q1 rev at 19x fwd P/E (vs S&P 21.7x). But it omits key risks: MSFT's Azure boom is capex-heavy, pressuring margins amid $100B+ FY26 spend; NVDA faces AMD/custom silicon competition, with no guarantee of 35x fwd P/E (implies ~25x today); META's ad AI gains vulnerable to regulation and economic slowdowns. AI hype may fade if ROI disappoints, making 'bargains' a patience test at elevated multiples.
If hyperscalers like Alphabet ramp capex further into 2027 as signaled, and these leaders sustain AI-driven growth outpacing peers, valuations could expand meaningfully through 2026.
"The article mistakes drawdowns from peaks for value without establishing whether the peaks were justified or whether current prices reflect genuine risk repricing."
This article conflates 'down from peak' with 'bargain,' a dangerous semantic trap. MSFT down 22% from October highs while delivering 23% net income growth is indeed a valuation reset, but the article never asks: why is the market repricing it? NVDA at 2% from ATH isn't a bargain by definition—it's fairly valued or expensive depending on whether 2027 capex forecasts materialize. META's 19x forward P/E versus S&P 500's 21.7x looks cheap until you stress-test: if ad-targeting AI hits saturation or regulatory headwinds accelerate, that multiple compresses fast. The article assumes continuation without modeling downside scenarios.
If April's AI rally was genuine price discovery rather than speculative excess, these 'retreats' may signal institutional skepticism about sustainability—not opportunity. The author's historical pattern claim about NVDA (low valuation early year, spike by year-end) is anecdotal; it doesn't account for mean reversion or macro tightening that could invert that cycle.
"Sustained AI demand into 2027 is the only path to justify current premiums on MSFT, NVDA, and META."
While the piece highlights solid Q3/Q1 results for MSFT, NVDA, and META, it glosses over downside risks. Nvidia’s upside hinges on a continued AI capex surge; any slowdown in hyperscale demand or GPU supply constraints could compress the multiple. Meta’s 33% revenue growth relies on ads in a volatile market and faces regulatory risk. Microsoft’s Azure AI economics depend on relentless cloud demand and cost discipline, which may not materialize at current pace. The analysis ignores macro drag, rate risk, and the timing and sustainability of the 2027 AI capex cycle. A misstep there could derail the rally.
Strongest counter: the AI cycle could prove durable if 2027 capex remains robust and Nvidia expands software monetization; in that case, downside risk may be limited. Conversely, the feared macro or policy shock that would justify the bearish case may never materialize.
"Massive CapEx is not just a drag; it is a strategic moat that secures long-term market dominance for hyperscalers."
Gemini’s utility analogy is the missing link. We are obsessing over CapEx as a cost, but failing to model it as a defensive moat. If these hyperscalers successfully internalize the AI stack—moving from renting compute to owning proprietary silicon and energy-efficient data centers—the 'CapEx drag' becomes a barrier to entry that crushes smaller competitors. We aren't looking at a bubble; we are looking at a consolidation of digital infrastructure that justifies premium long-term multiples.
"CapEx moat-building heightens antitrust breakup risks for hyperscalers, undermining defensibility."
Gemini, your CapEx-as-moat pivot sounds compelling but ignores antitrust timebombs: MSFT's FTC battles over OpenAI ties, META's looming DMA fines in EU, NVDA's CUDA monopoly probes. 'Internalizing the stack' screams 'breakup target' to regulators, not barrier to entry—potentially forcing divestitures that vaporize those investments. We're not building utilities; we're fueling monopolies in a trustbuster era.
"Regulatory risk is priced differently depending on execution speed: if margins expand faster than enforcement moves, current multiples survive the antitrust overhang."
Grok's antitrust risk is real, but the timing assumption is loose. MSFT, NVDA, META face regulatory scrutiny today—not hypothetically. Yet breakup timelines stretch years; capex moats compound quarterly. The question isn't whether regulators *could* act, but whether enforcement moves faster than margin expansion. If hyperscalers hit 35%+ EBITDA margins by 2026 before any forced divestitures, valuations may have already repriced the risk. Grok conflates regulatory risk with regulatory *inevitability*.
"The moat from internalizing the AI stack depends on ongoing capex and silicon access; if capex slows or supplier dynamics shift, margins could compress and valuations reprice before regulators act."
Grok, your antitrust warning is valid, but the bigger, under-discussed risk is capex sustainability and supplier dynamics. Even if regulators drag their feet, the moat from internalizing the stack hinges on perpetual access to advanced silicon and cheap energy. A faster capex pullback, easing supply constraints, or weaker AI monetization could compress margins and rerate multiples before any breakup action materializes. Regulation alone may not rescue valuation if the core fundamentals deteriorate or capex becomes less persuasive.
Panel Verdict
No ConsensusThe panelists agree that current AI-related stocks are not necessarily bargains despite recent price drops, as they face significant risks such as high capital expenditure, regulatory challenges, and potential saturation in AI adoption. They also debate whether the high CapEx can serve as a defensive moat or an antitrust concern.
The potential for high capital expenditure to serve as a defensive moat
Regulatory challenges and potential antitrust actions against the hyperscalers