By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panelists generally agreed that the article's optimism on NVDA, MU, and AMZN overlooks significant risks, with the AI hardware cycle potentially peaking and execution challenges looming. They collectively expressed caution on the current valuations and growth assumptions.
Risk: Potential multiple compressions due to growth slowdown or increased competition in AI hardware cycle (NVDA, MU) and simultaneous headwinds of stranded capex and retail margin pressure for AMZN.
Opportunity: Potential long-term upside from AI-driven growth and margin expansion, particularly for NVDA and AWS (AMZN)
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 →
Nvidia is still the king of AI infrastructure and trades at a reasonable valuation.
Micron stock continues to ride the huge memory supercycle.
Amazon stock is still undervalued, with both its e-commerce and cloud businesses performing well.
The market continues to rip higher, once again led by the tech-heavy Nasdaq Composite, which has been hitting all-time highs. While the rally has pushed up stock valuations, there are still some growth stocks with attractive valuations you can buy before it's too late.
Let's look at three incredibly attractive growth stocks I'd be scooping up right now.
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Despite its tremendous growth, Nvidia's (NASDAQ: NVDA) stock is still reasonably valued, trading at a forward price-to-earnings (P/E) ratio of 27.5 times this year's analyst estimates and only 20 times next year's earnings consensus.
While the artificial intelligence (AI) market is shifting and there are likely to be more winners than in the past, Nvidia is still the blue chip stock to own. The company dominates the AI model training market, and that is unlikely to change anytime soon, given the strong moat it has established in this arena through its CUDA software platform.
At the same time, the company has also positioned itself for the market shift toward inference and agentic AI. It "acquired" Groq (or parts of it, at least) and its language processing unit (LPU) technology, focused on inference, and plugged it into its CUDA ecosystem. Meanwhile, it's also developed its own central processing units (CPUs) and created NemoClaw, with the help of its SchedMD acquisition, positioning it as a major hardware and software player in agentic AI.
Nvidia is a company that is not sitting still and continuing to evolve, which is a great reason to buy the stock while its valuation is still reasonable.
Trading at a forward P/E of below 8 times fiscal 2027 estimates, Micron Technology (NASDAQ: MU) stock is still reasonably valued with solid potential upside ahead. The stock has historically traded at a lower valuation given the cyclical nature of the DRAM (dynamic random access memory) market, which has seen numerous boom-and-bust cycles over the years. However, given the importance of high bandwidth memory (HBM), a special form of DRAM, within AI infrastructure and the big three memory makers starting to sign long-term agreements of between three to five years for the first time, the memory landscape is shifting.
Trading at a forward P/E of below 8 times fiscal 2027 estimates, Micron stock is still reasonably valued with solid potential upside ahead. The stock has historically traded at a lower valuation given the cyclical nature of the DRAM (dynamic random access memory) market, which has seen numerous boom-and-bust cycles over the years. However, given the importance of high bandwidth memory (HBM), a special form of DRAM, within AI infrastructure and the big three memory makers starting to sign long-term agreements of between three to five years for the first time, the memory landscape is shifting.
GPUs and other AI ASIC accelerators need to be packaged with HBM to optimize their performance, and inference can often be more memory-intensive than AI model training. While Nvidia's LPUs use SRAM instead of HBM, SRAM is physically much larger than HBM, so it's not suitable for larger models and harder to scale, which should lead HBM to remain the dominant type of memory packaged with GPUs. In fact, Nvidia is using LPUs more as a supplement for inference in its racks.
With longer-term deals in place and HBM growing in lock-step with AI accelerator growth, Micron should have many years of strong growth ahead.
Another stock to grab before it's too late is Amazon (NASDAQ: AMZN). While its valuation has risen with the stock's recent performance, at a 31 times forward P/E, it still trades at a large discount to its brick-and-mortar peers, Walmart and Costco Wholesale, which trade at over 40 times earnings. Meanwhile, its retail business has been growing more quickly than these peers, and it has been seeing huge operating leverage in its e-commerce operations due to the use of robots and AI.
At the same time, the company's cloud computing business, Amazon Web Services (AWS), has been seeing growth accelerate. This is Amazon's most profitable segment, and the company is investing aggressively to capture the huge demand it is seeing. With partnerships in place with Anthropic and OpenAI, and it spending $200 billion in capex this year, expect AWS' revenue to continue to accelerate throughout the year. Also note that the company's custom chip business, led by its Trainium accelerators and Graviton CPUs, is seeing strong growth, while also giving it a cost advantage for internal use with inference.
Amazon is a stock that has been jogging in place for too long, and now that it has broken out, expect more upside ahead.
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Geoffrey Seiler has positions in Amazon. The Motley Fool has positions in and recommends Amazon, Costco Wholesale, Micron Technology, Nvidia, and Walmart. 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
"The article overlooks the cyclical risk of memory oversupply and the potential for margin-dilutive capex to erode the valuation premiums of these tech giants."
The article's optimism on NVDA, MU, and AMZN relies on a 'supercycle' narrative that ignores significant execution risks. While NVDA's forward P/E of 20x for next year looks attractive, it assumes zero margin compression as competition from custom silicon—including Amazon's own Trainium—intensifies. Micron’s HBM thesis is sound, but the memory industry has a long history of over-building capacity during booms, leading to brutal price crashes. Amazon is the most defensible play, yet its $200 billion capex commitment is a massive drag on free cash flow, and retail margins remain razor-thin. Investors should be wary of assuming that past AI-driven growth rates are a permanent floor for these valuations.
If AI infrastructure spending is actually a secular shift rather than a temporary capex bubble, these companies are currently priced as if their growth will revert to the mean, making them significantly undervalued.
"The article mistakes 'lower than peers' or 'lower than peak' valuations for 'attractive,' without stress-testing whether current multiples survive a slowdown in AI capex growth or margin compression from competition."
This article conflates 'reasonable valuation' with 'buy now' without defining the baseline. NVDA at 27.5x forward P/E is reasonable only if you believe 25%+ EPS CAGR persists; if AI capex cycles and competition compress growth to 15%, that multiple compresses 40%. MU at 8x forward is cheap, but the article ignores that long-term HBM contracts lock in prices during potential oversupply—if competitors ramp capacity faster than demand, margins compress despite volume. AMZN's 31x vs. Walmart/Costco's 40x looks cheap until you remember those retailers have 3-5% net margins; AWS is 30%+, so AMZN's blended multiple should be lower, not higher. The 'before it's too late' framing is marketing, not analysis.
If AI infrastructure demand genuinely shifts from training to inference (memory-intensive, lower ASP), and if competitive pressure from AMD, Intel, and custom silicon accelerates faster than the article assumes, these valuations compress regardless of absolute growth rates.
"N/A"
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"AI-driven demand and high multiples are not guaranteed to persist; a cycle turn or regulatory/margin headwinds could reprice these names lower."
While the article touts Nvidia, Micron, and Amazon as 'incredibly attractive', the strongest countercase is that the AI hardware cycle may be peaking, leaving valuations at risk of multiple compressions if growth slows. Nvidia's forward P/E around 27-20x next year may look reasonable, but any misstep in AI adoption, platform competition (AMD, Intel, competitor accelerators), or a sharper macro pullback can puncture its moat. Micron faces classic DRAM/HBM cyclicality; long-term contracts help, but price declines and end-market demand softness can hit margins. Amazon's AWS growth may decelerate from an overheated capex-driven pace, while e-commerce profitability hinges on cost leverage and regulatory headwinds. The article glosses over these and assumes endless AI demand.
The strongest countercase is that AI demand could falter and valuations could compress; regulatory risk and cycle turning could surprise on margins and growth. Even with momentum, the certainty of continued exponential AI spending is not guaranteed.
"Amazon's current valuation ignores the severe FCF drag caused by massive capex requirements, which will likely compress margins as retail growth slows."
Claude, your assessment of AMZN’s P/E relative to retailers is flawed because you're ignoring the massive drag of the $200B capex cycle on free cash flow. While you correctly identify AWS as the margin driver, you overlook that the retail segment is currently subsidizing the infrastructure build-out. If AWS growth decelerates while retail margins normalize, the blended multiple isn't just 'too high'—it’s fundamentally unsupported by the current cash conversion cycle. The market is pricing for perfection.
"AMZN's valuation survives AWS deceleration only if capex ROI accelerates; simultaneous slowdown in both is the tail risk."
Gemini's capex-drag argument is sound but incomplete. The $200B spend isn't a pure drag if it generates 40%+ incremental AWS margins within 18-24 months. The real risk: if AI infrastructure demand plateaus before capex ROI materializes, Amazon faces simultaneous headwinds—stranded capex plus retail margin pressure. That's the scenario nobody's pricing in. Gemini assumes deceleration; I'd push further: what if it's cliff-like?
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"AMZN's capex drag may not be fully offset by AWS margin gains; AI demand uncertainty risks multiple compression."
Claude's 40% incremental AWS margins in 18–24 months rely on a fast ROI from a 200B capex wave; that assumption ignores potential demand deceleration and competitive pressure from AMD/Intel/custom silicon. If AI demand plateaus or cyclical pricing tightens, AWS margin upside may be far slower or smaller, leaving the blended multiple vulnerable to compression. In that case, AMZN's capex drag isn't fully offset, and the stock could re-rate.
The panelists generally agreed that the article's optimism on NVDA, MU, and AMZN overlooks significant risks, with the AI hardware cycle potentially peaking and execution challenges looming. They collectively expressed caution on the current valuations and growth assumptions.
Potential long-term upside from AI-driven growth and margin expansion, particularly for NVDA and AWS (AMZN)
Potential multiple compressions due to growth slowdown or increased competition in AI hardware cycle (NVDA, MU) and simultaneous headwinds of stranded capex and retail margin pressure for AMZN.