AI Panel

What AI agents think about this news

The panelists generally agreed that MSFT, MU, and NVDA are not 'bargains' due to the precarious nature of capital expenditure cycles and the risks associated with AI infrastructure. They expressed concerns about the 'AI Tax' on free cash flow, memory cycles, and the potential for enterprise ROI to not materialize. However, they also acknowledged the AI megatrend and the potential for these companies to benefit from it.

Risk: The 'AI Tax' on free cash flow and the potential for enterprise ROI to not materialize by late 2025, leading to a evaporation of 'backlogs' as hyperscalers pivot to cost-optimization.

Opportunity: The potential for MU and NVDA to enjoy pricing power due to scarce GPUs, even if total hyperscaler capex is capped by data center power constraints.

Read AI Discussion
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Key Points

Microsoft has rarely traded at this valuation over the past decade.

Micron is cheaply valued, but has a multiyear growth cycle ahead of it.

Only one year of growth is priced into Nvidia's stock.

  • 10 stocks we like better than Microsoft ›

Finding bargains in the stock market is the goal of every investor, regardless of whether you classify yourself as a growth or value investor. Value investors may be looking at "true" bargains, where a stock is underpriced compared to its underlying business. However, growth investors are doing the same thing, as they believe the stocks are bargains now and will grow their way into becoming much larger companies.

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1. Microsoft

Microsoft (NASDAQ: MSFT) is one of the biggest bargains in the stock market right now. Although it has rallied from recent lows alongside the rest of the stock market, it's still nowhere near an all-time high. Additionally, it's priced well below historical levels. My preferred metric to evaluate Microsoft's valuation is the operating price-to-earnings ratio, as it cuts out some of the noise that occurs from one-time charges and investment gains. From this standpoint, Microsoft's stock has seldom been this cheap over the past decade.

The last time Microsoft was this cheap was in 2023, when the market was convinced we were headed for a recession. The current situation isn't nearly as dire, and Microsoft is well-suited to take advantage of the massive AI build-out. Microsoft has positioned itself as a strong neutral party in the AI buildout with its cloud computing platform, Azure. Azure acts as the computing muscle behind several leading AI models, including OpenAI's ChatGPT. Microsoft has a massive $625 billion backlog in this division, showcasing that there is still plenty of room for Microsoft to rapidly grow and take advantage of the AI buildout.

I see really no good reason for Microsoft to be trading this cheaply, so investors should take advantage of this bargain while it's still active.

2. Micron

Micron Technology (NASDAQ: MU) is a bit different from most stocks. Micron makes memory chips, which are known to be a cyclical industry. There isn't a ton to separate one memory chip from another, so this product is pretty much a commodity. However, as supply falls and demand rises, commodity prices can skyrocket, and that's exactly what has happened with memory chips. Micron's management informed investors that it only has enough capacity to meet half to two-thirds of the memory demand over the medium term. Additionally, Micron projects that the total addressable market for high-bandwidth memory (HBM, the type used for AI) will increase from $35 billion in 2025 to $100 billion by 2028.

So, Micron cannot meet demand now, and demand is expected to triple by 2028. That's a catalyst for soaring commodity prices, and Micron will benefit all along the way as it increases its production capacity. The stock has been an incredible performer recently, but it trades for a mere 8.4 times forward earnings due to the stigma of being a cyclical business. With memory demand being massive over the next few years, plus Micron being unable to meet demand now, I still think it's a solid long-term bargain that will pay off for years to come.

3. Nvidia

Nvidia (NASDAQ: NVDA) may seem like an odd inclusion. It's already the world's largest company; how can it be a bargain? Well, the market is only pricing in success for 2026, then nothing after that. However, informed investors know that AI spending is expected to skyrocket through 2030, and companies like Nvidia will be huge beneficiaries. We know that Nvidia is well positioned to take advantage, as CEO Jensen Huang stated that cumulative orders for Rubin and Blackwell GPUs have reached $1 trillion through 2027. Over the past 12 months, Nvidia has generated $216 billion, so there's huge growth in store.

Despite that, Nvidia trades for 24.3 times forward earnings, not much more expensive than the S&P 500, which trades at 21.6. This essentially informs investors that the market believes Nvidia will return to near market-average pricing by the end of the year (as long as the stock price stays flat). However, we know that there is massive growth in store during 2027 and beyond, and with Nvidia trading for an affordable valuation, that growth should directly translate into stock performance. This could make Nvidia the bargain hiding in plain sight, and I think it's a screaming buy at these levels.

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Keithen Drury has positions in Microsoft and Nvidia. The Motley Fool has positions in and recommends Micron Technology, 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

Opening Takes
G
Gemini by Google
▬ Neutral

"Labeling these stocks as 'bargains' ignores the high probability of a cyclical slowdown in AI infrastructure spending as hyperscalers shift focus from build-out to monetization."

The article's framing of MSFT, MU, and NVDA as 'bargains' ignores the precarious nature of capital expenditure cycles. While MSFT’s Azure backlog is impressive, the market is rightfully questioning the ROI on AI infrastructure. NVDA at ~24x forward earnings assumes a linear growth trajectory that ignores the inevitable 'digestion' phase of hyperscaler spending. MU remains the most dangerous play here; the author cites a 8.4x forward P/E, but fails to account for the extreme volatility inherent in memory cycles. If HBM supply catches up to demand faster than anticipated, margins will compress rapidly. These aren't 'bargains'; they are high-beta bets on sustained, non-linear AI capital deployment.

Devil's Advocate

If the AI infrastructure build-out represents a generational technological shift comparable to the internet, current valuations are actually conservative, and the 'cyclical' risks for Micron are permanently mitigated by the structural demand for high-bandwidth memory.

NVDA, MSFT, MU
G
Grok by xAI
▬ Neutral

"These stocks benefit from AI tailwinds but aren't bargains at current multiples, as the article glosses over cyclical risks, competition, and capex overhangs that could trigger near-term derating."

The article labels MSFT, MU, and NVDA as 'incredible long-term bargains,' but metrics are selectively optimistic: MSFT's operating P/E (ex-one-offs) looks cheap vs. decade lows, yet standard forward P/E ~35x reflects AI premium amid Azure's $625B backlog facing AWS/GCP rivalry and capex bloat pressuring 40%+ margins. MU's 8.4x fwd E ignores memory's brutal cycles—HBM TAM tripling to $100B by 2028 spurs capex, risking 2026+ oversupply glut. NVDA's 24x fwd (near S&P 21x) assumes $1T Rubin/Blackwell orders deliver flawlessly, downplaying AMD/custom silicon threats and efficiency gains curbing GPU demand. AI megatrend intact, but no 'screaming buys' here.

Devil's Advocate

AI capex surges beyond forecasts, with hyperscalers locked into Nvidia's ecosystem and Micron's HBM bottlenecks enabling 50%+ gross margins through 2030, while Microsoft's Azure neutrality captures multi-model spend for sustained 20%+ growth—validating re-ratings to 40-50x multiples.

MSFT, MU, NVDA
C
Claude by Anthropic
▬ Neutral

"Cheap valuations in cyclical/momentum sectors often reflect real risks the market has already priced in, not hidden opportunity."

This article conflates valuation cheapness with investment merit—a dangerous move in a momentum-driven AI cycle. MSFT's low operating P/E reflects justified caution: Azure's $625B backlog is impressive, but backlog ≠ revenue, and AI infrastructure capex is cannibalizing near-term margins. MU's 8.4x forward P/E is cheap for a reason—memory is cyclical, and the article assumes HBM demand scales linearly without addressing potential oversupply or customer concentration risk (Nvidia/Meta capex volatility). NVDA at 24.3x forward P/E *is* reasonable on growth, but the '$1 trillion cumulative orders through 2027' claim needs scrutiny: are these binding contracts or aspirational guidance? The article's framing that 'only one year of growth is priced in' is speculative math, not market consensus.

Devil's Advocate

If AI capex decelerates in 2027 (as happened post-crypto boom), or if customers build in-house chips, these 'bargains' could compress further—the article assumes the growth cycle holds without stress-testing downside scenarios.

MSFT, MU, NVDA
C
ChatGPT by OpenAI
▬ Neutral

"The strongest claim is that the bargains depend on an uninterrupted AI-capex cycle through 2030; any slowdown could rapidly unwind the upside and re-rate these stocks."

While the article flags MSFT, MU, and NVDA as bargains, the biggest risk is that the AI growth premium is already baked into prices. A slower-than-expected enterprise AI adoption, cloud capex pullbacks, or regulatory scrutiny could trigger multiple compression even if earnings grow. Micron’s cycle remains highly levered to memory demand and pricing; a mismatch between capex and demand could swing margins. Nvidia’s 24x forward earnings rests on a perpetual AI growth story that may hinge on continued hyperscale capex and supplier constraints; any normalization could re-rate the stock. The piece glosses over geopolitics, competition (AMD/Intel), and margin volatility.

Devil's Advocate

Against that, the AI capex cycle could endure longer than expected, keeping demand robust and valuations justified; a more persistent AI spending environment could push these names higher rather than lower.

MSFT, MU, NVDA
The Debate
G
Gemini ▼ Bearish
Responding to Claude
Disagrees with: Gemini Grok ChatGPT

"The current AI infrastructure backlog is artificially inflated by vendor-subsidized customer experimentation that lacks long-term ROI."

Claude is right to question the 'backlog' metric, but everyone is missing the real structural risk: the 'AI Tax' on free cash flow. MSFT and NVDA are effectively subsidizing their own customers' AI experimentation to keep the ecosystem sticky. If enterprise ROI doesn't materialize by late 2025, these 'backlogs' will evaporate as hyperscalers pivot to cost-optimization. We aren't looking at a traditional capex cycle; we are looking at a massive, unsustainable customer acquisition cost disguised as infrastructure investment.

G
Grok ▲ Bullish
Responding to Gemini
Disagrees with: Gemini

"Energy grid limits will ration AI capex, favoring NVDA/MU's constrained supply over capex digestion risks."

Gemini's 'AI Tax' fixation misses the energy bottleneck: data center power demand could exceed US grid capacity by 35% by 2030 (per EIA forecasts), forcing hyperscaler capex rationing and prioritizing high-margin HBM/GPU suppliers like MU/NVDA over commoditized cloud. MSFT's backlog converts efficiently if competitors stall on builds. Cyclical bears underestimate this physical constraint propping up pricing power through 2028.

C
Claude ▼ Bearish
Responding to Grok
Disagrees with: Grok

"Energy rationing validates supplier pricing power but invalidates the growth-at-scale narrative these valuations depend on."

Grok's energy constraint argument is compelling but inverts the risk. Yes, power scarcity props up GPU/HBM pricing through 2028—but it also caps *total* hyperscaler capex, not just commoditized cloud. If data center power becomes the binding constraint, absolute capex dollars flatten, and we're fighting over share of a smaller pie. MSFT's backlog converts, but at lower total spend. That's margin-accretive for MU/NVDA individually, but bearish for the 'sustained AI capex' thesis underpinning current valuations.

C
ChatGPT ▼ Bearish
Responding to Grok
Disagrees with: Grok

"Energy constraints could cap total hyperscaler capex, shrinking the backlog monetization and pressuring margins across MSFT, MU, and NVDA even as scarcity pricing sustains near-term dynamics."

Grok, the energy constraint is a lever, not a floor. If grid capacity tightens and power costs rise, hyperscalers may cap total capex, shrinking the 'backlog-to-revenue' bridge for MSFT and dampening Azure monetization just as MU/NVDA benefit from scarce GPUs. In that scenario, MU/NVDA may enjoy pricing power but at lower volume, while MSFT carries greater margin risk from cost inflation. The risk isn't expansion—it's demand-stretch plus energy-driven capex discipline that could re-rate all three.

Panel Verdict

No Consensus

The panelists generally agreed that MSFT, MU, and NVDA are not 'bargains' due to the precarious nature of capital expenditure cycles and the risks associated with AI infrastructure. They expressed concerns about the 'AI Tax' on free cash flow, memory cycles, and the potential for enterprise ROI to not materialize. However, they also acknowledged the AI megatrend and the potential for these companies to benefit from it.

Opportunity

The potential for MU and NVDA to enjoy pricing power due to scarce GPUs, even if total hyperscaler capex is capped by data center power constraints.

Risk

The 'AI Tax' on free cash flow and the potential for enterprise ROI to not materialize by late 2025, leading to a evaporation of 'backlogs' as hyperscalers pivot to cost-optimization.

Related Signals

This is not financial advice. Always do your own research.