Investors are increasingly debating whether parts of the artificial intelligence trade are starting to look like value. Among the most scrutinized names are Nvidia and Microsoft, two companies central to AI infrastructure and software—yet both have seen the market’s expectations shift in ways that, according to valuation measures cited in a recent analysis, make their earnings multiples appear relatively muted compared with what many investors typically pay for growth.
The comparison centers on price-to-earnings levels: Nvidia is described as trading at a P/E of 32, while Microsoft is noted at a P/E of 23. The analysis also points to divergences in performance this year—Nvidia has struggled to outperform the S&P 500 while Microsoft stock has pulled back—despite both benefiting from ongoing AI demand.
Key takeaways
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Nvidia is described as trading at about 32 times earnings, a level viewed as low relative to its AI-driven run-up.
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Microsoft is described as trading around 23 times earnings, closer to value territory as investors digest recent challenges.
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Catalyst for the “value” discussion is the combination of strong prior performance and then an expectation reset, particularly tied to AI spending and growth durability.
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Implication: both stocks may look less expensive on earnings, but the market remains sensitive to capex, competition, and how AI workloads flow through each company’s business.
What the valuation debate is focusing on
In the referenced analysis, Nvidia is framed as an outlier among AI leaders because the stock has already delivered an outsized surge from its 2022 low, yet still trades at a multiple only slightly above the S&P 500’s average P/E level mentioned by the report. That mismatch—between Nvidia’s growth story and its current earnings multiple—is presented as the core reason some investors are starting to label it a “value” candidate.
The same piece contrasts Microsoft’s current positioning: after a pullback earlier this year, the company’s earnings multiple is described as near multiyear lows, implying that investors have priced in more skepticism than usual around its outlook.
Nvidia: why some investors see “margin of safety”
The report argues that Nvidia’s valuation looks inexpensive in the context of its role in AI accelerators and the generative AI boom. It cites that Nvidia’s revenue and profitability growth remain robust in the latest fiscal period referenced: for the first quarter of fiscal 2027 (ended April 26), the analysis says revenue rose 85% year over year and net income increased 211% over the same period.
Despite that growth, the analysis points to reasons investors may be stepping back from paying a larger premium. One is simply scale: with a market capitalization cited in the report at $5.1 trillion, the author suggests it becomes harder for even strong companies to deliver “10-bagger” returns. Another is concern over capital expenditure commitments from hyperscalers, which could affect the pacing of accelerator demand.
To support the case that Nvidia may still offer a risk-managed growth profile, the report also highlights balance-sheet flexibility, including liquidity of more than $80 billion and relatively lower capex spending compared with the market’s broader AI infrastructure buildout. The author notes Nvidia spent $6.5 billion on capex in the last 12 months, positioning the company as able to innovate without the same funding strain faced by larger AI buyers.
Microsoft: a value-like multiple shaped by capex and AI uncertainty
While the analysis acknowledges Microsoft remains a defensive favorite for many investors, it argues that the company’s current earnings multiple is lower partly because the market is focused on execution risks and spending requirements. The report references Microsoft’s plan to spend $190 billion on capex this year, which it says has made some investors uneasy.
Beyond capex, the analysis notes investor questions about software economics. It cites concerns that AI can perform tasks that have historically belonged to parts of the software stack—raising skepticism for certain subscription-oriented models in the broader industry. It also references market uncertainty tied to Microsoft’s relationship with OpenAI and how investors interpret Microsoft’s AI differentiation and monetization strategy.
Still, the report stresses Microsoft’s financial momentum in the period it covers. For the third quarter of fiscal 2026 (ended March 31), it says revenue rose 17% annually and net income climbed 23% year over year. It also points to substantial liquidity of about $78 billion, implying Microsoft can fund both AI-related investments and other priorities even amid elevated spending.
On valuation, the report places Microsoft at a P/E of 23, arguing that while its growth may not match Nvidia’s rate, the earnings multiple is sufficiently depressed to offset near-term concerns in the author’s view—making the stock look attractive at current levels.
Nvidia versus Microsoft: why one may screen cheaper
The author’s conclusion is that Nvidia currently provides the stronger “value” profile between the two. The argument is less about disproving Microsoft’s fundamentals and more about comparing how each company’s earnings multiple relates to growth and competitive positioning.
According to the analysis, even if Nvidia’s revenue growth slows from the pace cited for its latest quarter, the report suggests the stock would not necessarily become expensive at a 32 P/E unless growth decelerates meaningfully beyond expectations. It also attributes Nvidia’s valuation support to continued leadership in the AI accelerator market, with the report suggesting that competitive pressure would be unlikely to remove Nvidia’s advantage soon.
For investors, the implied trade-off is timing and uncertainty: Microsoft’s valuation may reflect investors’ worries about AI-driven disruption and high spending, while Nvidia’s valuation may reflect skepticism about hyperscaler capex cycles and the durability of high growth. In both cases, the market’s willingness to underwrite continued earnings expansion appears to be the key variable.
What to watch next
Next up for both companies is how they translate AI demand into sustained earnings growth while managing capex intensity. Investors will likely focus on forward guidance around AI infrastructure spending cycles, updates on cost discipline and liquidity usage, and evidence of how AI workloads are shifting across hardware and software ecosystems. Quarterly results and any additional commentary on capex plans could be especially influential for how these “value” narratives develop.
