How AI Factory Expansion Will Impact NVIDIA (NVDA) Investors

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How AI Factory Expansion Will Impact NVIDIA (NVDA) Investors Sasha Jovanovic Thu, October 29, 2026 at 11:15 PM EDT 7 min read NVDA -0.80% ORCL -3.45% META +1.96% NVIDIA announced a broad slate of AI platforms, including the OpenShell Reference Architecture, DSX POD modular AI factories and RTX Spark PCs, alongside expanded collaborations with Oracle, Meta and industrial partners to scale AI training, inference and agent workloads across cloud, data center and edge environments. The news highlights NVIDIA's push to move from selling chips to supplying full AI factory blueprints, from liquid-cooled Vera Rubin clusters down to on-device RTX Spark systems, tightening its role in how customers design, deploy and govern large scale AI infrastructure. We will look at how NVIDIA's shift toward full-stack AI factories, highlighted by DSX POD, could shape its long-term investment narrative. Spot 54 AI infrastructure stocks that, like NVIDIA's partners, are building the compute, networking, and edge systems behind large-scale AI factories and agent workloads. To own NVIDIA, you have to believe AI factories keep scaling and that the firm keeps converting its backlog into shipped Vera Rubin capacity, despite supply constraints and rising input costs. In the short term, the key swing factor is how quickly those multi gigawatt buildouts translate into recognized data center revenue, while margins drift from the mid 70s toward the guided low 70s range. The biggest risk right now is not demand; it is concentration and competition. Large cloud customers are pushing in house accelerators, and regulators are scrutinizing deals like Hugging Face. The latest Oracle expansion strengthens NVIDIA's role in third party AI infrastructure and therefore supports the core thesis rather than changing it. The Oracle Cloud Infrastructure announcement is the clearest read through for NVIDIA's AI factory story. Scaling OCI superclusters with Vera Rubin NVL72 and Vera CPUs, plus Spectrum X networking, ties directly into the idea that revenue per gigawatt rises as customers adopt full stack Vera Rubin platforms instead of buying stand alone GPUs. Operationally, the Oracle deal matters because it lets customers scale CPU and GPU capacity independently. This aligns well with agentic workloads that are relatively GPU light but CPU hungry between model calls. That supports the key catalyst that AI factories need both accelerators and Vera CPUs at scale, while leaving intact the risk that over time, hyperscalers could still shift part of that stack to their own silicon. Analyst models around NVIDIA are not just big picture stories about AI factories. They are built on very specific revenue and earnings assumptions that readers can sanity check against their own view of how AI buildouts and chip supply might play out. The current consensus assumes NVIDIA's top line grows by 48.7% a year over the next three years, even as profit margins move from 63.7% today toward 54.3% in three years. That mix of rapid sales expansion and lower profitability per dollar of revenue sketches a future where scale matters more than peak margin, which fits the AI factory framing of Vera Rubin and Grace Blackwell clusters serving enormous workloads for hyperscalers, neoclouds and industrial customers. On earnings, analysts expect net profit to move from US$192.9b today to US$540.6b by 2029. That is an increase of about 2.8x in absolute profits, with the spread between the most bullish estimate at US$695.4b and the most cautious at US$379.5b highlighting how widely views differ on how far NVIDIA can extend its AI factory footprint. The same models assume the share count edges down by 0.82% per year for three years, so a portion of earnings growth per share is driven by buybacks rather than just higher net income. Valuation assumptions are just as specific. To line up with the analyst price target, NVIDIA would need to be earning US$540.6b on roughly US$995.9b of revenue in 2029 while trading at a P/E of 19.7x, down from 28.6x today and well below the cited 48.6x for the broader US semiconductor group. The consensus target price of US$328.72 sits 30.5% above a current quote of US$228.52, but the spread between the US$515 bull case and the US$180 bear case reinforces that there is meaningful disagreement about how durable today's AI infrastructure spending will be. NVIDIA's narrative projects US$995.9b revenue and US$540.6b earnings by 2029. Analysts are baking in 48.7% yearly revenue growth and an earnings increase of about 2.8x from US$192.9b today to reach that 2029 consensus figure. For readers tracking AI infrastructure beyond just NVIDIA, these assumptions set a useful reference frame. If AI factories, agentic workloads and broader accelerated computing demand scale in a way that supports close to US$1t of annual revenue and over half a trillion dollars of profit for a single supplier, that implies an enormous opportunity for the wider supply chain in power, networking, memory, cooling, and software orchestration that underpins DSX POD style deployments. Uncover why NVIDIA's fair value indicates a 54% potential upside to its current price, which could narrow quickly. One alternate NVIDIA story puts far more weight on DSX POD style AI factories as a long term earnings engine than the baseline view. Those bullish analysts were penciling in US$1,386.1b of revenue and US$673.4b of earnings by 2029 before the Oracle supercluster news, which could push their already optimistic narrative even further if they decide this latest buildout supports faster full stack adoption. Opinions clearly stretch from cautious to very optimistic, so treat this as a cue to compare several narratives before deciding how you see NVIDIA's future. Explore 86 other NVIDIA fair value estimates , including one that suggests up to 128% upside from the current price. Don't just follow the ticker. Dig into the data and build a conviction that's truly your own. A great starting point for your NVIDIA research is our analysis highlighting 4 key rewards and 2 important warning signs that could impact your investment decision. See our latest analysis for NVIDIA. The report includes a comprehensive fundamental analysis summarized in a single visual, the Snowflake, making it easy to evaluate NVIDIA's overall financial health at a glance. If NVIDIA has sharpened your interest in AI infrastructure, it can be useful to compare it with other businesses that show strong fundamentals or different risk and income profiles. The Simply Wall St Screener lets you move from a single stock story to a watchlist built around the metrics that matter most to you. If resilience and downside protection are high on your list, start with a basket of 30 resilient stocks with low risk scores that keep risk scores in focus. For readers who care most about balance sheets and cash backing the story, filter the market using a list of solid balance sheet and fundamentals (23 results) to see which companies match that profile. If you prefer to hunt for tomorrow's potential leaders before they are widely followed, scan through 18 high quality undiscovered gems and see which ones fit your own thesis. This article by Simply Wall St is general in nature. We provide commentary based on historical data and analyst forecasts only using an unbiased methodology and our articles are not intended to be financial advice. It does not constitute a recommendation to buy or sell any stock, and does not take account of your objectives, or your financial situation. We aim to bring you long-term focused analysis driven by fundamental data. Note that our analysis may not factor in the latest price-sensitive company announcements or qualitative material. Simply Wall St has no position in any stocks mentioned. Companies discussed in this article include NVDA . Have feedback on this article? Concerned about the content? Get in touch with us directly. Alternatively, email editorial-team@simplywallst.com

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