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AI Infrastructure Stocks to Buy on the Dip - 500-Word Summary

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  Published in Stocks and Investing on Thursday, November 20th 2025 at 13:05 GMT by The Motley Fool

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AI Infrastructure Stocks to Buy on the Dip – A 500‑Word Summary

The article from MSN Money, titled “2 AI infrastructure stocks to buy on the dip”, highlights how the current slowdown in the technology market presents a buying opportunity for investors looking to capitalize on the long‑term growth of artificial‑intelligence (AI) infrastructure. While the piece is concise, it offers a surprisingly detailed look at two specific stocks, explains why they’re positioned to thrive as AI adoption accelerates, and provides practical guidance on timing purchases during a market dip.

1. The Landscape: Why AI Infrastructure Matters

At the heart of the article is the observation that AI is no longer a niche buzzword. Instead, it is becoming a core component of many enterprise and consumer services—everything from cloud‑based data centers to autonomous vehicles. This has led to a surge in demand for specialized hardware (GPUs and other accelerators), software stacks, and data‑center capabilities. The author notes that companies that provide the underlying infrastructure for AI workloads are therefore likely to benefit from sustained growth, even when the broader tech sector is experiencing volatility.

2. The First Pick: Advanced Micro Devices (AMD)

Why AMD?
- Chip‑design expertise: AMD has positioned itself as a strong competitor to NVIDIA in the GPU space, especially with its Radeon Instinct line of data‑center GPUs. The article emphasizes that AMD’s RDNA architecture is increasingly being adopted by major cloud providers. - Diversification: Beyond GPUs, AMD’s central‑processing‑unit (CPU) business and its data‑center processor segment (EPYC) provide additional revenue streams that can buffer the company against GPU‑specific downturns. - Margin health: The piece cites AMD’s improved operating margins in recent quarters, a sign that the company is effectively managing its cost structure even as demand rises.

What the article suggests for investors:
- Buy on the dip: Given AMD’s current price volatility, the author recommends buying a small position during a short‑term sell‑off. Because the stock has a high beta, a dip could create a favorable entry point. - Set a target: The article proposes a price target based on a 12‑month forward P/E ratio that is slightly above the industry average but justified by the expected upside from AI demand.

3. The Second Pick: NVIDIA (NVDA)

Why NVIDIA?
- Market dominance: NVIDIA is the undisputed leader in GPU sales for AI, gaming, and professional visualization. The article stresses that the company’s data‑center revenue has seen double‑digit growth over the last two years. - Ecosystem advantages: NVIDIA’s software stack—CUDA, TensorRT, and the entire ecosystem of developer tools—creates a high switching cost for customers. The piece points out that once an AI platform is built around NVIDIA, migration costs are significant. - Expanding product lines: Recent launches such as the H100 GPU and the DGX systems are already positioned for high adoption in enterprise AI workloads. The article highlights the projected revenue impact of these products.

What the article suggests for investors:
- Watch for a pullback: Even though NVIDIA is often priced in for the AI boom, the author notes that short‑term market swings can create buying opportunities. - Use dollar‑cost averaging: Because the stock is a “mega‑cap” and can swing by a few percent in a day, the article recommends buying in smaller increments rather than a lump sum.

4. How to Time the Dip

The article devotes a short but actionable section to timing. The key points are:

1. Look for macro‑market cues – An earnings miss by a broader index (e.g., S&P 500) often creates a temporary dip in tech stocks.
2. Use technical levels – A 200‑day moving average or a significant Fibonacci retracement level can signal a “good entry” point.
3. Consider macro‑fundamental indicators – If overall interest rates rise or if the dollar strengthens, AI stocks might underperform temporarily.

The author stresses that timing is less about predicting a perfect moment and more about identifying a “reasonable price” relative to the company’s long‑term fundamentals.

5. Risks and Caveats

No investment is risk‑free, and the article lists several caveats:

• Valuation risk – Both AMD and NVIDIA trade at premium valuations. A market correction could erode expected earnings multipliers.
• Supply‑chain constraints – The global chip shortage still lingers, and any disruption could slow production for both companies.
• Competitive threat – Other players, notably AMD and Intel, are investing heavily in AI hardware, potentially eroding NVIDIA’s market share.
• Regulatory risk – Emerging data‑privacy and AI‑ethics regulations could impose new compliance costs on data‑center operators.

The piece recommends diversifying across other AI‑infrastructure sectors—cloud providers like Microsoft or Amazon, or semiconductor companies like Taiwan Semiconductor Manufacturing Company (TSMC)—to spread exposure.

6. Bottom Line

In its nutshell, the MSN Money article argues that while the broader tech sector may see a dip, AI infrastructure stocks are poised for long‑term growth due to sustained demand for GPUs, CPUs, and data‑center solutions. By focusing on AMD’s diversification and NVIDIA’s ecosystem dominance, investors can strategically position themselves to benefit from the AI wave. The recommended approach is cautious: buy on a dip, use dollar‑cost averaging, and stay mindful of valuation and supply‑chain risks.

For readers who want a deeper dive, the article links to related content on AI fundamentals, market analyses, and a short guide on how to evaluate semiconductor earnings. By following those links, investors can broaden their understanding of the industry dynamics that underpin the recommended stock picks.