Prediction: Nvidia Stock Could Rally After May 28

In This Article:

Key Points

  • Nvidia will continue to benefit from strong global demand for AI infrastructure.

  • Already a leader in the AI training market, Nvidia is also dominating the growing AI inference market.

  • Given its robust fundamentals and reasonable valuation, the company's stock has a strong chance of rising after its first-quarter results.

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A long-time darling of the stock market, Nvidia's (NASDAQ: NVDA) stock fell more than 40% from its 52-week high in January 2025 to a 52-week low in April 2025. Investors were concerned about the potential decline in enterprise spending on artificial intelligence (AI) infrastructure and the impact of tariff wars.

However, investor sentiment has recently turned for the better after Nvidia announced recent developments regarding its partnership with Humain, a new AI-focused branch of Saudi Arabia's Public Investment Fund. The stock has recovered most of its losses and is up 30% in the last month. While the stock remains approximately 9% below its January high, it appears positioned to surge in the coming months, especially after it releases its first-quarter 2026 earnings results (for the period ending April 27) on May 28.

An analyst presents a stock chart and key financial data to colleagues during a strategy meeting in a modern office.
Image Source: Getty Images.

Here are some reasons that support this hypothesis.

Continued dominance in the AI infrastructure market

Nvidia is an undisputed leader, accounting for roughly a 90% share of the data center graphics processing unit (GPU) market. The company stands to benefit significantly from the rapid expansion in data center capital expenditures, projected to increase from roughly $500 billion in 2025 to $1 trillion by 2028. Many cloud players reiterated their commitments to investing in AI infrastructure, which contradicts the narrative of a potential slowdown in AI spending.

Nvidia's market dominance is also set to continue, as evidenced by the robust demand for its Blackwell architecture systems, which are in full production across multiple configurations. Blackwell is already a success, accounting for $11 billion in revenues in the fourth quarter.

Blackwell has been optimized for running inference workloads, including the real-time deployment of AI models, such as computationally intensive reasoning AI or long-term thinking models. AI inference presents a significantly larger opportunity than AI training workloads, since a trained model is used multiple times in production. By offering dramatically higher price performance than previous Hopper architecture chips, Blackwell is well positioned to capitalize on this opportunity.