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Nvidia Faces Historic Market Loss As DeepSeek Dents Confidence In AI’s Future

by THEFUTURE.TEAM

January 28, 2025

Nvidia experienced the largest single-day market cap drop in history on Monday, as its stock tumbled by 17%, shedding nearly $600 billion in value. This staggering loss is directly linked to a new development in the AI space—DeepSeek, a Chinese AI firm that unveiled its version of ChatGPT, raising concerns over the cost-efficiency and competitive positioning of U.S. AI companies.

Key Details

Nvidia’s shares experienced a severe decline, marking its worst daily percentage drop since March 2020, during the initial shock of the COVID-19 pandemic. On Monday, Nvidia lost a record-breaking $589 billion in market capitalization, more than doubling the previous one-day loss of $279 billion in September 2024. To put it into perspective, this is significantly more than Meta’s $251 billion market cap loss in February 2022.

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As a result, Nvidia’s market valuation dropped from $3.5 trillion to $2.9 trillion, slipping behind Apple and Microsoft as the world’s most valuable company. Nvidia’s dramatic fall led a broader retreat in U.S. stocks, with the S&P 500 losing 1.5% and the Nasdaq dropping 3.1%. Other major players in the AI industry, such as chipmakers Arm and Broadcom, alongside Oracle, saw their stocks plummet by at least 10%.

The DeepSeek Effect

The cause of Nvidia’s catastrophic loss lies in DeepSeek’s release of its large-language model, which has cast doubt on the continued dominance of U.S. companies in generative AI. Initially, this might not seem like a negative development for Nvidia, as DeepSeek’s model was also powered by Nvidia’s powerful graphics processing units (GPUs), just like many other AI technologies. However, DeepSeek revealed that it spent just $5.6 million on Nvidia’s technology to develop its model. While experts believe this figure is likely a significant underestimation, it still calls into question the very foundation of Nvidia’s meteoric stock rise.

In recent years, Nvidia’s profits have skyrocketed, with projections indicating net profits could soar from $4.8 billion in 2022 to $66.7 billion in 2024, largely due to the soaring demand for its high-priced GPUs, which can cost up to $25,000 each. U.S. tech giants such as Meta, Tesla, and OpenAI have been among Nvidia’s biggest customers. However, if companies like these can replicate DeepSeek’s cost-efficient approach by using cheaper GPUs, Nvidia could face significant challenges in maintaining its market dominance.

As Ed Yardeni of Yardeni Research pointed out, this shift could be an unwelcome development for Nvidia.

Surprising Statistic

Nvidia’s near-$600 billion market cap loss on Monday exceeds the market values of all but 13 American companies, surpassing industry giants like UnitedHealth, Exxon Mobil, and Costco.

CEO’s Losses

Nvidia CEO Jensen Huang saw his wealth take a massive hit, losing $21 billion in a single day. His net worth dropped from $124.4 billion to $103.1 billion, according to Forbes estimates. Huang remains the largest individual shareholder in Nvidia, owning a 3% stake in the company.

Nvidia’s colossal market cap loss highlights the growing uncertainties in the AI sector, as DeepSeek’s cost-effective alternative to American AI models threatens to disrupt the industry’s balance. With AI becoming an increasingly competitive and global field, Nvidia’s future may hinge on how it adapts to these emerging challenges.

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AI Investment Doesn’t Always Mean Fewer Jobs, New Study Finds

Each new round of layoffs seems to deepen the same conclusion: artificial intelligence is not just changing how companies work, but how workers imagine their future. Through May 2026, employers had announced nearly 90,000 job cuts tied to AI, according to reporting from Yahoo Finance. Some projections suggest AI could eliminate as much as 15% of U.S. jobs over the next five years, intensifying concerns among workers, especially younger graduates entering a job market that already feels uncertain.

Yet a new report from Ramp and Revelio Labs adds a more nuanced layer to the debate. Drawing on enterprise AI spending data and workforce records from nearly 22,000 companies, the study suggests that firms investing aggressively in AI are not necessarily reducing staff. In many cases, they are hiring faster.

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High AI Spending, Higher Headcount

The report classifies “high-intensity adopters” as companies spending an average of $30 per employee each month on AI during the first three months of adoption. Among those businesses, headcount increased by 10.2%. Hiring expanded across engineering, sales, administration, customer service, finance, marketing and scientific roles.

The strongest growth was recorded in the information sector, which includes software, internet, media and other technology-related businesses.

AI Investment And Business Expansion

According to the report, AI can lower production costs and improve efficiency across software and technology companies by accelerating coding, debugging, internal tooling, technical documentation and product development.

The study suggests these productivity gains may allow some companies to expand operations while continuing to hire, rather than relying solely on workforce reductions.

Entry-Level Employment Shows Mixed Trends

The findings also differ from some broader labour market research.

Goldman Sachs has estimated that AI eliminated around 16,000 net jobs per month over the past year, with Gen Z workers and entry-level employees experiencing much of the impact. By contrast, Ramp and Revelio Labs found that entry-level headcount increased by 12% among high-intensity AI adopters.

The authors note, however, that the study focuses primarily on fast-growing, knowledge-based companies, many of which are backed by venture capital and were already positioned for expansion. As a result, the report does not conclude that AI itself caused the increase in hiring.

“This paper does not show that AI universally creates jobs, but it does counter claims that AI will lead to broad job losses,” the authors wrote.

Adoption Patterns Differ Across Companies

According to the report, companies with greater access to capital, technical expertise and organisational resources may be better positioned to turn AI investment into business growth.

The authors caution that organisations lacking those advantages could struggle to achieve similar results. “Firms without those channels may fall behind,” they said.