DeepSeek’s AI shockwave: What it means for tech giants and investors

The global AI industry has never been so rattled. Just a few weeks ago, DeepSeek unveiled a brand-new model capable of rivaling the world’s leading AI systems, but at a fraction of the cost and computing power. The little Chinese AI lab immediately shattered long-held assumptions about the expense and infrastructure required to develop cutting-edge artificial intelligence – sending investors and multinational giants scrambling to reassess the future of the technology.

Suddenly, there were big questions on everyone’s minds. Would America’s tech behemoths maintain their dominance in the field? How would global markets react? And how would it all affect investors?

Let’s take those one by one.

What is DeepSeek, anyway?

DeepSeek is an AI company based in China, backed by hedge fund billionaire Liang Wenfeng and spun out from a Zhejiang University startup that used AI for stock trading. In just two years, DeepSeek has positioned itself as a major force in AI, competing directly with established players like OpenAI, Google, and Anthropic.

Its biggest achievement so far is the DeepSeek-R1 model, which has stunned analysts by delivering performance on par with models like OpenAI’s GPT-4 but at a fraction of the cost. DeepSeek claims it spent only $5.6 million to develop its model – not billions, like OpenAI and Google. But what’s even more striking is that DeepSeek achieved this with just 2,048 Nvidia H800 chips – far fewer than the massive supercomputing clusters used by Western AI labs.

DeepSeek’s model is also open-source, meaning that developers around the world can use and modify it. This stands in contrast to OpenAI and Google, which have been keeping the secrets of their most advanced models under wraps.

Why are markets so unsettled by DeepSeek?

DeepSeek undermines the assumption that AI dominance requires boatloads of capital spending. If DeepSeek can produce high-performing models at just a fraction of the cost, the entire AI investment thesis – which is built on the idea that only the biggest, most elite companies can afford to compete – kind of falls apart. Here are three ways that DeepSeek is challenging its more sizable rivals.

1. Pressure on AI revenue models

Silicon Valley’s big AI names have spent billions on computing infrastructure. OpenAI, Microsoft, Meta, and Google have all made enormous investments to build their generative or “thinking” models. And the firms justified these expenses by promising investors that AI would remain a high-margin business. DeepSeek’s cost efficiency undercuts that argument though. After all, if AI models can be built and operated a lot more cheaply, companies may struggle to charge high prices for AI services.

2. Pressure on Nvidia’s margins

Nvidia has been the market’s favorite AI play. Now, though, investors worry that if AI can be developed more efficiently (i.e. with far fewer chips), then the industry’s growth projections might be overblown. That’s especially concerning for Nvidia – the primary supplier of high-end AI chips.

3. US-China AI competition

Then there’s the China factor: the US government has tried to restrict China’s access to cutting-edge AI chips, hoping to slow its tech progress. But DeepSeek’s success shows that Chinese companies can innovate around these restrictions. This could lead to more intense competition between US and Chinese AI firms.

Overall, the issue here is this: the stock market has been pricing AI companies as if they are the future of high-margin technology. DeepSeek’s success challenges that assumption. If AI becomes a commodity, it could lead to lower profitability for AI service providers while benefiting companies that integrate AI into their products at lower costs.

What does this mean for the future of AI?

Since its start, AI development has been tightly controlled by a handful of tech titans with almost unlimited computing resources. But if innovation can thrive on leaner models and open-source approaches, the AI landscape could become decentralized. Smaller firms, startups, and even non-traditional players could have a real shot at competing, weakening the dominance of big tech and making AI more accessible, accelerating the rate of AI adoption. This could lead to a surge in new applications, expanding AI’s reach beyond current uses – some helpful and others likely filled with quirks, like we see today.

One of the most surprising takeaways from DeepSeek’s progress is the idea that AI models might not need vast computing power to perform at a high level. Its success suggests that data centers are more efficient than expected. This could spark greater investment in infrastructure as businesses rethink AI’s cost-benefit equation.

And while DeepSeek’s rise may seem like bad news for American firms, it’s being cheered by executives in China. Companies like Alibaba, Tencent, and Baidu stand to gain a significant edge by incorporating DeepSeek’s models into their operations at a fraction of the cost. Meanwhile, global firms like Apple and Samsung, looking to embed AI into devices sold in China, will need local partnerships to navigate the market. This underscores how China’s AI ecosystem is becoming increasingly self-sufficient, relying less on Western technology and carving its own path.

In the long run, this shift could lead to a world where AI isn’t built by a select few but embedded across industries by those who integrate it most effectively. The real winners might not be the developers of AI models but the businesses that put them to the best use.

So what should investors do, then?

Here are five things you can do to keep ahead of the curve, even as the industry evolves.

1. Watch for policy and regulation changes.

The US government may respond to DeepSeek’s rise with stricter AI chip export controls. And that’d likely shake things up: any regulatory changes affecting AI technology could impact companies like Nvidia, AMD, and other semiconductor firms.

2. Assess AI profitability trends.

Look for clues into whether AI companies will be able to maintain their pricing power. If competition forces prices lower, companies with diversified revenue streams will be in a stronger position.

3. Diversify beyond AI stocks.

The AI boom has been a key driver of stock market gains, but DeepSeek’s rise shows that tech dominance can be disrupted. Consider diversifying into sectors that benefit from AI adoption, rather than just those building AI models. Companies that use AI for automation, cybersecurity, and enterprise software could see long-term gains.

4. Stay cautious (or not) on AI infrastructure stocks.

AI data center and computing infrastructure stocks tumbled following DeepSeek’s launch, as folks reassessed their valuations. Long-term demand for AI infrastructure is still strong, sure, but there’s a risk of overpaying for companies that depend on sustained high AI spending. On the other hand, cheaper AI could fuel broader adoption, potentially driving even greater demand for infrastructure in the long run. Ultimately, how you invest depends on your long-term outlook – whether you see cost reductions as a challenge or a catalyst for future growth.

5. Look for companies that will win regardless of the outcome.

If lower AI costs drive greater adoption, it could really benefit AI consulting firms like Accenture and IBM.

And cybersecurity companies that protect AI data could see increased demand too. The industry’s smaller stocks held up well amid recent market volatility – suggesting that investors are content to shift their focus to the next phase of AI growth rather than exiting the sector entirely.

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