Nvidia dominated 2024 big-time. Next year? Plenty of challenges.

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Nvidia (NVDA:) had a year that most companies can only dream of.

Its revenue and share price have been boosted by deliberate investments in artificial intelligence technologies that are paying off big on the back of a generative AI wave.

That’s not all. It has been replaced many times with Apple (AAPL:) as the world’s largest public company with a market capitalization exceeding $3 trillion. CEO Jensen Huang has become one of the most sought-after executives in Silicon Valley, meeting with everyone from tech partners to world leaders and then some.

And there’s more to come.The company is expanding production of its high-powered Blackwell chip for AI applications and expects to ship several billion dollars worth of hardware in the fourth quarter alone, with much more to come in the coming year.

“Nvidia really has [hardware and software] For the AI computing age,” Daniel Newman, CEO of Futurum Group, told Yahoo Finance. “It’s all connected internally [server] shelf, outside [server] shelf, and then the software is very well…liked in the developer communities.”

But the competition does not sit idly by.

Companies like AMD (dram) are looking to poach Nvidia’s customers and take about 80% to 90% of the market.Even Nvidia’s own customers are working on chips designed to reduce their reliance on the graphics giant’s semiconductors.

And Wall Street sits.

Shares of Broadcom (AVGO:), which works with companies like Google (GOOG, GOOGLE:for AI chip design, up 113% year-to-date and up 44% in just the past month after CEO Hock Tan said AI could be a $60-90 billion opportunity to present for the company only in 2027.

However, taking on Nvidia will be a tough task for any company, and dethroning it as the AI king, at least in 2025, will be impossible.

Nvidia gained a first-mover advantage in the AI market thanks to early investments in AI software that opened up its graphics chips for use as high-powered processors, and it has managed to maintain that lead in the space thanks to of its continued hardware advancements, as well as its Cuda software, which allows developers to build applications for its chips.

Because of this, so-called hyperscalers, massive cloud computing providers including Microsoft (MSFT:), Alphabet Google, Amazon (AMZN:), meta (AFTER:), and others continue to spend cash to buy as many Nvidia chips as possible. In its most recent quarter, Nvidia reported total revenue of $30.8 billion, or 87 percent, from its data center business.

“Everybody wants to build and train these massive models, and the most efficient way to do that is with CUDA software and Nvidia hardware,” Bob O’Donnell, president and principal analyst at TECHnalysis Research, told Yahoo Finance.

CEO Jensen Huang speaks during the Nvidia GTC keynote in San Jose, California, Monday, March 18, 2024. (AP Photo/Eric Risberg) · ASSOCIATED PRESS

Nvidia is expected to continue to power the bulk of the AI industry well into 2025. The company’s Blackwell chip, the successor to its popular Hopper line of processors needed to power artificial intelligence applications, is in production, and its customers like Amazon , are already adding new cooling capabilities to their data centers to manage the enormous heat generated by processors.

“I don’t know what the current backlog is [for Nvidia’s chips is]but if it’s not a year, it’s about a year,” O’Donnell said. “So they’re pretty much sold out for what they’re probably going to make next year.”

With hyperscales requiring increased capital spending in 2025, or at least the same level as in 2024, you can expect some of that to be driven by Blackwell chip purchases.

While Nvidia will retain control of the AI crown, there is no shortage of competitors looking to usurp its throne from AMD and Intel (INTC:) are the leading contenders among chipmakers, and both have products on the market. AMD’s MI300X series of chips is designed to take on Nvidia’s H100 Hopper chips, while Intel has its own Gaudi 3 processor.

AMD is better positioned to steal market share from Nvidia as Intel continues to struggle amid its turnaround efforts and the hunt for a new CEO. But even AMD is struggling to break Nvidia’s lead.

“What AMD needs to do is make the software really usable, build systems where there’s more demand…with developers, and ultimately that can drive more sales,” Newman said these cloud providers are going to sell what their customers are asking for.”

But it’s not just AMD and Intel. Nvidia’s customers are increasingly developing and pushing their own AI chips, while Amazon has its own Tensor Processing Unit (TPU) chips. h (AMZN:) has its own Trainium 2 processor and Microsoft (MSFT:) has its own Maia 100 accelerator.

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There is also concern that the move to “AI model inference” will reduce the need for powerful Nvidia chips.

Tech companies develop AI models by training them on massive amounts of data, otherwise known as the training process. Training takes incredibly powerful chips and a lot of energy. Making inferences or actually putting those AI models to work takes less resources and energy require.As inference becomes a bigger part of AI workloads, the thinking goes, companies will back away from needing to buy so many Nvidia chips.

Huang has said he’s ready for it, explaining at various events that Nvidia’s chips are just as good at inference as they are at training.

Even if Nvidia’s market share is slipping, that doesn’t mean its business will be any worse than before.

“It’s definitely a case of lifting all boats,” Newman said. “So even with a lot more competition, which I think they’re going to have, that doesn’t mean they’re going to fail they’re building a big pie.”