The biggest AI companies right now

New chips, more advanced models, record-high stocks — the AI industry has been feeling the rush ever since OpenAI’s ChatGPT took the world by storm in November 2022. Since then, OpenAI entered a multi-year, multi-billion dollar partnership with Microsoft, chipmaker Nvidia became the first semiconductor company to surpass a $2 trillion market cap — and now some analysts are warning it’s a bubble that could burst soon.
But Goldman Sachs analysts said last week that the AI investing craze is very much still heating up, and the bank forecast the companies set to benefit next from the boom. They don’t all make chips.
Here are the top seven U.S.-based AI companies by market cap.
Microsoft — $3.18 trillion

Microsoft was already among the top players in the tech industry before the hype around AI kicked off. Last January, Microsoft announced a multi-year, multi-billion dollar investment in ChatGPT-maker OpenAI, allowing it to use supercomputing systems powered by Microsoft’s Azure AI infrastructure to train and develop its models. Microsoft announced an investment into OpenAI’s French rival, Mistral AI, in February, to help the startup commercialize and scale up performance of its flagship models. However, both partnerships are currently under scrutiny in the EU and U.K.
The technology giant’s stock hit a record high in March after it announced its latest AI product, Copilot for Security.
Nvidia — $2.36 trillion

Producing the world’s most desired hardware gave Nvidia the honor of becoming the first semiconductor company to reach a $2 trillion valuation in February. The chipmaker has been on a hot streak due to its H100 chips, which power some of the world’s leading AI models. In doing so, it leapfrogged right over its own customers, Amazon and Google parent Alphabet, to become the U.S.’s third most valuable company by market cap. The company beat Wall Street expectations in February, reporting revenues of $22 billion in its fourth-quarter earnings — a $270 increase from the previous year.
Nvidia CEO Jensen Huang unveiled the chipmaker’s next-generation processor, Blackwell, at the company’s GPU Technology Conference (GTC), saying Microsoft and Google are already queuing up for the chips, which are more powerful than its Hopper predecessor.
Alphabet — $1.88 trillion

Despite dominating the search-engine market, Google’s attempts to compete with ChatGPT haven’t been smooth. When Google launched its chatbot, Bard, last February, the promotional ad listed an inaccurate answer. Bard has since been renamed to Gemini after its latest, most advanced large language model (LLM). Gemini is multimodal, meaning the LLM can understand different types of information, including audio, images, and video.
However, in February, Google had to pause Gemini’s ability to generate images of people, after users found it was doing some historically inaccurate things, including generating racially diverse Nazi-era German soldiers. Google CEO Sundar Pichai addressed Gemini’s responses in a memo to Google staff, calling the images “unacceptable.”
Meta — $1.3 trillion

Meta’s AI ambitions have led it to become a top spender on Nvidia’s AI chips. In 2023, the company spent $9 billion on H100 chips alongside Microsoft. As part of the company’s “technology roadmap” leading up to 2026, Meta is working on an AI model to power recommendations for its video and user Feeds.
“Instead of just powering Reels, we’re working on a project to power our entire video ecosystem with this single model, and then can we add our Feed recommendation product to also be served by this model,” Tom Alison, head of Facebook, said at a Morgan Stanley tech conference. “If we get this right, not only will the recommendations be kind of more engaging and more relevant, but we think the responsiveness of them can improve as well.”
Alison said Meta is working on scaling the use of generative AI to power its products.
After Nvidia debuted its Blackwell chips, Meta said it doesn’t expect to receive shipments of the chip this year, but plans to use them to train and build its next-generation AI models and other products.
Tesla — $534.94 billion

Tesla CEO Elon Musk has previously referred to the EV-maker as “an AI/robotics company that appears to many to be a car company,” and has relied on Nvidia-powered supercomputers to produce its electric vehicles. However, last July, Musk said during Tesla’s earnings presentation it would work on building its own $1 billion supercomputer named Dojo.
Musk also has his own AI company, xAI, which he started to compete with OpenAI, which he also cofounded but left in 2018.
IBM — $175.63 billion

IBM CEO Arvind Krishna said last May the company plans to slow or suspend hiring for jobs it thinks can be replaced by AI. Krishna said he could see back-office roles such as human resources, which make up about 26,000 jobs at the company, impacted by the change.
“I could easily see 30% of that getting replaced by AI and automation over a five-year period,” Krishna said, which would result in a loss of 7,800 roles.
Krisha wrote in Fortune last April that IBM used AI to reduce the amount of employees working on HR-related work from 700 to less than 50, which “freed up a very significant number of people to spend more time providing important talent-related services, such as career guidance and support for managers, which requires thought and creativity, rather than doing routine paperwork.”
IBM’s AI research has extended decades starting in the 1950s.
Palantir Technologies — $53.55 billion

In February, data management software company Palantir reported record-profit in its fourth-quarter earnings, generating $608 million in revenue — up 9% from the year prior. Palantir CEO Alex Karp said the company’s revenue was due to “surging demand” for its AI platform.
“The demand for large language models from commercial institutions in the United States continues to be unrelenting,” Karp said.
Palantir’s AI-platform, AIP, is also drawing new revenue and customers to the company, Karp said.