33 Most Important AI Companies You Should Pay Attention To

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In this article, we discuss the 33 Most Important AI Companies You Should Pay Attention To.

Artificial intelligence has led to a much-needed market rally in the technology industry over the past year. The benchmark S&P 500, dominated by tech giants, is up nearly 20% in the past year. The tech-heavy NASDAQ Composite is up over 21%. In light of easing inflation numbers and rate cuts, market analysts had forecast a jump in interest around growth options for 2024. However, the AI buzz has served to snowball this ordinary interest into an extraordinary wave of optimism around the whole economy. Although tech stocks have been the biggest beneficiary, there is little doubt that AI will soon penetrate other sectors of the economy, from manufacturing and supply chain, to transportation, entertainment, and retail.

There are numbers that illustrate this argument in quantifiable terms. Across the economic spectrum, investments in AI are increasing at a rapid pace. For example, according to a recent report on the AI industry by renowned investment bank Goldman Sachs, established businesses around the world are expected to spend nearly $1 trillion on developing AI infrastructure in the coming years. Investments in AI startups are also booming. So far in 2024, venture capital firms have made around 200 deals with AI firms, investing nearly $22 billion. The average size of a round of funding for AI startups is more than $100 million with an average valuation of more than $1 billion. In contrast, these numbers for non-AI startups are $20 million and $200 million.

Key players who were early to catch on to the AI trend have leapfrogged competitors. Stocks of companies that make graphics processing units (GPUs), specialized AI chips, and generative AI products have soared. In general, the median returns of AI-linked firms on the S&P 500 are 20% compared to 2% for non-AI stocks. On the NASDAQ Composite, AI firms are responsible for 90% of the overall returns on the border index. Analysts expect these gains to translate into earnings and GDP growth. Joseph Briggs, a senior global economist at Goldman Sachs, argues that in the next ten years, AI is likely to automate 25% of all work tasks and raise US productivity by 9% and GDP growth by more than 6%.

Research presented in the keynote address to the 2024 EMW Conference by Philippe Laffont of Coatue Management suggests that these gains may be the beginning of a new super cycle for the tech industry, following previous cycles such as PCs in the 1980s, networking in the 1990s, wired internet in the 2000s, and mobile internet in the 2010s that led to the popularity of the cloud. However, investors have more reason to be optimistic about this growth since it compares favorably to cycles of the past. Software and internet experts Kash Rangan and Eric Sheridan contend that tech companies seem to be investing in AI products by tying the spending to the revenues, ensuring a safety net that had not existed in previous cycles.

Since the beginning of the AI wave in early 2023 following the launch of ChatGPT by California-based Open AI, the focus of the industry has shifted from software towards AI hardware and infrastructure. AI infrastructure firms have added nearly $6 trillion to their market capitalization since the first quarter of 2023. Before a killer AI application can emerge or large scale AI automation can begin – Daron Acemoglu, a Turkish-American economist at MIT, predicts this will take more than a decade – new areas of AI infrastructure are emerging. These include utilities, energy, internet, and industrials (see 20 Industrial Stocks That Are Already Riding the AI Wave). The gains of prominent utility, industrial, energy, and internet firms critical to AI development rival the returns of traditional AI stocks.

Investments in energy and utilities are important if this AI potential is to be realized. Goldman analysts Carly Davenport and Alberto Gandolf expect the proliferation of AI technology and the accompanying need to maintain data centers to drive an increase in demand for utilities that has not been seen in a generation. It remains to be seen, however, if the pace at which AI is progressing will keep pace with investments in power. This is because the utilities sector is highly regulated and has supply chain constraints that will not be easily overcome. If investments are made at the levels needed, it might still be a few years before their full benefits make their way towards AI firms.

All this hullabaloo around AI has investors on edge, with ghosts of previous bubbles haunting their memories. Although comparisons to the past are the surest way of finding your footing in unfamiliar territory, data shows that this may not be the wisest strategy considering present market dynamics. For example, at the height of the dotcom bubble just before the turn of the millennium, some software firms were trading at 132x their earnings. The five-year average for this value in 1999 was only 37x. In contrast, in 2023, even the biggest AI stocks were trading at P/E multiples of around 39x. The five-year average for this last year was 40x, showcasing why AI valuations may not be overextended.

Indeed, AI firms can target multi-trillion dollar valuations, in line with some of the biggest software and internet firms on the market presently. That is the revolutionary power of AI technology. Over the past decade, tech giants have achieved a scale that few other businesses have before them. By combining billions in users, hundreds of billions in revenue, and tens of billions in net income, these handful of firms have reached 80% of the valuation of the Fortune 500. They are category leaders in fields such as smartphones, ecommerce, cloud, and software as a service (SaaS) – all of which AI promises to disrupt – and ahead of competitors in research and development spending. This is why many of these firms are aggressively incorporating AI into their business models, in hopes of holding onto their thrones.

Some investors remain concerned about AI firms bullying software companies on the market in the near and long term. A cursory glance at the Price-to-Sale (PS) ratios for software stocks in the past decade reveals that after topping out in 2021, the valuations for SaaS firms are near their all time lows. Some of this pessimism around software can also be attributed to slower earnings growth. Coatue research shows that over the next twelve months, only 1% of SaaS stocks expect 30% earnings growth, down from 30% at the peak of the Saas craze. As the future of human-machine interaction moves towards communication in natural language, software firms who adapt to AI changes are more likely to survive than those that do not.

As the markets become decoupled from rate hikes, inflation figures go down, and the prospects of a soft landing become brighter, the macro outlook for AI looks favorable as well. The main driver for future S&P 500 growth in terms of earnings remains AI. According to Coatue research, in the next three years, AI-linked stocks will grow at a compound annual rate of almost 20%, beating their non-AI counterparts by nearly 14 percentage points. 40% of the earnings from tech will be accelerated by AI tailwinds in the period. All indicators point towards a brighter future for AI investors in the long term.

Our Methodology

For this article, we selected AI infrastructure stocks with more than 25% gains in 2024 that are also popular among hedge funds. These are the best AI stocks to buy according to the market participants and hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (see more details here).

33 Most Important AI Companies You Should Pay Attention To

A scientist at a computer station, surrounded by a neural network of artificial intelligence code.

33 Most Important AI Companies You Should Pay Attention To

33. Fabrinet (NYSE:FN)

Number of Hedge Fund Holders: 33

YTD Return as of August 1: 16%

Fabrinet (NYSE:FN) offers optical packaging, along with precision optical, electro-mechanical, and electronic manufacturing services. The company produces fiber-optic cables that power telecommunications, AI data centers, and the global Internet infrastructure. While demand in the telecom sector remains relatively soft, the surge in AI activity has helped alleviate these concerns. Fabrinet’s datacom segment, focused on providing cables for AI data centers, has experienced rapid growth over the past two years. Starting at $88 million per quarter in 2022, the company recently reported that datacom revenue has surged to over $305 million.

In the third quarter earnings call, Seamus Grady, the CEO of Fabrinet (NYSE:FN), underlined how this 150% jump in datacom revenue had benefited from the rise in demand for 800 gigs technology for AI applications. NVIDIA, one of the biggest winners of the AI craze, is the flagship customer for Fabrinet.

32. Cognex Corporation (NASDAQ:CGNX)

Number of Hedge Fund Holders: 32

YTD Return as of August 1: 23%

Cognex Corporation (NASDAQ:CGNX) delivers machine vision products designed to capture and analyze visual data, automating manufacturing and distribution processes globally. The company is leading the integration of AI into machine vision technology. Earlier this year, Cognex introduced the Insight L38, the world’s first AI-enabled 3D industrial vision system. According to the company, this new product has already garnered twice the customer interest compared to its predecessor. Additionally, Cognex offers AI-powered modular tunnel vision systems and has integrated AI into its barcode readers for faster scanning capabilities.

Robert Willett, the CEO of Cognex Corporation (NASDAQ:CGNX), said during the second quarter earnings call that the company expected growth in semis as well as memory as AI made customers invest in chips and related offerings for growth in the latest tech domain. Willett noted that efforts to localize chip production bode well for the long term future of the company.

31. Teradyne, Inc. (NASDAQ:TER)

Number of Hedge Fund Holders: 34

YTD Return as of August 1: 25%

Teradyne, Inc. (NASDAQ:TER) designs, develops, manufactures, and sells automated test systems and robotics products globally. Recently, investments in advanced semiconductor manufacturing and fabrication have surged, exceeding $100 billion, as manufacturers scramble to meet the rising demand for complex chips essential for powering AI applications. This surge has driven up the demand for automated test equipment (ATE), a key area of expertise for Teradyne. ATEs are crucial for rapidly bringing AI devices to market, optimizing their yield, and enhancing silicon performance.

In the second quarter earnings call, Greg Smith, the CEO of Teradyne, Inc. (NASDAQ:TER), explained how Cloud AI products were driving strong demand for ATEs across chip and memory markets. In the first half of 2024, the company was able to exceed the revenue it had made from chipmakers in all of 2023.

30. Apple Inc. (NASDAQ:AAPL)

Number of Hedge Fund Holders: 150 

YTD Return as of August 1: 25%

Apple Inc. (NASDAQ:AAPL) is a consumer electronics firm. The company is working to include AI products into the consumer electronics it markets, most notably the iPhone, expected to be released later this year. Some reports indicate that the firm will debut Apple Intelligence in the new phone. At a tech event earlier this year, the firm revealed some of the capabilities of the new AI offering, which included massive changes to popular iPhone applications like Siri, Genmoji, and Image Playground. There are rumors that the firm may put advanced features of the AI software behind some kind of a paywall.

Tim Cook, the CEO of Apple Inc. (NASDAQ:AAPL), praised the performance of in-house chips during the second quarter earnings call, noting that Mac computers were powered by Apple silicon with a powerful neural engine and privacy built in at the chip level. He said these computers would be able to take advantage of Apple Intelligence with Mac OS Sequoia, two new AI products of the firm.

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