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Is the artificial intelligence stock market boom still wired or tired? Top AI stocks such as Microsoft (MSFT) and Nvidia (NVDA) face high expectations. For many companies — such as Google parent Alphabet (GOOGL), Amazon.com (AMZN) and Facebook parent Meta Platforms (META) — the rise of generative AI poses both risk and opportunity.
Amid the emergence of generative AI — which can generate text, images, and video — it’s a good time to be cautious amid the hype. Many companies suddenly tout AI product roadmaps. In general, look for AI stocks that use artificial intelligence to improve products or gain a strategic edge.
Capital spending has boomed at cloud computing giants Amazon, Microsoft and Google as well Meta Platforms. Tech giants are spending heavily on data center infrastructure, such as AI chips and servers, as well as research and development.
Amid increased capital spending by cloud computing giants, the big question is how much incremental AI-related revenue they’re getting.
Google earnings for the third quarter are due Oct. 29, with Microsoft and Meta reporting on Oct. 30. Amazon follows on Oct. 31.
Also, Microsoft is currently the biggest investor in startup OpenAI, the leader in generative AI.
UBS analyst Karl Keirstead in a report noted that OpenAI is losing money, which impacts Microsoft earnings. Microsoft also has expanded data center capacity to serve OpenAI’s computing needs.
“While the EPS dilution and the capital spending requirements are sources of pressure, we conclude that they’re offset by OpenAI’s lift to Azure (cloud) growth,” he said. “A potential shift from an exclusive to a primary provider of compute infrastructure to OpenAI may actually be a good thing for Microsoft.”
Also, Apple (AAPL) has been one of the top AI stocks to watch. Apple stock has gained 22% in 2024. The big question is whether Apple Intelligence features in iPhone 16 models will spur a big upgrade cycle.
Chipmaker Nvidia has been a bellwether for AI stocks. Nvidia stock has climbed jumped 178% in 2024 after surging 239% last year. Further, Nvidia stock remains on the IBD Leaderboard. For Nvidia, ramping up production of next-generation Blackwell AI chips in 2025 will be key.
The best AI stocks to buy span chipmakers, software companies, cloud computing service providers and technology giants.
What’s clear is that AI stocks are under more scrutiny.
“We expect AI to transition from a ‘tell me’ to a ‘show me’ story, with any disconnect between investments and revenue generation to come under increased scrutiny,” said a Bank of America report. “
Facebook-parent Meta is among the top AI stocks to watch. Meta stock has gained 62% in 2024.
Meanwhile, Nvidia and Arista Networks (ANET) are squaring off in the AI Ethernet networking market. Also, Arista stock has gained 70% in 2024.
Arista stock ranks No. 16 in the IBD 50 roster of growth stocks while Palantir stock ranks No. 8.
So far, the biggest demand for AI chips has come from cloud computing giants and internet companies.
Broadcom (AVGO), Qualcomm, ARM Holdings (ARM), and Marvell Technologies (MRVL) are other AI chipmakers to watch. Broadcom and Marvell make custom AI chips for cloud computing giants.
In general, semiconductor plays have out-performed software companies as the best AI stocks.
Many software companies, meanwhile, have yet to monetize AI products. One big issue for software companies is how fast customers ramp up pilot programs to commercial deployment.
Having struggled to generate new revenue from “copilots,” software companies are now turning to AI agents.
Meanwhile, data analytics software maker Palantir (PLTR) has bucked the trend that chipmakers are the best AI stocks. PLTR stock has gained 150% this year.
Also, for most big application software companies, how to charge for AI-related products has been an issue.
Further, most enterprise software makers will not monetize generative AI, or “conversational AI,” in a material way until late 2025, some analysts say. Many U.S. companies are pursuing custom AI software development projects, which will take longer to ramp up commercially.
Also, AI technology uses computer algorithms. The software programs aim to mimic the human ability to learn, interpret patterns and make predictions.
Until recently, machine learning was largely limited to models that processed data to make predictions. The AI models focused on pattern recognition from existing data. Corporate spending on AI projects was modest as companies mulled return on investment.
New generative AI models process “prompts,” such as internet search queries, that describe what a user wants to get. Generative AI technologies create text, images, video and computer programming code on their own.
Companies will aim to boost productivity by developing customized AI for specific industries. Proprietary company data will be used to train AI models.
AI systems require massive computing power to find patterns and make inferences from large quantities of data. So the race is on to build AI chips for data centers, self-driving cars, robotics, smartphones, drones and other devices.
For chipmakers, analysts expect a market for “edge AI” — on-device processing of AI apps to emerge.
While “training” AI models is now the biggest market for chipmakers like Nvidia, the market will shift to “inferencing,” or running AI applications, in the long run.
What’s more, one key question for investors is whether tech industry incumbents will be the big generative AI winners. Or, will a new wave of AI startups eventually dominate? OpenAI has told employees its now on an annual revenue run-rate of $3.4 billion, up from $2 billion in January.
OpenAI has raised $6.6 billion in new funding, valuing the startup at $157 billion, up from $86 billion early this year. The new round was led by venture-capital firm Thrive Capital. Microsoft again invested. New investors include SoftBank and Nvidia but not Apple as rumored.
OpenAI plans to convert from a nonprofit organization to a for-profit company as top researchers continue to leave.
Further, OpenAI has released a new large language training model capable of enhanced reasoning skills. Code-named “Strawberry,” it’s officially called OpenAI o1.
Large language models provide the building blocks to develop applications. Further, LLMs help AI systems understand the way that humans write and speak. Also, LLMs require training data for specific tasks. Companies with access to troves of data hold an edge.
OpenAI is part of a wave of LLM startups that includes AI21 Labs, Anthropic and Cohere. Anthropic introduced Claude 3, the newest version of its chatbot, and claimed its performance is better than OpenAI’s GPT-4.
However, OpenAI’s dominance faces a challenge from open-source LLMs. Musk’s xAI announced it will open source its Grok LLM, and released the source code for public use.
According to etf.com, there are 41 ETFs with assets of $10.9 billion that invest based on AI themes.
“We were also surprised that the five largest ones collectively underperformed the S&P 500 both year-to-date and over the past three years,” said economist Ed Yardeni in a report. “Many of the ETFs appear to be underperforming because AI and robotics investments are being lumped together. Robotics companies haven’t fared nearly as well as AI poster child Nvidia. The top performing large ETF in this category, Global X Artificial Intelligence & Technology, avoids robotics exposure. It invests in developers of products incorporating AI systems, like software programmers and social media platforms. Its top holdings: ServiceNow (NOW), IBM (IBM), Alibaba (BABA), Oracle (ORCL) and Meta.”
Follow Reinhardt Krause on Twitter @reinhardtk_tech for updates on artificial intelligence, cybersecurity and cloud computing.
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