12 Fast-Growing AI Stocks to Watch

Nvidia hardly needs an introduction. Its chips provide much of the computing power behind today’s AI models.

What’s remarkable is the growth it’s still producing at its size.

Q2 FY2027 revenue reached US$96.2 billion, up 106% year-on-year, with Data Center revenue alone hitting US$89 billion.

Broadcom may be one of the most important AI companies many consumers have never heard of.

It helps major technology companies design custom AI accelerators and provides the networking technology connecting thousands of chips inside AI data centres.

Q3 AI semiconductor revenue surged 221% year-on-year to US$16.7 billion.

AMD is emerging as the most credible large-scale challenger to Nvidia in AI accelerators.

Its Q2 revenue rose 50% to US$11.5 billion, while Data Center revenue more than doubled to US$6.7 billion.

Google is unusual because it operates across almost every layer of AI: Gemini models, consumer applications, Google Cloud and its own TPU chips.

Q2 Google Cloud revenue surged 82% to US$24.8 billion, while Gemini reached 950 million monthly active users.

AI chips need memory—and increasingly enormous amounts of it.

Micron produces high-bandwidth memory (HBM), a critical component sitting alongside advanced AI processors.

Its FY2026 revenue reached US$133.2 billion, compared with US$37.4 billion the previous year, as AI-driven memory demand and pricing surged.

Oracle wasn’t initially viewed as one of the obvious AI winners.

That’s changing quickly.

Its latest quarterly cloud infrastructure revenue jumped 121% to US$7.4 billion, while contracted remaining performance obligations reached US$664 billion.

Palantir sits much closer to the end user.

Its software helps companies and governments connect data, AI models and real-world operations—from manufacturing to defence.

Q2 revenue increased 93% to US$1.94 billion, while US commercial revenue jumped 149%.

Most AI portfolios are heavily tilted towards America.

Alibaba offers a window into the other major AI ecosystem: China.

The company has developed its Qwen models alongside Alibaba Cloud and its own AI infrastructure.

Its latest quarterly AI Cloud and Compute Services revenue rose 45%, while AI-related product revenue has recorded triple-digit growth for 12 consecutive quarters.

Here’s where the AI infrastructure story gets more interesting.

Astera Labs doesn’t make GPUs. It makes technology that helps increasingly powerful processors, memory and other components communicate with each other inside AI data centres.

As AI clusters become larger, moving data efficiently becomes increasingly important.

Marvell is another company benefiting from what happens between the GPUs.

It develops networking technology and custom silicon used inside data centres, giving it exposure to the buildout of increasingly large AI clusters.

One of AI’s biggest problems isn’t software.

It’s electricity.

AI data centres consume enormous amounts of power and generate enormous amounts of heat. Vertiv provides the power management, cooling and infrastructure required to keep those facilities running.

Nebius is the smallest—and arguably most speculative—name on this list.

The company builds cloud infrastructure specifically for AI developers, providing access to GPUs and the computing environments needed to train and run models.

Unlike Amazon or Microsoft, it doesn’t have an enormous legacy business surrounding it.

That means AI infrastructure growth can have a much larger impact on the company.