3 Top Artificial Intelligence (AI) Stocks Ready for a Bull Run

In This Article:

Key Points

With trade tensions easing, stocks have rallied and are looking to potentially head into their next bull run. After leading the last bull market higher, artificial intelligence (AI) stocks seem to have regained their footing and could be ready to lead again.

Let's look at three AI stocks ready for a bull run.

Artist rendering of AI chip.
Image source: Getty Images.

1. Nvidia

Where AI infrastructure spending goes, Nvidia (NASDAQ: NVDA) is sure to follow. It's both the biggest risk the company faces and its biggest opportunity.

The stock pulled back after the Trump administration enacted some tougher export restrictions for AI chips going into China, but trade deals with Middle Eastern countries that included investments in AI infrastructure eased investor concerns. Sovereign AI, or government AI spending, could be the next big driver of spending on the technology.

This would be on top of the strong spending already being seen from cloud computing companies and companies training foundation AI models, such as OpenAI and Meta Platforms.

With an over 80% market share in the graphics processing units (GPUs), Nvidia is very well positioned to continue to benefit from ongoing AI infrastructure spending. Meanwhile, its CUDA software platform and its collection of AI-focused libraries and tools that help streamline development and optimize the performance of its chips give it a wide competitive moat in the space.

The stock is still reasonably valued with a forward price-to-earnings ratio (P/E) of 31 times this year's analyst estimates and a 0.6 price/earnings-to-growth ratio (PEG), with numbers below 1 considered undervalued.

2. Broadcom

Another company well-positioned to benefit from increased AI infrastructure spending is Broadcom (NASDAQ: AVGO). The company makes components that are crucial parts of data center infrastructure.

It also has carved out a sizable niche in helping customers develop custom AI chips known as ASICs (application-specific integrated circuits). While GPUs are more readily available and offer more flexibility, custom AI chips can offer better performance for the specific task for which they were designed while reducing power consumption.

There are considerable up-front costs involved in designing these custom chips, but they can help lower the overall cost of ownership over time for customers, given that they are more energy efficient.