3 No-Brainer AI Stocks to Buy Right Now

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Artificial intelligence (AI) stocks have been some of the strongest drivers of the market this year. Given that the AI trend still appears to be in its early innings, though, it looks like a number of them could help drive the market higher next year as well.

These three AI stocks, in particular, are all trading at reasonable valuations and look look smart buys right now.

1. Nvidia

Nvidia (NASDAQ: NVDA) has been the biggest winner of the AI infrastructure build-out, as its graphic processing units (GPUs) are the go-to chips for data centers to use for their computing processing needs to train large language models (LLMs) and run AI inference. As AI models advance, they need more and more computing power. For example, xAI and Meta Platforms both used 10 times as many GPUs to train their latest LLMs than they used for their prior versions.

It is this continuing need for exponentially more computing power as well as the wide moat the company created with the help of its CUDA software platform that make Nvidia a buy right now. CUDA was initially created to make it easier for developers to program its GPUs for other uses beyond speeding up graphics rendering in video games, the task for which they were originally designed. This led to CUDA becoming the standard platform upon which developers learned to program GPUs, which has contributed to the moat NVIDIA now enjoys.

With AI infrastructure spending only expected to increase in 2025 and beyond, Nvidia still has a big opportunity in front of it. Meanwhile, the stock is attractively valued at a forward price-to-earnings (P/E) ratio of about 31.5 based on analysts' estimates for 2025 and a price/earnings-to-growth (PEG) ratio of approximately 0.98. A stock with a positive PEG ratio below 1 is typically considered undervalued, but growth stocks will often have PEG ratios well above 1.

2. Taiwan Semiconductor Manufacturing

Today, many chip companies use a fabless model, which means they design chips but then outsource the manufacturing to third parties. The reasons for this are simple. Building chip manufacturing facilities (also called fabs or foundries) is capital intensive (it costs a lot of money), and for a foundry to be profitable, it needs to be operated at as near to maximum capacity as possible. Producing chips for multiple clients helps these companies keep their foundries busy. Manufacturing chips also requires a high degree of expertise, and in many cases, the adaption to the latest technologies that continue to drive down chip sizes and increase wafer sizes.