AI Stocks

There is no official definition, so this page uses a curated view of the companies most investors mean by "AI": the chip designers and semiconductor-equipment makers, the hyperscalers and software platforms, the networking and server hardware vendors, the data-center real estate operators, and the power producers supplying the electricity behind AI workloads. This page tracks 30 of them with live market data.

Some do and many don't. The fastest-growing names typically reinvest everything and pay little or no dividend, while more mature platforms and the infrastructure layer — data-center REITs and power utilities — are more likely to pay and to raise their dividend. Each ticker page shows the current yield and our Distribution Safety Score.

We don't make individual recommendations, but the income tends to concentrate in the infrastructure layer of this list — data-center real estate and power producers — plus a few established software and semiconductor names that pay a growing dividend. Sort the table by yield or Safety Score to see where the paying names cluster, then review each on its own page.

It's Dividend Vision's proprietary measure of how durable a company's dividend looks, scored from 0 to 100 using the same single model applied across the entire site. A higher score suggests a more secure payout. Companies that don't pay a dividend carry no score.

They carry meaningful risk. Valuations across much of the group assume years of continued growth, the names are highly correlated to a single AI-demand narrative, and the semiconductor layer is cyclical. Export controls and customer concentration add company-specific risk. None of this is a recommendation for or against any name — it's context to research further.

Chip stocks design or manufacture the processors and memory that train and run models, and the equipment used to fabricate them — a cyclical, capital-intensive corner of the market. AI power stocks are utilities and independent power producers meeting the jump in electricity demand from data centers. They sit at opposite ends of the value chain and behave very differently.

Large language models run in physical buildings full of servers, cooling, and networking. Data-center real estate investment trusts own and lease that space, so they are a direct, income-paying way to participate in AI infrastructure rather than the chips themselves.

The membership is curated, while yields, prices, market caps, and Safety Scores refresh from our data pipeline on every build. The figures you see reflect the most recent data run, not a static snapshot.

No single fund maps exactly to this curated list, but several AI and technology ETFs hold many of these names. See our AI Income ETFs and Nuclear Energy ETFs lists for fund-based ways to get related exposure.

Most articles stop at a table. Every name here links to a full analysis page, the list carries a live DV Scorecard summarizing the group's yield, Safety Score, and standouts, and you can send any of these into the screener, compare tool, forecast calculator, or a portfolio to model the income yourself.

No. The Distribution Safety Score speaks only to how durable a dividend looks, not to valuation, growth, or whether the stock will rise. A company can have a very safe dividend and still be expensive or slow-growing. Always look at the full picture, and remember nothing here is investment advice.