AI Research
2 Top Artificial Intelligence (AI) Stocks That Pay Decent Dividends and Have Good Dividend-Paying Histories
Key Points
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Shares of Taiwan Semiconductor Manufacturing Co. (TSMC) and IBM have crushed the S&P 500’s returns over the last one year, three years, and five years.
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And TSMC stock has absolutely pulverized the broader market over the 10-year period.
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Shares of TSMC and IBM are currently yielding 1.26% and 2.31%, respectively.
Artificial intelligence (AI) is the biggest secular growth trend today. The global AI market will soar from $189 billion in 2023 to $4.8 trillion by 2033 — a 25-fold increase in a decade — according to a recent projection by the United Nations Conference on Trade and Development.
As with technology stocks in general, the vast majority of stocks that could be considered AI stocks either do not pay dividends or pay very small ones.
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While they are relatively rare, there are some top-performing AI stocks that pay decent dividends and have a good dividend payment history. These include the world’s largest semiconductor (or “chip”) foundry Taiwan Semiconductor Manufacturing Corp., or TSMC (NYSE: TSM), and International Business Machines, or IBM (NYSE: IBM), one of the world’s oldest large tech companies.
So, folks who like dividend-paying stocks and want to invest in AI — forgive the cliché — can have their cake and eat it too.
Image source: Getty Images.
2 Top AI stocks that pay decent dividends
|
Company |
Market Cap |
Dividend Yield |
Forward P/E Ratio |
Wall Street’s Projected Annualized EPS Growth Over Next 5 Years |
5-Year Return |
|---|---|---|---|---|---|
| Taiwan Semiconductor Manufacturing |
$963 billion |
1.26% | 24.2 | 22.7% | 296% |
| IBM | $270 billion | 2.31% | 26.7 | 6.3% | 223% |
|
S&P 500 |
N/A |
1.24% | N/A |
N/A |
112% |
Data sources: Finviz.com and Yahoo! Finance. P/E = price to earnings. EPS = earnings per share. Data as of July 8, 2025.
TSMC: The world’s largest chip foundry
Taiwan Semiconductor Manufacturing produces chips for companies that contract out all or some of the manufacturing of chips that they design. As the world’s largest chip foundry, TSMC is the dominant company in the production of advanced AI chips, so it’s been significantly benefiting from the growth of the AI market and should continue to benefit.
TSMC’s customers includes most of the big names in chip companies — such as Nvidia, Broadcom, and Arm Holdings. It also produces chips for big tech companies that have designed their own chips, including Apple, which is widely considered TSMC’s largest customer, followed by Nvidia.
The company is off to a great start in 2025. In the first quarter, its revenue jumped 35% year over year to $25.5 billion, driven by continued strong AI-related demand. Better yet, its EPS surged 54% to $2.12. Its EPS growing faster than its revenue reflects its expanding profit margin.
On the Q1 earnings call, management reaffirmed its 2025 guidance that its revenue from AI accelerators will double year over year.
TSMC started paying cash dividends in 2004 and has never halted or reduced its dividend per share.
TSMC stock is trading at 24.2 times its forward projected EPS, which is reasonable for a stock of a company that Wall Street expects will grow EPS at an average annual rate of nearly 23% over the next five years.
IBM: Successfully transitioning to AI and other high-growth markets
IBM has been in a years-long transitioning mode, divesting of legacy businesses and investing in growth markets, notably cloud computing and AI. This transitioning resulted in its revenue declining, which in turn caused its profits and cash flows to also decrease. But Big Blue is back in growth mode.
In 2024, IBM’s revenue increased 3% in constant currency to $62.8 billion, driven by a 9% rise in software revenue, offset by declines of 1% and 3% in its consulting and infrastructure segments, respectively. Adjusted earnings per share (EPS) from continuing operations was up 7% year over year. Free cash flow (FCF) rose 13% year over year to $12.7 billion.
IBM’s generative AI book of business ended the year at $5 billion inception to date. (Generative AI enables users to quickly generate new content based on a variety of inputs. It’s the type of AI that’s largely powering the AI boom.)
The AI business is growing fast, increasing $2 billion from the third to the fourth quarter 2024. Moreover, it tacked on another $1 billion-plus in the first quarter of 2025 to bring its total to more than $6 billion. About one-fifth of this business comes from software and four-fifths from consulting, CEO Arvind Krishna said on the Q1 earnings call.
The company expects revenue growth to accelerate in 2025. For the year, it guided for annual revenue growth of at least 5% in constant currency and FCF of about $13.5 billion, or over 6% growth year over year.
IBM has a great dividend history. It’s increased its quarterly cash dividend for 30 consecutive years.
IBM stock is trading at 26.7 times forward projected EPS. This might seem quite pricey for shares of a company that Wall Street expects will grow EPS at an average annual pace of 6.3% over the next five years. However, investors can expect to pay a premium for stocks of companies that have great track records of raising their dividends.
Moreover, the stock might turn out to be less pricey than it currently seems. IBM has solidly beat the analyst consensus estimate for earnings in the last four quarters, with two of the beats being quite large. Given how fast the company’s AI business is growing, it could continue to solidly surpass earnings estimates.
Mark your calendars
TSMC is slated to release its Q2 2025 results before the market open on Thursday, July 17.
IBM is scheduled to release its Q2 results after the market close on Wednesday, July 23.
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Beth McKenna has positions in Nvidia. The Motley Fool has positions in and recommends Apple, International Business Machines, Nvidia, and Taiwan Semiconductor Manufacturing. The Motley Fool recommends Broadcom. The Motley Fool has a disclosure policy.
The European Commission said Thursday (July 10) that it published the final version of a voluntary framework designed to help artificial intelligence companies comply with the European Union’s AI Act.
AI Research
Every Blooming Thing – Technology and Artificial Intelligence in the garden – appeal-democrat.com
Severe weather events, such as heavy rainfall, are on the rise worldwide. Reliable assessments of these events can save lives and protect property. Researchers at the Karlsruhe Institute of Technology (KIT) have developed a new method that uses artificial intelligence (AI) to convert low-resolution global weather data into high-resolution precipitation maps. The method is fast, efficient, and independent of location. Their findings have been published in npj Climate and Atmospheric Science.
“Heavy rainfall and flooding are much more common in many regions of the world than they were just a few decades ago,” said Dr. Christian Chwala, an expert on hydrometeorology and machine learning at the Institute of Meteorology and Climate Research (IMK-IFU), KIT’s Campus Alpin in the German town of Garmisch-Partenkirchen. “But until now the data needed for reliable regional assessments of such extreme events was missing for many locations.”
His research team addresses this problem with a new AI that can generate precise global precipitation maps from low-resolution information. The result is a unique tool for the analysis and assessment of extreme weather, even for regions with poor data coverage, such as the Global South.
For their method, the researchers use historical data from weather models that describe global precipitation at hourly intervals with a spatial resolution of about 24 kilometers. Not only was their generative AI model (spateGEN-ERA5) trained with this data, it also learned (from high-resolution weather radar measurements made in Germany) how precipitation patterns and extreme events correlate at different scales, from coarse to fine.
“Our AI model doesn’t merely create a more sharply focused version of the input data, it generates multiple physically plausible, high-resolution precipitation maps,” said Luca Glawion of IMK-IFU, who developed the model while working on his doctoral thesis in the SCENIC research project. “Details at a resolution of 2 kilometers and 10 minutes become visible. The model also provides information about the statistical uncertainty of the results, which is especially relevant when modeling regionalized heavy rainfall events.”
He also noted that validation with weather radar data from the United States and Australia showed that the method can be applied to entirely different climatic conditions.
Correctly assessing flood risks worldwide
With their method’s global applicability, the researchers offer new possibilities for better assessment of regional climate risks. “It’s the especially vulnerable regions that often lack the resources for detailed weather observations,” said Dr. Julius Polz of IMK-IFU, who was also involved in the model’s development.
“Our approach will enable us to make much more reliable assessments of where heavy rainfall and floods are likely to occur, even in such regions with poor data coverage.” Not only can the new AI method contribute to disaster control in emergencies, it can also help with the implementation of more effective long-term preventive measures such as flood control.
More information:
Luca Glawion et al, Global spatio-temporal ERA5 precipitation downscaling to km and sub-hourly scale using generative AI, npj Climate and Atmospheric Science (2025). DOI: 10.1038/s41612-025-01103-y
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Karlsruhe Institute of Technology
Citation:
Researchers develop AI model to generate global realistic rainfall maps (2025, July 10)
retrieved 10 July 2025
from https://phys.org/news/2025-07-ai-generate-global-realistic-rainfall.html
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