The contractual backlog reported by major cloud computing companies these days is over $1 trillion.
Filling this backlog requires a significant investment in additional AI infrastructure.
This is great news for Nvidia and Taiwan's semiconductor manufacturing, both playing a key role in AI infrastructure build-out.
I like it more than 10 shares Nvidia›
Artificial intelligence (AI) is expected to have a major impact on the global economy in the long term. A study by the University of Pennsylvania's Penn Wharton budget model estimates that the surge in technology could increase productivity and global total production by 1.5% over the next decade alone. And it predicts even greater profits in decades.
This explains why businesses and governments around the world are jumping into the AI bandwagon and trying to integrate generative AI tools into their businesses. That's why there's a demand for cloud computing infrastructure from things like this Amazon, MicrosoftGoogle, and Oracle It's far beyond supply.
Image source: Getty Images.
The above cloud computing companies use the leasing capacity of their infrastructure to enable customers to run AI models, design custom applications, and run inference applications. This will require these customers to invest and maintain expensive hardware.
Its cost-effectiveness explains why Amazon, Google, and Microsoft reported that they totaled a revenue backlog of $669 million at the end of the last quarter. Oracle's remaining performance obligations of $455 billion, with the backlog exceeding trillion dollars. But how can we take advantage of this enormous opportunity?
The above cloud computing giants are rapidly expanding their data center infrastructure, allowing them to meet large contract backlogs. This requires a significant increase in capital expenditures. Microsoft's Amazon total capital expenditure alphabetand Meta Platform It is set to increase by 63% to $364 billion in 2025.
As long as capacity demand increases, high capital investments can be expected to continue. So it's easy to see why sales of AI-enabled chips and accelerators such as graphics processing units (GPUs) are projected to jump from the expected $477 billion in 2025 to nearly $600 billion next year.
The easiest way for investors to make a profit from this wave of spending is to buy stocks of Taiwan Semiconductor Manufacturing(NYSE: TSM). Popularly known as TSMC, it is the world's largest semiconductor foundry and is the go-to fabricator for almost all AI chip designers as it offers cutting-edge manufacturing processes. Other chips manufactured by TSMC can enter consumer electronic devices such as computers, smartphones and gaming consoles.
All this explains why the rapid growth of AI has supercharged TSMC's top line. Revenue for the first eight months of 2025 increased 37% year-on-year. This is faster than the 30% growth recorded in 2024. TSMC expects AI Accelerator revenue to double this year, and during the first quarter revenue call, CEO CC Wei predicts revenue from AI Accelerators will grow at a combined annual rate of 40 years, starting in 2024.
The stock is a simple purchase as TSMC trading is just 24 times the progressive revenue, and so many revenue growth rates are clearly visible.
This will take us to other companies in pole position and take advantage of our large AI backlog. nvidia(NASDAQ: NVDA).
Designed by NVIDIA, GPUs are the go-to chip for cloud computing giants looking to train and run AI applications in their data centers. It controls the data center GPU market with a 92% share. Controlling that niche has helped me record impressive growth over the past three years.
In the first six months of fiscal 2026 (ends July 27), its revenues rose 62% year-on-year to $90.8 billion. Sales to Chinese customers have achieved despite being hit due to export restrictions and geopolitical factors. However, thanks to AI infrastructure projects such as Stargate, the growth trend could continue.
For example, Oracle reportedly placed a $40 billion order a few months ago by Nvidia GPUs to bring in a new Stargate data center. And now, the chip giant has entered into a $100 billion worth of strategic partnership with Openai, developing an AI data center that is at least 10 gigawatts. With annual spending on AI accelerators expected to increase by $62 billion in 2026, it is no surprise that Nvidia's data center business will maintain a healthy pace of growth.
This is expected to lead to a firm ultimate growth despite its size.
Estimates for current fiscal year data by NVDA EPS YCHARTS.
NVIDIA's trading is earnings prior to 40 times, a discount of a multiple of the average revenue of the US technology sector, so investors can consider purchasing this semiconductor stock as they could fly higher thanks to secular growth opportunities in AI infrastructure space.
Consider this before purchasing shares on Nvidia.
Motley Fool Stock Advisor The analyst team has identified what they believe 10 Best Stocks For investors to buy now…and Nvidia was not one of them. The 10 stocks that have made the cut could potentially generate monster returns over the next few years.
When should you think about it? Netflix I created this list on December 17, 2004…If you invested $1,000 at the time of recommendation, There is $652,872! *Or when nvidia I created this list on April 15, 2005… If you invested $1,000 at the time of recommendation, There is $1,092,280! *
Now it's worth noting Stock Advisor The total average return rate is 1,062% – Outperformance that breaks the market compared to 189% on the S&P 500. Don't miss the latest Top 10 list and get it when you join Stock Advisor.
View 10 shares »
*Stock Advisor will return as of September 22, 2025
The harsh Chauhan has no position in any of the stock mentioned. We recommend and recommend Alphabet, Amazon, Meta Platforms, Microsoft, Nvidia, Oracle, and Taiwan Semiconductor Manufacturing for Motley Fool. Motley Fool recommends the following options: A $395 phone at Microsoft for January 2026 length and a $405 phone to Microsoft for January 2026 short term. Motley Fools have a disclosure policy.
The artificial intelligence (AI) backlog is over $1 trillion.
