More than half of the investment has been earmarked for infrastructure in the U.S.. Microsoft President Brad Smith frames AI investment as key to economic growth.

Microsoft is one of the biggest spenders, followed closely by Google and AWS, Bloomberg Intelligence said. Its estimate of Microsoft’s capital spending on AI, at $62.4 billion for calendar 2025, is lower than Smith’s claim that the company will invest $80 billion in the fiscal year to June 30, 2025.

The tech giant has pledged that all data centers serving its cloud by this year will have power purchase agreements for 100 percent low-carbon energy.

The tech giant will funnel more than half of the investments into U.S.-based facilities, Microsoft Vice Chair and President Brad Smith said Friday.

Microsoft says it plans to spend $80 billion on building AI data centers in the 2025 financial year, a significant increase on last year.

Many companies and brands have begun shifting to more sustainable practices in recent years. Microsoft has long been leading the charge, pledging to be carbon negative by 2030. And it's now added another tactic in the fight for sustainability: building data centers made of wood and other low-carbon materials.

As Microsoft pledges $80 billion on data center spending this year, Michael Stewart of M12 - Microsoft's venture arm - says it will be the quality of AI that will matter in the long run. He joins Caroline Hyde on "Bloomberg Technology" to discuss.

According to its management, Microsoft (NASDAQ: MSFT) will invest $80 billion in data centers over the next year. To put this in some context, Microsoft’s revenue in the most recently reported quarter was $65.

The massive sum will go towards building out datacenters for training AI models, as well as deploying and improving global AI and cloud-based applications.

With those whopping returns who could argue with the premis... oh wait The AI datacenter spending splurge looks likely to continue in 2025, with Microsoft alone saying it will invest $80 billion this year on building out infrastructure to train and deploy AI models.