AWS will be a $1T business, Jassy says. But first, it will spend big.

AWS stands for Amazon Web Services. It is Amazon’s cloud-computing business and provides digital infrastructure and services to organizations. Instead of buying and operating every server themselves, customers can use computing capacity through a provider. This model matters because it gives businesses access to technology needed for websites, software, data, and AI workloads.

In practical terms, a cloud business supplies computing power, storage, networking, and related software services. Customers can obtain capacity when they need it and scale their usage as demands change. The article gives a clear example: enterprises are moving core business workloads and AI workloads onto AWS, helping its revenue grow 39 percent from the year-ago quarter.

AWS is already a $184 billion annualized revenue run-rate business. Amazon believes it can grow above 40 percent in both 2027 and 2028, eventually reaching $1 trillion in annual revenue. That goal shows how important AI-driven cloud demand has become to Amazon’s strategy.

AWS currently has a $184 billion annualized revenue run rate. That figure estimates what its latest pace would produce over a full year. It shows that AWS is already a very large business, but it remains far below Amazon CEO Andy Jassy’s proposed $1 trillion annual revenue milestone.

The comparison is stark. A $1 trillion business would generate about 5.4 times AWS’s current annualized revenue. Put another way, AWS would need roughly $816 billion more annual revenue to reach the target. The article says AWS revenue increased 39 percent from the year-ago quarter, marking its sixth straight quarter of steady growth.

Jassy forecast growth above 40 percent in both 2027 and 2028. He said AWS could become a trillion-dollar revenue business within the next five to 10 years. That forecast depends on continued innovation, enterprise adoption, and the capacity Amazon is adding for core and AI workloads.

Amazon is increasing capital spending to build the infrastructure AWS needs for rapid expansion. Jassy said the company expects approximately $220 billion in cash capital expenditures in 2026, with the majority going to AWS. Amazon expects to spend meaningfully more in 2027 as it prepares for rising demand.

The main driver is the AI boom. AI services depend on cloud infrastructure, and enterprises are beginning to run both AI and core workloads in AWS. Supporting those workloads requires Amazon to add substantial capacity. Jassy described the moment as a once-in-a-lifetime opportunity and said Amazon must invest now to remain the leader.

The spending comes before all the expected revenue arrives. Amazon says it has a clear line of sight to the financial returns, while Jassy argues the plan could permanently change Amazon’s revenue and size. Investors remain concerned because the investment is enormous and its payoff depends on future cloud growth.

Heavy infrastructure spending creates a timing gap in Amazon’s finances. The company pays for facilities, equipment, and capacity now, while the revenue and profits from using that capacity may arrive later. Amazon expects approximately $220 billion in 2026 cash capital expenditures and more spending in 2027, with most of the 2026 amount directed toward AWS.

That investment can support future growth, but it also raises financial questions. Analysts repeatedly asked Jassy about the spending, the evidence that growth would arrive, and the profit margins AWS could produce. Amazon argues the spending is justified because AI is creating an exceptional opportunity in global cloud demand.

Investor confidence has not fully followed that argument. The article reports that shares fell about 6 percent in after-hours trading on Thursday. Amazon says it can fund the plan and sees a clear path to financial returns, but investors are still weighing today’s huge outlays against tomorrow’s promised revenue.

AI workloads drive cloud demand because AI services need substantial computing infrastructure. Training and operating AI systems involve large amounts of data and repeated calculations, so companies need access to considerable computing capacity. Cloud providers supply that capacity and the related services needed to run AI applications.

The article describes the mechanism directly: AI services undergird the boom, and those services are supported by cloud infrastructure. Enterprises are also beginning to run both their core business workloads and AI workloads in AWS. To serve them, Amazon is adding capacity each year and investing heavily in new infrastructure.

Jassy said enterprise AI adoption is still in its very early days and that Amazon’s strategy is working. AWS revenue grew 39 percent from the year-ago quarter, its sixth straight quarter of steady growth. Amazon expects the opportunity to support growth above 40 percent in 2027 and 2028.

AWS is competing with other major cloud providers for the surge in demand created by AI. The article specifically names Microsoft and says other cloud providers are spending heavily while also earning significant revenue. This competition matters because companies are racing to attract enterprises that need infrastructure for AI and core workloads.

Microsoft illustrates the same strategy. It posted yet more record-breaking revenue growth, driven largely by its cloud business, while also spending a bundle. The mechanism is similar across the industry: providers invest in infrastructure and capacity so customers can run AI services, then seek revenue and returns as usage expands.

Amazon is making its own unusually large commitment. It expects approximately $220 billion in cash capital expenditures in 2026, mostly for AWS, and more in 2027. Jassy says Amazon will invest to remain the leader, but investors are scrutinizing whether the spending will produce the expected growth and margins.

A company does not have to rent infrastructure from a major public cloud provider. It can build and operate its own data centers, creating a private environment for computing, storage, and networking. This approach offers direct control, but it requires substantial equipment, facilities, technical staff, and ongoing maintenance.

Another option is colocation. A company owns or leases servers but places them in a data center operated by a specialist. It can also rent dedicated servers from hosting companies, use smaller cloud providers, or combine private infrastructure with public cloud services in a hybrid model. These alternatives let organizations choose different balances of control, cost, and flexibility.

The article focuses on AWS, Microsoft, and the broader cloud industry, not these alternatives. In the article’s context, public cloud providers are expanding capacity because AI services rely on cloud infrastructure. Companies choosing other models would still need enough computing power to run their applications and AI workloads.