Amazon CEO Says AWS Could Reach $1 Trillion in Revenue Within 10 Years

Amazon CEO Andy Jassy believes Amazon Web Services (AWS) could become a business generating more than $1 trillion in annual revenue within the next five to 10 years, as surging demand for cloud computing and artificial intelligence drives a new wave of infrastructure investment.

Jassy outlined the ambition during Amazon’s third-quarter earnings call on October 29, 2026, after AWS reported $46 billion in quarterly revenue, up 39.3% year over year.

That performance lifted AWS to an annualized revenue run rate of approximately $184 billion, giving Amazon a much larger base from which to pursue its long-term target.

The projection is not a guarantee, and AWS does not currently generate $1 trillion in annual revenue.

It is a forward-looking ambition from Amazon’s leadership, supported by accelerating cloud demand, increased AI adoption, and plans to expand computing capacity.

Jassy said Amazon expects AWS revenue growth to exceed 40% in both 2027 and 2028.

The challenge is that meeting this demand requires extraordinary spending.

Amazon expects capital expenditures of approximately $220 billion in 2026, with most of that investment directed toward AWS.

The company also expects to spend significantly more in 2027, making the race to build AI infrastructure both a major growth opportunity and a test of financial discipline.

AWS Reaches a $184 Billion Annualized Revenue Run Rate

Amazon’s latest results provide the clearest explanation for why Jassy believes AWS could eventually become a trillion-dollar business.

For the third quarter ended September 30, 2026, AWS generated $45.984 billion in net sales, compared with $33.006 billion in the same quarter of 2025.

That represents growth of approximately 39.3%, AWS’s fastest year-over-year revenue growth in nearly five years, according to Amazon.

AWS also reported $17.773 billion in operating income, up from $11.434 billion a year earlier.

Its operating margin was approximately 38.7%, demonstrating that the cloud division remains a substantial source of operating profit even as Amazon invests heavily in expanding capacity.

The $184 billion figure requires an important distinction.

It is an annualized revenue run rate, calculated by taking the latest quarter’s revenue and multiplying it by four.

It is not the amount AWS actually earned over the previous 12 months, nor is it a guarantee that the next four quarters will produce the same results.

AWS’s reported revenue over the 12 months through September 30, 2026, was approximately $161.4 billion.

The difference between that trailing figure and the annualized run rate reflects AWS’s recent acceleration.

For Amazon, the growth rate matters as much as the size of the business.

A cloud provider already generating tens of billions of dollars in quarterly sales can add substantial revenue when growth accelerates, particularly if demand continues to exceed the capacity currently available.

Why 39% growth matters

AWS has been one of Amazon’s most important businesses because it sells computing, storage, databases, networking, security, and other cloud services to organizations that would otherwise need to operate more of their own technology infrastructure.

AI is adding a new source of demand.

Companies developing and deploying AI systems need access to powerful computing hardware, large-scale data storage, networking, and the infrastructure required to run applications reliably.

Those requirements can generate spending across multiple layers of AWS’s business.

Customers may purchase computing capacity for AI model training, run inference workloads to generate AI responses, store large datasets, and use cloud services to connect AI systems to their existing applications.

AI is not the only driver of AWS revenue, but it is becoming an increasingly important reason for Amazon to expand its infrastructure.

How AWS Could Reach $1 Trillion in Revenue

Jassy’s target is ambitious because it would require AWS to grow far beyond its current scale.

However, the starting point is significant: AWS has an annualized revenue run rate of approximately $184 billion, and Amazon expects annual growth above 40% in 2027 and 2028.

If AWS were to sustain 40% annual growth for two consecutive years from a $184 billion starting point, its annualized revenue would approach $361 billion.

That illustrates how quickly a large business can expand when a high growth rate persists.

But the calculation also shows why the trillion-dollar target remains a longer-term objective.

AWS would need to continue growing beyond 2028, and maintaining a 40% growth rate becomes progressively harder as revenue increases.

The path depends on several factors:

• Enterprise AI adoption: More companies must move AI projects from experimentation into sustained production use.

• Cloud migration: Businesses must continue shifting workloads from their own data centers to cloud infrastructure where AWS can compete for the spending.

• Available capacity: Amazon must build and operate enough data centers to meet demand without excessive delays.

• Product innovation: AWS needs to remain competitive in computing, AI services, databases, security, and other cloud offerings.

• Economics: Revenue growth must translate into sufficient returns to justify the cost of new infrastructure.

Jassy’s projection is based on management’s assessment of these opportunities.

It should not be interpreted as a formal guarantee that AWS will reach $1 trillion by a specific year.

Amazon’s leadership has also emphasized that the company sees an unusually large opportunity in its retail business.

Jassy said Amazon could potentially develop two businesses generating more than $1 trillion in annual revenue over the next five to 10 years: AWS and retail.

That would be a remarkable scale for a company whose businesses already span e-commerce, logistics, advertising, entertainment, devices, and cloud computing.

AI Is Changing What Customers Buy From AWS

The traditional cloud business helped companies rent computing infrastructure instead of buying and maintaining all their own servers.

AI is expanding that market by creating new workloads that can require large amounts of computing power.

An organization deploying a generative AI assistant, for example, needs more than a model.

It may need infrastructure to process requests, retrieve information, connect the model to company data, monitor performance, and protect access to sensitive systems.

AWS can potentially earn revenue from several parts of that workflow.

Customers may use computing instances, managed databases, storage services, networking, security products, and specialized AI services within the same cloud environment.

This creates an opportunity for AWS to benefit from AI adoption even when it is not developing the underlying AI model itself.

Training and inference create different infrastructure demands

AI training involves processing large datasets to develop or update a model.

Inference is the process of using a trained model to generate outputs, such as answering a question, summarizing a document, or writing software.

Both can consume significant computing resources, but their requirements differ according to the model, workload, hardware, and performance expectations.

Training large models can require extensive parallel computing capacity.

Inference demand can grow as more people and businesses use AI applications throughout the day.

For cloud providers, inference is particularly important because successful AI applications may generate recurring usage as customers integrate them into everyday operations.

An AI service used by thousands of employees, for example, can create ongoing demand for computing, storage, networking, and supporting cloud services.

If organizations expand their use of AI across departments, their infrastructure needs can grow accordingly.

However, the commercial outcome is not automatic.

Customers may optimize their applications to use fewer computing resources, choose smaller models, or move workloads between cloud providers.

AI adoption can increase demand while competition and efficiency improvements put pressure on pricing.

AWS therefore needs to grow its customer base and deliver competitive services, not merely build more data centers.

Amazon Plans to Spend $220 Billion on Infrastructure in 2026

Amazon’s growth ambition comes with an enormous investment requirement.

During its third-quarter earnings announcement, the company maintained its expectation of approximately $220 billion in capital expenditures for 2026.

Jassy said most of that spending would support AWS and that Amazon expected to spend meaningfully more in 2027.

Capital expenditures, commonly called capex, are investments in long-lived assets such as data centers, servers, networking equipment, and power infrastructure.

They are different from routine operating expenses, such as salaries, utilities, and everyday business costs.

For AWS, expanding capacity means acquiring land or facilities, constructing data centers, securing electricity, installing servers, and ensuring that networking and cooling systems can support the workloads customers want to run.

These investments must often be made before the resulting infrastructure produces its full revenue potential.

That creates a timing challenge: Amazon spends cash to build capacity today in the expectation that customers will pay to use it over time.

The free cash flow challenge

Amazon reported a trailing 12-month free cash flow outflow of $42.4 billion through September 30, 2026.

That compared with a positive $14.8 billion over the corresponding period a year earlier.

Free cash flow is generally calculated as operating cash flow minus capital expenditures.

It helps investors understand how much cash a company generates after accounting for investments in long-term assets.

Amazon’s latest results showed that its capital spending was rising faster than the cash remaining after those investments.

The company attributed the deterioration primarily to increased property and equipment spending, driven largely by AI infrastructure.

This does not necessarily mean AWS’s growth strategy is failing.

A business can deliberately invest heavily in capacity to meet future demand.

But it does mean investors need to assess whether the additional revenue and operating profit eventually justify the cash committed to construction and equipment.

Amazon’s third-quarter results offered evidence of strong AWS profitability: the division generated $17.8 billion in quarterly operating income.

The broader company, however, must balance that performance against the cost and timing of its infrastructure expansion.

The central financial question is not simply whether AWS can generate more revenue.

It is whether Amazon can expand capacity at a pace that produces attractive returns without placing excessive pressure on cash flow.

Why Investors Are Watching Amazon’s AI Spending

Amazon’s third-quarter results presented investors with two different signals.

On one side, AWS delivered 39.3% year-over-year sales growth and a sharp increase in operating income.

That performance supports the argument that demand for cloud and AI infrastructure is strengthening.

On the other side, Amazon’s overall capital expenditure requirements are enormous, free cash flow has turned negative over the trailing 12 months, and the company expects spending to increase further.

The market reaction reflected those concerns.

Reuters reported that Amazon shares fell as much as 7% in after-hours trading following the earnings announcement, as investors weighed strong cloud growth against the spending outlook and the company's fourth-quarter sales forecast.

Investors are effectively evaluating two competing possibilities.

The optimistic scenario is that Amazon builds capacity ahead of demand, wins long-term cloud commitments, and generates enough additional revenue and operating profit to justify the investment.

In that case, today's spending could support a much larger business in the future.

The more cautious scenario is that AI demand grows more slowly than expected, hardware becomes less valuable before its cost is recovered, electricity and construction expenses rise, or competitors limit AWS's pricing power.

Under those conditions, the company could have invested heavily in capacity that takes longer than expected to generate attractive returns.

Neither outcome is inevitable.

The results will depend on customer demand, competition, infrastructure costs, and the economics of the workloads AWS serves.

AWS Faces Competition From Microsoft and Google

AWS is not pursuing the AI infrastructure opportunity alone.

Microsoft Azure and Google Cloud are also investing in data centers, AI infrastructure, and enterprise cloud services.

Microsoft can connect Azure's infrastructure to its broader enterprise software ecosystem, including Microsoft 365 and its AI products.

Google Cloud can draw on Google's AI research, model development, data analytics, and cloud infrastructure.

AWS benefits from its established cloud customer base, broad service portfolio, and relationships with businesses that already run important applications on its platform.

For customers, choosing a cloud provider involves more than comparing headline prices.

They also consider reliability, security, service availability, data governance, technical support, integration with existing systems, and the cost of moving workloads.

AI may strengthen the importance of these factors.

Organizations deploying AI in production need infrastructure that works reliably, connects to business data, and meets their performance and security requirements.

The providers that can combine computing capacity with usable AI services and dependable enterprise infrastructure may be better positioned to capture spending.

However, AWS's scale does not guarantee that it will win every AI workload.

Large customers may distribute their applications across multiple providers, negotiate aggressively over pricing, or use specialized infrastructure for particular tasks.

Amazon must continue investing in products and infrastructure while demonstrating that customers receive sufficient value from its services.

What Could Prevent AWS From Reaching $1 Trillion?

A trillion-dollar annual revenue business would represent a major expansion from AWS's current scale.

Several risks could make the target harder to achieve.

1. AI demand may not grow as quickly as expected

Businesses are investing in AI, but not every experiment becomes a profitable, long-term application.

If organizations struggle to demonstrate measurable returns, they may delay deployments or reduce spending.

The pace of adoption will depend on whether AI products deliver enough value to justify their computing costs.

2. Infrastructure can take time to build

Data centers require land, electricity, equipment, construction work, and regulatory approvals.

Power availability is particularly important because AI computing facilities can require substantial electrical capacity.

If construction or power connections are delayed, AWS may be unable to serve customers as quickly as planned, even when demand is strong.

3. Competition could pressure prices

Microsoft, Google, and other cloud providers are investing heavily in AI infrastructure.

Competition can benefit customers, but it can also limit the prices providers can charge.

AWS will need to maintain competitive services and operating efficiency while funding its expansion.

4. AI efficiency could change infrastructure demand

AI models and applications may become more efficient over time.

Better hardware utilization, smaller models, improved software, and optimized inference can reduce the computing resources required for a given task.

That efficiency could make AI more affordable and encourage broader adoption.

However, it could also mean that some workloads consume fewer resources than earlier projections anticipated.

The net effect on cloud revenue will depend on whether lower costs encourage enough additional usage to offset the reduction in resources required per task.

5. Spending may outpace financial returns

Amazon expects to invest heavily before all the resulting capacity generates revenue.

If returns take longer to materialize, free cash flow could remain under pressure.

The company will need to show that its infrastructure investment is producing durable growth and acceptable returns, rather than relying on revenue expansion alone as evidence of success.

What the $1 Trillion Target Means for Businesses Using AWS

For companies that already use AWS, the most immediate implications are likely to involve infrastructure availability, product development, and the growing range of AI services.

Continued investment could expand the computing capacity available to customers and support new services for training models, running AI applications, processing data, and integrating AI into business software.

However, Amazon's trillion-dollar ambition should not be interpreted as a reason for every business to increase its cloud spending.

Companies should continue evaluating cloud services based on their own requirements, including performance, reliability, security, compliance, and total cost of ownership.

For example, a company considering an AI customer-support system should estimate how many requests it expects to process, what level of response quality it requires, and how much it can afford to spend per interaction.

It should also evaluate whether a smaller model or a more efficient workflow can meet its needs.

A business running conventional applications may have little reason to increase its infrastructure consumption simply because AWS is expanding its AI capacity.

For technology leaders, the practical takeaway is to monitor how cloud providers translate their investments into services, availability, performance, and pricing.

The financial ambitions of a supplier and the economic needs of its customers are related, but they are not identical.

The Bottom Line: AWS Has Momentum, but the Trillion-Dollar Goal Is Still a Forecast

AWS enters this next phase of its growth with strong momentum.

Its third-quarter 2026 revenue reached approximately $46 billion, year-over-year growth accelerated to 39.3%, and quarterly operating income rose to $17.8 billion.

Those results provide a substantial foundation for Andy Jassy's ambition to turn AWS into a business generating more than $1 trillion in annual revenue within five to 10 years.

The path forward, however, will require more than sustained demand for AI.

Amazon must expand computing capacity, secure electricity, deliver competitive services, and turn its infrastructure investments into sufficient revenue and cash generation.

Its planned $220 billion in 2026 capital expenditures and expectation of meaningfully higher spending in 2027 demonstrate the scale of the commitment.

The negative $42.4 billion trailing 12-month free cash flow figure also shows why investors are paying close attention to the timing of financial returns.

AWS has demonstrated that AI and cloud demand can support rapid growth, but its trillion-dollar future depends on whether that growth can continue at scale while generating attractive returns on the capital invested.

Jassy's target is a statement of confidence in the opportunity, not a completed financial milestone.

The next several years will show whether AWS can convert its current momentum into a business of unprecedented size.