Seattle: Amazon Web Services (AWS) has announced a fresh increase in prices for one of its key artificial intelligence cloud services, adding to concerns that rising infrastructure costs could eventually make AI-powered applications and services more expensive for businesses and consumers.
AWS increases prices by 20 per cent
Amazon Web Services said prices for its EC2 Capacity Blocks for Machine Learning (ML) service will rise by around 20 per cent from July.
The service allows companies to reserve graphics processing unit (GPU) capacity in advance for artificial intelligence and machine learning workloads. It is widely used by businesses developing generative AI applications, chatbots and large-scale data processing systems.
This is the second price increase introduced by AWS this year. In January, the company had already raised prices for the same offering by approximately 15 per cent.
In its announcement, AWS stated that reservation prices for EC2 Capacity Blocks for ML are updated periodically based on supply and demand conditions.
The company did not provide additional details regarding the latest increase.
Higher costs could affect AI services
Unlike price increases for smartphones or gaming consoles, the latest hike affects the cloud infrastructure that powers a significant portion of the global artificial intelligence ecosystem.
AWS remains the world’s largest cloud computing provider and supports millions of developers and businesses that rely on its infrastructure to build and deliver software, AI tools and digital services.
Industry analysts believe the back-to-back increases could eventually lead to higher operating costs for companies using AWS for AI workloads.
If businesses decide to pass on these additional expenses to customers, users could see higher subscription charges for AI-powered applications, enterprise software and digital services in the coming months.
The development also reflects a broader challenge facing the technology sector, where the rapid growth of artificial intelligence has significantly increased demand for computing resources.
Memory shortage driving costs higher
A major factor behind the rising costs is the global shortage of high-bandwidth memory (HBM), a critical component used in modern AI processors.
HBM is essential for powering advanced graphics processing units that drive generative AI systems and large language models. However, limited manufacturing capacity has constrained the supply of these chips.
Economists and technology experts say the shortage has created a bottleneck in the expansion of AI infrastructure.
Peter Berezin, chief economist at BCA Research, noted that limitations in memory production also restrict the number of GPUs that can be manufactured and, consequently, the number of data centres that can be built.
He further argued that cloud providers currently possess significant pricing power because demand for AI computing resources continues to exceed available supply.
According to analysts, the persistent imbalance between demand and supply is likely to keep cloud computing costs elevated for the foreseeable future.
Wider impact across the technology industry
Amazon’s latest pricing decision is part of a larger trend affecting the global technology sector.
Several major technology companies have recently acknowledged that rising memory costs are putting pressure on their businesses. Apple has increased prices across parts of its product portfolio, while Xbox has also announced price revisions.
Billionaire entrepreneur Elon Musk has also publicly highlighted the sharp rise in memory costs, underlining the broader challenges facing companies involved in AI development.
The supply crunch has also benefited memory-chip manufacturers such as Micron Technology and SK hynix, with investors expecting AI-driven demand to keep memory markets tight and prices elevated for several years.
AI boom reshaping the cloud industry
The latest AWS price increase highlights how the global artificial intelligence boom is reshaping the economics of cloud computing.
As businesses increasingly adopt AI technologies, demand for computing power, specialised chips and advanced memory solutions is expected to continue rising.
For companies building AI products, managing infrastructure costs may become one of the biggest challenges in the coming years. For consumers, the effects could eventually be felt through higher prices for AI-powered services and subscriptions.
The development also serves as a reminder that the rapid expansion of artificial intelligence depends not only on software innovation but also on the availability of the hardware infrastructure needed to support it.