The latest data from Omdia shows that global cloud spending will reach US$110.9 billion in the fourth quarter of 2025, up 29% year-on-year. The firm said growth is driven by AI, with demand expanding to storage and networking. Full-year spending reached US$399.6 billion, up 24% year-on-year.
Amazon Web Services, Microsoft Azure, and Google Cloud are seeing increased use of connected AI models that require more computing and network power, the company says.
Deploying AI in manufacturing requires consistent access to high-performance systems. Models need to handle large datasets and respond quickly. They also need to increase as usage increases. These requirements are pushing companies to rely more on cloud platforms rather than on-premise systems.
Canalys analysts also identified AI as a key driver of recent growth in cloud use, with demand increasing due to increased use of AI and enterprise adoption.
The apparent growth in the use of AI is putting pressure on several aspects of cloud computing. Storage needs increase and network usage grows as data moves between systems and users. A single AI application can require more resources than a typical business model. As companies measure these tools across sectors, the overall demand rises rapidly.
Cloud providers are expanding the capacity of the data center and providing specialized equipment such as GPUs and custom chips for AI tasks, although these come at a high cost.
Pricing models are complex, with companies paying for storage, computing, data transfer, model training time, and the use of feedback, making it difficult for businesses to predict and control spending. Companies are making huge investments to maintain and scale AI systems, so cloud computing is becoming part of the core operating costs.
Omdia expects cloud computing spending to grow 27% by 2026, pushing annual spending to more than US$500 billion.
IT teams now need to closely monitor their usage and optimize workloads. They also need to decide where to run the different parts of the application. Others are exploring hybrid setups, with some workloads on private systems and others in the cloud.
High cloud costs raise questions about long-term cost management. AI tools can improve efficiency, but they can also introduce costs that are difficult to track. Companies are looking closely at how they use cloud resources. This includes which workloads require high-performance hardware and which can be run with low-cost systems. They also check how usage is tracked.
Some firms are also rethinking their cloud strategies by spreading workloads across multiple platforms to reduce reliance on a single vendor; strategy can add complexity. Cloud providers offer new pricing options and cost management tools, including usage dashboards, cost alerts, and reserved capacity plans.
The cloud as a basic foundation
Recent market data shows that cloud platforms are now critical to how businesses run modern operations, with cloud companies citing AI as a driver of infrastructure demand.
As AI becomes more prevalent in industries, the link between AI adoption and cloud adoption is likely to strengthen. The shift is redefining what cloud computing is used for, and how much companies are willing to spend on it.
(Photo by Jinyun)
See also: Cloud demand shifts to AI as business applications deepen
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