AI drives strong growth in cloud infrastructure market

Global spending on cloud infrastructure services reached $90.9 billion in the first quarter of 2025, according to estimates by industry analysts Canalys.

The company reported that this represents a 21 per cent increase compared to the same period in 2024.

Enterprises have recognised that deploying AI applications requires renewed emphasis on cloud migration.

Large-scale investment in both cloud and AI infrastructure remains a defining theme of the market in 2025.

To accelerate the enterprise adoption of AI at scale, leading cloud providers are intensifying efforts to optimise infrastructure.

These efforts are most notably focused on developing proprietary chips aimed at lowering the cost of AI usage and improving inference efficiency.

In the first quarter of 2025, the ranking of the top three cloud providers remained unchanged from the previous quarter.

Amazon Web Services, Microsoft Azure, and Google Cloud together accounted for 65 per cent of global cloud spending.

Collectively, these three hyperscalers recorded a 24 per cent year-on-year increase in cloud-related spending.

Growth momentum, however, varied among the top players.

Microsoft Azure and Google Cloud both maintained growth rates exceeding 30 per cent, though Google Cloud’s growth slowed slightly from the previous quarter.

Amazon Web Services grew by 17 per cent, a deceleration from the 19 per cent growth recorded in the fourth quarter of 2024.

This deceleration was largely attributed to supply-side constraints that limited AWS’ ability to meet rapidly rising AI-related demand.

In response, cloud hyperscalers have continued to invest aggressively in AI infrastructure to expand capacity and position themselves for long-term growth.

Overall, the global cloud services market maintained steady growth in the first quarter of 2025 as enterprises focused on accelerating cloud migration and exploring the adoption of generative AI.

The rise of generative AI, which heavily relies on cloud infrastructure, has reinforced enterprise cloud strategies and hastened migration timelines.

Rachel Brindley, Senior Director at Canalys, now part of Omdia, said that “as AI transitions from research to large-scale deployment, enterprises are increasingly focused on the cost-efficiency of inference, comparing models, cloud platforms, and hardware architectures such as GPUs versus custom accelerators.”

She explained that unlike training, which is a one-time investment, inference represents a recurring operational cost, making it a critical constraint on the path to AI commercialisation.

Yi Zhang, Analyst at Canalys, now part of Omdia, added that “many AI services today follow usage-based pricing models—typically charging by token or API call—which makes cost forecasting increasingly difficult as usage scales.”

He noted that when inference costs are volatile or excessively high, enterprises are forced to restrict usage, reduce model complexity, or limit deployment to high-value scenarios, resulting in the broader potential of AI remaining underutilised.

To address these challenges, leading cloud providers are deepening their investments in AI-optimised infrastructure.

Hyperscalers including Amazon Web Services, Azure, and Google Cloud have introduced proprietary chips such as Trainium and TPU, along with purpose-built instance families, all aimed at improving inference efficiency and reducing total cost of AI.

Amazon Web Services maintained its position as the market leader in the first quarter of 2025, capturing 32 per cent of global market share and recording a 17 per cent year-on-year increase in revenue.

Its AI business continues to grow at a triple-digit annual rate, though it remains in the early stages of development.

In March, Amazon Web Services introduced a price-cutting strategy to promote adoption of its Trainium AI chips over more costly NVIDIA-based solutions.

The company highlighted Trainium 2’s 30 to 40 per cent price-performance advantage.

Amazon Web Services also accelerated the expansion of its Bedrock service, adding Anthropic’s Claude 3.7 Sonnet and Meta’s Llama 4 models, and became the first cloud provider to fully manage DeepSeek R1 and Mistral’s Mixtral Large.

Further underscoring its long-term commitment to global infrastructure, Amazon Web Services announced a capital investment of over $4 billion in May 2025 to establish a new cloud region in Chile by the end of 2026.

Microsoft Azure remained the second-largest cloud provider in the first quarter of 2025, holding a 23 per cent market share and delivering strong year-on-year growth of 33 per cent.

Microsoft reported a 16-point growth rate lift to Azure from AI, marking the largest single-quarter uplift since the second quarter of 2024.

In April, Azure announced the availability of the GPT-4.1 model series on both Azure AI Foundry and GitHub, further broadening developer access to advanced AI capabilities across its ecosystem.

Azure AI Foundry, Microsoft’s platform for building and managing AI applications and agents, is now used by developers at more than 70,000 enterprises.

The platform processed over 100 trillion tokens in the quarter, a fivefold increase year-over-year.

Microsoft has also focused on lowering the cost of AI adoption, reporting a nearly 30 per cent improvement in its AI performance at constant power consumption and a reduction of over 50 per cent in cost per token.

As part of its ongoing global infrastructure expansion, Microsoft opened new data centres in 10 countries across four continents during the first quarter.

Google Cloud, the world’s third-largest cloud provider, maintained a 10 per cent market share in the first quarter of 2025 and delivered strong year-on-year growth of 31 per cent.

As of March 31, its revenue backlog reached $92.4 billion, marking a slight decline from the previous quarter.

This decrease was primarily attributed to supply constraints, particularly in compute capacity, that limited Google Cloud’s ability to fully meet customer demand.

In March, Google introduced the Gemini 2.5 model series, with Gemini 2.5 Pro receiving widespread acclaim for its leading benchmark performance and top ranking on Chatbot Arena.

With enhanced reasoning and coding capabilities, the model opens new possibilities for both developers and enterprise users.

Since the beginning of the year, active usage of Google AI Studio and the Gemini API has surged by over 200 per cent, reflecting strong developer adoption and growing demand for generative AI solutions.

Google also launched a new cloud region in Sweden, its 42nd globally, and committed $7 billion to expand its Iowa data centre, further supporting its growing AI and cloud workloads