# Platform

Cloud platforms are the interface through which most organizations access AI capabilities. US hyperscalers dominate globally, though Chinese platforms lead domestically.

**Measure:** Cloud AI Infrastructure & Developer Platform Reach

**US & Allies Score:** 7.0/10  
**China Score:** 5.0/10  
**Leader:** US & Allies

## Key Metrics

- **Distribution reach:** Reach = (Active developers) × (Enterprise penetration) × (Regions served with compliant offerings)
- **Compute allocation:** Allocation Share (%) = (Platform accelerator hours delivered / Total accelerator hours delivered) × 100

## What matters in this layer

The platform layer turns hardware into accessible capability: orchestration, networking, storage, monitoring, and security. Platforms also set the policy surface through export compliance and customer screening.

### Managed AI stack

Turnkey training and inference services reduce friction and pull demand. Tooling quality and reliability directly affect adoption.

### Procurement advantage

Platforms that can secure supply (accelerators, networking, power) can gate downstream innovation and attract the best workloads.

## Recent Developments

### AWS Expands AI Infrastructure
*3 days ago | Cloud*

Amazon Web Services continues to expand its AI infrastructure, offering access to NVIDIA GPUs, custom Trainium chips, and a growing suite of foundation models.

### Alibaba Cloud Deploys Domestic AI Chips
*1 week ago | Strategy*

Alibaba Cloud is increasingly deploying domestic AI accelerators across its infrastructure, reducing dependence on restricted US technology.

### Microsoft Azure AI Demand Surges
*2 weeks ago | Business*

Microsoft reports unprecedented demand for Azure AI services, with enterprise customers rapidly adopting Copilot and other AI-powered tools.