Comparison guide
AWS vs Azure vs GCP for AI Workloads (2026)
Hyperscaler comparison for AI agent deployments — data gravity, managed services, and enterprise fit.
Quick answer
Pick AWS for breadth and Bedrock; Azure for M365 enterprises; GCP for data/ML and Gemini-native stacks.
Last updated: May 2026
| Feature | AWS | Microsoft Azure | Google Cloud |
|---|---|---|---|
| Flagship AI service | Amazon Bedrock | Azure AI Foundry | Vertex AI |
| Data warehouse fit | Redshift | Synapse | BigQuery |
| Enterprise IT incumbency | Strong | Dominant | Growing |
| Agent tooling maturity | Mature | Mature | Strong |
| Typical Skylink client | SaaS on AWS | Enterprise Microsoft shop | Data-heavy ML teams |
Our recommendation
Follow data gravity: deploy agents where your data and identity already live. Skylink runs production agents on all three — the wrong choice is picking a cloud for marketing reasons instead of integration reality.
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