Why read this
Read this when the buyer has a Microsoft tenant and wants an implementation path that respects security, identity, operations, and exit requirements.
Keep the tenant and data boundary explicit
Document tenant, subscription, region, identity, network, logging, secrets, data sources, retention, and operator roles before a pilot. Azure capability does not automatically answer the buyer’s residency, privacy, or sector questions.
Evidence: IMDA AI Verify, Singapore PDPC AI governance guidance
Build a thin, observable slice
Start with one workflow and a small controlled set of sources. Monitor latency, quality, cost, access, safety, and human corrections. Keep the source material and output traceable so a reviewer can reproduce a result.
Evidence: Model AI Governance Framework, Singapore National AI Strategy
Plan change and exit
Define who approves model, prompt, retrieval, connector, and policy changes. Test rollback, provider substitution, export, deletion, and service failure before relying on the workflow.
Evidence: IMDA AI Verify, Model AI Governance Framework
Questions for the buying team
- Which Microsoft tenant, region, identity, and data controls are required?
- How are prompts, models, connectors, and policy changes approved?
- Can the buyer export data, evidence, configuration, and workflow logic if the supplier changes?
Local evidence boundary: this guide organises questions and sources. It is not a legal, security, clinical, financial, procurement, or implementation approval.
Sources and further reading
- IMDA AI Verify standards guidance
- Model AI Governance Framework standards guidance
- Singapore PDPC AI governance guidance standards guidance
- Singapore National AI Strategy standards guidance