6.1. Application Lifecycle Management for AI Solutions

Traditional ALM handles code, configurations, and deployments. AI ALM must additionally manage model versions, training data lineage, prompt templates, knowledge source updates, and connector configurations. The exam tests whether you can design ALM processes that account for these AI-specific artifacts across three platforms: Copilot Studio, Microsoft Foundry, and Dynamics 365.

Missing any of these AI-specific artifacts from your ALM process means that a working production agent can break when you promote a new version — because the model version changed, the prompt template drifted, or the knowledge base wasn't synced.

⚠️ Common Misconception: ALM for AI solutions follows the same process as traditional ALM. AI ALM must additionally account for model versioning, data lineage, prompt management, training data governance, and model drift monitoring — alongside standard code and configuration management.