Developed Azure AI Deployment Strategy Guidance within the Azure-Proactive-Resiliency-Library-v2 repository, focusing on optimizing resource deployment for cost-effectiveness, scalability, and data residency. The work involved delivering three targeted recommendations, updating deployment configurations, and integrating new data sources to enhance AI resource management and governance. Leveraging expertise in Azure AI, Cloud Computing, and DevOps, the developer utilized KQL and YAML to implement configuration changes that support informed decision-making for AI deployments. The feature addressed key challenges in resource optimization and compliance, providing actionable guidance and technical improvements that enable organizations to better manage and govern their Azure AI resources.