This week’s roundup highlights practical ways organizations are improving their AI readiness, forecasting, system reliability, and ethics alignment—especially within Microsoft-based environments.
Role-Based AI Readiness
Role-Based Readiness for AI Projects: How Project Managers and Department Heads Can Lead with Confidence
- Role-Based Readiness for AI Projects: How Project Managers and Department Heads Can Lead with Confidence
- AI Readiness for Project Managers: A Practical Framework for Success
- Leading Through AI Disruption: Change Management Strategies for Department Heads
Forecasting in .NET
Forecasting in .NET: Use Cases Across Operations
- Forecasting in .NET: Use Cases Across Operations
- Implementing Time Series Forecasting in .NET for Operational Efficiency
- Integrating Forecasting Models into .NET Microservices for Scalable Operations
logging and exception handling in AI systems
Why Logging and Exception Handling Matter in AI Systems
- Why Logging and Exception Handling Matter in AI Systems
- Implementing Structured Logging and Exception Handling in .NET AI Applications for Enhanced Observability
- Proactive AI Observability in .NET: Leveraging AI-Powered Log Analysis for Resilient Systems
AI ethics checklist for Microsoft environments
AI Ethics Checklist for Microsoft-Based Environments: Stop Flying Ethically Blind
- AI Ethics Checklist for Microsoft-Based Environments: Stop Flying Ethically Blind
- How to Integrate Responsible AI Practices into Your Microsoft Azure AI Workflows
- Operationalizing AI Ethics in Microsoft Environments: A QA-Centric Approach
AI in .NET applications
How to Apply AI to Existing .NET Applications?
- How to Apply AI to Existing .NET Applications?
- Integrating AI into Legacy .NET Applications Using ML.NET and Azure Cognitive Services
ML.NET vs Semantic Kernel
ML.NET vs Semantic Kernel: How to Choose the Right Microsoft AI Tool
- ML.NET vs Semantic Kernel: How to Choose the Right Microsoft AI Tool
- Integrating ML.NET and Semantic Kernel: Building Comprehensive AI Solutions in .NET
- AI-Driven Modularization: Transforming Monolithic .NET Applications into Intelligent Microservices
Prototyping AI in Microsoft environments
Prototyping AI in Microsoft Environments Without Risk