Microsoft AI Transformation Leader (AB-731) Cert Prep by Microsoft Press

Course details

Prepare to earn the Microsoft Certified: AI Transformation Leader credential. This exam prep course from Microsoft Press guides leaders, consultants, and decision makers through the concepts needed to lead AI transformation and pass the AB-731 exam. Start with generative AI fundamentals, how it differs from traditional AI, and how to evaluate cost, ROI, and use case fit. Explore Microsoft's AI ecosystem, including Microsoft 365 Copilot, Copilot Studio, and Azure AI Services, and see how each supports different organizational scenarios. Then move into the leadership side of AI: responsible AI principles, governance, risk mitigation, change management, and building sustainable, organization-wide adoption.

Concepts

Introduction

Exam AB-731 AI Transformation Leader - Introduction

Understanding the Foundational Concepts of Generative AI

Learning objectives
Core AI concepts - Contrasting generative AI and traditional AI
AI models - Pretrained vs. fine-tuned models and where each applies
Cost drivers and ROI considerations
When AI adds value - Scalability, automation benefits, and recognizing appropriate use cases

Exploring the Benefits and Capabilities of Generative AI Solutions

Learning objectives
Business opportunities - Efficiency and innovation
Limitations and risks - Hallucinations, reliability, and bias
Prompting - How crafting inputs influences AI output quality
Grounding and data - Importance of relevant data and RAG
Real-world examples

Understanding What You Can Do with Microsoft 365 Copilot

Learning objectives
Microsoft 365 Copilot capabilities across apps
Mapping AI workloads and scenarios
Differentiate between Copilot experiences
Extending Copilot - Custom agents, grounding, and governance
The value of Microsoft s integrated AI solutions

Introduction to Microsoft Azure AI Solutions

Learning objectives
Overview of Azure AI services and their business applications
How to map use cases to the right Azure service or AI model
Cloud advantages - Scalability, security, and integration benefits of Azure for AI deployments

AI Governance and Responsible AI

Learning objectives
Microsoft responsible AI principles and why they matter
The vital role of AI governance
Policies and compliance
Risk mitigation

Preparing for Change and Driving AI Adoption

Learning objectives
Adoption roadmap - Steps to successfully introduce and scale AI
Change management - How to make AI adoption stick
The power of peer-to-peer learning - Microsoft Copilot Champions case study
Overcoming barriers - Common obstacles and mitigation strategies
Licensing and cost planning - Understanding Microsoft 365 Copilot licensing and Azure cost models

Summary

Exam AB-731 AI Transformation Leader - Summary