Use this quick start guide to collect all the information about Microsoft AI Transformation Leader (AB-731) Certification exam. This study guide provides a list of objectives and resources that will help you prepare for items on the AB-731 Microsoft AI Transformation Leader exam. The Sample Questions will help you identify the type and difficulty level of the questions and the Practice Exams will make you familiar with the format and environment of an exam. You should refer this guide carefully before attempting your actual Microsoft AI Transformation Leader certification exam.
The Microsoft AI Transformation Leader certification is mainly targeted to those candidates who want to build their career in Microsoft Power Platform domain. The Microsoft Certified - AI Transformation Leader exam verifies that the candidate possesses the fundamental knowledge and proven skills in the area of Microsoft AI Transformation Leader.
Microsoft AI Transformation Leader Exam Summary:
| Exam Name | Microsoft Certified - AI Transformation Leader |
| Exam Code | AB-731 |
| Exam Price | $99 (USD) |
| Duration | 45 mins |
| Number of Questions | 40-60 |
| Passing Score | 700 / 1000 |
| Books / Training | AB-731T00-A: Drive AI transformation in your organization |
| Schedule Exam | Pearson VUE |
| Sample Questions | Microsoft AI Transformation Leader Sample Questions |
| Practice Exam | Microsoft AB-731 Certification Practice Exam |
Microsoft AB-731 Exam Syllabus Topics:
| Topic | Details |
|---|---|
Identify the business value of generative AI solutions (35 - 40%) |
|
| Identify the foundational concepts of generative AI |
- Describe the differences between generative AI and other types of AI - Select a generative AI solution to meet a business need - Describe the differences between AI models, including fine-tuned and pretrained models - Explain the cost drivers in generative AI usage, including tokens and return-on-investment (ROI) considerations - Identify the challenges of using generative AI solutions, including fabrications, reliability, and bias - Identify when generative AI solutions can provide business value, including scalability and automation |
| Identify benefits and capabilities of generative AI solutions |
- Describe the impact of prompt engineering - Understand techniques of prompt engineering - Identify business requirements for grounding solutions - Understand how retrieval-augmented generation (RAG) is used for AI solutions - Understand the impact of data on AI solutions, including data type, data quality, and representative datasets - Describe the importance of secure AI - Identify scenarios when machine learning adds value - Describe the lifecycle of a machine learning solution - Identify security considerations for AI systems, including application security, data security, and authentication requirements |
Identify benefits, capabilities, and opportunities for Microsoft’s AI apps and services (35 - 40%) |
|
| Identify benefits and capabilities of Microsoft 365 Copilot and Microsoft Copilot |
- Map business processes and use cases to Copilot - Understand differences in capabilities between versions of Copilot - Understand capabilities of Microsoft 365 Copilot Chat web and mobile experiences - Understand capabilities of the Copilot experience in various Microsoft 365 apps - Understand capabilities of Microsoft Copilot Studio - Understand capabilities of Microsoft Graph - Identify benefits and capabilities of an integrated Microsoft AI solution, including risk mitigation and safety benefits - Map business processes and use cases to Microsoft’s AI apps and services - Identify when to use Researcher or Analyst in Copilot - Identify when to build, buy, or extend, including the Microsoft 365 Copilot extensibility framework |
| Identify benefits and capabilities of Foundry Tools |
- Map business processes and use cases to Foundry Tools - Identify capabilities of Azure AI services, including Azure Vision in Foundry Tools, Azure AI Search, and Microsoft Foundry - Match an AI model to a business need - Identify the benefits of Microsoft Foundry and Foundry Tools, including scalability and security |
Identify an implementation and adoption strategy for Microsoft’s AI apps and services (20 - 25%) |
|
| Align an AI strategy with Microsoft responsible AI policies |
- Explain the importance of responsible AI - Establish governance principles for AI use - Establish an AI council to guide strategy, oversight, and cross-functional alignment - Ensure that AI solutions meet responsible AI standards, including fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability |
| Plan for AI adoption across the organization |
- Establish an adoption team - Identify common barriers to adoption - Establish an AI champions program - Understand potential impacts to data, security, privacy, and cost - Understand Copilot license types, including pay-as-you go, monthly, and included with Microsoft 365 subscription - Understand Azure AI services subscription models, including pay-as-you-go and prepaid |
To ensure success in Microsoft AI Transformation Leader certification exam, we recommend authorized training course, practice test and hands-on experience to prepare for Microsoft AI Transformation Leader (AB-731) exam.
