Microsoft Certified AB 731 AI Transformation Leader Exam

3 Exam Practice set for Microsoft Certified AB 731 AI Transformation Leader Exam

This practice set has been designed for all leaders who want to get certified in gen AI skill that Leverage AI tools across Microsoft 365 to draft documents, analyze data, collaborate, and automate tasks for improved productivity and decision-making.

There are 3 Practice set added in course. Each Practice set having 50 unique questions based on listed below concept and techniques as per Microsoft documentation about AB 731.

There are 50 minutes assigned to each practice set and passing score in 75%. Try to complete the each practice set before 50 mins. After test review your incorrect responses against well defined explanation added against.

There 150 unique questions added in this practice set.

As a candidate for this Microsoft Certification, you should understand how to recognize opportunities for AI transformation, identify the right AI tools and resources, plan for AI adoption, optimize business processes, and drive innovation by using Microsoft 365 Copilot and Azure AI services.

This Certification is designed for business decision-makers at all levels who are responsible for guiding transformation and innovation within their teams or organizations. In this role, you’re expected to demonstrate AI fluency, strategic vision, and the ability to lead AI adoption across teams and functions but are not expected to write any code.

As a candidate for this Certification, you should be able to evaluate AI opportunities, champion responsible AI practices, and align AI investments with business goals. You need experience leading adoption or change management in a business context. You must also be familiar with Microsoft 365 services, Azure AI services, and general AI capabilities.

Following Skills require before attempt the practice set. It is recommend that before attempting the practice set make sure you understand the following listed concepts.

• Identify the business value of generative AI solutions (35–40%)

• Identify benefits, capabilities, and opportunities for Microsoft’s AI apps and services (35–40%)

• Identify an implementation and adoption strategy for Microsoft’s AI apps and services (20–25%)

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 Azure AI services

• Map business processes and use cases to Azure AI services

• Identify capabilities of Azure AI services, including Azure AI Vision, Azure AI Search, and Azure AI Foundry

• Match an AI model to a business need

• Identify the benefits of Azure AI services for generative AI, 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