Microsoft - AB-731: AI Transformation Leader
Sample Questions
Question: 104
Measured Skill: Identify benefits, capabilities, and opportunities for Microsoft’s AI apps and services (35–40%)
Your company uses Microsoft 365 Copilot.
You identify several business processes that require custom workflows and specialized automation.
You need to recommend a solution that extends Copilot capabilities while minimizing development effort and costs.
What should you recommend?| A | Create an agent by using Microsoft Foundry. |
| B | Deploy a Copilot connector. |
| C | Build a custom agent by using the full experience of Microsoft Copilot Studio. |
| D | Build a declarative agent by using the lite experience of Microsoft Copilot Studio. |
Correct answer: DExplanation:
Declarative agents enable you to customize Microsoft 365 Copilot to help you meet the unique business needs of your users. When you build a declarative agent, you provide the instructions, actions, and knowledge to tailor Copilot for your business scenarios. Declarative agents run on the same orchestrator, foundation models, and trusted AI services that power Microsoft 365 Copilot. By building declarative agents, you can optimize collaboration, increase productivity, and streamline workflows in your organization.
With declarative agents, you can establish consistent, personalized experiences and automate intricate processes, ranging from team onboarding to efficient resolution of customer issues. You can also add capabilities to your agent to unlock more functionality for your users.
References:
Declarative agents for Microsoft 365 Copilot
Choose between Microsoft 365 Copilot and Copilot Studio to build your agent
Introduction to declarative agents for Microsoft 365 Copilot
Question: 105
Measured Skill: Identify an implementation and adoption strategy for Microsoft’s AI apps and services (20–25%)
What is a key feature of Microsoft 365 Copilot that aligns with the Microsoft responsible AI principles of transparency, reliability, and safety?| A | Automatically approves AI-generated content for company-wide publishing. |
| B | Removes the need for a human to review AI-generated outputs. |
| C | Provides grounded, verifiable responses based on organizational data. |
| D | Enables users to select from an authorized catalog of AI models. |
Correct answer: CExplanation:
Microsoft created a Responsible AI Standard, a framework for building AI systems based on six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. These principles are the foundation of a responsible and trustworthy approach to AI, especially as intelligent technology becomes more common in everyday products and services.
Fairness and inclusiveness
AI systems should treat everyone fairly and avoid affecting similar groups differently. For example, when AI systems provide guidance on medical treatment, loan applications, or employment, they should make the same recommendations to people with similar symptoms, financial circumstances, or qualifications.
Reliability and safety
To build trust, AI systems must operate reliably, safely, and consistently. They should function as designed, respond safely to unexpected conditions, and resist harmful manipulation. Their behavior and ability to handle different conditions reflect the range of situations developers anticipated during design and testing.
Transparency
When AI systems inform decisions that impact people's lives, it's critical that people understand how those decisions are made. For example, a bank might use an AI system to decide if a person is creditworthy, or a company might use one to select job candidates.
A crucial part of transparency is interpretability: providing useful explanations of AI system behavior. Improving interpretability helps stakeholders understand how and why AI systems work, so they can identify performance issues, fairness concerns, exclusionary practices, or unintended outcomes.
Privacy and security
As AI becomes more common, protecting privacy and securing personal and business information is more important and complex. Privacy and data security require close attention because AI systems need data to make accurate predictions and decisions. AI systems must comply with privacy laws that:
- Require transparency about the collection, use, and storage of data.
- Mandate that consumers have appropriate controls to choose how their data is used.
Accountability
People who design and deploy AI systems must be accountable for how those systems operate. Organizations should use industry standards to develop accountability norms. These norms help ensure that AI systems are not the final authority on decisions that affect people's lives and that humans maintain meaningful control over highly autonomous systems.
Reference: What is Responsible AI?
Question: 106
Measured Skill: Identify the business value of generative AI solutions (35–40%)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
(NOTE: Each correct selection is worth one point.)
| A | Users that want to reason over work data by using a natural language prompt in Microsoft 365 Copilot must have a Copilot add-on license: Yes
Microsoft 365 Copilot is included in Microsoft 365 E3 and Microsoft 365 E5 licenses: Yes
Some Microsoft 365 Copilot services are available through a pay-as-you-go plan: Yes |
| B | Users that want to reason over work data by using a natural language prompt in Microsoft 365 Copilot must have a Copilot add-on license: Yes
Microsoft 365 Copilot is included in Microsoft 365 E3 and Microsoft 365 E5 licenses: Yes
Some Microsoft 365 Copilot services are available through a pay-as-you-go plan: No |
| C | Users that want to reason over work data by using a natural language prompt in Microsoft 365 Copilot must have a Copilot add-on license: Yes
Microsoft 365 Copilot is included in Microsoft 365 E3 and Microsoft 365 E5 licenses: No
Some Microsoft 365 Copilot services are available through a pay-as-you-go plan: Yes |
| D | Users that want to reason over work data by using a natural language prompt in Microsoft 365 Copilot must have a Copilot add-on license: No
Microsoft 365 Copilot is included in Microsoft 365 E3 and Microsoft 365 E5 licenses: Yes
Some Microsoft 365 Copilot services are available through a pay-as-you-go plan: Yes |
| E | Users that want to reason over work data by using a natural language prompt in Microsoft 365 Copilot must have a Copilot add-on license: No
Microsoft 365 Copilot is included in Microsoft 365 E3 and Microsoft 365 E5 licenses: No
Some Microsoft 365 Copilot services are available through a pay-as-you-go plan: Yes |
| F | Users that want to reason over work data by using a natural language prompt in Microsoft 365 Copilot must have a Copilot add-on license: No
Microsoft 365 Copilot is included in Microsoft 365 E3 and Microsoft 365 E5 licenses: No
Some Microsoft 365 Copilot services are available through a pay-as-you-go plan: No |
Correct answer: CExplanation:
To reason over organizational work data (emails, files, meetings, Teams chats via Microsoft Graph) using natural-language prompts, users must have the Microsoft 365 Copilot add-on license. Without the add-on, users are limited mainly to web-grounded Copilot Chat and do not get tenant-grounded reasoning over Microsoft Graph data.
Microsoft 365 Copilot is not included by default in Microsoft 365 E3 or E5. E3 and E5 are eligible base licenses, but Microsoft 365 Copilot must be purchased and assigned as a separate add-on.
Microsoft offers a pay-as-you-go (PAYG) option for certain Copilot services, including Microsoft 365 Copilot Chat, SharePoint agents, and some agent and retrieval scenarios. This allows organizations to use selected Copilot capabilities without assigning a full Copilot license, paying instead based on usage.
References:
License options for Microsoft 365 Copilot
Microsoft 365 Copilot pay-as-you-go overview for IT admins
License options for Microsoft 365 Copilot
Question: 107
Measured Skill: Identify an implementation and adoption strategy for Microsoft’s AI apps and services (20–25%)
Match the Microsoft responsible AI principles to the appropriate descriptions.
(To answer, drag the principle from the column on the left to its description on the right. Each principle may be used once, more than once, or not at all. NOTE: Each correct match is worth one point.)
| A | Protect personal information and apply strong safeguards to keep data secure: Privacy and security
Make AI solutions understandable by explaining how and why decisions are made: Transparency
Design AI solutions that are accessible to people of all abilities and experiences: Inclusiveness
Involve human oversight in the control of AI solutions: Accountability |
| B | Protect personal information and apply strong safeguards to keep data secure: Reliability and safety
Make AI solutions understandable by explaining how and why decisions are made: Fairness
Design AI solutions that are accessible to people of all abilities and experiences: Transparency
Involve human oversight in the control of AI solutions: Inclusiveness |
| C | Protect personal information and apply strong safeguards to keep data secure: Privacy and security
Make AI solutions understandable by explaining how and why decisions are made: Transparency
Design AI solutions that are accessible to people of all abilities and experiences: Inclusiveness
Involve human oversight in the control of AI solutions: Accountability |
| D | Protect personal information and apply strong safeguards to keep data secure: Reliability and safety
Make AI solutions understandable by explaining how and why decisions are made: Inclusiveness
Design AI solutions that are accessible to people of all abilities and experiences: Fairness
Involve human oversight in the control of AI solutions: Accountability |
| E | Protect personal information and apply strong safeguards to keep data secure: Accountability
Make AI solutions understandable by explaining how and why decisions are made: Reliability and safety
Design AI solutions that are accessible to people of all abilities and experiences: Privacy and security
Involve human oversight in the control of AI solutions: Fairness |
| F | Protect personal information and apply strong safeguards to keep data secure: Privacy and security
Make AI solutions understandable by explaining how and why decisions are made: Transparency
Design AI solutions that are accessible to people of all abilities and experiences: Inclusiveness
Involve human oversight in the control of AI solutions: Reliability and safety |
Correct answer: AExplanation:
Microsoft created a Responsible AI Standard, a framework for building AI systems based on six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability. These principles are the foundation of a responsible and trustworthy approach to AI, especially as intelligent technology becomes more common in everyday products and services.
Fairness and inclusiveness
AI systems should treat everyone fairly and avoid affecting similar groups differently. For example, when AI systems provide guidance on medical treatment, loan applications, or employment, they should make the same recommendations to people with similar symptoms, financial circumstances, or qualifications.
Reliability and safety
To build trust, AI systems must operate reliably, safely, and consistently. They should function as designed, respond safely to unexpected conditions, and resist harmful manipulation. Their behavior and ability to handle different conditions reflect the range of situations developers anticipated during design and testing.
Transparency
When AI systems inform decisions that impact people's lives, it's critical that people understand how those decisions are made. For example, a bank might use an AI system to decide if a person is creditworthy, or a company might use one to select job candidates.
A crucial part of transparency is interpretability: providing useful explanations of AI system behavior. Improving interpretability helps stakeholders understand how and why AI systems work, so they can identify performance issues, fairness concerns, exclusionary practices, or unintended outcomes.
Privacy and security
As AI becomes more common, protecting privacy and securing personal and business information is more important and complex. Privacy and data security require close attention because AI systems need data to make accurate predictions and decisions. AI systems must comply with privacy laws that:
- Require transparency about the collection, use, and storage of data.
- Mandate that consumers have appropriate controls to choose how their data is used.
Accountability
People who design and deploy AI systems must be accountable for how those systems operate. Organizations should use industry standards to develop accountability norms. These norms help ensure that AI systems are not the final authority on decisions that affect people's lives and that humans maintain meaningful control over highly autonomous systems.
References:
What is Responsible AI?
Identify guiding principles for responsible AI
Question: 108
Measured Skill: Identify the business value of generative AI solutions (35–40%)
Select the answer that correctly completes the sentence.
| A | The cost of using generative AI language models is based typically on the number of documents processed. |
| B | The cost of using generative AI language models is based typically on the number of requests processed. |
| C | The cost of using generative AI language models is based typically on the number of tokens processed. |
| D | The cost of using generative AI language models is based typically on the number of words processed. |
Correct answer: CExplanation:
Each Azure OpenAI API has a different billing methodology. For processing and generating text with the Responses or Chat Completions API, you're billed based on the number of tokens you submit as a prompt and the number of tokens that are generated as a result (completion).
Each LLM model (for example, GPT-5.2, or GPT-5.2-mini) usually has a different price, which reflects the amount of computation required to process and generate tokens. Many times, price is presented as "price per 1,000 tokens" or "price per 1 million tokens."
This pricing model has a significant effect on how you design the user interactions and the amount of preprocessing and post-processing you add.
Reference: Key concepts and considerations for building generative AI solutions