Free AB-731 Questions for Microsoft AI Transformation Leader AB-731 Exam as PDF & Practice Test Engine
What is a key feature of Microsoft 365 Copilot that aligns with the Microsoft responsible AI principles of transparency, reliability, and safety?
Correct Answer: C
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A mid-sized company wants to give all 500 employees access to AI assistance. The company uses Microsoft 365 E3 but has not purchased any additional AI licences. The CEO wants to understand the difference between the free Microsoft Copilot available to all employees and the paid Microsoft 365 Copilot add-on before approving the budget.
What is the key difference between these two products?
What is the key difference between these two products?
Correct Answer: C
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Your company stores hundreds of internal business reports.
You need to recommend a generative AI solution that uses an agent to answer questions based on the content in the reports.
What should you include in the recommendation?
You need to recommend a generative AI solution that uses an agent to answer questions based on the content in the reports.
What should you include in the recommendation?
Correct Answer: B
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Your company is reviewing a new AI solution before deploying it. The company wants to ensure that the solution follows Microsoft responsible AI principles. What is the best approach to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.
Correct Answer: B
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Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: No
No - Retrieval Augmented Generation (RAG) requires model fine-tuning.
Retrieval Augmented Generation (RAG) does not require model fine-tuning; it is designed to enhance Large Language Models (LLMs) with external data without modifying their internal parameters. RAG enables fast knowledge updates and reduces hallucinations by fetching relevant information. While fine-tuning adjusts weights for domain-specific behavior, RAG is for dynamic, up-to-date knowledge.
Box 2: Yes
Yes - Retrieval Augmented Generation (RAG) is helpful when you need a generative AI solution that can access current, verifiable information.
Think of Retrieval Augmented Generation (RAG) as giving an AI an "open-book exam" instead of forcing it to rely solely on its internal memory.
By connecting the model to external, authoritative data sources-like a company's private knowledge base or real-time news-it becomes significantly more reliable in several ways:
Reduces Hallucinations: Because the AI must ground its answers in the retrieved documents, it's less likely to "make things up".
Transparency: You can see the exact source used for the answer, making it easy to verify facts.
Cost-Efficiency: It is often much cheaper and faster to update a RAG database than it is to retrain or fine-tune a massive model on new information Box 3: Yes Yes - Retrieval Augmented Generation (RAG) enables you to get more relevant responses based on your organization's documents without retraining the base model.
Retrieval-Augmented Generation (RAG) is an AI framework that improves the accuracy and relevance of Large Language Model (LLM) outputs by incorporating, in real-time, external data that was not part of the model's original training, all without the need to retrain or fine-tune the base model. This method is particularly effective for allowing AI systems to access and utilize an organization's proprietary, private, or constantly updating data to generate more contextually accurate and authoritative responses.
Reference:
https://www.redhat.com/en/topics/ai/rag-vs-fine-tuning
https://pub.towardsai.net/how-rag-powers-smart-ai-applications-8d005696baa3
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: Yes
Prompt engineering is the practice of designing, structuring, and refining text inputs given to a generative AI model. By providing explicit constraints, formatting parameters, and guidelines, it directly steers the model to yield highly accurate and relevant output.
Box 2: No
The part of the prompt that includes examples to demonstrate the desired output structure or style is called Examples (often referred to in context as few-shot examples or learning data). The Instruction is the specific task, command, or action you want the model to perform (e.g.,
"Summarize this document" or "Translate the text").
Box 3: Yes
The Context provides background data, domain-specific details, situational boundaries, or source documents (such as grounding data) that the model must reference or operate within to formulate a targeted and contextualized response.
An organization wants to enhance employee productivity by using generative AI within tools such as Word, Excel, PowerPoint, Outlook, and Teams.
The solution must assist users by generating content, summarizing meetings, analyzing data, and drafting communications within their daily workflow.
Which solution should the organization implement?
The solution must assist users by generating content, summarizing meetings, analyzing data, and drafting communications within their daily workflow.
Which solution should the organization implement?
Correct Answer: B
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Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: Yes
Yes - Microsoft 365 Copilot enable you to index data from multiple sources to make the data available in Copilot.
Microsoft 365 Copilot enables you to index data from multiple external, non-Microsoft sources- such as Salesforce, Jira, Confluence, and enterprise databases-into the Microsoft Graph to make that data available, searchable, and actionable within Copilot. This is primarily achieved through Microsoft Graph Connectors and Copilot Studio.
Box 2: Yes
Yes - You can build custom Microsoft 365 Copilot connector when the available connectors do not meet your data integration requirements.
Building a custom Microsoft 365 Copilot connector is the recommended approach when pre-built connectors do not meet specific data integration requirements, allowing you to bring external, line-of-business data into the Microsoft Graph for Copilot to reason over.
Box 3: No
No - To use Microsoft 365 Copilot connectors, you need a Microsoft Copilot Studio license.
This is not entirely correct. While Microsoft Copilot Studio is a primary tool for managing extensions, you do not necessarily need a standalone Copilot Studio license to use Microsoft 365 Copilot connectors.
Reference:
https://learn.microsoft.com/en-us/microsoft-365-copilot/extensibility/overview-copilot-connector
https://office365itpros.com/2025/09/29/microsoft-365-copilot-connector
https://learn.microsoft.com/en-us/microsoft-365-copilot/extensibility/cost-considerations
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