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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Certified: AI Transformation Leader |
| Exam Number: | AB-731 |
| Available Languages: | English |
| Passing Score: | 700 / 1000 |
| Related Certifications: | Microsoft Certified: AI Transformation Leader |
| Exam Duration: | 45 minutes |
| Real Exam Qty: | 40-60 |
| Certificate Validity Period: | 1 year (renewable) |
| Exam Price: | USD 99 |
| Exam Format: | Drag and drop, Multiple choice, Case studies, Build list |
| Sample Questions: | Microsoft AB-731 Sample Questions |
| Exam Way: | Online or at a test centre |
| Pre Condition: | No formal prerequisites. Recommended: familiarity with Microsoft 365 services, Azure AI services, and experience with adoption or change management in a business context. This certification is designed for business decision-makers at all levels; no coding is required. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/ab-731 |
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NEW QUESTION # 74
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Answer Area
* A manufacturer can use Azure Vision in Foundry Tools to identify product defects on an assembly line. Answer: Yes
* A logistics company can use Azure Vision in Foundry Tools to recognize package shipping labels. Answer: Yes
* The HR department at your company can only use Azure Vision in Foundry Tools to extract written content from Microsoft Word files. Answer: No Azure Vision in Foundry Tools provides computer vision capabilities to analyze images, including identifying visual features and reading text with OCR. Because it is designed to "analyze images" and support vision scenarios, it can be applied to manufacturing quality inspection use cases where the goal is to detect anomalies/defects from images captured on a production line. This aligns with statement 1 being Yes .
Statement 2 is also Yes because recognizing shipping labels is fundamentally text extraction from images (often plus some layout/field parsing). Azure Vision supports optical character recognition (OCR) to read printed text from images, and Microsoft documentation explicitly notes OCR can extract text from images such as product labels and similar real-world text surfaces-making shipping labels a direct fit.
Statement 3 is No because it is incorrectly restrictive. Azure Vision is not limited to extracting written content from Word documents, nor is OCR restricted to Word files. Vision capabilities apply broadly to images (and, depending on the capability, various document/image inputs) for tasks like image analysis and text recognition. HR could use it for many scenarios such as extracting text from scanned images, photos, or other visual inputs-not "only" Word files.
NEW QUESTION # 75
Your company is preparing to adopt Microsoft 365 Copilot and wants to follow Microsoft responsible AI principles.
As a business leader, you propose establishing an AI governance council to ensure alignment with the responsible AI principles.
What is the primary purpose of the council? More than one answer choice may achieve the goal.
Select the BEST answer.
Answer: D
Explanation:
Establishing an AI Governance Council is a critical step for organizations adopting Microsoft 365 Copilot to ensure that AI initiatives remain safe, ethical, and strategically aligned. This multidisciplinary body acts as the "operating system" for trustworthy AI, bridging the gap between technical teams and executive leadership.
Core Responsibilities of the Council
The council typically oversees the entire AI lifecycle across several key areas:
*-> Strategic Guidance: Aligning AI adoption with business goals and defining the organization's AI vision and acceptable use policies.
Ethical Oversight: Ensuring all solutions adhere to responsible AI principles such as fairness, transparency, and accountability.
Risk Management: Identifying and mitigating potential harms, including data leakage, algorithmic bias, and regulatory non-compliance.
*-> Cross-Functional Alignment: Bringing together stakeholders from IT, Legal, HR, Compliance, and individual business units to prevent siloed decision-making.
Policy Enforcement: Approving specific high-risk use cases and overseeing the implementation of technical guardrails like Microsoft Purview for data classification and protection.
Reference:
https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/scenarios/ai/strategy
https://adoption.microsoft.com/files/copilot/LeadingintheEraofAI_%20CreatinganAICouncil_Mar20
24.pdf
NEW QUESTION # 76
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.
Answer:
Explanation:
Explanation:
Box 1: Yes
Yes - Content filtering controls can prevent AI-generated responses from exposing confidential and sensitive information.
Content filtering controls are a critical safeguard for preventing AI-generated responses from inadvertently exposing confidential or sensitive information. These controls operate as
"guardrails" by inspecting data at both the input (prompt) and output (completion) stages.
Box 2: Yes
Yes - AI-generated content can unintentionally reveal sensitive information if the generative AI model has access to unsecured data source.
Unsecured data sources significantly increase the risk of AI-generated content exposing sensitive information through several mechanisms. Because generative AI models are "data-hungry" and often lack transparent data boundaries, they can absorb and later reproduce confidential data they were exposed to during training or operation.
Box 3: No
No - To prevent data exposure, only the prompts used by users must be protected by using policies.
While protecting user prompts is a critical first step, it is not sufficient on its own to prevent data exposure. Relying solely on prompt policies leaves significant gaps where sensitive data can still leak through other vectors.
Reference:
https://noma.security/resources/ai-application-security/
https://pacific.ai/managing-privacy-risks-llm-guidance/
https://www.paloaltonetworks.com/blog/network-security/securing-the-future-by-protecting- sensitive-data-in-ai-systems
NEW QUESTION # 77
Your company plans to build a generative AI solution based on internal data. You recommend using Microsoft Foundry as a starting point to develop and manage the solution. What is a key benefit of using Microsoft Foundry for this project?
Answer: B
Explanation:
Microsoft Foundry is positioned as a unified, enterprise-grade platform that helps organizations build, deploy, scale, and govern AI apps and agents-especially generative AI solutions that need to work with business context and internal data. That directly aligns with A: Foundry provides a scalable platform for developing and deploying generative AI solutions. Microsoft describes Foundry as an interoperable platform that makes it easier to build, deploy, and scale AI apps and agents, while also providing centralized security and governance features for organizations.
B is incorrect because Foundry does not remove model choice/configuration; in fact, it supports selecting among models and using tools/frameworks to build solutions. You still choose appropriate model(s), configure endpoints, and design grounding and safety controls.
C and D are not the best characterization of Foundry's primary benefit. While Foundry offers "friendly interfaces," Microsoft primarily positions it for developers, model builders, and enterprise AI operations-not as a low-code platform for business users (that role is more commonly filled by Copilot Studio/Power Platform).
NEW QUESTION # 78
You are exploring how Microsoft 365 Copilot uses Microsoft Graph to deliver AI-powered experiences.
Which information in Microsoft Graph can Copilot use by default?
Answer: D
Explanation:
Microsoft 365 Copilot is designed to act as an AI-powered assistant that leverages Microsoft Graph to access your organization's data, including emails, files, chats, and meetings. By default, Copilot integrates with Microsoft 365 apps and uses this data to provide contextually relevant, real-time assistance.
Key Capabilities via Microsoft Graph
*-> Data Access: Copilot retrieves information from emails, files (OneDrive/SharePoint), meetings (Teams transcripts), and chats.
Grounding: It uses this data to "ground" prompts, providing responses that are specific to your actual work rather than general information.
Semantic Indexing: Copilot creates a semantic index of your Graph data to understand relationships and intent, making search and retrieval more accurate.
Reference:
https://learn.microsoft.com/en-us/copilot/microsoft-365/enterprise-data-protection
NEW QUESTION # 79
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