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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Certified: AI Transformation Leader |
| Exam Number: | AB-731 |
| Related Certifications: | Microsoft Certified: AI Transformation Leader |
| Available Languages: | English |
| Passing Score: | 700 / 1000 |
| Real Exam Qty: | 40-60 |
| Exam Duration: | 45 minutes |
| Certificate Validity Period: | 1 year (renewable) |
| Exam Price: | USD 99 |
| Exam Format: | Build list, Multiple choice, Case studies, Drag and drop |
| 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 # 42
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 - Microsoft Foundry provides a unified platform for developers and data professionals to create custom end-to-end AI solutions.
Microsoft Foundry is an interoperable, unified platform designed to help organizations build, deploy, and govern AI applications and agents.
The platform serves a wide range of professionals, including developers, data scientists, machine learning groups, data engineers, and IT administrators. It centralizes fragmented AI tools into a single environment to streamline the transition from prototyping to production Box 2: Yes Yes - Microsoft Foundry provides a unified platform for low-code developers and business users to create custom end-to-end AI solutions.
Azure AI Foundry is a unified platform designed for developers, data scientists, and business users to build, deploy, and govern end-to-end AI applications, agents, and copilots securely. It integrates tools for model selection, evaluation, and customization (including OpenAI and open- source models) with enterprise-grade governance and a no-code Agent Builder.
Box 3: No
No - You need a Microsoft 365 Copilot license to access Microsoft Foundry services.
You do not need a Microsoft 365 Copilot license to access or build with Microsoft Foundry (now primarily known as Azure AI Foundry).
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/what-is-foundry
https://azure.microsoft.com/en-us/products/ai-foundry
https://learn.microsoft.com/en-us/microsoft-365-copilot/extensibility/faq
NEW QUESTION # 43
Your company manages an online catalog of office supplies.
You plan to use a generative AI solution to create product descriptions for your company's website.
The solution must ensure descriptions can be posted immediately after creation, enable selection/inclusion of product details, and be fast and simple for non- technical staff.
What is the best type of solution to use? Select the BEST answer.
Answer: C
NEW QUESTION # 44
You have a business unit that uses an AI solution to process loan applications. You discover that the solution rejects the application of all applicants that are older than 60 years of age. Which Microsoft responsible AI principle is this violating?
Answer: C
NEW QUESTION # 45
You need to recommend a service that supports indexing information and knowledge mining by extracting insights from documents. What should you recommend?
Answer: C
Explanation:
The requirement has two key phrases: indexing information and knowledge mining by extracting insights from documents. The Microsoft service purpose-built for this is Azure AI Search (formerly Azure Cognitive Search), which provides a search index over your content and supports "AI enrichment" workflows to extract and structure insights from documents during indexing.
Azure AI Search can ingest content from common enterprise sources (files, blobs, databases), build searchable indexes, and enrich the indexed content using built-in skills or integrated AI capabilities-such as entity recognition, key phrase extraction, language detection, and OCR (depending on the pipeline). This is exactly what "knowledge mining" refers to: turning large volumes of unstructured documents into structured, searchable knowledge that applications and users can query.
The other choices are partial fits: Azure Vision focuses on image/video analysis, not general document indexing. Azure Document Intelligence is excellent for extracting fields/tables from forms and documents, but on its own it does not provide the full indexing/search and knowledge mining layer across a corpus. Microsoft Foundry is an overarching platform for building AI apps/agents; it can incorporate search, but the specific service that directly delivers indexing + knowledge mining is Azure AI Search.
NEW QUESTION # 46
- 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
* Content filtering controls can prevent AI-generated responses from exposing confidential and sensitive information. Answer: Yes
* AI-generated content can unintentionally reveal sensitive information if the generative AI model has access to unsecured data sources. Answer: Yes
* To prevent data exposure, only the prompts used by users must be protected by using policies. Answer:
No
* Yes - Content filtering (and related safety controls) can help reduce the chance that responses contain policy-violating or sensitive outputs by detecting and blocking certain categories of content. While filtering is not a perfect guarantee, it is a recognized control to prevent or reduce exposure risk in outputs (for example, blocking regulated data patterns, disallowed content categories, or unsafe disclosures).
* Yes - If a model (or the solution's retrieval layer) can access poorly governed repositories-such as broadly shared folders, misconfigured SharePoint sites, or unsecured databases-then the system can surface sensitive information in responses even without malicious intent. This is why access control, data classification, and permission hygiene are critical prerequisites for deploying AI assistants grounded in organizational content.
* No - Protecting only user prompts is insufficient. Data exposure can occur through multiple paths:
retrieved documents, generated outputs, logs/telemetry, training/fine-tuning data, and connector/index configuration. Preventing exposure requires layered controls: data governance (labels, DLP, least privilege), secure connectors, output filtering, auditing, and user training-not prompt policy alone.
NEW QUESTION # 47
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