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  1. Home
  2. Microsoft Certification
  3. AB-731 Exam
  4. Microsoft.AB-731.v2026-10-16.q88 Dumps
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Question 51

Hotspot Question
Select the answer that correctly completes the sentence.

Correct Answer:
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Question 52

Hotspot Question
What should you use for each task? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation:
Box 1: Azure Document Intelligence in Foundry Tools
Extracting structured-data forms and invoices.
Azure Document Intelligence (formerly known as Azure Form Recognizer) within the Foundry Tools ecosystem can be used to extract structured data, including key-value pairs, tables, and specific fields from forms and invoices. It is designed to transform unstructured or semi-structured data from PDFs, images, and other files into actionable, structured JSON output.
Box 2: Azure Language in Foundry Tools
Summarizing written content from business reports.
Azure Language in Foundry Tools (formerly Azure AI Language) includes specific features for summarizing written content, including business reports, in both extractive and abstractive formats.
Key Summarization Capabilities
Native Document Summarization: This feature can directly parse and summarize files in their original formats, such as PDF, Word (DOCX), and plain text.
Summarization Approaches:
-Extractive: Selects the most important original sentences from the document to create a summary.
-Abstractive: Generates new, concise sentences that capture the main idea without directly copying the source text.
Powered by Advanced Models: The service utilizes Large Language Models (LLMs) and Small Language Models (SLMs), such as GPT-4o and Phi-3.5-mini, to provide high-quality, low-latency results.
Box 3: Azure Vision in Foundry Tools
Generate descriptive text for uploaded images.
Azure Vision in Foundry Tools (part of Azure AI Services within the Foundry ecosystem) can be used to analyze uploaded images and automatically generate descriptive, human-readable text.
This capability is part of the Image Analysis feature, which generates English-language captions describing the content of an image.
Key aspects of this functionality include:
*-> Descriptive Captions: The service generates complete sentences based on objects identified in the image, providing multiple options ordered by a confidence score.
*-> Image Tagging: It can generate a list of words (tags) identifying objects, beings, scenery, or actions.
Reference:
https://azure.microsoft.com/en-us/products/ai-foundry/tools/document-intelligence
https://azure.microsoft.com/en-us/products/ai-foundry/tools/vision
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Question 53

Your company plans to use an AI-powered solution to analyze customer feedback for insights related to future product designs.
You need to mitigate the privacy risks associated with the solution.
What is the best approach to achieve the goal? More than one answer choice may achieve the goal. Select the BEST answer.

Correct Answer: D
An AI-powered solution to analyze customer feedback while mitigating privacy risks requires a
"privacy by design" approach, utilizing automated, AI-driven PII (Personally Identifiable Information) masking to remove sensitive data before it reaches the analysis model. This process ensures compliance with regulations like GDPR and CCPA while maintaining data utility for sentiment and theme analysis.
That is a sound strategy. To effectively mitigate privacy risks while maintaining the utility of your AI analysis, you should implement a robust De-identification or Data Masking layer before the data hits the LLM.
Reference:
https://encompaas.cloud/blog/ai-and-privacy
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Question 54

Your company plans to use generative AI to help build a website that will showcase various existing products. Which capability best describes a benefit of using generative AI for this project?
More than one answer choice may achieve the goal. Select the BEST answer.

Correct Answer: C
Generative AI (GenAI) can significantly streamline the creation and localization of a product showcase website. Beyond standard word-for-word translation, GenAI tools--particularly those powered by Large Language Models (LLMs)--provide context-aware localization that adapts product descriptions to specific cultural nuances and brand tones.
Key Benefits of GenAI for Product Descriptions
Context-Aware Translation: Unlike older machine translation, GenAI understands the "intent" behind phrases, correctly handling idioms and technical terminology relevant to the product category.
Tone & Style Adaptation: You can instruct AI to translate a description into a "professional,"
"creative," or "technical" tone depending on the target audience.
Scalability: GenAI can process thousands of product listings simultaneously, reducing time-to- market by up to 90% compared to manual translation.
SEO Optimization: Some tools can automatically incorporate localized keywords into the translated description to improve search visibility in different regions.
Reference:
https://amplience.com/blog/create-personalized-product-descriptions-that-convert-with-ai
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Question 55

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
The correct answer is B. Testing the AI solution to identify and mitigate unfair or inconsistent outcomes directly supports Microsoft responsible AI principles, especially fairness, reliability and safety, accountability, and inclusiveness. Before deployment, organizations should evaluate whether the system behaves consistently across different user groups, avoids discriminatory outcomes, and produces safe and reliable outputs.
Automatically approving or rejecting loan applications increases risk unless strong governance and human oversight are in place. Collecting personal data can increase privacy exposure if it is not necessary and controlled. Prioritizing model performance alone is also insufficient because a technically accurate model can still produce biased, unsafe, or non-transparent outcomes. Responsible AI requires evaluation, mitigation, oversight, and monitoring.
insert code
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