2026年JPNTestの最新AB-731 PDFダンプおよびAB-731試験エンジンの無料共有：https://drive.google.com/open?id=1knthgcF_khwhDPqu_PMBMjz4UjwtntRl
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| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Microsoft Certified: AI Transformation Leader |
| Exam Number: | AB-731 |
| Certificate Validity Period: | 1 year (renewable) |
| Exam Price: | USD 99 |
| Passing Score: | 700 / 1000 |
| Related Certifications: | Microsoft Certified: AI Transformation Leader |
| Available Languages: | English |
| Exam Format: | Build list, Case studies, Drag and drop, Multiple choice |
| Exam Duration: | 45 minutes |
| Real Exam Qty: | 40-60 |
| 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 |
AB-731認定資格を取得して、専門能力を高めてください。認定資格を取得すると、より良い仕事の機会とより高い給料を得ることができます。それでは、AB-731試験トレーニングガイドから準備を始めましょう。 JPNTestが提供するAB-731実践PDFは、すべてのお客様に適した最新かつ有効なものです。無料デモは、特に購入前に無料でダウンロードして試してみることができます。 AB-731模擬試験ダンプから多くを取得し、AB-731認定を簡単に取得できます。
| トピック | 出題範囲 |
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| トピック 1 |
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| トピック 2 |
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| トピック 3 |
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質問 # 23
Your company receives thousands of scanned invoices each month.
You need to recommend an AI solution that can automatically extract key details, such as invoice numbers, vendor names, and total amounts.
What is the best solution to recommend? More than one answer choice may achieve the goal.
Select the BEST answer.
正解：D
解説：
Azure Document Intelligence in Foundry Tools is the preferred solution for automatically extracting structured data-such as vendor names, invoice IDs, and total amounts-from invoices, PDFs, and images. It utilizes advanced AI and OCR to convert unstructured documents into structured JSON data.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/prebuilt/invoice
質問 # 24
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
* A manufacturer can use Azure Vision in Foundry Tools to identify product defects on an assembly line.
The answer: Yes
* A logistics company can use Azure Vision in Foundry Tools to recognize package shipping labels.
The 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.
質問 # 25
For each of the following statements, select Yes if the statement is true. Otherwise, select No. NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Answer Area
* Allowing AI models to make autonomous decisions supports the Microsoft responsible AI principle of accountability. Answer: No
* Regularly testing AI models for fairness and inclusiveness helps ensure they align with Microsoft's Responsible AI principles. Answer: Yes
* Protecting user data and limiting access to personal information supports the Microsoft responsible AI principles of privacy and security. Answer: Yes Microsoft's Responsible AI principles emphasize that people and organizations must remain accountable for AI systems and their outcomes. Accountability is strengthened by governance, human oversight, clear ownership, auditability, and processes to review and address issues-not by letting models make unchecked autonomous decisions. Therefore, statement 1 is No : increasing autonomy can actually increase risk unless paired with human-in-the-loop controls and clear escalation paths, because accountability requires clear responsibility for decisions and impacts.
Statement 2 is Yes because fairness and inclusiveness are explicitly supported through ongoing evaluation.
Regular testing helps detect disparate impact, performance gaps across user groups, and unintended bias introduced by data drift or changes in usage patterns. It's not a one-time activity; it's continuous assurance that the system behaves appropriately as conditions change.
Statement 3 is Yes because privacy and security are directly supported by protecting personal/sensitive data, enforcing least privilege access, and implementing controls such as data loss prevention, encryption, access logging, and strong identity governance. Limiting access to personal information reduces exposure and supports compliance obligations while aligning with privacy-by-design and secure-by-design expectations for AI-enabled solutions.
質問 # 26
Hotspot Question
Select the answer that correctly completes the sentence.
正解：
解説：
Explanation:
Box: Batch API
An organization that runs continuous, large-scale workloads with Azure OpenAI models should choose the _______ pricing model.
An organization that runs continuous, large-scale, non-time-sensitive workloads with Azure OpenAI models should choose the Batch API pricing model.
This approach provides significant cost savings and operational advantages for high-volume, asynchronous tasks.
For continuous, non-urgent workloads, the Batch API provides the best balance of cost- effectiveness and throughput, often allowing organizations to cut their AI inference costs in half while maximizing scalability.
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/batch?view=foundry-classic
質問 # 27
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?
正解：A
解説：
An AI solution that rejects all loan applications based solely on an applicant being older than a certain age violates the Fairness principle in Microsoft's Responsible AI framework.
Here is a breakdown of why this constitutes a violation:
Violation of the "Fairness" Principle
Microsoft defines fairness as the commitment to treating all individuals and groups equitably, avoiding biases that could lead to unfair discrimination.
Discriminatory Outcome: Automatically rejecting a group based on a protected characteristic (age) is a textbook example of algorithmic bias and "allocation harm," where an AI system unfairly denies resources or opportunities.
Lack of Individual Assessment: The system treats every applicant in a certain age group the same, ignoring individual creditworthiness, financial stability, or income.
Reference:
https://infusedinnovations.com/blog/responsible-ai-fairness
質問 # 28
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AB-731試験対策: https://www.jpntest.com/shiken/AB-731-mondaishu
2026年JPNTestの最新AB-731 PDFダンプおよびAB-731試験エンジンの無料共有：https://drive.google.com/open?id=1knthgcF_khwhDPqu_PMBMjz4UjwtntRl