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Microsoft AI Transformation Leader Sample Questions (Q70-Q75):

NEW QUESTION # 70
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 # 71
Your company plans to use generative AI to help summarize and analyze internal business documents. You need to recommend a solution to prevent generative AI from accessing confidential or classified information.
What should you include in the recommendation?

Answer: A

Explanation:
Preventing generative AI from accessing confidential or classified information is primarily a data access and classification control problem. The most effective broad solution is data governance (B) -the framework of policies and controls that ensures sensitive content is identified, classified, protected, and access is restricted using least privilege. Data governance includes information classification/sensitivity labels, access control reviews, secure sharing practices, data loss prevention (DLP), and auditing-controls that directly limit what data is available to the AI through permission trimming and policy enforcement.
An information barrier (A) policy is more specific: it's intended to prevent communication and collaboration between defined user groups (often for regulatory/ethical walls). It does not comprehensively address document classification or restrict AI access to sensitive files across the tenant. A data retention policy (C) governs how long content is kept and when it's deleted; it's not a primary access-prevention mechanism. Communication monitoring (D) is a detection/oversight control; it can help identify risky activity, but it does not itself prevent access to confidential content by the AI.
Therefore, to prevent AI from surfacing confidential/classified data during summarization and analysis, you should recommend data governance as the primary control layer.


NEW QUESTION # 72
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: B

Explanation:
The task is high-volume content generation with consistent structure and immediate publishing: product descriptions that reliably include chosen product attributes (brand, specs, materials, dimensions, use cases) and can be produced quickly by non-technical staff. The best fit is a fine-tuned LLM (D) because fine-tuning can standardize tone, format, and completeness against your catalog schema, reducing variability and minimizing manual editing before posting. With a fine-tuned model, you can strongly enforce style guidelines (length, voice, prohibited claims), and you can template prompts so staff only supply product fields and get publish-ready copy.
Option A is not best: Azure Machine Learning is excellent for predictive models but is unnecessary for straightforward text generation. B (Researcher) is optimized for multistep research across work data + web, not deterministic product copy generation. C (interactive agent) can help collect requirements, but it's more complexity than needed; the core need is consistent text generation from structured product data, which fine- tuning addresses directly while keeping user interaction simple (fill fields # generate description).


NEW QUESTION # 73
HOTSPOT - Select the answer that correctly completes the sentence.
Microsoft 365 Copilot can be used to __________.

Answer:

Explanation:

Explanation:
create a Microsoft Word document.
Microsoft 365 Copilot is a productivity-focused AI capability embedded across Microsoft 365 apps such as Word, Excel, PowerPoint, Outlook, and Teams. A core, common use case is drafting and generating documents in Word from prompts and existing context. Therefore, "create a Microsoft Word document" is the best completion.
The other options are not appropriate for Microsoft 365 Copilot's scope. "Monitor network traffic and alerts in real time" is a security/operations function more aligned to security monitoring tools and, in Microsoft's product set, closer to Microsoft Security Copilot or dedicated SIEM/SOAR platforms (for example, Microsoft Sentinel). "Modify administrative permissions for SharePoint files" is an admin/governance action that is intentionally protected by role-based access control and is not something end-user Copilot features are meant to perform as a default capability. "Create a list in Microsoft SharePoint" is closer, because Copilot can assist in generating content and can work within Microsoft 365 collaboration contexts; however, the most universally accurate and directly supported capability among the options is creating/drafting a Word document, which is a primary Copilot scenario in Word.
In short, Microsoft 365 Copilot is designed to help users create, summarize, rewrite, and transform content within Microsoft 365 apps, and document creation in Word is a canonical example of that value.


NEW QUESTION # 74
Your company is building a portfolio of AI-powered business solutions. Company executives want to understand how Microsoft responsible AI principles can support the company ' s long-term goals. Which benefit best demonstrates the importance of responsible AI? Select the BEST answer.

Answer: B

Explanation:
Responsible AI is fundamentally about earning and maintaining trust while scaling AI across the enterprise. Option C is the best answer because responsible AI practices (fairness, reliability and safety, privacy and security, transparency, accountability, and inclusiveness) reduce reputational, legal, and operational risk and make adoption sustainable over time. When stakeholders trust that AI is governed, tested, and monitored, the organization can expand AI usage confidently across business units.
The other options are incorrect because they make absolute or counterproductive claims. A is false:
responsible AI does not "guarantee" accuracy; it reduces risk and improves assurance, but no model can be guaranteed correct in all contexts. B is the opposite of reality: responsible AI increases the importance of data protection and governance; it does not reduce the need for them. D is also incorrect: responsible AI requires clear ownership and oversight, especially from leadership, because accountability is a core principle. In short, responsible AI matters because it builds stakeholder confidence and provides guardrails that support long- term, scalable, and compliant AI adoption-exactly what executives care about when investing in an AI portfolio.


NEW QUESTION # 75
......

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