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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify the business value of generative AI solutions | 35โ40% | - Business benefits, ROI, and efficiency gains - Foundational concepts of generative AI - Differences between generative AI and other AI types - Selecting generative AI solutions for business needs |
| Topic 2: Identify an implementation and adoption strategy for Microsoft's AI apps and services | 20โ25% | - Responsible AI principles and governance - Organizational readiness and change management - Adoption planning and scaling AI solutions - Measuring success and continuous improvement |
| Topic 3: Identify benefits, capabilities, and opportunities for Microsoft's AI apps and services | 35โ40% | - Azure AI services and Azure AI Foundry tools - Microsoft 365 Copilot features and use cases - Aligning Microsoft AI tools to business requirements - Microsoft Copilot Studio capabilities |
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NEW QUESTION # 56
- 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 # 57
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.
Answer: C
Explanation:
Following Microsoft's responsible AI principles--fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability--requires a structured, end-to-end testing approach to identify and mitigate bias. Testing to ensure fair and consistent outcomes involves auditing data, validating model performance across subgroups, and using specific technical tools.
Reference:
https://www.microsoft.com/en-us/research/blog/responsible-ai-the-research-collaboration-behind-new-open-source-tools-offered-by-microsoft
NEW QUESTION # 58
Hotspot Question
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 59
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 generative AI solution is well-suited to predict next-quarter sales trends. Answer: No
* A generative AI solution can summarize lengthy policy documents. Answer: Yes
* A generative AI solution can create product descriptions from product specifications. Answer: Yes
* No - Predicting next-quarter sales trends is primarily a forecasting/predictive analytics problem.
Microsoft differentiates predictive AI (forecasting outcomes from historical patterns) from generative AI (creating content like text, images, or code). While you can use LLMs to assist analysts (explain trends, draft narratives), the core forecasting model is typically traditional ML/time-series methods rather than generative AI as the main engine.
* Yes - Summarization is a classic, high-value generative AI capability. Given a long policy, an LLM can compress it into executive summaries, key obligations, risks, and action items, often with formatting constraints (bullets, sections, "do/don't" lists). Microsoft highlights summarization and analysis as common generative AI use cases in business contexts.
* Yes - Generative AI is well-suited to transform structured inputs (features/specs) into natural- language outputs (product descriptions). This is straightforward "content generation," where you control tone, length, and required fields (benefits, differentiators, disclaimers). Microsoft also points to generating product descriptions and similar marketing/customer-facing text as a practical generative AI scenario.
NEW QUESTION # 60
You need to help analysts investigate incidents across endpoint, identity, cloud, and security operations data.
The analysts must summarize alerts, identify affected resources, and review recommended next steps by using natural language.
What should you use?
Answer: D
Explanation:
The correct answer is A. Microsoft Security Copilot. The requirement is clearly a security operations scenario: analysts must investigate incidents across endpoint, identity, cloud, and security operations data.
Microsoft Security Copilot is designed for security teams and supports natural-language investigation, alert summarization, incident context, affected-resource identification, and recommended response actions.
Microsoft 365 Copilot is focused on productivity tasks such as drafting, summarizing, and analyzing content in Microsoft 365 apps. Azure Document Intelligence extracts structured information from documents such as forms and invoices. Microsoft Copilot Studio is used to build and customize agents for business workflows.
Because the scenario centers on security incident investigation and response guidance, Microsoft Security Copilot is the correct solution.
NEW QUESTION # 61
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