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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Identify the business value of generative AI solutions | 35–40% | - AI value identification
|
| Topic 2: Identify benefits, capabilities, and opportunities for Microsoft AI apps and services | 35–40% | - Microsoft AI ecosystem
|
| Topic 3: Identify an implementation and adoption strategy for Microsoft AI apps and services | 20–25% | - AI adoption strategy
|
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NEW QUESTION # 44
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: No
No - Microsoft 365 Copilot provides a single AI app that has identical features and experiences across all Microsoft products.
Microsoft 365 Copilot is not a single, identical app with uniform features across all Microsoft products. Instead, it is an AI-powered assistant embedded within the existing Microsoft 365 apps (Word, Excel, PowerPoint, Outlook, Teams, etc.), and its capabilities are tailored to the specific functions of each application.
Box 2: Yes
Yes - Microsoft 365 Copilot delivers AI capabilities for business users that use Microsoft 365 apps.
Microsoft 365 Copilot is an AI-powered assistant designed to enhance productivity and collaboration by integrating directly into Microsoft 365 apps, including Word, Excel, PowerPoint, Outlook, and Teams. It acts as a "second pilot" that works alongside users, utilizing Large Language Models (LLMs) and Microsoft Graph to automate routine tasks, draft content, and provide real-time insights based on organizational data.
Box 3: Yes
Yes - Microsoft Security Copilot helps companies understand risks and the organizational security posture.
Microsoft Security Copilot is a generative AI-powered security tool designed to help organizations understand risks, assess their security posture, and accelerate threat response. By integrating with the Microsoft Security portfolio-including Defender XDR, Microsoft Sentinel, and Microsoft Intune-it provides a centralized view of security data and offers natural language, actionable guidance.
Reference:
https://techcommunity.microsoft.com/blog/microsoft365copilotblog/copilot-chat-comes-to-the- microsoft-365-apps/4453349
https://www.quest.com/learn/what-is-microsoft-copilot-for-security.aspx
NEW QUESTION # 45
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: No
No - A generative AI solution is well-suited to predict next-quarter sales trends.
Predictive AI, not generative AI, is designed to forecast future trends and outcomes.
While Generative AI (GenAI) and Predictive AI both use historical data and machine learning, their primary purposes are distinct: Generative AI is designed to create new, original content (text, images, code), whereas Predictive AI is designed to forecast future trends and outcomes.
Box 2: Yes
Yes - A generative AI solution is well-suited to summarize lengthy policy documents.
Generative AI solutions are exceptionally well-suited to summarize lengthy policy documents, offering a transformative approach to document management that enhances efficiency, reduces manual labor, and improves accuracy. These systems can analyze hundreds of pages in minutes, extracting key obligations, deadlines, and critical information while removing redundancy.
Box 3: Yes
Yes - A generative AI solution can create product descriptions from product specifications.
Generative AI solutions significantly streamline e-commerce by transforming raw product specifications-such as materials, dimensions, and technical features-into engaging, human- readable product descriptions. By leveraging Large Language Models (LLMs) and Natural Language Processing (NLP), these tools can automate content creation for thousands of items in minutes, ensuring consistency in brand voice and improving search engine optimization (SEO) Reference:
https://nfina.com/generative-ai-vs-predictive-ai/
https://artificio.ai/blog/generative-ai-for-document-summarization-and-insights
https://describely.ai/blog/ai-generated-product-descriptions-for-ecommerce
NEW QUESTION # 46
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:
NEW QUESTION # 47
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 # 48
You are exploring how Microsoft 365 Copilot uses Microsoft Graph to deliver AI-powered experiences.
Which information in Microsoft Graph can Copilot use by default?
Answer: D
Explanation:
Microsoft 365 Copilot is designed to work within the Microsoft 365 ecosystem and use organizational context that is already governed by Microsoft Entra ID, Microsoft 365 permissions, and compliance controls. By default, Copilot can use Microsoft Graph signals and content that exist in Microsoft 365 workloads the user already has access to-most commonly emails, files, meetings, and chats . That corresponds to A .
The key concept is permission-trimming: Copilot doesn't magically gain access to everything; it can only surface or use data that the signed-in user is permitted to access in Microsoft 365. This is what makes Copilot valuable for productivity scenarios-summarizing email threads, drafting replies, generating meeting recaps, creating documents from your files, or pulling context from Teams chats-because those artifacts are already part of daily work and already subject to tenant policies.
The other options are not "by default" Microsoft Graph content for Copilot: B (file shares) typically requires additional integration or migration into Microsoft 365 repositories or indexing via connectors; it's not inherently available. C is unrelated to Microsoft 365 tenant work data. D (public web) is not "information in Microsoft Graph"; web grounding is a separate capability and not the default Graph workload data source referenced here.
NEW QUESTION # 49
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