AB-730 Practice Questions

suggested prompts

In Microsoft 365 Copilot, suggested prompts are designed to help users get started quickly and interact with an agent effectively. Microsoft guidance for Copilot agents emphasizes that many users struggle most at the beginning—knowing what to ask, how to phrase requests, and how to take advantage of an agent’s purpose. Suggested prompts address this by providing ready-to-use examples that demonstrate the best ways to engage the agent for its intended scenarios.

Suggested prompts also act as lightweight “guardrails” for good prompting. They show users the expected input patterns, the types of tasks the agent can perform, and the kinds of outputs they can request. This accelerates adoption and improves the quality of results by steering users toward well-structured requests and appropriate context.

By contrast, capabilities describe what an agent can do (tools/features), instructions define how the agent should behave, and agent settings control configuration. None of those are primarily meant to help users begin conversations through example starters.

Therefore, the correct completion is suggested prompts .

Agents created in the Microsoft 365 Copilot app are primarily designed for use within the Copilot Chat experience and related Copilot surfaces, not directly embedded inside individual applications like Word. Therefore, such agents are not automatically available in Microsoft Word, making Statement 1 incorrect.

However, these agents are designed for collaboration and reuse within an organization. Microsoft guidance confirms that agents can be shared with other users in the same tenant , allowing teams to leverage common tools, prompts, and knowledge sources. Hence, Statement 2 is correct.

For advanced automation scenarios involving complex workflows and third-party connectors, Microsoft provides Copilot Studio rather than the standard Copilot app. The Copilot app focuses on lightweight agent creation using natural language, files, and simple configurations. It does not support complex orchestration with external connectors. Therefore, Statement 3 is incorrect.

Thus, the correct answers are No, Yes, No .

Microsoft Purview is the correct choice because it is Microsoft’s unified compliance and data governance solution that helps organizations apply and enforce policies across Microsoft 365 content— including Copilot-related interactions where those interactions are captured in services such as Microsoft 365 audit, eDiscovery, and Purview compliance experiences. Purview supports capabilities such as data loss prevention (DLP) , retention , eDiscovery , audit , and sensitivity labeling so organizations can manage and govern data and AI-assisted content in line with regulatory and internal requirements. In contrast, Microsoft Entra ID focuses on identity and access management, Intune focuses on device and application management, and Defender for Cloud focuses on cloud security posture management. Governance policies for Copilot-generated conversations and associated compliance controls align most directly with Purview , which is designed to manage information protection and compliance across the Microsoft 365 environment.

To generate an effective monthly summary with Copilot in Excel, Microsoft prompting guidance emphasizes two core elements: clear intent and expected output structure . First, you should state the goal explicitly—such as “summarize total sales by month based on OrderDate and Amount, and highlight month-over-month changes.” This directs Copilot to the correct aggregation and analysis behavior (Option D).

Second, specifying the desired format improves usability and reduces ambiguity. For example, requesting “a table with Month, Total Sales, Number of Orders, and Average Order Value” or “a bulleted executive summary plus a small summary table” ensures Copilot returns results in a format you can immediately use (Option A).

A specific cell range (Option B) is usually unnecessary when the data is already in a recognized Excel table, because Copilot can work from the table context. The workbook file name (Option C) does not help analysis. Providing a formula (Option E) is not required because Copilot can compute monthly totals; formulas are optional if you want a specific calculation method, but they are not the best prompt ingredients for an effective summary.

Therefore, the best answers are A and D .

 When Microsoft 365 Copilot searches for content on the web, it uses the Bing search service.

Answer: Yes

 When Microsoft 365 Copilot searches for content on the web, it uploads the entire conversation history into the search request.

Answer: No

 When Microsoft 365 Copilot searches for content on the web, the query is anonymized and stripped of any user-identifiable information.

Answer: Yes

Microsoft 365 Copilot can use web grounding when a response requires current or public information. For web search, Copilot uses the Bing search service to retrieve relevant web results, so Statement 1 is Yes . This allows Copilot to supplement its response with up-to-date internet content when web grounding is enabled or selected.

Statement 2 is No because Copilot does not send the entire conversation history to Bing as a web search request. Instead, Copilot generates a search query based on the user’s prompt and relevant context. Sending the complete conversation would create unnecessary privacy and data exposure risk, which would conflict with Microsoft’s enterprise data protection model.

Statement 3 is Yes because Microsoft 365 Copilot is designed to protect user and tenant information during web grounding. Search queries are handled in a privacy-preserving way, with user-identifiable and tenant-identifiable information removed before the query is sent to Bing.

All three statements are false because generative AI responses are not guaranteed to be identical even when the prompt is the same. First, when grounded in the web , results can vary due to changing web content, different retrieved sources, or differences in how information is summarized at run time. Second, when grounded in your organization’s data , responses can change based on updates to files, emails, meetings, permissions, or which specific items Copilot retrieves as the most relevant context at that moment. Third, even when relying only on the model’s general knowledge, large language models are probabilistic: they may choose different wording, structure, examples, or emphasis across runs, especially when temperature/decoding settings and internal routing differ. In business scenarios, this means Copilot outputs should be treated as drafts that may require validation, and repeatability should be improved by adding precise constraints (cite specific sources, use fixed formats, specify exact sections, and request verbatim quotes where appropriate).