Microsoft AB-730 Actual Free Exam Questions & Community Discussion

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Explanation:

Prompt injection is a generative AI security risk where an attacker inserts instructions (often hidden in text, documents, webpages, or user inputs) to override or manipulate the assistant's intended behavior. This can lead to unintended actions such as ignoring policy controls, producing unsafe outputs, or attempting to reveal sensitive information. Because generative AI systems follow natural-language instructions, they can be socially engineered to prioritize malicious content unless safeguards are in place. This is why prompt injection can cause data exposure (for example, attempting to extract confidential content from grounded sources) and can also embed harmful instructions that redirect the model's behavior. In enterprise settings like Microsoft
365 Copilot, mitigations include grounding boundaries, permission trimming, content filtering, and instruction hierarchy (system policies over user instructions). From a business governance perspective, users should treat untrusted inputs (emails, documents, web text) as potentially hostile and apply least-privilege access and validation when using AI outputs in decision-making.

Explanation:

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).

Explanation:

Microsoft 365 Copilot in Teams relies heavily on meeting transcripts to provide post-meeting intelligence such as summaries, key points, decisions, and action items. The transcript serves as the structured textual data that Copilot analyzes to understand what was discussed during the meeting.
The feature commonly referred to as recap or intelligent recap is generated based on this transcript. Without transcription enabled, Copilot lacks the necessary detailed conversation data to accurately reconstruct the meeting content. As a result, generating a recap of what was discussed is only possible when a transcript is available.
Other options such as scheduling a follow-up meeting or identifying attached content do not depend on transcription, as they rely on calendar data or meeting metadata rather than conversational analysis. However, summarization and recap capabilities are directly tied to the transcript.
Therefore, the correct completion is generate a recap of what was discussed during the meeting , as this action specifically requires the meeting to be transcribed.

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