Explanation:

Microsoft 365 Copilot does not train the underlying large language model on your organization's tenant data.
Instead, it uses your organization's data at run time to ground responses (for example, by retrieving relevant emails or documents you have permission to access). This separation protects confidentiality and supports enterprise compliance.
If a mailbox (or specific folders) is shared with you and your account has the required permissions, Copilot can summarize emails from that shared content because Copilot respects Microsoft 365 access controls ("permission trimming").
Copilot also relies on Microsoft 365's established security and compliance framework-identity, permissions, and policy enforcement-so it only surfaces content you're authorized to see. This ensures Copilot's outputs remain aligned with organizational governance, information protection, and least-privilege access principles.

Microsoft 365 Copilot in Teams is designed to provide real-time meeting assistance, including summarizing discussions, identifying key decisions, and highlighting action items. When joining a meeting late, the most efficient and immediate method to catch up is to directly prompt Copilot within the Teams meeting experience.
Option A is the best answer because Copilot in Teams can summarize what has occurred so far during the live meeting. It leverages the meeting transcript, speaker attribution, and contextual signals to generate a concise, structured summary in real time. This minimizes delay and provides actionable insights instantly.
Reading the transcript (Option B) would require manual review and is not the fastest method. Intelligent recap (Option D) is typically available after the meeting concludes and processes recording data. Asking Copilot from the separate Microsoft 365 Copilot app (Option C) may not provide immediate, in-meeting contextual awareness.
Therefore, the fastest and most effective approach is to ask Copilot in Teams to summarize what you missed.

In Microsoft 365 Copilot, agents such as Researcher are accessed through the Agents experience within the Copilot app. If the user interface does not immediately display a specific agent, the correct action is to browse or search the available agents catalog. The exhibit shows the left navigation pane with an Explore agents option.
According to Microsoft AI Business Professional guidance, built-in and custom agents can be discovered and enabled through the Explore agents section. If the user already has the appropriate Copilot license and is signed in with their work account, there is no need to switch accounts or request another license.
Signing in through a browser does not change feature availability, and using a personal account would remove access to organizational features. Therefore, to access the Researcher agent, you should select Explore agents and search for Researcher.

When you use Microsoft 365 Copilot Chat without a Microsoft 365 Copilot license, Copilot Chat operates in a
"general" mode rather than a Microsoft Graph-grounded work mode. In this configuration, Copilot does not have the entitlement to access and reason over your organization's protected Microsoft 365 content (such as SharePoint sites, OneDrive files, Outlook mail, Teams messages, or other tenant resources). It also does not connect directly to your organization's internal databases unless separate, explicitly configured integrations exist.
Instead, Copilot relies on three primary sources to generate a response: (1) the prompt context you provide in the current request (what you ask, plus any text you paste), (2) the conversation history within the current chat thread to maintain continuity, and (3) internet search data (when web grounding is available) to supplement general knowledge with up-to-date public information.
Therefore, the correct selections are C (prompt context), E (internet search data), and F (conversation history), while organizational Microsoft 365 data and Teams chat data are not used without the Copilot license.

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.