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NEW QUESTION # 23
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: A
Explanation:
Microsoft 365 Copilot is designed to act as an AI-powered assistant that leverages Microsoft Graph to access your organization's data, including emails, files, chats, and meetings. By default, Copilot integrates with Microsoft 365 apps and uses this data to provide contextually relevant, real-time assistance.
Key Capabilities via Microsoft Graph
*-> Data Access: Copilot retrieves information from emails, files (OneDrive/SharePoint), meetings (Teams transcripts), and chats.
Grounding: It uses this data to "ground" prompts, providing responses that are specific to your actual work rather than general information.
Semantic Indexing: Copilot creates a semantic index of your Graph data to understand relationships and intent, making search and retrieval more accurate.
Reference:
https://learn.microsoft.com/en-us/copilot/microsoft-365/enterprise-data-protection
NEW QUESTION # 24
Your company is preparing to adopt Microsoft 365 Copilot and wants to follow Microsoft responsible AI principles. As a business leader, you propose establishing an AI governance council to ensure alignment with the responsible AI principles. What is the primary purpose of the council? More than one answer choice may achieve the goal. Select the BEST answer.
Answer: A
Explanation:
An AI governance council (often called an "AI Council") exists primarily to set direction and provide cross- functional oversight so AI adoption stays aligned to the organization's values, risk posture, and Responsible AI commitments. That maps most directly to D . Microsoft's guidance on creating an AI Council describes leadership responsibilities such as defining and communicating the organization's AI vision, values, and policies , reviewing and approving AI use cases/projects, and coordinating with enablement and technical readiness teams to understand risks, issues, and opportunities. It also emphasizes representation across distinct functions (for example: senior leadership, legal, compliance, risk, ethics, data, technology, business, HR) to ensure governance decisions reflect a broad, accountable perspective.
The other options describe activities that may be supporting outcomes of governance, but they are not the council's primary purpose. A is narrow (IT policy enforcement/user monitoring) and is typically handled by security/compliance operations rather than the top-level governance body. B is user enablement/training (commonly owned by adoption/change management teams). C focuses on technical delivery and performance management (often owned by engineering/MLOps/service owners). The governance council's central value is strategic guidance + oversight + cross-functional alignment to ensure Responsible AI adoption is consistent, accountable, and sustainable across the business.
NEW QUESTION # 25
Your company plans to implement a proof of concept (PoC) agent that uses Azure OpenAI.
The solution must start small and provide flexibility to scale usage as demand grows.
Which pricing model should you use?
Answer: C
Explanation:
The Standard (On-Demand) tier is the best choice for this scenario because it follows a pay-as- you-go consumption model. This allows a company to start a Proof of Concept (PoC) with virtually zero upfront cost or commitment, paying only for the tokens processed. As demand grows, the service provides the flexibility to scale without needing to manage complex capacity planning early on.
Reference:
https://azure.microsoft.com/en-us/products/ai-foundry/models/openai
NEW QUESTION # 26
- Select the answer that correctly completes the sentence.
To ensure that your organization follows trustworthy AI principles, the organization should establish an AI governance council to __________.
Answer:
Explanation:
Explanation:
guide AI strategy, ensure responsible AI oversight, and promote alignment across business units.
A trustworthy AI program requires more than technical implementation; it requires enterprise governance :
clear ownership, risk management, policy, and cross-functional coordination. An AI governance council's primary role is to provide strategic direction and oversight so AI initiatives align with business goals while meeting Responsible/Trustworthy AI expectations (fairness, reliability and safety, privacy and security, transparency, accountability, and inclusiveness).
Therefore, the best completion is that the council should guide AI strategy, ensure responsible AI oversight, and promote alignment across business units . This captures why councils are created: to avoid siloed deployments, define guardrails and approval processes, standardize evaluation/monitoring practices, and coordinate stakeholders such as legal, compliance, security, data governance, HR, and business leadership. The council also helps prioritize use cases, establish policies for data use and access, set documentation requirements, and require ongoing monitoring and incident response for AI systems in production.
The other options are narrower operational responsibilities. Configuring and deploying models in Azure is typically owned by engineering/cloud teams. Day-to-day model training and labeling is handled by data science/ML teams. The council sits above those activities to ensure the organization's AI work is consistent, accountable, and strategically aligned .
NEW QUESTION # 27
You have a business unit that uses an AI solution to process loan applications. You discover that the solution rejects the application of all applicants that are older than 60 years of age. Which Microsoft responsible AI principle is this violating?
Answer: A
Explanation:
This scenario is a clear violation of the fairness principle. Fairness in Microsoft's Responsible AI framework is about ensuring AI systems do not create unjustified bias or discriminatory outcomes-especially when decisions affect people's access to opportunities such as credit, employment, housing, or education. A rule or learned behavior that rejects all applicants over a certain age creates a systematic, categorical disadvantage for a protected demographic group and indicates a discriminatory decision boundary rather than an individualized assessment of creditworthiness.
Even if the model designers believed age correlates with risk, using a hard cutoff that rejects every applicant older than 60 is not an equitable approach. It suggests the model is either using age directly as a dominant feature or reflects biased training data/labels that encoded discriminatory outcomes. Fairness requires you to evaluate model outcomes across groups (for example, age brackets), measure disparate impact, and apply mitigations such as feature review (removing or constraining sensitive attributes), rebalancing training data, adjusting thresholds, or using fairness-aware training/evaluation methods. It also requires governance and review of high-stakes automated decisions.
The other principles are not the best match: transparency concerns explainability and user understanding, accountability concerns human oversight and ownership, and reliability and safety concerns consistent and safe operation. The core issue here is discriminatory treatment across an age group- fairness .
NEW QUESTION # 28
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