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| Section | Weight | Objectives |
|---|---|---|
| Implement Agentic AI Solutions | 30-35% | - Set up agent-to-agent communication - Implement data connections and plugins - Configure AI agents using Microsoft Copilot Studio - Configure security and compliance settings |
| Governance and Best Practices | 10-15% | - Ensure regulatory compliance - Implement data privacy and security controls - Apply responsible AI principles |
| Design Agentic AI Solutions | 30-35% | - Select appropriate AI models and services - Design multi-agent architectures - Define agent capabilities and boundaries - Identify business scenarios for agentic AI |
| Deploy and Monitor Agentic AI Solutions | 20-25% | - Implement error handling and logging - Configure monitoring and analytics - Publish and deploy agent solutions - Optimize agent performance |
周知するように、自分でAB-100試験に合格することは無理です。あなたはAB-100試験のいくつかの知識に迷っています。幸いにして、今から、あなたは弊社のAB-100復習教材を購入できます。弊社のAB-100復習教材は専門家によって編集されていました。彼らは何年も毎年実際のAB-100試験を研究してきました。だから、あなたは、弊社のAB-100復習教材を買うと、あなたの多くの難問を解決できます。
質問 # 80
A company has an Azure environment that supports multiple business units. The company plans to implement an Al solution that will perform sentiment analysis on customer product reviews.
You need to evaluate the potential cost of the solution to support return on Al investment (ROAI) analysis. What should you use?
正解：A
解説：
The requirement is to evaluate the potential cost of an AI solution before deployment so the company can support a return on AI investment (ROAI) analysis.
The correct choice is C. Azure pricing calculator.
Why C is correct:
The Azure pricing calculator is used to estimate the expected cost of Azure services before implementation. For an AI solution such as sentiment analysis on customer product reviews, it helps estimate likely spending across the relevant Azure components and usage patterns. That makes it the right tool for cost forecasting as part of ROAI planning.
質問 # 81
A company plans to deploy a Microsoft Foundry agent.
You need to recommend an application lifecycle management (ALM) process to ensure that the agent evaluates against baseline accuracy metrics before being deployed.
What should you recommend?
正解：B
解説：
To implement an Application Lifecycle Management (ALM) process for Microsoft Foundry agent deployment, you must integrate Foundry Control Plane Observability into your CI/CD pipeline.
This ensures the agent is validated against baseline metrics before reaching production and monitored for drift thereafter.
Pre-Deployment: Baseline Evaluation
Before a new agent version is deployed, it must pass a rigorous evaluation stage within your ALM pipeline to prevent performance regressions.
Post-Deployment: Drift & Continuous Monitoring
Once deployed, the agent's performance must be continuously validated against the pre- deployment baseline using Observability in the Control Plane.
Continuous Evaluation: Configure the Control Plane to sample live production traffic and run the same evaluators used during development.
Drift Detection: Monitor for changes in Quality Scores and Accuracy Metrics over time. Significant drops indicate "drift," where real-world usage differs from your training/testing assumptions.
Unified Dashboard: Use the Foundry Monitoring Dashboard to visualize trends in latency, token usage, and accuracy side-by-side.
Alerting: Set up Azure Monitor alerts to notify developers immediately if evaluation scores fall below the established baseline.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/building-production-ready-secure-observable-ai-agents-with-real-time-voice-with-/4501074
質問 # 82
A global manufacturing company wants to integrate AI across its operations. The CTO has asked you to lead the initiative. The company has no existing AI governance framework and limited AI experience among its staff.
Which approach should you recommend as the first step?
正解：A
解説：
The Cloud Adoption Framework for Azure provides a structured methodology for AI adoption that begins with strategic planning and governance establishment before any deployment. For an organisation with no existing AI governance and limited AI experience, jumping straight to deployment (Options A, C, or D. creates significant risks around security, compliance, data handling, and user adoption. The framework guides organisations through defining their AI strategy, establishing an AI Centre of Excellence, creating governance policies, conducting readiness assessments, and then progressively adopting AI capabilities. This structured approach ensures that the organisation builds the necessary foundations before scaling.
質問 # 83
A company has an AI agent that automates the review of customer feedback stored in a cloud database.
You plan to generate monthly reports from the agent's output to provide insights into customer sentiment and guide product development and marketing.
You need to ensure that the data ingested by the agent is clean and suitable for the intended use.
What should you do to prepare the data?
正解：C
解説：
To automate feedback assessment and monthly reporting, you can build an agent flow in Microsoft Copilot Studio that functions as a "data pre-processor" and "insight generator." By using Agent Flows, you can move beyond simple Q&A to create structured, multi-step processes that clean raw data before it is ingested by the agent's main knowledge base.
Step 1: Design the Feedback Agent Flow
The "Flow" acts as the bridge between your cloud database (e.g., Azure SQL, Cosmos DB) and the final report.
Step 2: Ensure Data Quality (The "Clean Room")
For the agent to give accurate insights for marketing, the data must be grounded and structured.
Step 3: Automate the Monthly Report
Once the data is clean, the agent can summarize it into a report suitable for stakeholders.
Reference:
https://cps.co.uk/insights/how-to-use-copilot-studio-to-automate-repetitive-tasks
質問 # 84
A company has an Azure environment that supports multiple business units.
The company plans to implement an AI solution that will perform sentiment analysis on customer product reviews.
You need to evaluate the potential cost of the solution to support return on AI investment (ROAI) analysis.
What should you use?
正解：B
解説：
Correct:
* Azure pricing calculator (Best choice)
The best tool to evaluate the potential cost of a new AI solution to support ROI analysis is the Azure pricing calculator.
Why Azure Pricing Calculator is BestProactive Estimation: It is specifically designed to estimate the costs of Azure services before they are deployed.
Granular Planning: It allows you to select specific services (e.g., Azure AI Language, Cognitive Services, Azure Machine Learning), define usage patterns, regions, and tiers to create a detailed cost estimate.
Scenario Comparison: You can create different scenarios (e.g., comparing different language models or usage volumes) to estimate the impact on ROAI Comparison of Tools Azure Pricing Calculator: Estimates costs for new, un-deployed projects. (Best Choice).
Total Cost of Ownership (TCO) Calculator: Compares on-premises infrastructure costs against Azure, typically used for large-scale migration strategies, not specific AI service modeling.Cost Management + Billing: Monitors and analyzes actual, real-time spending on already deployed resources. For a complex AI solution involvin
* Total Cost of Ownership (TCO) Calculator (Second best choice)
While Cost Management + Billing is essential for tracking actual spend once a solution is running, the TCO Calculator is specifically designed for the pre-implementation phase to support Return on AI Investment (ROAI) analysis. It allows you to estimate and compare the potential costs of moving a workload to Azure-including labor, networking, and storage-against an existing process or alternative solution.
* Cost Management + Billing (Third best)
Azure pricing calculator and Total Cost of Ownership (TCO) Calculator are both better than Cost Management + Billing, as they evaluate the potential cost and support a Return on AI Investment (ROAI) analysis before the solution is built, you need to estimate future expenses based on expected usage. Cost Management + Billing does post-deployment tracking.
A good tool still for this scenario is Cost Management + Billing. Cost Management + Billing allows you to break down and evaluate costs across many business units using tags and scope filtering.
This granular data is essential for calculating the Return on AI Investment (ROAI) for specific departments or the entire organization.
Incorrect:
* Azure Monitor
* Azure Reservations
* Azure savings plans
Is used to reduce costs for compute services via long-term commitment. It is a way to lower your bill, but not a tool for evaluating or reporting on investment performance.
* Microsoft Fabric SKU Estimator
Is used to estimate capacity needs for Fabric-specific data projects. It is eseful only if your sentiment analysis solution is built specifically on the Microsoft Fabric platform.
Note:
* Azure pricing calculator
To evaluate the potential cost of an AI solution for sentiment analysis on Azure, you should use the Azure Pricing Calculator.This tool allows you to estimate the monthly and annual costs of the specific services required for your solution-such as Azure AI Language (which provides sentiment analysis) or Azure OpenAI Service-based on your expected volume of feedback data.
* Total Cost of Ownership (TCO) Calculator
To evaluate the cost of an Azure sentiment analysis solution and support a Return on AI Investment (ROAI) analysis for multiple business units, you should use the Azure Total Cost of Ownership (TCO) Calculator.
The TCO Calculator is essential for calculating the financial impact of migrating or implementing a new solution compared to your existing infrastructure.
Step-by-Step: Using the TCO Calculator for ROAI
To perform a comprehensive ROAI analysis, follow these steps to capture the full scope of ownership:
1. Define Your Current Workload
Enter details about your existing infrastructure that the AI solution might replace or augment.
2. Adjust Assumptions
Tailor the calculator to your business environment by adjusting key metrics.
3. Review the TCO Report
The calculator generates a detailed report comparing your current costs against Azure.
Reference:
https://www.synextra.co.uk/knowledge-base/azure-tco-vs-pricing-calculator
https://www.dev4side.com/en/blog/azure-ai
質問 # 85
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