- A
Create a custom Azure AI Language model using the documents. Then build a bot with Azure Bot Service and connect it to Copilot Studio.
Why wrong: Custom model training is not allowed per requirements, and this is not the minimal approach.
- B
Use Power Virtual Agents to create a bot. Add a custom entity to map document content. Use Power Automate to retrieve documents.
Why wrong: Power Virtual Agents is now Copilot Studio, but this approach does not use generative answers natively and is more complex.
- C
Use Azure AI Search to index the documents. Create a custom connector in Copilot Studio to query the search index. Configure authentication and publish to Teams.
Why wrong: This requires additional infrastructure (Azure AI Search) and is not minimal.
- D
In Copilot Studio, create a new copilot. Add the SharePoint document library as a knowledge source. Configure authentication with Microsoft Entra ID. Enable generative answers. Publish to the Teams channel.
This uses built-in features without custom coding, meeting all requirements.
Quick Answer
The correct answer is to create a new copilot in Copilot Studio, add the SharePoint document library as a knowledge source, configure Microsoft Entra ID authentication for SSO, enable generative answers, and publish to the Teams channel. This works because Copilot Studio’s prebuilt generative AI model can directly ground responses in SharePoint content without custom training, automatically citing source documents to meet the grounding requirement. On the AI-102 exam, this scenario tests your understanding of when to use a low-code knowledge source versus building a custom Azure AI Search pipeline—a common trap is overcomplicating the solution with Azure AI Language or custom skills, which violates the “no custom model training” constraint. Remember the key distinction: Copilot Studio’s “add knowledge” feature handles SharePoint grounding natively, while Azure AI Search requires index creation and is not minimal. Memory tip: “SharePoint source, Copilot Studio course—no custom, just connect and enforce.”
AI-102 Plan and manage an Azure AI solution Practice Question
This AI-102 practice question tests your understanding of plan and manage an azure ai solution. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are an AI engineer at Contoso. Contoso has a Microsoft Copilot for Microsoft 365 deployment. They want to build a custom copilot in Microsoft Copilot Studio that can answer questions about their internal IT support knowledge base stored in a SharePoint Online document library. The knowledge base includes hundreds of PDF and Word documents. Requirements: - The copilot must only answer from the approved knowledge base documents. - Responses must be grounded in the documents and include citations. - The solution must use generative answers with a prebuilt AI model (no custom model training). - Authentication must be via Microsoft Entra ID with single sign-on (SSO). - The copilot should be published to a Microsoft Teams channel. You need to recommend the minimal configuration steps. What should you do?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
In Copilot Studio, create a new copilot. Add the SharePoint document library as a knowledge source. Configure authentication with Microsoft Entra ID. Enable generative answers. Publish to the Teams channel.
Option B is correct. Copilot Studio allows connecting to SharePoint Online as a knowledge source for generative answers. Setting up authentication with Microsoft Entra ID provides SSO. Publishing to Teams is a built-in channel. This meets all requirements without custom development. Option A is wrong because building a custom Azure AI Language model is unnecessary and violates the 'no custom model training' requirement. Option C is wrong because Azure AI Search requires creating an index and custom skills, which is more complex and not minimal. Option D is wrong because Power Virtual Agents (now part of Copilot Studio) does not natively support generative answers with SharePoint grounding in the same simple way; the recommended approach is Copilot Studio with knowledge sources.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create a custom Azure AI Language model using the documents. Then build a bot with Azure Bot Service and connect it to Copilot Studio.
Why it's wrong here
Custom model training is not allowed per requirements, and this is not the minimal approach.
- ✗
Use Power Virtual Agents to create a bot. Add a custom entity to map document content. Use Power Automate to retrieve documents.
Why it's wrong here
Power Virtual Agents is now Copilot Studio, but this approach does not use generative answers natively and is more complex.
- ✗
Use Azure AI Search to index the documents. Create a custom connector in Copilot Studio to query the search index. Configure authentication and publish to Teams.
Why it's wrong here
This requires additional infrastructure (Azure AI Search) and is not minimal.
- ✓
In Copilot Studio, create a new copilot. Add the SharePoint document library as a knowledge source. Configure authentication with Microsoft Entra ID. Enable generative answers. Publish to the Teams channel.
Why this is correct
This uses built-in features without custom coding, meeting all requirements.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
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FAQ
Questions learners often ask
What does this AI-102 question test?
Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: In Copilot Studio, create a new copilot. Add the SharePoint document library as a knowledge source. Configure authentication with Microsoft Entra ID. Enable generative answers. Publish to the Teams channel. — Option B is correct. Copilot Studio allows connecting to SharePoint Online as a knowledge source for generative answers. Setting up authentication with Microsoft Entra ID provides SSO. Publishing to Teams is a built-in channel. This meets all requirements without custom development. Option A is wrong because building a custom Azure AI Language model is unnecessary and violates the 'no custom model training' requirement. Option C is wrong because Azure AI Search requires creating an index and custom skills, which is more complex and not minimal. Option D is wrong because Power Virtual Agents (now part of Copilot Studio) does not natively support generative answers with SharePoint grounding in the same simple way; the recommended approach is Copilot Studio with knowledge sources.
What should I do if I get this AI-102 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on AI-102
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. You are implementing a chatbot using Microsoft Copilot Studio that helps employees find company policies. The chatbot must: - Use generative answers based on a SharePoint Online site. - Only respond with information from approved policy documents. - Include citations in responses. - Be accessible from Microsoft Teams. - Require no custom code. What should you do?
easy- A.Use Power Automate to retrieve documents and feed them to Azure OpenAI. Build a custom connector for Teams.
- ✓ B.In Copilot Studio, create a new copilot. Add the SharePoint site as a knowledge source. Enable generative answers with citations. Publish to Teams.
- C.Build a bot using Azure Bot Service and QnA Maker. Train it with the policy documents. Deploy to Teams.
- D.Create a custom GPT in Azure OpenAI Studio. Upload the policy documents. Deploy via Azure API Management and expose to Teams.
Why B: Option B is correct because Microsoft Copilot Studio natively supports adding a SharePoint Online site as a knowledge source, enabling generative answers that retrieve and cite only approved policy documents. It requires no custom code, automatically includes citations in responses, and can be published directly to Microsoft Teams, fulfilling all stated requirements.
Variation 2. You are designing a conversational AI solution using Microsoft Copilot Studio. The solution must: - Allow users to ask questions about company policies stored in SharePoint Online. - Use generative answers with grounding data. - Ensure that responses are based only on approved documents. - Support authentication via Microsoft Entra ID. Which THREE components must be configured as part of the solution?
hard- ✓ A.Create a new data source in Copilot Studio pointing to SharePoint Online.
- B.Create a Power Automate flow to retrieve documents from SharePoint.
- ✓ C.Configure authentication settings to require Microsoft Entra ID sign-in.
- D.Train an AI Builder model to classify policy documents.
- ✓ E.Add a generative answers topic with a 'knowledge source' node referencing SharePoint.
Why A: Option A is correct because Copilot Studio allows you to create a new data source that connects directly to SharePoint Online, enabling the generative answers feature to retrieve and ground responses on approved policy documents stored there. This ensures that only content from the specified SharePoint site is used, meeting the requirement for grounding data from approved documents.
Last reviewed: Jun 20, 2026
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