Exam Name: Developing AI Apps and Agents on Azure
Certification Provider: Microsoft
Corresponding Certification: Azure AI Engineer Associate
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Instant Download Microsoft : AI-103 Questions & Answers as PDF & Test Engine
Updated: Sep 12, 2026
No. of Questions: 159 Questions & Answers with Testing Engine
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- Total Questions: 159
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Microsoft AI-103 Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Developing AI Apps and Agents on Azure AI |
| Exam Number: | AI-103 |
| Real Exam Qty: | 40-60 |
| Passing Score: | 700/1000 |
| Related Certifications: | Microsoft Certified: Azure AI Engineer Associate Microsoft Certified: Azure AI Fundamentals Microsoft Certified: Azure Developer Associate |
| Exam Duration: | 120-180 |
| Available Languages: | English |
| Certificate Validity Period: | 1 year (renewable via Microsoft Learn assessment) |
| Exam Price: | USD 165 (may vary by region) |
| Exam Format: | Scenario-based questions, Multiple response, Drag and drop, Multiple choice, Case studies |
| Recommended Training: | Azure OpenAI Service Documentation Microsoft Learn - Azure AI Engineer Learning Path |
| Exam Registration: | Microsoft Certification Dashboard Pearson VUE Microsoft Exams |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam or authorized test center |
| Pre Condition: | Recommended: experience with Azure services, Python or C#, and basic machine learning concepts. Prior knowledge of Azure AI-102 or equivalent is helpful but not mandatory. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-engineer/ |
Microsoft AI-103 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Implement Natural Language Processing Solutions | - Translation and multilingual support - Text analytics and summarization - Language understanding and intent recognition |
| Develop Generative AI Applications and Agents | - Azure OpenAI Service integration
|
| Plan and Manage Azure AI Solutions | - Azure AI resource provisioning and configuration - Responsible AI principles and governance - Model selection and lifecycle management |
| Knowledge Mining and Information Retrieval | - Indexing and semantic search - Azure AI Search configuration - RAG (Retrieval Augmented Generation) patterns |
| Implement Computer Vision Solutions | - OCR and document intelligence - Image classification and object detection |
Microsoft Developing AI Apps and Agents on Azure: Frequently Asked Questions
The AI-103 exam leads to the Microsoft Certified: Azure AI Engineer Associate certification from Microsoft. It is positioned at the Professional level. The exam validates the knowledge and skills expected of candidates preparing for Microsoft Developing AI Apps and Agents on Azure.
Related certifications include:
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure AI Fundamentals
- Microsoft Certified: Azure Developer Associate
The AI-103 exam includes 40-60 questions and allows 120-180. Before test day, divide the available time by the number of questions in a timed practice set to establish a steady per-question pace. If a difficult item starts consuming too much time, mark it for review and move forward instead of losing momentum. A full timed practice session can help you decide when to move on, when to return, and how much buffer to reserve for a final check.
The passing score for AI-103 is 700/1000, and the official exam fee is USD 165 (may vary by region). Because a retake requires paying the exam fee again, use timed practice results as a readiness check before scheduling your next attempt. If your performance remains inconsistent, continue reviewing weak domains and repeat a timed session before booking the exam.
Recommended: experience with Azure services, Python or C#, and basic machine learning concepts. Prior knowledge of Azure AI-102 or equivalent is helpful but not mandatory.
Eligibility rules can change, so confirm the current requirements on the official exam page before registering.
You can register through the official channels listed below:
The available exam delivery method is Online proctored exam or authorized test center.
The official training options include:
After reviewing the recommended training, reinforce what you learned with Actual4dump's 159 practice questions for AI-103.
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If you purchase the corresponding AI-103 preparation material and do not pass that exam within 60 days of purchase, you may apply for a full refund under the 100% Money Back Guarantee. The request requires a scanned exam enrollment slip and the official Score Report PDF, submitted within two days after the exam. Eligible requests are processed within seven days.
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The current AI-103 outline is organized into 5 top-level domains. The first listed areas include:
- Plan and Manage Azure AI Solutions
- Implement Computer Vision Solutions
- Knowledge Mining and Information Retrieval
Review the Exam Topics section above for the complete outline and any nested subtopics.
Microsoft Developing AI Apps and Agents on Azure Sample Questions:
Hotspot Question
You have a Microsoft Foundry project.
- You need to create a customer support agent that meets the following
requirements:
- Grounds responses only in company policy documents stored in curated
repositories
- Retains customer preferences across separate chat sessions
How should you configure the agent? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation:
Box 1: Configure retrieval from approved data sources
You should configure retrieval from approved data sources to meet this requirement.
In Microsoft Foundry (and broader Azure AI Foundry / Azure OpenAI architectures), grounding an agent exclusively in company policy documents requires implementing a Retrieval-Augmented Generation (RAG) pattern. This ensures the AI model only answers using the provided context and does not hallucinate or rely on its public training data.
Box 2: Enable agent memory that uses persistent storage
To retain user preferences across completely separate chat sessions or conversations, you must use persistent agent memory. Traditional chat history only tracks messages within a single active thread or session. By contrast, the Memory Store feature provides a managed, long-term memory system that structurally indexes user preferences and facts across different devices and separate sessions.
Reference:
https://techcommunity.microsoft.com/blog/azure-ai-foundry-blog/announcing-new-capabilities-for-azure-openai-on-your-data/4144636
You have a Microsoft Foundry project that contains an agent.
The agent uses a knowledge source built from documents stored in Azure Blob Storage. The documents include digitally scanned PDFs that contain multipage tables.
You have an ingestion job that extracts only plain text, causing loss of table structure, headings, and page-number metadata.
Users frequently ask questions that require the retrieval of specific table rows across the pages.
You need to configure an ingestion job for a Retrieval Augmented Generation (RAG) pipeline that performs optical character recognition (OCR) on scanned PDFs, preserves tables and headings as structure-aware chunks, and stores page-number metadata with each chunk.
How should you configure the ingestion job?
- A. Use basic parsing and fixed-size chunking.
- B. Use page-level OCR extraction and store each page as a single chunk.
- C. Use advanced data parsing to reingest the documents.
- D. Use OCR and page-level chunking.
Correct Answer: D 🗳️
Explanation: Only visible for Actual4dump members. You can sign-up / login (it's free).
You have a Microsoft Foundry project that contains an agent. The agent generates summaries from retrieved policy documents.
You need to improve response completeness. The solution must be implemented in the logic of the application code before responses are returned.
What should you do?
- A. Replace the model with a smaller deployment.
- B. Add a retry evaluation before the responses are returned.
- C. Increase the value of the presence_penalty parameter
- D. Decrease the value of the temperature parameter.
Correct Answer: B 🗳️
Explanation: Only visible for Actual4dump members. You can sign-up / login (it's free).
In mid-2026 you are starting a brand-new agentic application on Azure and want to build on the generally available, supported entry point for Foundry agents. Which API should you target?
- A. The Responses API via Foundry Agent Service
- B. The Assistants API
- C. The LUIS runtime API
- D. The legacy text Completions API
Correct Answer: A 🗳️
Explanation: Only visible for Actual4dump members. You can sign-up / login (it's free).
You have an Azure AI agent solution.
You plan to create an agent-based app named App1 that will analyze and summarize data for users and generate data-driven recommendations. App1 will be used by non-technical business users and must adapt to new and unforeseen business challenges and improve its performance over time.
You need to identity which type of agent to use in App1. The solution must meet the following requirements:
- Adapt and improve the agents' performance over time based on user
feedback.
- Provide tailored recommendations to help users make informed
decisions.
- Provide the best possible performance of the app.
Which agent type should you identify?
- A. autonomous
- B. cognitive
- C. prompt-and-response
- D. task automation
Correct Answer: B 🗳️
Explanation: Only visible for Actual4dump members. You can sign-up / login (it's free).
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