Quick Answer
The correct answer is Object Detection and Optical Character Recognition (OCR). Object Detection is essential because it identifies and locates products on shelves by generating bounding boxes around each item, directly supporting inventory tracking and shelf analysis. OCR then extracts the printed text from those detected regions, allowing the system to read expiration dates on labels or packaging. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your ability to pair Azure AI Vision’s prebuilt capabilities for a real-world retail workflow—a common trap is confusing image classification (which only labels the whole image) with object detection, or assuming OCR alone can locate items. Remember the memory tip: “Detect the box, then read the text” to recall that Object Detection finds where products are, and OCR extracts the date details from those locations.
This AI-102 practice question tests your understanding of plan and manage an azure ai solution. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 planning to use Azure AI Vision to analyze images for a retail inventory management application. The solution must detect products on shelves and read expiration dates. Which two Azure AI Vision capabilities should you use?
Image Captioning
Why wrong: Generates captions, not needed.
Object Detection
Detects and locates products.
Face Detection
Why wrong: Not relevant for products or dates.
Optical Character Recognition (OCR)
Reads text like expiration dates.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Object Detection
Object Detection (B) is correct because it identifies and locates products on shelves by drawing bounding boxes around each detected item, which is essential for inventory tracking. Optical Character Recognition (OCR) (D) is correct because it extracts text from images, enabling the reading of expiration dates printed on product labels or packaging.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Image Captioning
Why it's wrong here
Generates captions, not needed.
Object Detection
Why this is correct
Detects and locates products.
Related concept
Read the scenario before looking for a memorised answer.
Face Detection
Why it's wrong here
Not relevant for products or dates.
Optical Character Recognition (OCR)
Why this is correct
Reads text like expiration dates.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates may confuse Image Captioning with Object Detection, assuming a descriptive caption could identify products, or overlook OCR because they think expiration dates are purely numeric and can be handled by simpler methods, but Azure AI Vision's OCR is specifically designed for text extraction from images.
Detailed technical explanation
Azure AI Vision Object Detection uses deep learning models like YOLO or Faster R-CNN to output bounding box coordinates and class labels for multiple objects in a single image, supporting up to 80 common object categories. OCR in Azure AI Vision leverages the Read API, which employs a combination of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to handle both printed and handwritten text, and can process images with varying lighting and angles, making it robust for reading expiration dates on curved or reflective packaging.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..
The correct answer is: Object Detection — Object Detection (B) is correct because it identifies and locates products on shelves by drawing bounding boxes around each detected item, which is essential for inventory tracking. Optical Character Recognition (OCR) (D) is correct because it extracts text from images, enabling the reading of expiration dates printed on product labels or packaging.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Same concept, more angles
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Variation 1. You need to analyze images to detect objects and read text from documents using a single Azure AI service. Which service should you use?
mediumWhy A: Azure AI Vision is the correct choice because it provides both image analysis (object detection) and optical character recognition (OCR) for reading text from documents within a single service. Its Read API and Analyze Image API cover both requirements without needing separate services.
Last reviewed: Jun 24, 2026
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