The answer is Azure AI Custom Vision with image classification. This service is the correct choice because it allows you to train a model to recognize specific products from an entire image, assigning a single label to the photo as a whole, which is exactly what is needed when a user snaps a picture of a product for identification. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your ability to distinguish between image classification and object detection: object detection draws bounding boxes around multiple items within an image, while classification labels the entire scene, making it the right fit for product identification from images. A common trap is choosing object detection because it also “identifies” objects, but remember the key difference—classification answers “what is this whole picture?” whereas detection answers “where are the objects and what are they?”. For a quick memory tip, think “Classify the whole, detect the hole” to recall that classification labels the entire image, while detection finds specific locations.
AI-102 Implement computer vision solutions Practice Question
This AI-102 practice question tests your understanding of implement computer vision solutions. 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 developing a mobile app that allows users to take a photo of a product and get information about it. The app must identify the product from the image. Which Azure AI service should you use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Custom Vision with image classification
The correct answer is Azure AI Custom Vision with image classification. Custom Vision can be trained to recognize products from images. Option A is wrong because object detection is for locating objects, not classifying the entire image. Option C is wrong because Face API is for faces. Option D is wrong because OCR is for text extraction.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Azure AI Vision OCR
Why it's wrong here
OCR extracts text from images, not product identification.
✗
Azure AI Face API
Why it's wrong here
Face API is designed for detecting and recognizing human faces.
✓
Azure AI Custom Vision with image classification
Why this is correct
Image classification assigns a label to the entire image, which is suitable for product identification.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure AI Custom Vision with object detection
Why it's wrong here
Object detection identifies and locates objects, but the requirement is to identify the product as a whole.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Implement computer vision solutions — This question tests Implement computer vision solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure AI Custom Vision with image classification — The correct answer is Azure AI Custom Vision with image classification. Custom Vision can be trained to recognize products from images. Option A is wrong because object detection is for locating objects, not classifying the entire image. Option C is wrong because Face API is for faces. Option D is wrong because OCR is for text extraction.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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