AI-102 Implement computer vision solutions Practice Question
A financial services company is building a computer vision solution to automatically extract data from scanned checks. The solution must recognize handwritten amounts, printed account numbers, and signature presence. The company has a large dataset of labeled check images. They need high accuracy and the ability to retrain with new data. Which Azure service should they use?
⚠ Common exam trap
AI-102 often tests whether candidates confuse Document Intelligence (structured document extraction with custom training) with Vision OCR (generic text extraction) or Custom Vision (image classification), so they pick a service that cannot learn custom fields.
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
✓
Azure AI Document Intelligence (Form Recognizer) with a custom model trained on check images
Azure AI Document Intelligence (Form Recognizer) with a custom model is designed for extracting structured fields from domain-specific documents like checks, and it supports training on your labeled dataset with the ability to retrain as new data arrives. It handles handwriting, printed text, and layout, and can be trained to detect signature presence as a labeled field. This matches the accuracy and retraining requirements.
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 with a custom dataset using Custom Vision
Why it's wrong here
Custom Vision classifies or detects objects in images; it does not perform OCR, so handwritten amounts and printed account numbers cannot be extracted. It is tempting because it supports custom labelled datasets and retraining, but its output is labels and bounding boxes, not text.
- ✗
Azure AI Language with custom entity recognition
Why it's wrong here
Azure AI Language performs text analytics on existing text, so it cannot read handwriting or printed characters from check images. It is tempting because custom entity recognition extracts structured fields, but that requires text input already produced by an OCR step.
- ✓
Azure AI Document Intelligence (Form Recognizer) with a custom model trained on check images
Why this is correct
A custom Document Intelligence model trains on your labelled check images, learning the specific layouts, handwriting and field positions, and supports retraining as new data arrives. This satisfies the high-accuracy and retraining constraints for handwritten amounts, printed account numbers and signature presence.
- ✗
Azure AI Vision Image Analysis with a custom model
Why it's wrong here
Image Analysis with a custom model returns classifications and tags rather than transcribed field values, so check amounts and account numbers are not extracted. It is tempting because custom models retrain on labelled images, but the service lacks the document field extraction the scenario requires.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.