AI-102 Implement computer vision solutions Practice Question
A company uses Azure AI Vision to extract text from scanned invoices. They need to preserve the layout information, such as tables and key-value pairs, to automate data entry. Which Azure service should they use?
⚠ Common exam trap
The trap here is assuming the Read API is sufficient for invoices, but it lacks layout understanding and structured field extraction that Document Intelligence provides.
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 (formerly Form Recognizer)
Document Intelligence provides prebuilt invoice models that extract text, tables, and key-value pairs while preserving layout. The Read API only returns text lines, and Custom Vision and Face API are for different domains. For automating data entry from invoices with tables, Document Intelligence is the appropriate service.
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 Face API
Why it's wrong here
The Face API is for human face analysis and has no document processing capabilities. It cannot extract text or understand invoice layout. Using it for this purpose would be entirely ineffective. The scenario requires document understanding, so the Face API is not relevant and would not fulfill any part of the requirement.
- ✗
Azure AI Custom Vision
Why it's wrong here
Custom Vision is for image classification and object detection, not document text extraction. It cannot parse tables or key-value pairs from invoices. While you could train a model to detect regions, it would not provide the text content or structured relationships. Therefore, Custom Vision is unsuitable for automating data entry from invoices with layout requirements.
- ✗
Azure AI Vision Read API
Why it's wrong here
The Read API extracts text lines and words but does not understand document structure like tables or key-value pairs. It returns plain text with bounding boxes, which may be sufficient for simple OCR but not for preserving layout for automated data entry. For invoices with tables and fields, a more specialized document analysis service is needed to capture relationships between labels and values.
- ✓
Azure AI Document Intelligence (formerly Form Recognizer)
Why this is correct
Document Intelligence is designed to extract text, tables, and key-value pairs from documents such as invoices. It provides prebuilt models for invoices that understand layout and can return structured data like invoice ID, date, and line items. This directly meets the need to preserve layout information and automate data entry, making it the correct choice for this scenario.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AI-102 question from scratch — 761 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
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.