AI-103 Information Extraction Practice Question
You are migrating a custom extraction solution from a Custom Template model to a Custom Neural model in Azure AI Document Intelligence. What is a key advantage of choosing a Custom Neural model over a Custom Template model?
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
✓
Custom Neural models can automatically generalize across documents with varying visual layouts and structures.
Custom Neural models support deep learning to handle documents with varying layouts and structures automatically, removing the need for strict template matching.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Custom Neural models can automatically generalize across documents with varying visual layouts and structures.
Why this is correct
Neural models use advanced deep learning to understand document semantics and layouts even when fields shift positions.
- ✗
Custom Neural models only support English language documents.
Why it's wrong here
Neural models support multiple languages and are not restricted to English.
- ✗
Custom Neural models require zero training documents.
Why it's wrong here
All custom models require a training dataset (minimum of 5 documents).
- ✗
Custom Neural models do not support table extraction.
Why it's wrong here
Custom Neural models fully support both fields and table extraction.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 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-103 exam.