AI-102 Plan and manage an Azure AI solution Practice Question
Which THREE factors should you consider when choosing between Azure AI Document Intelligence prebuilt models and custom models for invoice processing?
⚠ Common exam trap
Watch out — candidates often assume prebuilt models are always less accurate than custom models, but accuracy depends on the document's similarity to the training data; prebuilt models can outperform custom ones on standard layouts, especially when training data is limited.
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
✓
Prebuilt models require no training data.
Azure AI Document Intelligence prebuilt models are designed to extract common fields from standard invoice layouts without requiring any labeled training data. They are pretrained on a large corpus of documents, enabling immediate use for typical invoice structures.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Both model types can be deployed on-premises.
Why it's wrong here
Document Intelligence is a cloud service; on-premises deployment is not supported.
- ✓
Prebuilt models require no training data.
Why this is correct
Prebuilt models are ready to use immediately.
- ✗
Prebuilt models are always less accurate than custom models.
Why it's wrong here
Accuracy depends on the use case; prebuilt models are highly accurate for standard formats.
- ✓
Custom models require a large set of labeled training invoices.
Why this is correct
Labeled data is essential for training custom models.
- ✓
Custom models can handle non-standard invoice layouts.
Why this is correct
Custom models adapt to unique layouts.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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