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Plan and manage an Azure AI solutioneasyMultiple ChoiceObjective-mapped

AI-102 Plan and manage an Azure AI solution Practice Question

This AI-102 practice question tests your understanding of plan and manage an azure ai solution. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 planning to use Azure AI Document Intelligence to process a large volume of mixed document types (invoices, receipts, and purchase orders). The solution must automatically classify each document type and extract relevant fields. What should you configure?

Question 1easymultiple choice
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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

Create a custom classification model to identify document types, then use extraction models

Option B is correct because Azure AI Document Intelligence (formerly Form Recognizer) requires a two-step process for mixed document types: first, a custom classification model identifies each document type (invoice, receipt, purchase order), then separate extraction models (custom or prebuilt) extract the relevant fields from each classified type. This approach ensures accurate routing and field extraction without relying on filenames or brittle regex patterns.

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.

  • Use the Form Recognizer service with neural models

    Why it's wrong here

    Form Recognizer is the old name; neural models do not classify.

  • Create a custom classification model to identify document types, then use extraction models

    Why this is correct

    Custom classification model handles mixed types accurately.

    Related concept

    Read the scenario before looking for a memorised answer.

  • Use prebuilt models for each document type and route based on filename

    Why it's wrong here

    Filename routing is unreliable; prebuilt models don't handle classification.

  • Use the Read model to extract all text and then use regular expressions to classify

    Why it's wrong here

    Complex and error-prone.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates assume a single model (like neural or prebuilt) can both classify and extract, but Azure AI Document Intelligence requires a separate classification step before extraction for mixed document types.

Detailed technical explanation

How to think about this question

Under the hood, Document Intelligence’s custom classification model uses a multi-label classifier trained on document layouts and content, outputting a confidence score for each document type. The extraction models (prebuilt or custom) then use OCR and deep learning to map fields like invoice total or purchase order number to key-value pairs. In a real-world scenario, you might train the classifier on 500 samples per type and then use separate prebuilt invoice and receipt models for extraction, avoiding the need to train custom extraction models from scratch.

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.

TExam Day Tips

  • 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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this AI-102 question test?

Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Create a custom classification model to identify document types, then use extraction models — Option B is correct because Azure AI Document Intelligence (formerly Form Recognizer) requires a two-step process for mixed document types: first, a custom classification model identifies each document type (invoice, receipt, purchase order), then separate extraction models (custom or prebuilt) extract the relevant fields from each classified type. This approach ensures accurate routing and field extraction without relying on filenames or brittle regex patterns.

What should I do if I get this AI-102 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 24, 2026

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