The correct answer is to modify the Document Intelligence skill configuration to enable OCR processing. This is necessary because scanned PDFs are essentially images, and the Document Intelligence custom extraction model requires OCR to convert those images into machine-readable text before it can extract clauses, parties, and dates. Without enabling OCR in the skill, the pipeline treats the scanned documents as blank images, causing the extraction to fail. On the AI-102 exam, this scenario tests your understanding of how Azure AI Document Intelligence handles document types—digital PDFs have embedded text, while scanned ones need explicit OCR activation within the skill, not as a separate skill. A common trap is thinking you need an additional OCR skill, but Document Intelligence handles OCR natively when configured correctly. Remember the memory tip: “Scanned means OCR enabled; digital means text embedded.”
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 developing a knowledge mining solution for a legal firm that needs to process thousands of legal contracts stored as PDFs in Azure Blob Storage. The solution must extract clauses, parties, and dates using a custom model. You are using Microsoft Foundry with Azure AI Search and Azure AI Document Intelligence. The custom model must be trained on labeled contract data. After training, you deploy the model and integrate it into the AI Search enrichment pipeline. The pipeline must also perform OCR for scanned contracts. You have configured the following:
- A custom classification model in Document Intelligence for document types.
- A custom extraction model in Document Intelligence for clauses, parties, and dates.
- An Azure AI Search index with fields: clause, party, date.
- A skillset with a Document Intelligence skill pointing to the custom extraction model.
During testing, the pipeline runs successfully for digital PDFs but fails for scanned PDFs. The error indicates that OCR is not being applied. What should you do to fix the issue?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Modify the Document Intelligence skill configuration to enable OCR processing.
Option B is correct because scanned PDFs require OCR to convert images to text. The Document Intelligence custom extraction model can process images if OCR is enabled in the skill. Option A is wrong because the issue is OCR, not the model type. Option C is wrong because an OCR skill would duplicate functionality; Document Intelligence handles OCR internally. Option D is wrong because reindexing won't fix the missing OCR step.
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.
✗
Retrain the custom extraction model with scanned document images.
Why it's wrong here
Retraining will not add OCR capability; the skill must be configured to use OCR.
✗
Delete and recreate the index with a different field mapping.
Why it's wrong here
The field mapping is unrelated to OCR; the issue is in the enrichment pipeline.
✓
Modify the Document Intelligence skill configuration to enable OCR processing.
Why this is correct
Document Intelligence can perform OCR on images; enabling it in the skill allows processing of scanned PDFs.
Related concept
Read the scenario before looking for a memorised answer.
✗
Add an OCR skill to the skillset before the Document Intelligence skill.
Why it's wrong here
Document Intelligence already includes OCR; adding an OCR skill is redundant and may cause conflicts.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Modify the Document Intelligence skill configuration to enable OCR processing. — Option B is correct because scanned PDFs require OCR to convert images to text. The Document Intelligence custom extraction model can process images if OCR is enabled in the skill. Option A is wrong because the issue is OCR, not the model type. Option C is wrong because an OCR skill would duplicate functionality; Document Intelligence handles OCR internally. Option D is wrong because reindexing won't fix the missing OCR step.
What should I do if I get this AI-102 question wrong?
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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