AI-102 Practice Question: Implement knowledge mining and document intelligence solutions
You are designing an Azure AI Search enrichment pipeline that processes scanned PDF invoices stored in Azure Blob Storage. You need to extract both printed text and handwritten notes from the documents before sending the content to an Azure AI Language entity recognition skill. The solution must minimize development effort and cost. Which skill should you add to the skillset?
⚠ Common exam trap
The trap here is assuming that any text-analysis skill can process scanned documents directly, when image content must first be converted to text by an OCR skill.
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
✓
Microsoft.Skills.Vision.OcrSkill
The built-in OCR skill reads printed and handwritten text from images and PDFs and writes the extracted text into the enrichment tree. Because it is a first-party Azure AI Search skill, it requires no custom code, which satisfies the goals of low effort and predictable cost. Other text skills assume machine-readable input and cannot perform image recognition.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Microsoft.Skills.Vision.OcrSkill
Why this is correct
The built-in OcrSkill extracts printed and handwritten text from image files and PDFs, producing a text output that downstream skills can consume. It is a first-party Azure AI Search skill, so no custom code is required. Using it minimizes development effort while supporting the handwriting requirement, and it is billed through the Azure AI services attached to the search service.
- ✗
Microsoft.Skills.Text.MergeSkill
Why it's wrong here
MergeSkill combines text and offset information from multiple inputs into a single consolidated string. It performs no image analysis and cannot read scanned pages or handwriting. Placing it before an OCR step would simply merge empty text fields, leaving the entity recognition skill with no source content to process.
- ✗
Microsoft.Skills.Custom.WebApiSkill
Why it's wrong here
A custom WebApiSkill can call any external endpoint, but you would have to build, host, and maintain that endpoint yourself. That adds significant development and operational cost compared with a built-in skill. For straightforward OCR of printed and handwritten text, the first-party OCR skill already meets the requirement without custom infrastructure.
- ✗
Microsoft.Skills.Text.KeyPhraseExtractionSkill
Why it's wrong here
KeyPhraseExtractionSkill identifies main talking points from text that is already available. Scanned PDFs contain no machine-readable text until OCR is applied, so this skill would receive empty or unusable input. It cannot read pixels or recognize handwriting, and it would not produce the raw text needed by the downstream entity recognition skill.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
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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.