AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Your team has built a knowledge mining pipeline using Azure AI Search and Document Intelligence. After ingestion, you notice that some documents are not appearing in search results. What is the most likely cause?
⚠ Common exam trap
AI-102 often tests the misconception that search service configuration (like replicas or semantic ranker) affects document indexing, when in fact indexing failures are the primary cause of missing documents.
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
✓
The indexer encountered errors and marked the documents as failed
When an indexer runs, it processes each document and can encounter errors such as unsupported file formats, corrupt content, or permission issues. If a document fails during indexing, the indexer records the error and does not add that document to the index, making it invisible to search queries. This is the most direct cause of missing documents after ingestion. Other options affect search behavior but not whether documents are indexed in the first place.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The indexer encountered errors and marked the documents as failed
Why this is correct
Indexers record per-document status during enrichment; documents failing skill execution or field mapping are marked failed and omitted from the index, so they never surface in queries. Checking indexer execution history and error details identifies the specific failing documents.
- ✗
The index does not have a semantic configuration
Why it's wrong here
A semantic configuration only affects ranking and relevance of results already indexed; it cannot exclude documents from the index. It is tempting because semantic ranking is a common Azure AI Search feature to configure, and would be the answer if results appeared but ranked poorly.
- ✗
The search service has insufficient replicas
Why it's wrong here
Replicas govern query availability and read throughput, not whether ingested documents enter the index. It is tempting because adding replicas is the standard remedy for query performance and high availability, which would be correct if searches were slow or the service unavailable.
- ✗
The search service is throttled due to high query volume
Why it's wrong here
Throttling degrades query throughput and latency, but documents missing from results indicates an ingestion or indexing failure, not query-side limits. It is tempting because throttling genuinely causes search errors during heavy query load, which would be the cause if queries failed rather than documents being absent.
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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
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