AI-900 Practice Question: Describe features of computer vision workloads on Azure
What is 'ID document recognition' in Azure AI Document Intelligence?
⚠ Common exam trap
A common mix-up: candidates confuse document data extraction with identity verification or facial recognition, leading candidates to select options that imply authentication or person identification rather than structured field extraction.
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
✓
Extracting structured fields (name, DOB, document number) from passports and identity cards
ID document recognition in Azure AI Document Intelligence is a prebuilt model designed to extract structured fields such as name, date of birth, document number, and expiration date from passports, driver licenses, and identity cards. It uses optical character recognition (OCR) and trained machine learning models to parse the document layout and return key-value pairs, not to verify authenticity or perform identity matching.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Verifying whether a provided ID document is genuine or a counterfeit
Why it's wrong here
Checking whether an identity document is genuine or counterfeit is a document-fraud-detection task that requires verifying physical security features, ink, holograms, and potentially cross-referencing issuance databases. The ID document recognition API performs no authenticity validation; it only reads and extracts the visible fields from a scanned or photographed document. Therefore, this is outside the scope of the described AI capability and is incorrect.
- ✓
Extracting structured fields (name, DOB, document number) from passports and identity cards
Why this is correct
Azure AI Document Intelligence's prebuilt ID model is purpose-built to perform OCR and semantic field extraction on government-issued identity documents, returning structured key-value pairs such as name, date of birth, and document number. This is the exact capability used in KYC and customer-onboarding workflows, where structured data is needed for downstream systems. It is the correct match because it directly describes extracting fields from passports and identity cards.
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Assigning employee ID numbers to workers in an HR management system
Why it's wrong here
Assigning employee ID numbers to workers is an HR administration workflow that involves database operations such as inserting records and generating unique identifiers. This is not an AI document-analysis capability; the ID document recognition service extracts data but does not create, assign, or manage employee identifiers. It simply outputs text fields, and the assignment logic would be implemented in the calling application.
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Recognising which employees are present using their ID badge photos
Why it's wrong here
Determining which employees are present from ID badge photos is a person-recognition or facial-identity task, typically handled by Azure Face API or a custom vision model, not by document extraction. Badge photos show people and often contain name text, but the goal is to match faces to identities, not to parse structured fields like a passport. This is a different AI workload, so it is not what ID document recognition does.
Go deeper
Related to this question
Learn chapter
What is Artificial Intelligence?
Key term
OCR
Optical Character Recognition is technology that converts images of text, like scanned documents or photos, into machine-readable text data.
Key term
Document intelligence
Document intelligence is a cloud-based service that uses artificial intelligence to extract, analyze, and understand information from documents like forms, invoices, and receipts automatically.
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