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AI-900 Practice Question: Describe features of computer vision workloads on Azure

What is 'document intelligence' (Azure AI Document Intelligence) and what types of documents can it process?

⚠ Common exam trap

Watch out — candidates often confuse 'document intelligence' with general document management or editing tools, but the exam specifically tests that it is an extraction service for structured data from forms and 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

A service that extracts structured data (fields, tables, key-value pairs) from forms and documents

Azure AI Document Intelligence (formerly Form Recognizer) is a service that uses optical character recognition (OCR) and machine learning to extract structured data—such as fields, tables, and key-value pairs—from scanned forms and documents. This enables automated processing of invoices, receipts, business cards, and other structured documents without manual data entry.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • A service that creates documents from structured data in a database

    Why it's wrong here

    Azure AI Document Intelligence (formerly Form Recognizer) performs information extraction, not document generation; it consumes PDFs and images and outputs structured JSON with recognized fields, tables, and key-value pairs. Creating documents from database records is the opposite pipeline, typically handled by template-based rendering or report-building tools, and is not a capability of this OCR-centric service.

  • A service that extracts structured data (fields, tables, key-value pairs) from forms and documents

    Why this is correct

    The correct answer is accurate: Document Intelligence uses optical character recognition (OCR), layout analysis, and trained models to interpret documents such as invoices, receipts, and forms, then emits structured data—fields, tables, and key-value pairs—as JSON. This extraction pipeline is what makes it a foundation for automated document processing workflows, unlike tools that merely store files or review text.

  • A document management system for storing and organising files in Azure

    Why it's wrong here

    Document Intelligence is not a storage or management plane; Azure provides dedicated services like Blob Storage, SharePoint, and Azure Files for organizing and persisting documents. While an extraction pipeline can read files from those stores and write results back, the AI service itself performs no long-term file management and offers no user interface for document classification, versioning, or retention policies.

  • A grammar checking tool that reviews documents for writing quality

    Why it's wrong here

    A grammar checker evaluates linguistic quality—spelling, style, and tone—which is a language-understanding task, not a layout-understanding task. Document Intelligence ignores writing quality and instead locates visual structures like form labels and table cells, using positional cues and OCR rather than semantic analysis of prose. Critiquing writing belongs to language AI services (e.g., Azure AI Language), not document extraction.

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