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Identify Document Processing Workloads (AI-900 Exam Prep)

Overview

Document processing workloads use Artificial Intelligence (AI) to extract, analyze, and organize information from documents. These documents are often semi-structured or unstructured and may include scanned images, PDFs, forms, invoices, receipts, or contracts.

For the AI-900: Microsoft Azure AI Fundamentals exam, the emphasis is on recognizing document processing scenarios, understanding what problems they solve, and identifying which Azure AI services are typically used—not on implementation or coding.

This topic falls under:

  • Describe Artificial Intelligence workloads and considerations (15–20%)
    • Identify features of common AI workloads

What Is a Document Processing Workload?

A document processing workload focuses on extracting structured information from documents that are primarily text-based but may also contain tables, forms, handwriting, and images.

These workloads often combine capabilities from:

  • Computer vision (reading text from images)
  • Natural language processing (understanding extracted text)

Common inputs:

  • Scanned PDFs
  • Images of receipts or invoices
  • Forms and applications
  • Contracts and reports

Common outputs:

  • Extracted text
  • Key-value pairs
  • Tables and line items
  • Structured data stored in databases

Common Document Processing Use Cases

On the AI-900 exam, document processing workloads are usually described through business automation scenarios.

Optical Character Recognition (OCR)

What it does: Extracts printed or handwritten text from images or scanned documents.

Example scenarios:

  • Digitizing paper documents
  • Reading text from scanned contracts
  • Extracting text from images of receipts

Key idea: OCR converts visual text into machine-readable text.

Form Processing

What it does: Extracts structured information such as fields, key-value pairs, and tables from standardized or semi-standardized forms.

Example scenarios:

  • Processing loan applications
  • Extracting data from tax forms
  • Reading insurance claim forms

Key idea: Form processing focuses on structured data extraction, not just raw text.

Receipt and Invoice Processing

What it does: Extracts common fields such as vendor name, date, total amount, and line items.

Example scenarios:

  • Automating expense reporting
  • Processing supplier invoices
  • Auditing financial documents

Key idea: This is a specialized form of document processing optimized for common business documents.

Table Extraction

What it does: Identifies and extracts tabular data from documents.

Example scenarios:

  • Extracting tables from PDFs
  • Importing spreadsheet-like data from scanned reports

Handwritten Text Recognition

What it does: Extracts handwritten content from documents.

Example scenarios:

  • Processing handwritten forms
  • Digitizing handwritten notes

Azure Services Commonly Associated with Document Processing

For AI-900, you should recognize these services at a high level.

Azure AI Document Intelligence (formerly Form Recognizer)

Supports:

  • OCR
  • Form processing
  • Invoice and receipt analysis
  • Table extraction

This is the primary service associated with document processing workloads on the exam.

Azure AI Vision

Supports:

  • Basic OCR

Used when scenarios mention simple text extraction from images rather than full document understanding.

How Document Processing Differs from Other AI Workloads

Understanding these distinctions is essential for AI-900.

AI Workload TypePrimary Focus
Document ProcessingExtracting structured data from documents
Computer VisionUnderstanding image and video content
Natural Language ProcessingUnderstanding meaning in text
Speech AIAudio and spoken language

Exam tip: If the scenario mentions forms, invoices, receipts, PDFs, or document automation, think document processing first.

Responsible AI Considerations

Document processing workloads often involve sensitive information.

Key considerations include:

  • Protecting personal and financial data
  • Ensuring secure document storage
  • Limiting access to extracted information

AI-900 focuses on awareness, not technical controls.

Exam Tips for Identifying Document Processing Workloads

  • Look for keywords like invoice, receipt, form, contract, PDF, scanned document
  • Identify whether the goal is extracting structured data, not just reading text
  • Choose document processing over NLP if the input is primarily a document
  • Remember that OCR alone may not be sufficient for full document understanding

Summary

For the AI-900 exam, you should be able to:

  • Recognize document processing scenarios
  • Identify common document processing capabilities such as OCR and form extraction
  • Associate document processing workloads with Azure AI Document Intelligence
  • Distinguish document processing from vision and NLP workloads

A solid understanding of document processing workloads will help you answer several scenario-based questions with confidence.

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