The correct answer is Form Recognizer, with Computer Vision also being a valid choice for extracting text from scanned invoices and receipts. Both Azure services leverage OCR technology, but Form Recognizer is purpose-built for structured document extraction, using prebuilt models to pull out key-value pairs, tables, and line items from invoices and receipts, while Computer Vision’s OCR reads printed and handwritten text from images more broadly. On the AI-900 exam, this question tests your understanding of which Azure AI services specialize in document intelligence versus general image analysis—a common trap is selecting only Computer Vision and forgetting that Form Recognizer is the more targeted tool for forms and invoices. Remember the memory tip: “Form Recognizer for forms, Computer Vision for captions”—if the task involves extracting structured data from a document layout, Form Recognizer is your go-to, but both can handle the OCR basics.
AI-900 Practice Question: Describe features of computer vision workloads on Azure
This AI-900 practice question tests your understanding of describe features of computer vision workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company needs to extract text from scanned invoices and receipts. Which Azure services are suitable for this task? (Select all that apply.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Computer Vision
Computer Vision (A) is correct because its OCR (Optical Character Recognition) capability can extract printed and handwritten text from images, including scanned invoices and receipts. Form Recognizer (B) is correct because it is specifically designed to extract text, key-value pairs, and tables from forms and documents like invoices and receipts, using prebuilt models. Both services can handle the task, but Form Recognizer is more specialized for structured document extraction.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Computer Vision
Why this is correct
Computer Vision includes an OCR capability that can detect and extract text from images and documents.
Related concept
Read the scenario before looking for a memorised answer.
✓
Form Recognizer
Why this is correct
Form Recognizer is designed to extract text and structured data from forms, invoices, and receipts using prebuilt models.
Related concept
Read the scenario before looking for a memorised answer.
✗
Text Analytics
Why it's wrong here
Text Analytics is a natural language processing service that analyzes text but does not perform optical character recognition (OCR).
✗
Custom Vision
Why it's wrong here
Custom Vision is used for training custom image classification and object detection models, not for text extraction.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Text Analytics with OCR capabilities, assuming it can process images, when in fact it only works on raw text input.
Detailed technical explanation
How to think about this question
Computer Vision's OCR uses the Read API, which leverages deep learning models to recognize text at the word and line level, supporting multiple languages and handwritten text. Form Recognizer builds on this by adding layout analysis and custom model training, allowing it to extract structured data like invoice line items and totals. In a real-world scenario, a company might use Computer Vision for quick OCR on a single receipt, but Form Recognizer is better for batch processing hundreds of invoices with consistent fields.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Computer Vision — Computer Vision (A) is correct because its OCR (Optical Character Recognition) capability can extract printed and handwritten text from images, including scanned invoices and receipts. Form Recognizer (B) is correct because it is specifically designed to extract text, key-value pairs, and tables from forms and documents like invoices and receipts, using prebuilt models. Both services can handle the task, but Form Recognizer is more specialized for structured document extraction.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company needs to extract text from scanned invoices and receipts. Which Azure services are suitable for this task? (Choose two.)
medium
✓ A.Computer Vision
✓ B.Azure AI Document Intelligence
C.Azure AI Language
D.Custom Vision
Why A: Computer Vision (option A) is correct because it provides OCR capabilities to extract printed and handwritten text from images, including scanned invoices and receipts. Its Read API can process text from various surfaces and layouts, making it suitable for document digitization tasks.
Last reviewed: Jun 11, 2026
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
This AI-900 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-900 exam.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.