AI-901: Information Extraction (Foundry)

Information Extraction (Foundry) is one of the skill areas tested on the Azure AI Fundamentals (Foundry refresh) (AI-901) exam. Below are free AI-901 practice questions with worked answers and a concept diagram — each with a plain-language explanation. Practice the first 10 questions of AI-901 free, no signup.

The concept, in one picture

Concept flowExtracting structured data from documents
Extracting structured data from documentsDocument (PDF, form, image)OCR + layoutread text, tables, structureExtract fields & entitieskey-value pairs, names, datesStructured data (JSON)ready for your app

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Sample AI-901 question

You are building a web application that reads invoices to compute expenses. You must pull structured fields, including nested values, from each invoice according to a schema you define. What should you use?

  • a transcription workflow in Azure Speech in Foundry Tools
  • an optical character recognition (OCR)-only document processing pipeline
  • an analyzer in Azure Content Understanding in Foundry Tools
  • an Azure AI Search service
Explanation

Extracting schema-defined structured fields, including nested values, from invoices is the job of an analyzer in Azure Content Understanding. An analyzer defines how content is processed, which fields are extracted, and how the structured (JSON) output is shaped, and Content Understanding supports invoice extraction (for example, the prebuilt-invoice analyzer). A Speech transcription workflow only turns audio into text, an OCR-only pipeline extracts raw text but not schema-based nested fields, and Azure AI Search indexes and queries content rather than defining extraction schemas.

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