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Azure AI-900 AI Workloads Guide

Study Azure AI-900 AI Workloads: key concepts, common traps, and exam decision cues.

This chapter gives AI-900 its first decision rule: understand the problem class before you choose the Azure capability. Microsoft also uses this chapter to test whether you can identify the responsible-AI principle most directly at risk in a short scenario.

Current weight in the study guide

Microsoft currently weights this skill area at 15-20% of the exam.

Work this skill area in order

Lesson Focus
1.1 Workload Classification and Scenario Fit Learn how to separate vision, document processing, NLP, speech, ML, and generative AI from short business scenarios.
1.2 Responsible AI Principles and Risk Signals Learn how fairness, safety, privacy, inclusiveness, transparency, and accountability show up in exam wording.

Fast routing inside this chapter

If the question is really about… Go first to…
what kind of problem the system is solving 1.1 Workload Classification and Scenario Fit
which responsible-AI principle the scenario threatens 1.2 Responsible AI Principles and Risk Signals

What strong answers usually do

  • identify the primary workload even if the business process includes multiple AI steps
  • separate document extraction from generative AI when the goal is reading existing content
  • classify the risk in responsible-AI questions before thinking about mitigation
  • remember that human review often points to accountability and sometimes reliability, not automatically to transparency

In this section

Revised on Sunday, May 10, 2026
2. ML