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calendar_todayJun 03, 2026 schedule12 min read

AI-900 Azure AI Fundamentals Practice Questions 2026

Try AI-900 Azure AI Fundamentals practice questions with answer explanations, scenario clues, and a focused review of common AI workload patterns.

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AI-900 Azure AI Fundamentals

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AI-900 Azure AI Fundamentals Practice Questions 2026

AI-900 Azure AI Fundamentals Practice Questions 2026

How to use these AI-900 practice questions

AI-900 Azure AI Fundamentals practice questions are most useful when they are treated as a reasoning exercise rather than a memory quiz. The exam is built around recognizing the right workload family, identifying the main AI concept in the scenario, and choosing the best answer without overcomplicating the problem.

If you want the official exam page, start here: AI-900 Azure AI Fundamentals exam page. For a full concept review, use the study guide: AI-900 Azure AI Fundamentals Study Guide 2026. For the live question set, use: Try 35 free AI-900 practice questions. For the vendor source, review: Microsoft Azure AI Fundamentals official page.

These questions are exam-style practice written to match the kind of thinking AI-900 expects. They are not actual exam questions and they are not meant to reproduce protected content.

Official exam facts

Detail Info
Exam code AI-900
Certification Azure AI Fundamentals
Vendor Microsoft
Time limit 90 minutes
Passing score 70%
Official source Microsoft Azure AI Fundamentals official page
Cert-Pass exam page AI-900 Azure AI Fundamentals exam page
Study support AI-900 Azure AI Fundamentals Study Guide 2026
Retirement date Not announced

Question 1

A company wants to automatically classify customer support emails into categories such as billing, account access, and product defects.

Which AI workload is the best fit?

  • A. Classification using machine learning
  • B. Object detection using computer vision
  • C. Speech synthesis
  • D. Image segmentation

Correct answer: A. Classification using machine learning

Why this is correct: The company wants to assign a label to text based on patterns in historical data.

Why the other answers are weaker:

  • B and D are vision workloads.
  • C is about generating speech, not classifying text.

Question 2

A business wants to extract text from scanned receipts and invoices so that the data can be stored in a database.

Which capability is most relevant?

  • A. OCR or text extraction
  • B. Clustering
  • C. Anomaly detection
  • D. Prompt temperature tuning

Correct answer: A. OCR or text extraction

Why this is correct: OCR is used to read text from images or scans.

Why the other answers are weaker:

  • B groups data, but does not read text.
  • C finds unusual patterns.
  • D is a generative AI setting, not the main need here.

Question 3

A team wants a system that can answer questions based on a set of internal policy documents.

What is the best AI family for this use case?

  • A. Retrieval-augmented generative AI or question answering
  • B. Object detection
  • C. Reinforcement learning
  • D. Image classification

Correct answer: A. Retrieval-augmented generative AI or question answering

Why this is correct: The task is about using documents as a knowledge source and responding to questions.

Why the other answers are weaker:

  • B and D are vision tasks.
  • C is not the most relevant concept here.

Question 4

A company wants a model that predicts how many units of a product it will sell next month based on historical sales data.

What type of machine learning problem is this?

  • A. Regression
  • B. Clustering
  • C. Image classification
  • D. Translation

Correct answer: A. Regression

Why this is correct: The model is predicting a numeric value.

Why the other answers are weaker:

  • B groups items rather than predicting a number.
  • C and D are unrelated workload types.

Question 5

A data scientist has labeled examples showing which customers canceled a subscription and which did not. The goal is to train a model that predicts whether a future customer will cancel.

What type of learning is this?

  • A. Supervised learning
  • B. Unsupervised learning
  • C. Speech recognition
  • D. Reinforcement learning only

Correct answer: A. Supervised learning

Why this is correct: The training data includes labels, which is the defining feature of supervised learning.

Why the other answers are weaker:

  • B uses unlabeled data.
  • C is a different AI workload.
  • D is not the primary fit here.

Question 6

A retailer wants to identify individual products in photos and draw boxes around them.

Which AI task is the best fit?

  • A. Object detection
  • B. Sentiment analysis
  • C. Language translation
  • D. Text summarization

Correct answer: A. Object detection

Why this is correct: Object detection finds and locates objects in an image.

Why the other answers are weaker:

  • B, C, and D are language tasks.

Question 7

A company wants to understand whether customer feedback in a survey is positive, negative, or neutral.

Which workload is most relevant?

  • A. Sentiment analysis
  • B. Image classification
  • C. Object detection
  • D. OCR

Correct answer: A. Sentiment analysis

Why this is correct: Sentiment analysis measures the emotional tone of text.

Why the other answers are weaker:

  • B and C are vision tasks.
  • D is about reading text from images.

Question 8

A support team wants to automatically route messages written in different languages to the correct regional queue.

Which capability is most useful?

  • A. Language detection or text classification
  • B. Image segmentation
  • C. Anomaly detection
  • D. Recommender systems

Correct answer: A. Language detection or text classification

Why this is correct: The system needs to identify the language or classify the text.

Why the other answers are weaker:

  • B is a vision task.
  • C is for unusual pattern detection.
  • D recommends items and is not the best fit here.

Question 9

A company wants a chatbot that can draft a response to a customer question in a conversational style.

Which AI workload is the best fit?

  • A. Generative AI
  • B. Image classification
  • C. Clustering
  • D. Anomaly detection

Correct answer: A. Generative AI

Why this is correct: The task involves creating new natural-language output.

Why the other answers are weaker:

  • B and C are unrelated.
  • D is about finding unusual patterns.

Question 10

A candidate is asked to choose a responsible AI principle that deals with making sure the system does not produce harmful or dangerous behavior.

Which principle is the best match?

  • A. Reliability and safety
  • B. Shelf life
  • C. Compression
  • D. Redundancy

Correct answer: A. Reliability and safety

Why this is correct: Reliability and safety are about dependable operation and avoiding harmful failure.

Why the other answers are weaker:

  • B, C, and D are unrelated to responsible AI.

Question 11

A company is worried that an AI system trained on historical data may treat different user groups unfairly.

Which concern is the most relevant?

  • A. Fairness
  • B. Availability zones
  • C. Load balancing
  • D. Replication lag

Correct answer: A. Fairness

Why this is correct: Fairness addresses biased or uneven treatment.

Why the other answers are weaker:

  • B, C, and D are infrastructure topics, not AI ethics topics.

Question 12

A customer service manager wants an AI model to summarize long chat transcripts into short action items.

Which capability is most relevant?

  • A. Generative AI summarization
  • B. Object detection
  • C. Clustering
  • D. Anomaly detection

Correct answer: A. Generative AI summarization

Why this is correct: Summarization is a common generative AI use case.

Why the other answers are weaker:

  • B and C do not work on text summarization.
  • D is not the right workload family.

Question 13

A warehouse team wants to identify items that appear unusual compared with normal inventory patterns.

Which machine learning task is most relevant?

  • A. Anomaly detection
  • B. Translation
  • C. Text generation
  • D. Image captioning only

Correct answer: A. Anomaly detection

Why this is correct: The team wants to identify outliers or unusual cases.

Why the other answers are weaker:

  • B and C are language tasks.
  • D is not the best fit for the inventory scenario.

Question 14

A company is deciding whether it needs AI at all. The process is simple, rule-based, and always follows the same path with no variation.

What is the best conclusion?

  • A. A simple rule-based solution may be enough
  • B. Generative AI is always required
  • C. Computer vision is automatically the best choice
  • D. The system should use clustering by default

Correct answer: A. A simple rule-based solution may be enough

Why this is correct: Not every problem needs AI, especially if rules already solve the task reliably.

Why the other answers are weaker:

  • B, C, and D overcomplicate the problem.

Question 15

A team wants to build a model that learns from examples where each item already has a known category label.

What type of training is being used?

  • A. Supervised learning
  • B. Unsupervised learning
  • C. Speech synthesis
  • D. Document scanning

Correct answer: A. Supervised learning

Why this is correct: Known category labels are the hallmark of supervised learning.

Why the other answers are weaker:

  • B is unlabeled.
  • C and D are different AI tasks.

Question 16

A company wants to translate customer feedback from Spanish into English before the text is analyzed.

Which capability is most relevant?

  • A. Language translation
  • B. Object detection
  • C. Reinforcement learning
  • D. OCR

Correct answer: A. Language translation

Why this is correct: The text must be converted from one language to another.

Why the other answers are weaker:

  • B is a vision task.
  • C is a learning approach, not the described function.
  • D reads text from images, which is not the main need.

Question 17

A candidate wants to know the best way to prepare for AI-900 if they are unsure about the service names.

What is the most effective approach?

  • A. Learn the workload type from the scenario first
  • B. Memorize only product names
  • C. Skip practice questions
  • D. Focus only on deep coding details

Correct answer: A. Learn the workload type from the scenario first

Why this is correct: AI-900 questions are easiest when the candidate identifies the problem type first.

Why the other answers are weaker:

  • B is too shallow.
  • C removes the feedback loop.
  • D is unnecessary for a fundamentals exam.

Question 18

A company wants a system that reads short text from a photo of a receipt and then uses that information in a workflow.

Which combined capability is most relevant?

  • A. OCR followed by automation or processing
  • B. Clustering followed by compression
  • C. Object detection followed by translation
  • D. Reinforcement learning followed by encryption

Correct answer: A. OCR followed by automation or processing

Why this is correct: The text must first be extracted from the image, then the workflow can use it.

Why the other answers are weaker:

  • B, C, and D do not match the problem.

Common answer patterns to watch

AI-900 often repeats the same logic in different wording. The candidate should learn these patterns:

  • text and language problems often point to NLP or generative AI
  • image and photo problems often point to computer vision
  • numeric prediction problems often point to machine learning regression
  • category prediction problems often point to classification
  • unlabeled grouping problems often point to clustering
  • fairness, transparency, and safety questions often point to responsible AI

How to study from missed questions

When a question is missed, do not just memorize the correct answer letter. Ask:

  1. What type of data was in the scenario?
  2. Was the problem about generating, classifying, detecting, or predicting?
  3. Which clue should have narrowed the answer faster?
  4. What rule will help next time?

That method is much more useful than trying to brute-force a score.

Final review checklist

Before the exam, the candidate should be able to:

  • distinguish generative AI from traditional machine learning
  • identify supervised vs unsupervised learning
  • recognize computer vision and NLP scenarios
  • understand basic responsible AI principles
  • map a business problem to the right workload family
  • explain why a simpler non-AI solution may be the best choice

Related links

Frequently asked questions

Are these questions close to the real exam style?

Yes. They are written to reflect the type of reasoning AI-900 expects, without reproducing protected exam content.

Is AI-900 more about concepts or Azure service names?

It is mostly about concepts and workload recognition, with Azure service context included.

Should I memorize every AI service name?

No. Understanding what each service family does is more important than memorizing a giant list.

What should I do if I keep mixing up AI workload types?

Slow down and look at the data type and task first: text, image, prediction, or generation.

Is AI-900 a good stepping stone to AI-102?

Yes. AI-900 can help candidates build the foundation needed for deeper AI work.

Final advice

AI-900 becomes much easier when the candidate trains their brain to classify the problem before searching for the answer. If the scenario is about text, image, prediction, or generation, the right workload family usually becomes visible very quickly.

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Cert-Pass Editorial Team

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