Match each Azure AI service to its primary capability.
Drag a concept onto its matching description — or click a concept then click the description.
AI-powered cloud search service
Build conversational AI bots
Extract information from documents
Extract insights from videos
Monitor and detect anomalies in metrics
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Computer Vision: Extract information from images and videos
Azure AI services are specialized: Computer Vision for images, Speech for audio, Language for text, and Decision for predictive decisions. Common confusions include mixing vision with speech or language with decision.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Computer Vision: Extract information from images and videos
Why this is correct
Computer Vision, part of Azure AI Vision, extracts structured information from images and video by performing optical character recognition (OCR), object and people detection, image tagging, dense captioning, scene classification, and spatial analysis. The Computer Vision API can read text from documents and signage, track objects across video frames, and generate captions from visual content. It is the appropriate service for any task where the source data is visual—images or video—rather than text or audio.
Speech: Recognize and synthesize speech
Why this is correct
The Speech service handles all spoken-language modalities, including real-time speech-to-text transcription, text-to-speech synthesis with neural voices, speech translation across languages, and speaker recognition/verification. It uses audio input/output and acoustic models to convert between speech and text. This pairing is correct because recognizing and synthesizing speech is the core purpose of the Azure Speech service, not of Language, Vision, or Decision.
Language: Understand and analyze text
Why this is correct
The Language service provides deep understanding of textual content, including sentiment detection, key phrase extraction, named entity recognition (NER), personally identifiable information (PII) detection, summarization, and conversational language understanding (CLU) for intents and entities. It processes natural language text to extract meaning, categorize content, and answer questions. This is distinct from the more visual, audio, or decision-focused capabilities of the other Azure AI service categories.
Decision: Build intelligent applications that make decisions
Why this is correct
Azure AI Decision services—Anomaly Detector, Personalizer, and Content Moderator—are designed to help applications make informed decisions on unseen data, such as detecting unusual patterns, recommending personalized experiences, or flagging inappropriate content. These services consume signals from data or user behavior and produce an action or score that guides intelligent decision-making. This capability aligns with building intelligent applications that take actions based on analysis, not simply recognizing or understanding input.
Computer Vision: Convert speech to text
Why it's wrong here
Converting speech to text is a speech-to-text feature of the Azure Speech service, which processes audio waveforms and acoustic signals to produce a transcript. Computer Vision operates exclusively on visual input—images and video frames—and has no audio-processing pipeline. Therefore, assigning speech-to-text to Computer Vision confuses the input modality, because Computer Vision cannot ingest audio files or streams.
Language: Detect anomalies in data
Why it's wrong here
Azure AI Language is built for natural language processing tasks—sentiment analysis, key phrase extraction, named entity recognition, language detection, summarization, and question answering—all on unstructured text. Anomaly detection, by contrast, identifies statistical outliers in time-series or sensor data using the Anomaly Detector service, which is classified under Decision services, not Language. Therefore, linking Language to data anomaly detection is a category mismatch.
Go deeper
Learn chapter
Azure Machine Learning Studio
Key term
Computer vision
Computer vision is a field of artificial intelligence that enables computers to interpret and make decisions based on visual data from the world, such as images and videos.
Key term
Azure AI Services
Azure AI Services is a collection of pre-built, cloud-based artificial intelligence APIs and services that allow developers and IT professionals to integrate capabilities like vision, speech, language, and decision-making into applications without needing deep machine learning expertise.
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Same concept, more angles
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Variation 1. Match each Azure AI service to its use case.
mediumWhy A: Each Azure AI service is designed for specific tasks: Computer Vision for image analysis (e.g., OCR), Translator for text translation, Speech for speech-to-text, and Anomaly Detector for time series pattern detection. Common confusions arise from overlapping capabilities like text extraction vs translation.
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.