Quick Answer
The answer is Conversation summarization, Custom NER, and Sentiment analysis. Conversation summarization is specifically designed to condense lengthy call transcripts into concise summaries of issues and resolutions, while Custom Named Entity Recognition (NER) allows you to train a model to extract domain-specific entities like product names or complaint categories that standard models miss. Sentiment analysis then evaluates the emotional tone of each speaker segment, providing the required insight into customer satisfaction. On the AI-102 exam, this question tests your ability to match Azure AI Language features to real-world business scenarios, often presenting distractors like Key Phrase Extraction or PII detection—remember that key phrases are too generic for structured issue extraction, and PII focuses on privacy, not insights. A common trap is choosing “Key Phrase Extraction” because it sounds similar to summarization, but it only returns isolated words, not coherent summaries. Memory tip: “SCS” for Summarize, Custom entities, Sentiment—think of a call center agent who first summarizes the call, then tags the specific problem, and finally rates the customer’s mood.
This AI-102 practice question tests your understanding of implement natural language processing solutions. 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.
Your organization needs to analyze customer call transcripts to extract key insights, including sentiment, issues, and resolution. Which THREE Azure AI Language features should you use?
Custom named entity recognition
Can be trained to extract issues and resolutions.
Sentiment analysis
Detects sentiment in the conversation.
Conversation summarization
Summarizes the call transcript.
Key phrase extraction
Why wrong: Key phrases are not specific enough for issues and resolutions.
PII detection
Why wrong: PII detection is for personal data, not insights.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Custom named entity recognition
Conversation summarization summarizes call transcripts; custom NER can extract specific entities like issues and resolutions; sentiment analysis detects sentiment. Key phrase extraction and PII detection are not the primary needs.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Custom named entity recognition
Why this is correct
Can be trained to extract issues and resolutions.
Related concept
Read the scenario before looking for a memorised answer.
Sentiment analysis
Why this is correct
Detects sentiment in the conversation.
Related concept
Read the scenario before looking for a memorised answer.
Conversation summarization
Why this is correct
Summarizes the call transcript.
Related concept
Read the scenario before looking for a memorised answer.
Key phrase extraction
Why it's wrong here
Key phrases are not specific enough for issues and resolutions.
PII detection
Why it's wrong here
PII detection is for personal data, not insights.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Trap categories for this question
Keyword trap
Key phrases are not specific enough for issues and resolutions.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Implement natural language processing solutions — study guide chapter
Learn the concepts, then practise the questions
Implement natural language processing solutions practice questions
Targeted practice on this topic area only
All AI-102 questions
988 questions across all exam domains
Microsoft Azure AI Engineer Associate AI-102 study guide
Full concept coverage aligned to exam objectives
AI-102 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
Practise AI-102 questions linked to Implement an agentic solution.
Practise AI-102 questions linked to Implement computer vision solutions.
Practise AI-102 questions linked to Implement knowledge mining and information extraction solutions.
Practise AI-102 questions linked to Implement image and video processing solutions.
Practise AI-102 questions linked to Implement natural language processing solutions.
Practise AI-102 questions linked to Implement generative AI solutions.
Practise AI-102 questions linked to Implement agentic AI solutions.
Practise AI-102 questions linked to Implement knowledge mining and document intelligence solutions.
Practise AI-102 questions linked to Plan and manage an Azure AI solution.
Practise AI-102 questions linked to Implement content moderation solutions.
Practise AI-102 questions linked to AI-102 fundamentals.
Practise AI-102 questions linked to AI-102 scenario.
Practice this exam
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Implement natural language processing solutions — This question tests Implement natural language processing solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Custom named entity recognition — Conversation summarization summarizes call transcripts; custom NER can extract specific entities like issues and resolutions; sentiment analysis detects sentiment. Key phrase extraction and PII detection are not the primary needs.
Identify which AI-102 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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 →
Last reviewed: Jun 20, 2026
This AI-102 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-102 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.