AI-102 Implement generative AI solutions Practice Question
You are developing a custom chatbot using Azure AI Bot Service and Language Understanding (CLU). The chatbot needs to escalate to a human agent when the user's sentiment is negative. Which component should you use to detect sentiment?
⚠ Common exam trap
Watch out — candidates often confuse Azure Cognitive Search (a search service) with AI Language services, or assume that QnA Maker includes sentiment analysis, when in fact only Azure AI Language provides dedicated sentiment detection.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Language sentiment analysis
Azure AI Language sentiment analysis is the correct component because it provides pre-built sentiment detection capabilities that analyze text and return sentiment labels (positive, negative, neutral) and confidence scores. This directly meets the requirement to detect negative user sentiment in chatbot conversations, enabling escalation to a human agent when needed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure AI Language sentiment analysis
Why this is correct
Azure AI Language sentiment analysis returns per-utterance sentiment scores and confidence values, which the bot can evaluate to trigger escalation. CLU handles intent and entity extraction only, not sentiment, so it cannot satisfy the negative-sentiment escalation condition. This component directly meets the requirement to detect sentiment within the conversation flow.
- ✗
Azure Cognitive Search
Why it's wrong here
Azure Cognitive Search indexes and queries documents; it returns no sentiment score. It would be correct for searching a document corpus, but escalation logic needs a sentiment analysis call, such as the Language service, to classify the user's utterance.
- ✗
Orchestration workflow
Why it's wrong here
Orchestration workflow sequences intents and connected services within a CLU project; it returns intent and entity results, not sentiment scores. Sentiment analysis is a separate capability, so escalation logic keyed to negative sentiment cannot read it here. It is tempting because orchestration coordinates multi-step bot flows, which would be the right choice for routing between skills.
- ✗
QnA Maker
Why it's wrong here
QnA Maker answers questions from a curated knowledge base; it performs no sentiment scoring. It would be the right component for FAQ-style retrieval, whereas negative-sentiment detection requires the Text Analytics or Language service sentiment capability.
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