The correct answer is to set the 'multipleIntents' parameter to true in the project settings. This is because Conversational Language Understanding (CLU) by default applies single-intent detection, returning only the highest-confidence intent—in this case, 'Greeting' at 0.85—while ignoring the secondary 'OrderStatus' intent. Enabling multi-intent detection instructs the model to evaluate all intents against the confidence threshold, allowing it to return both 'Greeting' and 'OrderStatus' from a single utterance like 'hi, where is my order?'. On the Microsoft Azure AI Engineer Associate AI-102 exam, this scenario tests your understanding of CLU configuration options, often appearing as a trick where candidates assume multi-intent is automatic or confuse it with entity detection. A common trap is forgetting that the feature must be explicitly enabled; the default behavior is single-intent only. Memory tip: think "Multiple Intents = Multiple Flags," meaning you must flip the 'multipleIntents' switch to true for the model to return more than one intent.
AI-102 Plan and manage an Azure AI solution Practice Question
This AI-102 practice question tests your understanding of plan and manage an azure ai solution. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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.
Refer to the exhibit. You deployed a Conversational Language Understanding (CLU) project. A user says 'hi, where is my order?' The model returns a single intent 'Greeting' with confidence 0.85. You need the model to detect both intents. What should you change?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Set 'multipleIntents' to true.
Option C is correct because the Conversational Language Understanding (CLU) service supports multi-intent detection only when the 'multipleIntents' flag is explicitly set to true in the project settings. By default, CLU returns only the highest-confidence intent; enabling this flag allows the model to return all intents whose confidence exceeds the threshold, enabling detection of both 'Greeting' and 'OrderStatus' from a single utterance.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Lower the confidenceThreshold to 0.5.
Why it's wrong here
Threshold affects confidence, but multipleIntents must be enabled.
✗
Add more utterances to the 'OrderStatus' intent.
Why it's wrong here
More utterances improve accuracy but do not enable multiple intents.
✓
Set 'multipleIntents' to true.
Why this is correct
Enabling multipleIntents allows the model to return multiple intents.
Related concept
Read the scenario before looking for a memorised answer.
✗
Change the project kind to 'Orchestration'.
Why it's wrong here
Orchestration is used for routing, not for multiple intents in one utterance.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the confidenceThreshold parameter with the mechanism for returning multiple intents, assuming lowering the threshold will surface additional intents, when in fact the multipleIntents flag must be enabled first.
Detailed technical explanation
How to think about this question
Under the hood, CLU uses a classification model that computes a confidence score for each defined intent per utterance. When multipleIntents is false (default), the API returns only the intent with the highest score; when true, the API returns all intents with scores above the confidenceThreshold, allowing downstream logic to handle multiple detected intents. In real-world scenarios, this is critical for utterances like 'hi, where is my order?' where a user both greets and requests order status—enabling multi-intent detection avoids forcing the developer to split the utterance or rely on a single intent that loses context.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Plan and manage an Azure AI solution — This question tests Plan and manage an Azure AI solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set 'multipleIntents' to true. — Option C is correct because the Conversational Language Understanding (CLU) service supports multi-intent detection only when the 'multipleIntents' flag is explicitly set to true in the project settings. By default, CLU returns only the highest-confidence intent; enabling this flag allows the model to return all intents whose confidence exceeds the threshold, enabling detection of both 'Greeting' and 'OrderStatus' from a single utterance.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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