Quick Answer
The correct answer is Option C because the Azure AI Language asynchronous batch API is designed to batch process multiple language reviews with async API calls, allowing you to combine sentiment analysis, key phrase extraction, and language detection into a single request while setting the language parameter to 'multi' for automatic language detection. This directly addresses the need to reduce latency and cost by eliminating individual synchronous calls, as the batch API processes all reviews together regardless of language. On the AI-102 exam, this scenario tests your understanding of when to choose asynchronous batch operations over synchronous or translation-based approaches—a common trap is assuming you must separate languages by batch (Option B) or translate first (Option D), which adds unnecessary overhead. Remember the memory tip: “Batch it all, multi-task, skip the translate” to recall that the async batch API with multi-language support handles mixed-language reviews efficiently in one go.
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.
You are an AI engineer at a global e-commerce company. The company uses Azure AI Language to analyze product reviews in English, Spanish, and French. The current solution calls the sentiment analysis API for each review individually, resulting in high latency and cost. You need to design a new solution that processes reviews in batches, reduces the number of API calls, and still supports multiple languages. The solution must also extract key phrases and detect the language automatically. You have the following options:
Option A: Use the Azure AI Language synchronous API with the 'multi-language' parameter set to true. Send reviews one by one.
Option B: Use the Azure AI Language asynchronous batch API. Combine all reviews into a single batch request, but only for one language at a time.
Option C: Use the Azure AI Language asynchronous batch API. Send a single batch request with all reviews, setting the 'language' parameter to 'multi' to auto-detect language, and specify sentiment analysis, key phrase extraction, and language detection as tasks.
Option D: Use the Azure AI Translator service to translate all reviews to English, then use the Azure AI Language batch API for English-only sentiment and key phrase extraction.
Option C
Asynchronous batch API with multi-language and multiple tasks reduces calls and supports all languages.
Option B
Why wrong: Processes only one language per batch, requiring multiple batches.
Option A
Why wrong: Synchronous one-by-one calls increase latency/cost.
Option D
Why wrong: Adds translation cost and latency, may lose nuances.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Option C
Option C is correct. The asynchronous batch API supports multiple tasks (sentiment, key phrases, language detection) in a single request, and setting language to 'multi' enables auto-detection. This reduces API calls and latency. Option A is wrong because synchronous one-by-one calls increase latency/cost. Option B is wrong because it processes only one language per batch, requiring multiple batches. Option D is wrong because it adds translation cost and latency, and may lose nuances.
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.
Option C
Why this is correct
Asynchronous batch API with multi-language and multiple tasks reduces calls and supports all languages.
Related concept
Read the scenario before looking for a memorised answer.
Option B
Why it's wrong here
Processes only one language per batch, requiring multiple batches.
Option A
Why it's wrong here
Synchronous one-by-one calls increase latency/cost.
Option D
Why it's wrong here
Adds translation cost and latency, may lose nuances.
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.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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.
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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: Option C — Option C is correct. The asynchronous batch API supports multiple tasks (sentiment, key phrases, language detection) in a single request, and setting language to 'multi' enables auto-detection. This reduces API calls and latency. Option A is wrong because synchronous one-by-one calls increase latency/cost. Option B is wrong because it processes only one language per batch, requiring multiple batches. Option D is wrong because it adds translation cost and latency, and may lose nuances.
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.
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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.
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