AI-102 Implement generative AI solutions Practice Question
This AI-102 practice question tests your understanding of implement generative ai 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.
Which TWO actions should you take to reduce the cost of using Azure OpenAI for a chatbot that handles high traffic?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the batch API for non-real-time requests.
Option B is correct because the batch API allows you to submit non-real-time requests that are processed asynchronously, often at a lower cost per token compared to real-time inference. This is ideal for chatbot scenarios where some queries (e.g., historical analysis or bulk processing) do not require immediate responses, reducing overall Azure OpenAI consumption costs.
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.
✗
Increase max_tokens to reduce the number of requests.
Why it's wrong here
Increasing max_tokens increases tokens per request.
✓
Use the batch API for non-real-time requests.
Why this is correct
Batch API has lower cost per token.
Related concept
Read the scenario before looking for a memorised answer.
✓
Implement caching for frequently asked questions.
Why this is correct
Caching reduces API calls.
Related concept
Read the scenario before looking for a memorised answer.
✗
Lower the temperature to 0 to reduce token usage.
Why it's wrong here
Temperature does not affect token count.
✗
Fine-tune the model to reduce prompt length.
Why it's wrong here
Fine-tuning incurs additional training cost.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse token-related parameters (max_tokens, temperature) with cost-saving mechanisms, when in reality cost reduction for high-traffic chatbots relies on architectural patterns like batching and caching, not on tweaking inference parameters.
Detailed technical explanation
How to think about this question
The batch API in Azure OpenAI uses a separate queue-based endpoint (e.g., /batches) that processes requests with a lower priority, allowing Microsoft to optimize infrastructure utilization and pass savings to customers. Caching (Option C) reduces cost by storing responses to frequently asked questions, avoiding redundant API calls and token consumption; this is a common pattern using services like Azure Cache for Redis or Azure Cosmos DB with TTL policies.
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 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
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.
Implement generative AI solutions — This question tests Implement generative AI solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the batch API for non-real-time requests. — Option B is correct because the batch API allows you to submit non-real-time requests that are processed asynchronously, often at a lower cost per token compared to real-time inference. This is ideal for chatbot scenarios where some queries (e.g., historical analysis or bulk processing) do not require immediate responses, reducing overall Azure OpenAI consumption costs.
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.
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 →
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.
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.