The answer is enabling autoscaling on Azure AI Language to adjust capacity based on demand, alongside using provisioned throughput units (PTUs) for Azure OpenAI Service and selecting the appropriate pricing tier for Azure AI Vision. Autoscaling is essential for Azure AI Language because it dynamically matches throughput to real-time usage, preventing over-provisioning costs during low demand while ensuring availability during spikes. PTUs for Azure OpenAI Service provide reserved capacity, which guarantees predictable performance and cost for stable enterprise workloads by avoiding pay-per-token variability. On the AI-102 exam, this question tests your ability to balance cost and performance across multiple AI services, often appearing as a scenario where you must avoid the trap of applying the same strategy to all services—for instance, autoscaling is ideal for Language but not for OpenAI’s PTU model. A memory tip: remember “LAP” for Language autoscale, OpenAI PTUs, and Vision tier—each service demands a distinct cost lever.
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. 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 THREE considerations are essential when designing a cost management strategy for an enterprise Azure AI solution that uses multiple AI services, including Azure OpenAI Service, Azure AI Language, and Azure AI Vision?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Choose provisioned throughput units (PTUs) for Azure OpenAI Service for predictable workloads.
Option B is correct because provisioned throughput units (PTUs) for Azure OpenAI Service provide reserved capacity, ensuring predictable performance and cost for stable workloads. PTUs are ideal for enterprise scenarios where latency and throughput must be consistent, as they allocate dedicated model processing capacity and avoid pay-per-token variability.
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.
✗
Use the Free tier for all services to minimize upfront costs.
Why it's wrong here
Free tier has strict limits and is not scalable for enterprise.
✓
Choose provisioned throughput units (PTUs) for Azure OpenAI Service for predictable workloads.
Why this is correct
PTUs provide cost savings over pay-as-you-go for steady usage.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use a single multi-service Cognitive Services account to consolidate usage.
Why this is correct
Multi-service account simplifies management and may offer tiered pricing.
Related concept
Read the scenario before looking for a memorised answer.
✗
Deploy Azure Site Recovery to replicate AI services across regions.
Why it's wrong here
Site Recovery is for disaster recovery, not cost optimization.
✓
Enable autoscaling on Azure AI Language to adjust capacity based on demand.
Why this is correct
Autoscaling prevents paying for unused capacity.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the Free tier's suitability for production or assume Azure Site Recovery can replicate stateless API endpoints, when in fact it is designed for infrastructure-level failover, not cost management.
Detailed technical explanation
How to think about this question
Provisioned throughput units (PTUs) for Azure OpenAI Service are allocated per model deployment and guarantee a fixed number of tokens per minute (e.g., 1 PTU provides 60,000 tokens per minute for GPT-4). This contrasts with pay-as-you-go pricing, which can cause cost spikes during burst usage; PTUs shift cost from variable to fixed, enabling budget forecasting. In a multi-service solution, consolidating usage under a single multi-service Cognitive Services account (Option C) simplifies key management and billing, while autoscaling on Azure AI Language (Option E) dynamically adjusts capacity to match demand, preventing over-provisioning.
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.
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: Choose provisioned throughput units (PTUs) for Azure OpenAI Service for predictable workloads. — Option B is correct because provisioned throughput units (PTUs) for Azure OpenAI Service provide reserved capacity, ensuring predictable performance and cost for stable workloads. PTUs are ideal for enterprise scenarios where latency and throughput must be consistent, as they allocate dedicated model processing capacity and avoid pay-per-token variability.
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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Question Discussion
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