AI-103 Implement Generative AI And Agentic Solutions Practice Question
Which TWO criteria are typically used to evaluate the grounding of an LLM-based application?
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
✓
Relevance
Groundedness and relevance are core metrics in Azure AI Foundry evaluation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Relevance
Why this is correct
Measures if the response is relevant to the user query.
- ✗
Latency
Why it's wrong here
Latency is a performance metric, not a grounding one.
- ✗
Token cost
Why it's wrong here
Cost is an operational metric.
- ✓
Groundedness
Why this is correct
Measures if the response is based on the source context.
- ✗
Model version number
Why it's wrong here
Version is metadata, not a quality metric.
About these practice questions
This AI-103 question is part of Courseiva's 510-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 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-103 exam.