AIF-C01 Guidelines for Responsible AI Practice Question
A retail company is preparing to launch a generative AI customer support assistant built on Amazon Bedrock. Before launch, the responsible AI review board asks the team to document the assistant's intended purpose, its known limitations, and the evaluation results from fairness and accuracy testing. Which AWS resource should the team produce to satisfy this request?
⚠ Common exam trap
It's easy for candidates to confuse provider-side compliance documentation such as AWS Artifact with customer-side model governance documentation, which must describe the customer's own model, not AWS's certifications.
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
✓
An Amazon SageMaker Model Card that records intended use, risk rating, and evaluation results for the model.
A responsible AI review board wants structured documentation of purpose, limitations, and evaluation outcomes. SageMaker Model Cards are purpose-built for this, capturing intended use, out-of-scope applications, risk rating, and performance and fairness metrics in a consistent format. The other artifacts cover AWS compliance posture, runtime telemetry, or account advisories, none of which describe the model itself.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
An Amazon CloudWatch dashboard showing invocation counts, latency percentiles, and error rates for the assistant.
Why it's wrong here
A CloudWatch dashboard presents operational telemetry such as traffic volume, latency, and failures. Those metrics show whether the system is healthy, but they say nothing about intended purpose, design limitations, or fairness and accuracy evaluation outcomes, so they do not satisfy a responsible AI documentation request.
- ✗
An AWS Trusted Advisor check report listing cost optimization and security recommendations for the account.
Why it's wrong here
Trusted Advisor inspects an account for cost, security, fault tolerance, and service quota issues and returns recommendations. It is an operational advisory tool with no concept of model documentation, so it cannot record intended use, limitations, or evaluation results for a generative AI assistant.
- ✓
An Amazon SageMaker Model Card that records intended use, risk rating, and evaluation results for the model.
Why this is correct
SageMaker Model Cards are the governance artifact designed for exactly this purpose: they capture intended use, out-of-scope uses, risk rating, training details, and evaluation metrics in a structured document. Producing a model card gives the review board a single, standardized record of purpose, limitations, and fairness and accuracy results, which is what the scenario asks the team to deliver.
- ✗
An AWS Artifact report downloaded from the compliance portal covering the AWS services in use.
Why it's wrong here
AWS Artifact provides AWS's own compliance reports and agreements, such as SOC and ISO certifications, covering the cloud provider's infrastructure. It documents AWS's controls, not the customer's assistant, so it cannot describe the intended purpose, known limitations, or fairness testing results of the company's own generative AI application.
Go deeper
Related to this question
About these practice questions
This AIF-C01 question is part of Courseiva's 862-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 September 2026 · checked against the official Amazon Web Services exam blueprint
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIF-C01 exam.