Get Your CertAIF-C01PlayCompete
‹ All AIF-C01 questions

AIF-C01 Practice Question 58: AI Service Cards

AWS Certified AI Practitioner (AIF-C01) · Test 6 · question 8 of 10

Guidelines for Responsible AIeasy

Before adopting a managed AWS AI service, a risk and procurement team asks for AWS's own published statement of that service's intended use cases, its known limitations, the responsible AI design choices behind it, and best practices for deploying it well. Which AWS resource exists for exactly this purpose?

Select one answer
Show answer and explanation

Answer:

  • D. AWS AI Service Cards

AI Service Cards are AWS's own responsible AI documentation for its AI services and models. AWS describes them as enhancing transparency by giving customers *a single place to find information on the intended use cases and limitations, responsible AI design choices, and performance optimization best practices*, which is item for item what the risk team asked for (option D).

- A is wrong because SageMaker Model Cards document your own models: your intended uses, your risk rating, your training details and evaluation results. They are the right artefact for a model you built, not for an AWS service you are buying. - B is wrong because a Well-Architected review assesses *your architecture* against AWS's pillars and best practices. It produces findings about your workload, not a vendor statement about a service's responsible AI profile. - C is wrong because an evaluation job reports how a model scored on your prompts and your dataset. That is your own measurement, valuable, but it is not AWS's published account of the service's intended use and limitations, and it exists only after you have already adopted the service.

Reference: Responsible AI Tools and Resources

Practice Test 6 ›

Study guides for AIF-C01

AI engineer roadmap 2026: skills, certs and the orderAI engineer roadmap for 2026: skills to learn in order, AI engineer vs ML engineer, which certifications fit each stage, and what to skip.
How AI Is Changing Software Jobs: Where to PrepareHow AI is changing software jobs: what history shows, the evidence on junior developers, what Klarna learned, new AI roles and five domains to prepare for.
How AWS Certification Exams Work: Scoring and RenewalHow AWS certification exams work: levels, booking, question types, unscored questions, scaled scores, pass marks, validity and how recertification works.
What Is Amazon Bedrock? Models, Pricing and GuardrailsWhat is Amazon Bedrock? How a request reaches a model, what happens to your data, token pricing, Guardrails, Knowledge Bases, AgentCore and the exam traps.
Google Cloud Generative AI Leader vs AWS AI PractitionerGoogle Cloud Generative AI Leader vs AWS AI Practitioner: format, cost, topics, free preparation and which certification to take first.
AWS certification cost in 2026, and free ways to prepareWhat every AWS certification costs in 2026 in USD and INR, retake and reschedule rules, the 50% voucher, and the free official ways to prepare.
AWS Generative AI Developer Professional (AIP-C01) guideWhat the AWS Certified Generative AI Developer – Professional (AIP-C01) exam covers - format, cost, the five domains, the services, and how to prepare.
Best AI certifications 2026: AWS, Google, Microsoft, ClaudeThe best AI certifications in 2026 from AWS, Google, Microsoft, Claude and Databricks, by level, with price, status and which one to take first.
Which AWS certification should you get? 2026 roadmapWhich AWS certification to get first, by role and experience, with each exam's status in October 2026, what is changing, and prices in USD and INR.
What Is RAG? How Retrieval-Augmented Generation WorksWhat RAG is and how it works: chunking, embeddings, vector search, hybrid search, reranking, GraphRAG and agentic RAG on AWS, Google and Azure.
Prompt engineering vs RAG vs fine-tuningWhen to use prompt engineering, retrieval-augmented generation, fine-tuning or continued pre-training, compared on cost, freshness, hallucination and privacy.