AIF-C01 Practice Question: Security, Compliance, and Governance for AI Solutions
A healthcare startup is using Amazon SageMaker to train a model on patient data. They need to ensure that the training data does not contain any personally identifiable information (PII) before being used. Which AWS service can automatically detect and report PII in the data stored in S3?
⚠ Common exam trap
AIF-C01 often tests the confusion between Macie and Comprehend Medical — candidates may think Comprehend Medical detects all PII, but Macie is the dedicated service for PII discovery in S3, while Comprehend Medical is for clinical text extraction.
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
✓
Amazon Macie
Amazon Macie is a fully managed data security and privacy service that uses machine learning to automatically discover, classify, and protect sensitive data stored in Amazon S3. It can detect personally identifiable information (PII) such as names, addresses, and credit card numbers, and provides detailed reports. This directly addresses the requirement to detect and report PII in S3 before using it for training.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Rekognition
Why it's wrong here
Rekognition analyses images and video for faces, objects and moderation labels; it cannot inspect tabular or textual S3 objects for PII. It suits visual content analysis, not the required automated detection and reporting of personally identifiable information held in data stores.
- ✗
AWS Glue DataBrew
Why it's wrong here
DataBrew profiles and cleans datasets, offering pattern-based PII detection as part of transformation recipes, but it does not automatically scan S3 objects and report findings as a standalone detection service. It suits interactive data preparation, not the required automated PII identification and reporting across stored data.
- ✗
Amazon Comprehend Medical
Why it's wrong here
Comprehend Medical extracts medical entities such as medications and conditions from clinical text; it does not detect general PII across arbitrary S3 data. It suits clinical NLP tasks, whereas the requirement is automated PII detection and reporting for stored objects, which Amazon Macie performs.
- ✓
Amazon Macie
Why this is correct
Amazon Macie uses machine learning and pattern matching to automatically discover, classify and report sensitive data such as PII in S3. It continuously evaluates buckets and raises findings, directly satisfying the requirement to detect and report PII before SageMaker training begins.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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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.