An organization is implementing an AI-based credit assessment engine using internal and third- party customer data. Which of the following BEST aligns with data management controls for the AI life cyc

The correct answer is A. Documented procedures for data sourcing, lineage tracking, and quality validation. AAISM emphasizes that data governance over the full AI life cycle is foundational. The official content describes effective AI data management as including documented procedures for: (1) how data is sourced, (2) how lineage is tracked from origin to model, and (3) how data qualit

AI Security Strategy and Governance

Question

An organization is implementing an AI-based credit assessment engine using internal and third- party customer data. Which of the following BEST aligns with data management controls for the AI life cycle?

Options

ADocumented procedures for data sourcing, lineage tracking, and quality validation
BUse of hashed identifiers to anonymize datasets used for model validation and internal analytics
CEncrypted isolation and dynamic access controls on training data pipelines
DLimitation of model training to structured data from vetted sources to minimize ingestion risk

How the community answered

(34 responses)

A
76% (26)
B
3% (1)
C
12% (4)
D
9% (3)

Explanation

AAISM emphasizes that data governance over the full AI life cycle is foundational. The official content describes effective AI data management as including documented procedures for: (1) how data is sourced, (2) how lineage is tracked from origin to model, and (3) how data quality is validated and monitored. This ensures transparency, accountability, and auditability, which are especially critical in regulated areas like credit assessments.

Topics

#Data Management#Data Quality#Data Governance#AI Lifecycle

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