PECB ISO-IEC-42001-Lead-Auditor Exam With Confidence Using Practice Dumps

The principle being neglected is Due Professional Care.

According to ISO 19011:2018 – Clause 4(f), auditors are expected to apply diligence, competence, and judgment during audit activities. If an auditor proceeds with an audit without the required expertise, especially for a high-risk system like autonomous driving, this violates the principle of due care.

The PECB Lead Auditor Guide – Domain 3 clearly states that in complex technical environments (such as AI or autonomous systems), auditors must seek assistance from domain specialists when they lack direct experience.

Machine Learning (ML) is the most suitable AI concept in this scenario. ML focuses on developing algorithms that can learn from structured or unstructured data and make predictions based on historical patterns.

In this case, analyzing customer browsing history and purchase records falls directly under supervised learning, a subcategory of ML, which is typically used for predictive modeling in retail (such as next-best-offer, product recommendation, or demand forecasting).

According to the PECB Lead Auditor Study Guide (Domain 1), ML is specifically referenced as the core technique for prediction systems, user behavior modeling, and data-driven decision-making systems.

Though Deep Learning (DL) is a subset of ML, it is often used for more complex pattern recognition tasks such as image or speech recognition, which is not explicitly required here.

A combined audit refers to a single audit that covers two or more management systems (e.g., AIMS and ISMS) managed as a single system. In this case, the organization is undergoing a certification audit for both ISO/IEC 42001 and ISO/IEC 27001 simultaneously.

According to ISO 19011:2018 (Clause 3.11), a combined audit is “an audit conducted at one auditee on two or more management systems of different disciplines.”