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

Exam Code:
ISO-IEC-42001-Lead-Auditor
Exam Name:
ISO/IEC 42001:2023 Artificial Intelligence Management System Lead Auditor Exam
Vendor:
Questions:
198
Last Updated:
May 18, 2026
Exam Status:
Stable
PECB ISO-IEC-42001-Lead-Auditor

ISO-IEC-42001-Lead-Auditor: AI management system (AIMS) Exam 2025 Study Guide Pdf and Test Engine

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ISO/IEC 42001:2023 Artificial Intelligence Management System Lead Auditor Exam Questions and Answers

Question 1

According to Scenario 8, Sharona played a vital role in the certification decision. Is this acceptable?

Scenario 8: VeridicAI. based in San Francisco. USA, specializes in market research using Al technologies to analyze customer behavior. Founded in 2023, the company

employs natural language processing, machine learning, and predictive analytics to provide real time insights to a range of businesses. VeridicAI has implemented an

artificial intelligence management system AIMS based on ISO/IEC 42001 to manage its Al technologies effectively. The AIMS scope includes select departments within

the company, for which it has received a four-year certification against ISO/IEC 42001. Committed to transparency. VeridicAI publicly shares details of this certification.

As the certification nears its end, VeridicAI is preparing for an audit to renew its certification.

The audit process was led by Sharona, the audit team leader, who is a full-time employee of the certification body. Sharona and the audit team undertook all planned

audit activities. Afterward, they organized the closing meeting with VeridicAl’s management. During the meeting, Sharona and the team made a recap on audit

objectives and scope, presented the audit findings and conclusions, presented identified nonconformities, and organized a session for questions and answers for the

auditee.

VeridicAI received a conditional recommendation for certification, underscoring its compliance with the industry's standards. Sharona confirmed that the company met

the essential requirements but noted some identified minor nonconformities. In response, VeridicAI compiled and submitted a comprehensive action plan that

addresses all identified nonconformities within a designated timeframe. Because of the comprehensive action plan, Sharona did not see the need for an additional on-

site visit to verify the effectiveness of the action plan.

Sharona played an integral role in the certification decision process. Her thorough understanding of VeridicAI's operations, gained from the audit, guided the

certification body towards a well-informed certification decision.

Options:

A.

Yes, because Sharona is a full-time employee of the certification body

B.

Yes, all auditors who participate in the audit can take part in the certification decision

C.

No, only the certification body has the authority to make the certification decision

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Question 2

The certification body did not include all departments covered by the AIMS scope in the audit scope. Is this acceptable? Refer to Scenario 5.

Scenario 5: Alterhealth is a mid-sized technology firm based in Toronto. Canada. It develops Al systems for healthcare providers, focusing on improving patient care,

optimizing hospital workflows, and analyzing healthcare data for insights that can improve health outcomes. To ensure responsible and effective use of Al in its

operations, Alterhealth has implemented an artificial intelligence management system AIMS based on ISO/IEC 42001. After a year of having the AIMS in place, the

company decided to apply for a certification audit to obtain certification against ISO/IEC 42001.

The company contracted a certification body to conduct the audit, who assembled the audit team and appointed the audit team leader. The audit team leader had

conducted a certification audit at Alterhealth in the past. The top management of Alterhealth decided to reject the appointment of this auditor because they believed

that they would not receive added value from the audit. In response, the certification body appointed Jonathan, an independent auditor with no prior engagements with

Alterhealth, as the new audit team leader. Jonathan's introduction marked the beginning of a collaborative process aimed at evaluating the conformity of the AIMS to

ISO/IEC 42001 requirements.

The certification body determined the audit scope, which included only specific departments essential to the integration and application of Al, such as the Al Research,

Machine Learning Applications, and Al Ethics and Compliance Departments, and did not cover all of the departments covered by the AIMS scope. Meanwhile,

Alterhealth determined the audit time, setting the necessary time frame for planning and conducting a thorough and effective review to ensure all aspects of the AIMS

within the selected departments were meticulously reviewed.

Afterward, Jonathan received a detailed offer from the certification body, outlining his role and including information related to the audit, such as the audit's duration,

team members, their responsibilities, the limits to the audit engagement, and their salary compensation. With a clear mandate, Jonathan was tasked with a multitude

of responsibilities: defining the audit objectives and criteria, planning the audit process, identifying and addressing audit risks, managing communication with

Alterhealth, overseeing the audit team, and ensuring a smooth and conflict free execution.

With Jonathan's leadership and a well-defined audit framework in place, the certification audit proceeded with a structured and objective evaluation of Alterhealth's

AIMS.

Options:

A.

No, the audit scope must include all of the auditee's departments part of the AIMS scope

B.

No, the audit scope must cover all of the auditee's departments regardless of whether they are included in the AIMS scope

C.

Yes, the audit scope does not necessarily include all of the auditee's departments covered by the AIMS scope

D.

Yes, if it is a Stage 1 audit only

Question 3

Based on Scenario 1, which AI principle did NeuraGen fail to apply?

Scenario: NeuraGen, founded by a team of AI experts and data scientists, has gained attention for its advanced use of artificial intelligence. It specializes in developing personalized learning platforms powered by AI algorithms. MindMeld, its innovative product, is an educational platform that uses machine learning and stands out by learning from both labeled and unlabeled data during its training process. This approach allows MindMeld to use a wide range of educational content and personalize learning experiences with exceptional accuracy. Furthermore, MindMeld employs an advanced AI system capable of handling a wide variety of tasks, consistently delivering a satisfactory level of performance. This approach improves the effectiveness of educational materials and adapts to different learners' needs.

NeuraGen skillfully handles data management and AI system development, particularly for MindMeld. Initially, NeuraGen sources data from a diverse array of origins, examining patterns, relationships, trends, and anomalies. This data is then refined and formatted for compatibility with MindMeld, ensuring that any irrelevant or extraneous information is systematically eliminated. Following this, values are adjusted to a unified scale to facilitate mathematical comparability. A crucial step in this process is the rigorous removal of all personally identifiable information (PII) to protect individual privacy. Finally, the data is subjected to quality checks to assess its completeness, identify any potential bias, and evaluate other factors that could impact the platform's efficacy and reliability.

NeuraGen has implemented an advanced artificial intelligence management system (AIMS) based on ISO/IEC 42001 to support its efforts in AI-driven education. This system provides a framework for managing the life cycle of AI projects, ensuring that development and deployment are guided by ethical standards and best practices.

NeuraGen's top management is key to running the AIMS effectively. Applying an international standard that specifically provides guidance for the highest level of company leadership on governing the effective use of AI, they embed ethical principles such as fairness, transparency, and accountability directly into their strategic operations and decision-making processes.

While the company excels in ensuring fairness, transparency, reliability, safety, and privacy in its AI applications, actively preventing bias, fostering a clear understanding of AI decisions, guaranteeing system dependability, and protecting user data, it struggles to clearly define who is responsible for the development, deployment, and outcomes of its AI systems. Consequently, it becomes difficult to determine responsibility when issues arise, which undermines trust and accountability, both critical for the integrity and success of AI initiatives.

Options:

A.

Fairness

B.

Transparency

C.

Accountability