International / AI Management

ISO 42001

Artificial Intelligence Management System standard

⏱️ Estimated time: 30-60 minutes

What you'll receive:

  • Scored gap report showing your compliance level
  • AI-generated findings prioritized by severity (Critical, High, Medium, Low)
  • Actionable recommendations for each finding
  • Professional PDF report for leadership and auditors
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Overview

ISO/IEC 42001 is the world's first international standard for AI management systems. It provides requirements and guidance for establishing, implementing, maintaining, and continually improving an AI Management System (AIMS) within organizations. The standard addresses responsible development and use of AI systems, covering risk management, transparency, accountability, and ethical considerations.

Key Features

AI lifecycle management from design to decommissioning

Risk assessment and mitigation for AI systems

Data governance and quality requirements

Transparency and explainability controls

Bias detection and fairness testing

Human oversight and accountability mechanisms

Third-party certification available

Benefits

Demonstrates responsible AI governance

Reduces AI-related risks and liabilities

Builds trust with customers and regulators

Supports compliance with emerging AI regulations

Improves AI system quality and reliability

Facilitates ethical AI development

Competitive advantage in AI adoption

Who Should Use This Framework

Organizations developing AI systems

Companies deploying AI in operations

AI service providers and vendors

Organizations subject to AI regulations

Businesses using high-risk AI applications

Companies seeking AI certification

Sample Assessment Questions

Get a preview of the types of questions included in this assessment. Our comprehensive questionnaires help you identify gaps and strengthen your security posture.

1

Have you established an AI management system with defined scope and objectives?

2

Do you conduct risk assessments for all AI systems throughout their lifecycle?

3

Have you implemented data governance procedures to ensure AI training data quality?

4

Do you have processes to detect and mitigate bias in AI systems?

5

Have you documented the intended purpose and limitations of each AI system?

6

Do you maintain human oversight mechanisms for high-risk AI decisions?

7

Have you implemented transparency measures to explain AI system outputs?

8

Do you conduct regular testing and validation of AI system performance?

9

Do you have procedures for incident response and AI system failures?

10

Have you established accountability for AI system outcomes and impacts?

Note: These are just a few examples. The complete assessment includes comprehensive questions across all control areas, with AI-powered guidance to help you implement improvements.

Related Frameworks

ISO 27001
NIST AI RMF
EU AI Act
ISO 31000

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