Overview
The ISO 42001 Foundation program introduces core principles & practices for establishing & managing an Artificial Intelligence Management System (AIMS). The training program provides a solid grounding in the standard’s structure & intent, preparing audience to contribute to AI strategy & governance.
The training program equips audience with both conceptual knowledge & operational awareness to support or contribute to the design, implementation, or audit of an AI management system aligned with ISO 42001.
The training program is an ideal starting point for professionals aiming to specialize in AI governance & compliance.
Objectives
- Fundamental concepts of AI governance & management systems, including definition & purpose of an AIMS.
- Standard requirements describing the main requirements of ISO/IEC 42001 for establishing, operating & improving an AI management system.
- Implementation techniques identifying approaches for risk assessment, AI impact analysis, & control selection
- Understanding how to integrate AI risk management & regulatory requirements into organizational processes to ensure responsible AI uses.
Key Training Takeaways
- Understanding of ISO/IEC 42001 and Its Purpose
- AI Management System (AIMS) Fundamentals
- Governance, Roles & Responsibilities in AI
- Risk & Opportunity Management for AI
- AI Lifecycle & Operational Controls
- Cross-Functional Relevance
Who should attend?
AI developers, product managers, data scientists, technical staff, risk managers, legal/compliance officers, internal auditors, Senior Management, Board Members, Strategic Decision Makers.
Syllabus
Module 1: Building a case for AI Governance
- Define what AI is?
- AI systems & lifecycle stages
- Bias, explainability, data quality, ethical risks & fairness, adversarial attacks
Module 2: Real-world AI Systems
Scenario 1
- Retail company using AI chatbots and recommendations
- Retailer’s AI system (chatbots / recommendations) bias & oversight
Scenario 2
- Company’s AI hiring tool shows unfair bias where the training data skewed results
- AI recruiting tool that showed bias against women
Scenario 3
- An image-recognition AI makes an offensive error
Module 3: Why ISO 42001 Matters to AI Practitioners
- Overview of ISO 42001
- Its role in the AI ecosystem
- Structure & components
- AI risk management lifecycle
Scenario 1
- Real-world AI system failures & harms
Scenario 2
- Ethical, legal & technical considerations
Module 4: Core Requirements of ISO 42001
- Clause 4: Understanding the AIMS context
- Clause 5: AI governance, roles & responsibilities
- Clause 6: AI risk assessments & opportunities
- Clause 7: Competence, communication & documentation
- Clause 8: Operational AI controls (data, monitoring, impact assessment)
- Clause 9: Audits, monitoring & KPIs
- Clause 10: Nonconformity handling & improvement
- Implementation risks
- Core & essential documentation
- Core & essential roles
- Core & essential activities
- AI Governance
- Mapping ISO 42001 with EU AI act
Module 6: Future of AI
- Possible societal impact
- New & emerging roles, Redundant roles
- Sector-specific impact – BFSI / Retail / Healthcare / IT Services / Logistics
Training Handouts
- ISO 42001 clauses
- Documentation list
- Activity list
- ISO & EU AI Act mapping
- Implementation risks
- Quiz program
