Governance, Risk & Compliance
ISO/IEC 42001 AI Management System Implementation
This in-depth course develops directly applicable capability in ISO/IEC 42001 AI Management System Implementation. It connects AI Management System Context, AI Risk and Impact Assessment, and Lifecycle Controls and Documentation to the decisions, controls, and activities participants need to perform in their workplace.
Overview
Practical learning for workplace transfer.
This in-depth course develops directly applicable capability in ISO/IEC 42001 AI Management System Implementation. It connects AI Management System Context, AI Risk and Impact Assessment, and Lifecycle Controls and Documentation to the decisions, controls, and activities participants need to perform in their workplace. The five-module curriculum progresses toward AIMS Implementation Workshop, using evidence, scenarios, and work products appropriate to the subject.
Prerequisites
Relevant workplace familiarity is recommended; exact technical prerequisites can be adapted to the participant group.
Objectives
- Analyze ai management system context, including organizational context, interested parties, scope, and ai system inventory.
- Configure or structure ai risk and impact assessment, including use context, affected parties, intended purpose, and foreseeable misuse.
- Evaluate lifecycle controls and documentation, including data, models, suppliers, development, validation, deployment, monitoring, and retirement.
- Manage performance evaluation and improvement, including objectives, metrics, internal audit, management review, and corrective action.
- Apply aims implementation workshop, including define scope and ai inventory.
Target audience
- Professionals responsible for this subject area
- Managers, supervisors, and team leaders
- Analysts, specialists, engineers, or coordinators working with the relevant processes
- Project, implementation, assurance, or improvement team members
- Professionals preparing for broader responsibilities in this field
Program outline
A clear structure for the learning journey.
Outline points are grouped in one designed block instead of being treated as separate module cards.
01AI Management System Context3 topics
- Organizational context, interested parties, scope, and AI system inventory
- Leadership policy, roles, accountability, and resources
- Integrate with existing risk and management systems
02AI Risk and Impact Assessment3 topics
- Use context, affected parties, intended purpose, and foreseeable misuse
- Risk criteria, treatment, residual risk, and approval
- Impact assessment across lifecycle changes
03Lifecycle Controls and Documentation3 topics
- Data, models, suppliers, development, validation, deployment, monitoring, and retirement
- Human oversight, transparency, security, and incident controls
- Documented information and evidence ownership
04Performance Evaluation and Improvement3 topics
- Objectives, metrics, internal audit, management review, and corrective action
- Nonconformity, incident, feedback, and continual improvement
- Certification-readiness boundaries without promising certification
05AIMS Implementation Workshop3 topics
- Define scope and AI inventory
- Build risk, control, and evidence mappings
- Prepare a phased implementation roadmap
Materials provided
- ○ Course-specific presentation slides
- ○ Guided exercises, scenarios, or configured-environment activities appropriate to the subject
- ○ Course-specific worksheets, checklists, or calculation templates
- ○ Applied workplace case materials
- ○ 4D Certificate of Completion issued by 4D Training & Consultancy
- ○ Post-course support for implementation questions
Training Options
Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.
Why choose 4D
4D Training & Consultancy adapts the program to the client’s operating environment. Delivery combines structured explanation with subject-specific analysis, exercises, and implementation decisions so participants can transfer the learning to real responsibilities without implying vendor authorization.
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