Training Module

AI System Scope, Lifecycle & Inventory

Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001

Training Module

AI System Scope, Lifecycle & Inventory

Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001

Training Module

AI System Scope, Lifecycle & Inventory

Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001

Abstract data streams and layered system timelines visualising the scope, lifecycle stages, and inventory of AI systems within a governed, traceable system landscape.

Are your AI system boundaries clearly defined and traceable?

Clear AI boundaries are the foundation of credible governance. This module shows how to define AI system scope, lifecycle limits, and a traceable inventory aligned with ISO/IEC 42001.

Abstract data streams and layered system timelines visualising the scope, lifecycle stages, and inventory of AI systems within a governed, traceable system landscape.

Are your AI system boundaries clearly defined and traceable?

Clear AI boundaries are the foundation of credible governance. This module shows how to define AI system scope, lifecycle limits, and a traceable inventory aligned with ISO/IEC 42001.

Abstract data streams and layered system timelines visualising the scope, lifecycle stages, and inventory of AI systems within a governed, traceable system landscape.

Are your AI system boundaries clearly defined and traceable?

Clear AI boundaries are the foundation of credible governance. This module shows how to define AI system scope, lifecycle limits, and a traceable inventory aligned with ISO/IEC 42001.

Training module overview

Training module overview

Training module overview

When AI capabilities are embedded across products and services, boundaries blur and inventories become unreliable. Without clear definitions, governance weakens and assurance findings follow.

This module establishes a structured approach to defining AI system boundaries, distinguishing management system scope from individual system scope, and setting meaningful lifecycle checkpoints. Participants learn how to design and maintain a traceable AI system inventory with clear ownership, defined metadata, and embedded update routines. The focus is on creating defensible traceability from system definition to risk, controls, and monitoring activities.

When AI capabilities are embedded across products and services, boundaries blur and inventories become unreliable. Without clear definitions, governance weakens and assurance findings follow.

This module establishes a structured approach to defining AI system boundaries, distinguishing management system scope from individual system scope, and setting meaningful lifecycle checkpoints. Participants learn how to design and maintain a traceable AI system inventory with clear ownership, defined metadata, and embedded update routines. The focus is on creating defensible traceability from system definition to risk, controls, and monitoring activities.

Applicable environments

This module applies to organisations implementing or operating a AI Management System (AIMS) in line with ISO/IEC 42001. It focuses on how the standard’s requirements are interpreted and applied in practice within real organisational contexts.

The content is relevant for organisations seeking certification as well as for those using ISO/IEC 42001 as a reference framework to structure responsibilities, processes, and controls in the AI management domain.

Target audience

Target audience

Target audience

  • People involved in designing, building, operating, or improving an AIMS aligned with ISO/IEC 42001

  • Executives and department heads accountable for the effectiveness and performance of an AIMS

  • Those responsible for processes, policies, applications, risks or risk controls related to AI

  • Auditors of ISO/IEC 42001 who want to deepen their understanding of management-side best practices (not audit technique)

  • People involved in designing, building, operating, or improving an AIMS aligned with ISO/IEC 42001

  • Executives and department heads accountable for the effectiveness and performance of an AIMS

  • Those responsible for processes, policies, applications, risks or risk controls related to AI

  • Auditors of ISO/IEC 42001 who want to deepen their understanding of management-side best practices (not audit technique)

Decision support

Is this module for you?

It is a good fit if you…

  • need a defensible definition of what counts as an “AI system” in your organisation.

  • struggle with fragmented AI use cases, pilots, embedded features, or vendor models.

  • need clear lifecycle boundaries to support governance, assurance, and audit.

  • want a maintained AI system inventory as a shared baseline for implementation and control.

  • support or review ISO/IEC 42001 scope, readiness, or effectiveness.

  • need a defensible definition of what counts as an “AI system” in your organisation.

  • struggle with fragmented AI use cases, pilots, embedded features, or vendor models.

  • need clear lifecycle boundaries to support governance, assurance, and audit.

  • want a maintained AI system inventory as a shared baseline for implementation and control.

  • support or review ISO/IEC 42001 scope, readiness, or effectiveness.

If most of the points above apply, this module is likely a good fit.

It may not be the best fit if you…

  • are looking for AI technical foundations or model behaviour concepts.

  • expect risk assessment, control design, or operational control methods.

  • want tooling, registers, or automation specifics rather than structure and logic.

  • already operate a complete, consistent AI system inventory with clear lifecycle ownership.

  • are looking for AI technical foundations or model behaviour concepts.

  • expect risk assessment, control design, or operational control methods.

  • want tooling, registers, or automation specifics rather than structure and logic.

  • already operate a complete, consistent AI system inventory with clear lifecycle ownership.

Agenda

Agenda

Agenda

  • What ISO/IEC 42001 needs from “scope” at the AI system level

  • Defining “AI system” consistently for inventory purposes

  • Lifecycle boundaries that matter for governance and assurance

  • Designing the AI system inventory

  • Inventory governance and maintenance routines

  • Using the inventory as a backbone for audit-ready implementation

  • Case-based workshop

Show detailed agenda...

  • What ISO/IEC 42001 needs from “scope” at the AI system level

  • Defining “AI system” consistently for inventory purposes

  • Lifecycle boundaries that matter for governance and assurance

  • Designing the AI system inventory

  • Inventory governance and maintenance routines

  • Using the inventory as a backbone for audit-ready implementation

  • Case-based workshop

Show detailed agenda...

  • What ISO/IEC 42001 needs from “scope” at the AI system level

  • Defining “AI system” consistently for inventory purposes

  • Lifecycle boundaries that matter for governance and assurance

  • Designing the AI system inventory

  • Inventory governance and maintenance routines

  • Using the inventory as a backbone for audit-ready implementation

  • Case-based workshop

Show detailed agenda...

Learning outcomes

Learning outcomes

Learning outcomes

Key outcomes

  • Apply criteria to identify AI systems and describe their purpose and operating context

  • Define lifecycle boundaries for AI systems, including development, deployment, maintenance and retirement

  • Build a maintained inventory of AI systems with minimum metadata and ownership assignments

  • Apply criteria to identify AI systems and describe their purpose and operating context

  • Define lifecycle boundaries for AI systems, including development, deployment, maintenance and retirement

  • Build a maintained inventory of AI systems with minimum metadata and ownership assignments

Additional capabilities

  • Distinguish between AIMS scope definition and AI system identification to avoid conflation

  • Design ownership, change and maintenance routines for the AI system inventory

  • Create traceability links from the inventory to risk assessments, impact/harm evaluations and operational control activities

  • Distinguish between AIMS scope definition and AI system identification to avoid conflation

  • Design ownership, change and maintenance routines for the AI system inventory

  • Create traceability links from the inventory to risk assessments, impact/harm evaluations and operational control activities

Additional benefits

Additional benefits

Additional benefits

Learning materials

  • Slide deck

  • Participant workbook

Templates & tools

Practical, reusable artefacts to apply the module directly to your organisation.

  1. AI system inventory management process

  2. AI system identification checklist

  3. AI system inventory register

  4. Lifecycle boundary and accountability canvas

  5. AI prompt set for AI system inventory management

  1. AI system inventory management process

  2. AI system identification checklist

  3. AI system inventory register

  4. Lifecycle boundary and accountability canvas

  5. AI prompt set for AI system inventory management

Confirmation

  • Certificate of completion

Module ID

HAM-AI-S-01

Audience

Auditor

Manager

Language

English

Delivery

Live virtual

Duration

7 h

List price

CHF 550

Excl. VAT. VAT may apply depending on customer location and status.

Delivery & learning format

Delivery & learning format

Delivery & learning format

Virtual live teaching

This module is delivered live, with a strong focus on discussion, practical application, and direct interaction with the instructor.

Sessions work through realistic examples, clarify concepts in context, and apply methods directly to participants’ organisational realities.

Custom delivery options

For organisations with specific constraints or learning objectives, the module can be adapted in format or scope, including in-house delivery and contextualised case material.

Not sure if this module is right for you?

Not sure if this module is right for you?

Not sure if this module is right for you?

Send a short message and describe your context.

For an optimal learning experience

Preparation guidance

This module is designed as part of a modular training approach. Topics are deliberately distributed across modules and are not repeated in full, in order to avoid unnecessary redundancy. Each module is self-contained and can be taken on its own. Where prior knowledge or experience is helpful, this is indicated below so you can decide whether any preparation is useful for you.

For an optimal learning experience

Preparation guidance

This module is designed as part of a modular training approach. Topics are deliberately distributed across modules and are not repeated in full, in order to avoid unnecessary redundancy. Each module is self-contained and can be taken on its own. Where prior knowledge or experience is helpful, this is indicated below so you can decide whether any preparation is useful for you.

For an optimal learning experience

Preparation guidance

This module is designed as part of a modular training approach. Topics are deliberately distributed across modules and are not repeated in full, in order to avoid unnecessary redundancy. Each module is self-contained and can be taken on its own. Where prior knowledge or experience is helpful, this is indicated below so you can decide whether any preparation is useful for you.

Assumed background

This module assumes general familiarity with management system implementation concepts and documented information discipline. Participants should also be comfortable with basic AI lifecycle terminology at a conceptual level (no technical depth required).

Helpful background includes:

  • Understanding of management system scope concepts and boundary thinking

  • Familiarity with registers, ownership, and change control as governance tools

  • Basic awareness of how AI-enabled capabilities are developed or sourced (build/buy/embedded)

This module assumes general familiarity with management system implementation concepts and documented information discipline. Participants should also be comfortable with basic AI lifecycle terminology at a conceptual level (no technical depth required).

Helpful background includes:

  • Understanding of management system scope concepts and boundary thinking

  • Familiarity with registers, ownership, and change control as governance tools

  • Basic awareness of how AI-enabled capabilities are developed or sourced (build/buy/embedded)

Preparatory modules

Foundational modules (depending on background)

Useful if you are new to the underlying concepts or want a shared baseline before attending this module.

AI Fundamentals I

Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services

7 h

AI Fundamentals I

Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services

7 h

AI Fundamentals I

Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services

7 h

Supporting modules (optional)

Helpful if you want to deepen related skills, but not required to participate effectively.

System Foundations

Understand organisational context, stakeholders, and system boundaries to build and operate effective management systems

7 h

System Foundations

Understand organisational context, stakeholders, and system boundaries to build and operate effective management systems

7 h

System Foundations

Understand organisational context, stakeholders, and system boundaries to build and operate effective management systems

7 h

Continuous learning

Follow-up modules

Continuous learning

Follow-up modules

Continuous learning

Follow-up modules

After completion of this module, the following modules are ideal to further deepen your competence. If you are looking for a structured learning path, modules can also be taken as part of a professional track.

Office scene with people standing, walking and sitting

Ready to improve your management systems?

We support continuous improvement by embedding ISO requirements into everyday practice and daily operations.

Office scene with people standing, walking and sitting

Ready to improve your management systems?

We support continuous improvement by embedding ISO requirements into everyday practice and daily operations.

Office scene with people standing, walking and sitting

Ready to improve your management systems?

We support continuous improvement by embedding ISO requirements into everyday practice and daily operations.