Training Module
Training Module
Operational Control of AI Systems
Understand how to define, implement, and maintain operational controls for AI systems across deployment, change, and monitoring
Understand
Implement
Manage
Audit
Training module overview
Operational control is where an AI management system becomes real: requirements and risk decisions are translated into consistent practices for development, deployment, use, and change. Without this, organisations rely on informal heroics, approvals become fragile, and monitoring becomes reactive.
This ISO/IEC 42001 specialisation module focuses on operational control expectations for AI systems and typical control artefacts and routines. It assumes that AI system scope and inventory exist, and that risk/impact/harm assessments and generic operational control methods are handled in their respective modules; this module applies those inputs to ISO/IEC 42001 implementation and audit-ready evidence.
Operational control is where an AI management system becomes real: requirements and risk decisions are translated into consistent practices for development, deployment, use, and change. Without this, organisations rely on informal heroics, approvals become fragile, and monitoring becomes reactive.
This ISO/IEC 42001 specialisation module focuses on operational control expectations for AI systems and typical control artefacts and routines. It assumes that AI system scope and inventory exist, and that risk/impact/harm assessments and generic operational control methods are handled in their respective modules; this module applies those inputs to ISO/IEC 42001 implementation and audit-ready evidence.
Target audience
AI management system managers and implementers (ISO/IEC 42001)
AI product/service owners accountable for deployment and operation decisions
Control owners responsible for operational procedures, change, and monitoring
Risk/compliance staff supporting operationalisation of AI requirements (method assumed elsewhere)
Internal auditors reviewing operational control design and effectiveness (without audit craft training)
AI management system managers and implementers (ISO/IEC 42001)
AI product/service owners accountable for deployment and operation decisions
Control owners responsible for operational procedures, change, and monitoring
Risk/compliance staff supporting operationalisation of AI requirements (method assumed elsewhere)
Internal auditors reviewing operational control design and effectiveness (without audit craft training)
Agenda
Operational control in an ISO/IEC 42001 AI management system
What “operational control” means for AI systems (in practice, not slogans)
Interfaces to scope/inventory and to risk/impact/harm decisions (inputs, not re-taught)
Defining operational control requirements per AI system and use context
Control objectives and constraints derived from approvals and risk acceptance
Minimum control set vs. proportional tailoring (without inventing new risk scoring)
Lifecycle control points: build, deploy, use, and monitor
Control points for data, model, and deployment artefacts (traceable, auditable)
Operational routines for monitoring, issue handling, and usage conditions
Change and release discipline for AI systems
Versioning, re-approval triggers, and controlled rollout patterns
Maintaining traceability across updates (what changed, why, who approved)
Operational roles, responsibilities, and competence in AI control
Clear ownership for controls, exceptions, and escalations
Awareness and handovers across teams (implementation-facing, not HR frameworks)
Documented information and evidence for operational control
Minimum viable evidence: procedures, logs, approvals, and review records
Avoiding “paper controls”: common gaps that fail in readiness reviews
Workshop (case-based)
Design an operational control pack for a provided AI system scenario
Peer review for completeness, traceability, and maintainability (case-based, not organisation-specific)
Operational control in an ISO/IEC 42001 AI management system
What “operational control” means for AI systems (in practice, not slogans)
Interfaces to scope/inventory and to risk/impact/harm decisions (inputs, not re-taught)
Defining operational control requirements per AI system and use context
Control objectives and constraints derived from approvals and risk acceptance
Minimum control set vs. proportional tailoring (without inventing new risk scoring)
Lifecycle control points: build, deploy, use, and monitor
Control points for data, model, and deployment artefacts (traceable, auditable)
Operational routines for monitoring, issue handling, and usage conditions
Change and release discipline for AI systems
Versioning, re-approval triggers, and controlled rollout patterns
Maintaining traceability across updates (what changed, why, who approved)
Operational roles, responsibilities, and competence in AI control
Clear ownership for controls, exceptions, and escalations
Awareness and handovers across teams (implementation-facing, not HR frameworks)
Documented information and evidence for operational control
Minimum viable evidence: procedures, logs, approvals, and review records
Avoiding “paper controls”: common gaps that fail in readiness reviews
Workshop (case-based)
Design an operational control pack for a provided AI system scenario
Peer review for completeness, traceability, and maintainability (case-based, not organisation-specific)
Course ID:
HAM-OCAI-1
Audience:
Auditor
Manager
Domain:
Artificial Intelligence
Available in:
English
Duration:
7 h
List price:
CHF 550
Excl. VAT. VAT may apply depending on customer location and status.
What you get
Learning outcomes
Translate ISO/IEC 42001 operational control expectations into practical lifecycle control points for AI systems
Define a proportionate operational control set per AI system/use context, using existing scope/inventory and risk decision inputs (not redoing them)
Establish change and release practices that make AI system updates auditable and governable
Specify roles, responsibilities, and escalation points that keep controls owned and usable in daily operations
Identify the minimum evidence needed to demonstrate operational control design and effectiveness without over-documenting
Recognise typical “paper control” patterns and operational gaps that drive repeat issues and weak assurance outcomes
Translate ISO/IEC 42001 operational control expectations into practical lifecycle control points for AI systems
Define a proportionate operational control set per AI system/use context, using existing scope/inventory and risk decision inputs (not redoing them)
Establish change and release practices that make AI system updates auditable and governable
Specify roles, responsibilities, and escalation points that keep controls owned and usable in daily operations
Identify the minimum evidence needed to demonstrate operational control design and effectiveness without over-documenting
Recognise typical “paper control” patterns and operational gaps that drive repeat issues and weak assurance outcomes
Learning materials
Slide deck
Participant workbook
Certificate of completion
Slide deck
Participant workbook
Certificate of completion
Templates & tools
AI Operational Control Pack (per-system checklist of required procedures, owners, and evidence)
Lifecycle Control Points Map (data → training → deployment → monitoring, as control gates)
AI Change & Release Checklist (versioning, approvals, rollback readiness, comms)
Re-approval Trigger Log (changes/events that require review and decision)
Operational Monitoring Review Log (monitoring signals, review cadence, actions)
Exception & Escalation Record (temporary deviations, compensating actions, approvals)
AI prompt set for drafting control procedures and summarising evidence (supporting, not replacing judgement)
AI Operational Control Pack (per-system checklist of required procedures, owners, and evidence)
Lifecycle Control Points Map (data → training → deployment → monitoring, as control gates)
AI Change & Release Checklist (versioning, approvals, rollback readiness, comms)
Re-approval Trigger Log (changes/events that require review and decision)
Operational Monitoring Review Log (monitoring signals, review cadence, actions)
Exception & Escalation Record (temporary deviations, compensating actions, approvals)
AI prompt set for drafting control procedures and summarising evidence (supporting, not replacing judgement)
Prerequisites
This module assumes participants can work within a management system and can interpret operational responsibilities and evidence requirements.
Helpful background includes:
Basic understanding of management system roles, procedures, and documented information
Familiarity with how risk decisions and approvals create operational constraints (method assumed elsewhere)
Practical understanding of AI lifecycle artefacts and monitoring concepts (concepts covered in AI Foundations modules, not re-taught)
This module assumes participants can work within a management system and can interpret operational responsibilities and evidence requirements.
Helpful background includes:
Basic understanding of management system roles, procedures, and documented information
Familiarity with how risk decisions and approvals create operational constraints (method assumed elsewhere)
Practical understanding of AI lifecycle artefacts and monitoring concepts (concepts covered in AI Foundations modules, not re-taught)
Strongly recommended preparatory modules
Objectives & Performance Foundations: Objective Setting and KPI Design
Learn the fundamentals of objective setting, KPI definition, and KPI governance for management systems
7 h
Objectives & Performance Foundations: Objective Setting and KPI Design
Learn the fundamentals of objective setting, KPI definition, and KPI governance for management systems
7 h
Objectives & Performance Foundations: Objective Setting and KPI Design
Learn the fundamentals of objective setting, KPI definition, and KPI governance for management systems
7 h
Operational Control Foundations: Translating Plans into Controlled, Repeatable Processes
Learn the fundamentals of designing and running controlled operational processes with clear roles, controls, records, and change handling.
7 h
Operational Control Foundations: Translating Plans into Controlled, Repeatable Processes
Learn the fundamentals of designing and running controlled operational processes with clear roles, controls, records, and change handling.
7 h
Operational Control Foundations: Translating Plans into Controlled, Repeatable Processes
Learn the fundamentals of designing and running controlled operational processes with clear roles, controls, records, and change handling.
7 h
ISO/IEC 42001: AI Risk, Impact & Harm Assessment
Understand how to assess AI impacts and harms, document results, and connect them to risk decisions in an AI management system
7 h
ISO/IEC 42001: AI Risk, Impact & Harm Assessment
Understand how to assess AI impacts and harms, document results, and connect them to risk decisions in an AI management system
7 h
ISO/IEC 42001: AI Risk, Impact & Harm Assessment
Understand how to assess AI impacts and harms, document results, and connect them to risk decisions in an AI management system
7 h
AI System Scope, Lifecycle & Inventory (ISO/IEC 42001)
Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001
7 h
AI System Scope, Lifecycle & Inventory (ISO/IEC 42001)
Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001
7 h
AI System Scope, Lifecycle & Inventory (ISO/IEC 42001)
Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001
7 h
Governance Foundations: Role Design, Decision Rights, and Escalation in Management Systems
Learn the fundamentals of role design, decision rights, governance mechanisms, and escalation paths in management systems
7 h
Governance Foundations: Role Design, Decision Rights, and Escalation in Management Systems
Learn the fundamentals of role design, decision rights, governance mechanisms, and escalation paths in management systems
7 h
Governance Foundations: Role Design, Decision Rights, and Escalation in Management Systems
Learn the fundamentals of role design, decision rights, governance mechanisms, and escalation paths in management systems
7 h
Helpful preparatory modules
The modules below prepare for an optimal learning experience – but are not strictly necessary for participants to follow.
AI Foundations I: AI Concepts & System Types
Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services
7 h
AI Foundations I: AI Concepts & System Types
Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services
7 h
AI Foundations I: AI Concepts & System Types
Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services
7 h
AI Foundations II: AI Limitations, Uncertainty & Failure Modes
Understand AI uncertainty, limitations, and common failure modes across predictive and generative AI systems
7 h
AI Foundations II: AI Limitations, Uncertainty & Failure Modes
Understand AI uncertainty, limitations, and common failure modes across predictive and generative AI systems
7 h
AI Foundations II: AI Limitations, Uncertainty & Failure Modes
Understand AI uncertainty, limitations, and common failure modes across predictive and generative AI systems
7 h
Documentation & Knowledge Foundations: Documented Information, Records, and Organisational Knowledge
Fundamentals of documented information control, records, and knowledge capture for management systems
7 h
Documentation & Knowledge Foundations: Documented Information, Records, and Organisational Knowledge
Fundamentals of documented information control, records, and knowledge capture for management systems
7 h
Documentation & Knowledge Foundations: Documented Information, Records, and Organisational Knowledge
Fundamentals of documented information control, records, and knowledge capture for management systems
7 h
People & Communication Foundations: Building Competence, Awareness, and Communication
Learn the fundamentals of competence planning, awareness building, and structured communication in management systems
7 h
People & Communication Foundations: Building Competence, Awareness, and Communication
Learn the fundamentals of competence planning, awareness building, and structured communication in management systems
7 h
People & Communication Foundations: Building Competence, Awareness, and Communication
Learn the fundamentals of competence planning, awareness building, and structured communication in management systems
7 h
Continuous learning
Follow-up modules
Follow-up modules
After completion of this module, the following modules are ideal to further deepen the participant's competence.
After completion of this module, the following modules are ideal to further deepen the participant's competence.
Ready to achieve mastery?
Bring ISO requirements into everyday practice to reduce avoidable issues and strengthen the trust of your customers and stakeholders.
Ready to achieve mastery?
Bring ISO requirements into everyday practice to reduce avoidable issues and strengthen the trust of your customers and stakeholders.
Ready to achieve mastery?
Bring ISO requirements into everyday practice to reduce avoidable issues and strengthen the trust of your customers and stakeholders.