Professional Track
Professional Track
AI Manager
Develop the capability to design, operate and continuously improve an AI Management System aligned with ISO/IEC 42001.
Manager
Artificial Intelligence
ISO/IEC 42001
Make AI a managed capability — not an unmanaged risk
Make AI a managed capability — not an unmanaged risk
By embedding governance, risk management and lifecycle controls into normal management processes, this track shows how AI systems can be deployed, monitored and improved responsibly over time.
By embedding governance, risk management and lifecycle controls into normal management processes, this track shows how AI systems can be deployed, monitored and improved responsibly over time.
By embedding governance, risk management and lifecycle controls into normal management processes, this track shows how AI systems can be deployed, monitored and improved responsibly over time.
Overview
The AI Management System Manager Track prepares participants to establish, maintain and continuously improve an AI Management System (AIMS) aligned with ISO/IEC 42001 and broader regulatory expectations for trustworthy and responsible AI.
The programme is designed for organisations deploying, developing or integrating AI systems and facing increasing demands for governance, risk management and lifecycle controls. It goes beyond standard interpretation and provides practical tools for managing AI-specific risks, data quality challenges, monitoring requirements and operational integration.
Through the Halderstone modular curriculum, participants learn how to:
analyse context, stakeholders, and regulatory drivers specific to AI systems,
establish governance, roles, policies and accountability structures for AI,
identify AI-specific risks and apply consistent risk assessment methods,
design lifecycle controls for data, models, deployment and monitoring,
ensure transparency, explainability and human oversight where needed,
integrate AI system management with existing management systems (ISMS, QMS, etc.),
monitor system behaviour in production and handle deviations,
and continuously improve AI systems and their oversight mechanisms.
Most modules are shared with other Halderstone manager tracks. AI-specific modules complement the shared foundations with the additional depth required for governing AI responsibly. A final assessment consolidates learning in an AIMS case scenario.
The AI Management System Manager Track prepares participants to establish, maintain and continuously improve an AI Management System (AIMS) aligned with ISO/IEC 42001 and broader regulatory expectations for trustworthy and responsible AI.
The programme is designed for organisations deploying, developing or integrating AI systems and facing increasing demands for governance, risk management and lifecycle controls. It goes beyond standard interpretation and provides practical tools for managing AI-specific risks, data quality challenges, monitoring requirements and operational integration.
Through the Halderstone modular curriculum, participants learn how to:
analyse context, stakeholders, and regulatory drivers specific to AI systems,
establish governance, roles, policies and accountability structures for AI,
identify AI-specific risks and apply consistent risk assessment methods,
design lifecycle controls for data, models, deployment and monitoring,
ensure transparency, explainability and human oversight where needed,
integrate AI system management with existing management systems (ISMS, QMS, etc.),
monitor system behaviour in production and handle deviations,
and continuously improve AI systems and their oversight mechanisms.
Most modules are shared with other Halderstone manager tracks. AI-specific modules complement the shared foundations with the additional depth required for governing AI responsibly. A final assessment consolidates learning in an AIMS case scenario.
Learning outcomes
After completing this track, participants will be able to:
Explain the purpose and value of an AI Management System (AIMS) in supporting safe and responsible AI.
Analyse context and stakeholders in an AI lifecycle, including regulatory, ethical and operational dimensions.
Establish governance structures, roles and policies that assign clear responsibilities for AI oversight.
Apply risk-based thinking to AI systems, focusing on data risks, model risks, bias, drift and system misuse.
Design lifecycle controls that address dataset quality, model documentation, testing, deployment and monitoring.
Integrate AI management practices with existing standards (e.g., ISO/IEC 27001, ISO 9001).
Build documentation and knowledge structures supporting transparency and accountability.
Define appropriate objectives and KPIs for AI performance, safety and effectiveness.
Monitor AI systems in operation, detect deviations and manage incidents.
After completing this track, participants will be able to:
Explain the purpose and value of an AI Management System (AIMS) in supporting safe and responsible AI.
Analyse context and stakeholders in an AI lifecycle, including regulatory, ethical and operational dimensions.
Establish governance structures, roles and policies that assign clear responsibilities for AI oversight.
Apply risk-based thinking to AI systems, focusing on data risks, model risks, bias, drift and system misuse.
Design lifecycle controls that address dataset quality, model documentation, testing, deployment and monitoring.
Integrate AI management practices with existing standards (e.g., ISO/IEC 27001, ISO 9001).
Build documentation and knowledge structures supporting transparency and accountability.
Define appropriate objectives and KPIs for AI performance, safety and effectiveness.
Monitor AI systems in operation, detect deviations and manage incidents.
Modular architecture
Two credentials with one track
Halderstone Professional Diploma in Management Systems
The Halderstone Professional Diploma in Management Systems certifies a solid, cross-domain foundation in designing, operating and improving management systems. It focuses on the common principles that apply across standards such as ISO 9001, ISO 14001, ISO/IEC 27001, ISO 22301 and ISO/IEC 42001.
The diploma demonstrates that you can analyse organisational context, establish governance and roles, apply risk-based thinking, define objectives and controls, evaluate performance and drive continual improvement. It confirms your ability to manage systems as living organisational capabilities, not as isolated compliance initiatives.
This core diploma is shared across all Halderstone Manager tracks and forms the basis for adding further domain specialisations efficiently.
The Halderstone Professional Diploma in Management Systems certifies a solid, cross-domain foundation in designing, operating and improving management systems. It focuses on the common principles that apply across standards such as ISO 9001, ISO 14001, ISO/IEC 27001, ISO 22301 and ISO/IEC 42001.
The diploma demonstrates that you can analyse organisational context, establish governance and roles, apply risk-based thinking, define objectives and controls, evaluate performance and drive continual improvement. It confirms your ability to manage systems as living organisational capabilities, not as isolated compliance initiatives.
This core diploma is shared across all Halderstone Manager tracks and forms the basis for adding further domain specialisations efficiently.
Halderstone Specialist Certificate in AI Management Systems
The AI Management Systems specialisation focuses on applying management system principles to the unique challenges of AI. Participants explore the AI lifecycle from data acquisition to model retirement, learning where governance and controls matter most.
The modules address risks such as bias, robustness, privacy leakage, model drift, inadequate testing, dependency on third-party models, and unsafe integration into business processes. Practical frameworks for transparency, explainability, dataset governance, continuous monitoring and human oversight are covered, along with approaches to meet emerging regulatory expectations and customer trust requirements.
The AI Management Systems specialisation focuses on applying management system principles to the unique challenges of AI. Participants explore the AI lifecycle from data acquisition to model retirement, learning where governance and controls matter most.
The modules address risks such as bias, robustness, privacy leakage, model drift, inadequate testing, dependency on third-party models, and unsafe integration into business processes. Practical frameworks for transparency, explainability, dataset governance, continuous monitoring and human oversight are covered, along with approaches to meet emerging regulatory expectations and customer trust requirements.
Modular architecture
Module recognition across tracks
Previously completed modules are recognized, avoiding duplication when pursuing additional Halderstone tracks.
Core Modules
Specialization Modules
Capstone Project
Final Exam
Core Modules
Specialization Modules
Capstone Project
Final Exam
Core Modules
Specialization Modules
Capstone Project
Final Exam
The AI Management System Manager Track shares most of its modules with other Halderstone manager programmes such as Quality, Information Security and Environmental Management. This allows participants to receive additional specialisation certificates with limited additional training.
For example, completing this track places participants close to earning the Information Security Management or Quality Management specialisation by attending only the relevant domain-specific modules. This modular approach supports development of integrated management system competence without doubling training effort.
Track composition
Track composition
Track composition
Full curriculum
Core modules
Shared foundations common to all tracks
System Foundations
Understand organisational context, stakeholders, and system boundaries
7 h
System Foundations
Understand organisational context, stakeholders, and system boundaries
7 h
System Foundations
Understand organisational context, stakeholders, and system boundaries
7 h
Leadership & Policy Foundations
Understand leadership responsibilities in management systems and how top management sets clear policy direction and accountability
7 h
Leadership & Policy Foundations
Understand leadership responsibilities in management systems and how top management sets clear policy direction and accountability
7 h
Leadership & Policy Foundations
Understand leadership responsibilities in management systems and how top management sets clear policy direction and accountability
7 h
Policy Management
Build a coherent, auditable policy framework that aligns with strategy, scales across entities, and stays current without bureaucracy.
7 h
Policy Management
Build a coherent, auditable policy framework that aligns with strategy, scales across entities, and stays current without bureaucracy.
7 h
Policy Management
Build a coherent, auditable policy framework that aligns with strategy, scales across entities, and stays current without bureaucracy.
7 h
Governance Foundations
Learn the fundamentals of role design, decision rights, governance mechanisms, and escalation paths in management systems
7 h
Governance Foundations
Learn the fundamentals of role design, decision rights, governance mechanisms, and escalation paths in management systems
7 h
Governance Foundations
Learn the fundamentals of role design, decision rights, governance mechanisms, and escalation paths in management systems
7 h
Resource Management Foundations
Learn the fundamentals of resourcing management systems across people, time, budget, infrastructure, and external support
7 h
Resource Management Foundations
Learn the fundamentals of resourcing management systems across people, time, budget, infrastructure, and external support
7 h
Resource Management Foundations
Learn the fundamentals of resourcing management systems across people, time, budget, infrastructure, and external support
7 h
Documentation & Knowledge Foundations
Fundamentals of documented information control, records, and knowledge capture for management systems
7 h
Documentation & Knowledge Foundations
Fundamentals of documented information control, records, and knowledge capture for management systems
7 h
Documentation & Knowledge Foundations
Fundamentals of documented information control, records, and knowledge capture for management systems
7 h
Risk Management Foundations
Learn the fundamentals of identifying, evaluating, treating, and monitoring risks and opportunities across management systems.
7 h
Risk Management Foundations
Learn the fundamentals of identifying, evaluating, treating, and monitoring risks and opportunities across management systems.
7 h
Risk Management Foundations
Learn the fundamentals of identifying, evaluating, treating, and monitoring risks and opportunities across management systems.
7 h
Objectives & Performance Foundations
Learn the fundamentals of objective setting, KPI definition, and KPI governance for management systems
7 h
Objectives & Performance Foundations
Learn the fundamentals of objective setting, KPI definition, and KPI governance for management systems
7 h
Objectives & Performance Foundations
Learn the fundamentals of objective setting, KPI definition, and KPI governance for management systems
7 h
Process Design Foundations
Learn the fundamentals of defining process boundaries, mapping flows and handovers, and embedding controls and required evidence into usable process documentation
7 h
Process Design Foundations
Learn the fundamentals of defining process boundaries, mapping flows and handovers, and embedding controls and required evidence into usable process documentation
7 h
Process Design Foundations
Learn the fundamentals of defining process boundaries, mapping flows and handovers, and embedding controls and required evidence into usable process documentation
7 h
People & Communication Foundations
Learn the fundamentals of competence planning, awareness building, and structured communication in management systems
7 h
People & Communication Foundations
Learn the fundamentals of competence planning, awareness building, and structured communication in management systems
7 h
People & Communication Foundations
Learn the fundamentals of competence planning, awareness building, and structured communication in management systems
7 h
Operational Control Foundations
Learn the fundamentals of designing and running controlled operational processes with clear roles, controls, records, and change handling.
7 h
Operational Control Foundations
Learn the fundamentals of designing and running controlled operational processes with clear roles, controls, records, and change handling.
7 h
Operational Control Foundations
Learn the fundamentals of designing and running controlled operational processes with clear roles, controls, records, and change handling.
7 h
Supplier Management Foundations
Learn the fundamentals of selecting, qualifying, and controlling suppliers and outsourced processes across their lifecycle
7 h
Supplier Management Foundations
Learn the fundamentals of selecting, qualifying, and controlling suppliers and outsourced processes across their lifecycle
7 h
Supplier Management Foundations
Learn the fundamentals of selecting, qualifying, and controlling suppliers and outsourced processes across their lifecycle
7 h
Monitoring & Measurement Foundations
Learn the fundamentals of measurement methods, data quality checks, and measurement registers for consistent performance data.
7 h
Monitoring & Measurement Foundations
Learn the fundamentals of measurement methods, data quality checks, and measurement registers for consistent performance data.
7 h
Monitoring & Measurement Foundations
Learn the fundamentals of measurement methods, data quality checks, and measurement registers for consistent performance data.
7 h
Performance Evaluation Foundations
Learn the fundamentals of analysing performance results, interpreting trends and deviations, and summarising evaluation outputs for management decisions
7 h
Performance Evaluation Foundations
Learn the fundamentals of analysing performance results, interpreting trends and deviations, and summarising evaluation outputs for management decisions
7 h
Performance Evaluation Foundations
Learn the fundamentals of analysing performance results, interpreting trends and deviations, and summarising evaluation outputs for management decisions
7 h
Internal Audit Foundations
Understand the purpose of internal audits, role responsibilities, independence expectations, and how audit results are used in governance and improvement
7 h
Internal Audit Foundations
Understand the purpose of internal audits, role responsibilities, independence expectations, and how audit results are used in governance and improvement
7 h
Internal Audit Foundations
Understand the purpose of internal audits, role responsibilities, independence expectations, and how audit results are used in governance and improvement
7 h
Management Review Foundations
Learn the fundamentals of planning, conducting, and documenting management reviews using integrated inputs and decision-focused outputs
7 h
Management Review Foundations
Learn the fundamentals of planning, conducting, and documenting management reviews using integrated inputs and decision-focused outputs
7 h
Management Review Foundations
Learn the fundamentals of planning, conducting, and documenting management reviews using integrated inputs and decision-focused outputs
7 h
Improvement Management
Understand corrective actions, root cause analysis, action tracking, and effectiveness verification in management systems
7 h
Improvement Management
Understand corrective actions, root cause analysis, action tracking, and effectiveness verification in management systems
7 h
Improvement Management
Understand corrective actions, root cause analysis, action tracking, and effectiveness verification in management systems
7 h
Specialization modules
Role-specific modules that deepen your expertise in AI Management
AI Fundamentals 1
Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services
7 h
AI Fundamentals 1
Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services
7 h
AI Fundamentals 1
Learn core AI concepts, AI system types, and the technical building blocks that underpin modern AI-enabled products and services
7 h
AI Fundamentals 2
Understand AI uncertainty, limitations, and common failure modes across predictive and generative AI systems
7 h
AI Fundamentals 2
Understand AI uncertainty, limitations, and common failure modes across predictive and generative AI systems
7 h
AI Fundamentals 2
Understand AI uncertainty, limitations, and common failure modes across predictive and generative AI systems
7 h
AI System Scope, Lifecycle & Inventory
Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001
7 h
AI System Scope, Lifecycle & Inventory
Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001
7 h
AI System Scope, Lifecycle & Inventory
Define AI system scope, lifecycle boundaries, and a maintained AI system inventory aligned to ISO/IEC 42001
7 h
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 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 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
Operational Control of AI Systems
Understand how to define, implement, and maintain operational controls for AI systems across deployment, change, and monitoring
7 h
Operational Control of AI Systems
Understand how to define, implement, and maintain operational controls for AI systems across deployment, change, and monitoring
7 h
Operational Control of AI Systems
Understand how to define, implement, and maintain operational controls for AI systems across deployment, change, and monitoring
7 h
Capstone project and final exam
Practical and theoretical demonstration of your acquired competence in AI Management
The programme concludes with:
a written exam covering AI-specific management system principles and cross-standard foundations, and
a capstone project in which participants develop or refine an AIMS for a selected AI use case or organisational context.
The project includes defining governance, assessing AI-specific risks, designing lifecycle controls, identifying monitoring requirements and planning improvements. Successful participants receive the Halderstone Professional Diploma in Management Systems Management and the Halderstone Specialist Certificate in AI Management Systems.
Continuous learning
Other tracks
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.