Course : AI Governance Framework Foundation, Preparation for APMG Certification

Course Materials in English

Practical course - 3d - 21h00 - Ref. APG
Price : 2010 € E.T.

AI Governance Framework Foundation, Preparation for APMG Certification

Course Materials in English


New course

This training course prepares participants for the AIPGF Foundation (APMG) certification and provides a structured understanding of the governance of “AI-assisted” projects: why traditional project management approaches are insufficient, what risks (ethical, legal, data, and security) arise, and how the AIPGF framework provides a layer of governance for ethical, efficient, and effective human-AI collaboration.


INTER
IN-HOUSE
CUSTOM

Practical course in person or remote class
Disponible en anglais, à la demande

Ref. APG
  3d - 21h00
2010 € E.T.
En option :
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Certification : 300 € H.T.




This training course prepares participants for the AIPGF Foundation (APMG) certification and provides a structured understanding of the governance of “AI-assisted” projects: why traditional project management approaches are insufficient, what risks (ethical, legal, data, and security) arise, and how the AIPGF framework provides a layer of governance for ethical, efficient, and effective human-AI collaboration.


Teaching objectives
At the end of the training, the participant will be able to:
Explain the purpose, scope, and key terms of the AIPGF framework
Identify the main ethical and legal issues related to the use of AI in project management
Present the AIPGF framework (life cycle stages, elements, and relationships) and the “method vs. mindset” distinction
Describe the key roles and responsibilities for effective AI governance in a project environment
Explain the three AIPGF principles, values, and behaviors, and their role in guiding human-AI collaboration
Explain the three stages of the AIPGF life cycle (Foundation, Activation, Evaluation) and the associated objectives, activities, and deliverables

Intended audience
Portfolio managers and PMO staff, sponsors and steering committees, project managers and coordinators, as well as professionals in governance, risk management, compliance, auditing, legal affairs, and digital transformation.

Prerequisites
Basic knowledge of project management; practical experience with the use of AI in a project context is a plus.

Course schedule

1
Introduction to the AIPGF

  • The Need for Governance in “AI-Assisted” Projects.
  • Objectives of the framework.
  • Terminology.
  • “Ethical / Efficient / Effective” Scope.
  • Applicability and scalability.

2
Artificial Intelligence in Project Management

  • Rule: Human-in-the-Loop (HITL).
  • Differences Between AI and Traditional Computing.
  • AI disciplines useful for managing projects.
  • The Evolving Role of AI in Project Management.
  • Challenges Associated with the Use of AI.
  • Security, Ethical, and Legal Implications.

3
Overview of the AIPGF Structure

  • The stages of the life cycle.
  • Mindset: Principles, Values, and Behaviors.
  • The Method: Activities and Deliverables.
  • Integration with existing approaches.
Exercise
Summary + practical exercises for reinforcement.

4
Roles and Responsibilities

  • Key roles: project sponsor, project manager, data owner, steering committee.
  • The role of "AI Ethics Advisor."
  • The project team.
  • Additional roles.
  • Flexible allocation strategies based on size and risk.
  • Stakeholder mapping.
  • Building AI Governance Teams.

5
The AIPGF Principles

  • People-centered.
  • Transparency.
  • Adaptation.
  • Principles in Practice.

6
AIPGF's Values

  • Empowerment.
  • Sensitivity.
  • Collaboration.
  • Curiosity.
  • Continuous improvement.

7
AIPGF Behaviors

  • Behaviors associated with the 5 values.
  • Adaptation to the project/organizational context.
Exercise
Case Study (Guided Discussion).

8
The Stages of the AIPGF Life Cycle

  • Foundation: Defining the scope of AI support, objectives, tool selection, data readiness, risk identification and management, and deliverables.
  • Implementation: putting the plan into operation, monitoring and controlling AI usage, managing AI incidents and issues, reporting on usage, and updating risk assessments.
  • Evaluation: Assess the impact of AI, leverage feedback, and improve human-AI collaboration.
Exercise
Create an “Activities & Deliverables” checklist tailored to a specific scenario.

9
Preparation for the Foundation Exam

  • Case Study (Application and Discussion).
  • Foundation Exam Prep + Mock Exam (mock/sample exam).


Options
Certification : 300 € H.T.


This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.

Dates and locations
Select your location or opt for the remote class then choose your date.
Remote class

Dernières places
Date garantie en présentiel ou à distance
Session garantie

REMOTE CLASS
2026 : 30 Nov.

2027 : 17 Mar., 12 May, 16 June, 25 Aug., 8 Nov., 13 Dec.

PARIS LA DÉFENSE
2027 : 17 Mar., 12 May, 16 June, 25 Aug., 8 Nov., 13 Dec.



This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.