Generative AI Leader
In this course, you will take a journey from a broad overview of gen AI to understanding how to leverage gen AI and Google Cloud for organizational transformation.
2 d
Fundamental
AGENTICAIGOVERNANCEESS
Agentic AI Governance Essentials Training
This course provides learners with the essential skills to govern the design, deployment, and scaling of autonomous, Agentic AI systems. It focuses on enabling rapid innovation and accelerating speed-to-market while managing the unique risks presented by AI systems that can make decisions without constant human input.
The course is structured around the practical application of the four-phase Agentic AI Governance Maturity Roadmap (Establish, Implement, Scale, Accelerate). It uses a blend of presentations, detailed case-study scenarios (Cymbal Health, Cymbal Insurance, etc.), group discussions, a tabletop exercise, and quizzes.
What you will learn
- Define Agentic AI and identify the key risk vectors unique to autonomous systems (e.g., opacity of logic and the accountability void).
- Establish the foundational structure, including a cross-functional AI governance committee and core ethical principles.
- Implement technical enforcement mechanisms, such as real-time audit logging (Decision Provenance Logs) and building in technical guardrails like the Human Veto Point (HVP).
- Scale governance enterprise-wide by standardizing tooling, establishing a centralized orchestration platform, and integrating controls into the CI/CD pipeline.
- Leverage governance as a competitive advantage by shifting from oversight to enablement and monetizing trust through external transparency.
Prerequisites
- None
Target audience
- Business leaders, Technical practitioners, Governance professionals
Training Program
6 modules to master the fundamentals
Objectives
- Define agentic AI and understand its governance implications.
Topics covered
- →Defining agentic AI
- →The governance gap
- →Agentic AI risk
- →Introduction to the governance maturity roadmap
Objectives
- Identify key risk vectors unique to autonomous AI systems.
- Establish accountability and oversight mechanisms.
Topics covered
- →Setting strategic vision and accountability
- →Business scenario: Cymbal Health
- →6 steps for the Establish phase
Activities
Group discussion
Objectives
- Implement governance frameworks for agentic AI deployments.
- Design controls that balance innovation with risk management.
Topics covered
- →Building technical enforcement
- →Business scenario: Cymbal Insurance
- →6 steps for the Implement phase
Activities
Group discussion
Objectives
- Establish accountability and oversight mechanisms at enterprise scale.
Topics covered
- →Embedding governance enterprise-wide
- →Business scenario: Cymbal Shops
- →5 steps for the Scale phase
Activities
Tabletop exercise
Objectives
- Design controls that balance innovation with risk management.
Topics covered
- →Leveraging governance for competitive advantage
- →Business scenario: Cymbal Fintech
- →5 steps for the Accelerate phase
Activities
Group discussion
Topics covered
- →Recap
- →Q&A
- →Quiz
- →Survey
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Upcoming sessions
No date suits you?
We regularly organize new sessions. Contact us to find out about upcoming dates or to schedule a session at a date of your choice.
Register for a custom dateQuality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
Teaching Methods Used
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Case Study — Analysis of a real or fictional business scenario to derive solutions.
- Group Discussion — Open exchange among peers and the instructor on a specific topic.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Frequently Asked Questions
No technical prerequisites are required. This training is designed for business leaders, technical practitioners, and governance professionals who need to understand the specific challenges of agentic AI.
It is designed for business leaders and decision-makers, technical practitioners, and governance and compliance professionals who need to oversee the deployment of autonomous AI systems in their organization.
The training uses detailed case-study scenarios including Cymbal Health, Cymbal Insurance, Cymbal Shops, and Cymbal Fintech. Each case illustrates a phase of the governance maturity roadmap.
It is a four-phase framework (Establish, Implement, Scale, Accelerate) that structures the progressive implementation of governance for autonomous AI systems, from foundations to competitive advantage.
The training covers Decision Provenance Logs (real-time audit logging), the Human Veto Point (HVP), technical guardrails, CI/CD pipeline control integration, and setting up a centralized orchestration platform.
Our training organizations SFEIR SAS and SFEIR-Est are Qualiopi certified for training activities, which allows you to request funding from your OPCO. Funding approval remains at your OPCO's discretion. Contact us for a quote.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote