| Date | Venue | Fees | |
|---|---|---|---|
| 21 - 25 Sep 2026 | Paris - France | $ 5,950 | |
| 21 - 25 Dec 2026 | London - UK | $ 5,950 | |
| 20 - 24 Sep 2027 | Paris - France | $ 5,950 | |
| 20 - 24 Dec 2027 | London - UK | $ 5,950 |
Introduction
This Agentic AI Governance and Control training course is designed for professionals responsible for governing autonomous AI systems that make or influence decisions with minimal human intervention. This Agentic AI Governance and Control training course provides the governance frameworks and practical oversight techniques required to establish accountability, manage risk, and ensure defensible decision-making in increasingly autonomous operational environments. As organisations adopt agentic AI technologies, clear governance structures become essential to maintaining transparency, regulatory compliance, and organisational confidence.
Throughout this training course, participants will examine how accountability, decision rights, escalation processes, and governance controls should be applied when AI systems operate with greater autonomy. The training course focuses on governance practices rather than technical system design, enabling participants to strengthen oversight, define ownership boundaries, and implement evidence-based governance processes. By developing practical judgement and structured governance discipline, participants will be better prepared to manage AI-enabled decisions that withstand internal review, audit scrutiny, and regulatory expectations.
This GLOMACS Agentic AI Governance and Control training course will highlight:
- Establishing accountability for autonomous AI systems
- Strengthening AI governance and oversight practices
- Managing AI-related risks and escalation
- Developing evidence-based governance controls
- Supporting defensible AI decision-making
Objectives
At the end of this Agentic AI Governance and Control training course, you will learn to:
- Define autonomous AI accountability boundaries
- Apply effective AI governance principles
- Analyse risks within agentic AI
- Establish robust escalation mechanisms
- Document defensible governance decisions
Training Methodology
This training course adopts a practical, scenario-based learning approach that combines facilitated discussions, governance case studies, applied exercises, and structured reflection. Participants will analyse realistic agentic AI governance situations, practise accountability mapping, evaluate escalation decisions, and strengthen oversight capabilities through interactive learning designed for immediate workplace application.
Organisational Impact
The Organisation will have the following benefits:
- Stronger AI governance frameworks
- Improved accountability across operations
- Enhanced regulatory readiness
- Reduced governance and control risks
- Better escalation decision consistency
- Greater confidence in AI oversight
Personal Impact
At the end of this Agentic AI Governance and Control training course, the participants will gain the following:
- Enhanced AI governance expertise
- Improved accountability judgement
- Stronger oversight decision-making
- Greater risk assessment capability
- Better escalation management skills
- Increased governance confidence
Who should Attend?
This training course is designed for professionals responsible for governing, overseeing, or supporting AI-enabled decision-making within their organisations. It is equally valuable for individuals seeking to strengthen governance practices, improve accountability, and enhance oversight of autonomous and semi-autonomous AI environments.
This GLOMACS Agentic AI Governance and Control training course is suitable to a wide range of professionals but will greatly benefit:
- Professionals accountable for AI-enabled processes or outcomes
- Leaders approving or overseeing autonomous or semi-autonomous AI decisions
- Governance, risk, compliance, and audit professionals
- Technology risk and operational oversight managers
- Senior managers responsible for escalation and accountability
- Professionals required to justify AI-related decisions and controls
- What agentic AI means from a governance perspective
- Where technical responsibility ends and governance accountability begins
- How autonomy changes decision ownership and accountability
- Common accountability failures in agentic AI deployments and their consequences
- Building an Agentic AI accountability and escalation map for your role
- Understanding AI related risk for non-technical decision-makers
- Operational, compliance, conduct and reputational risks from agentic systems
- Applying risk appetite and tolerance to autonomous decision-making
- Controls as management and governance responsibilities, not technical safeguards
- Applying risk awareness to a live agentic AI governance scenario
- Decision-making when authority is partially delegated to AI systems
- Trade-offs between autonomy, speed, oversight and escalation
- Managing uncertainty, exceptions and opaque AI behaviour
- Over-reliance on automated outputs and the myth of neutral systems
- Decision workshop: justify, evidence and defend AI governance choices
- Escalation judgement for agentic AI behaviour and outcomes
- Timing escalation correctly to avoid noise or exposure
- Communicating AI risks clearly without technical complexity
- Documentation standards for defensible AI governance and oversight
- Escalation role-play: raising AI governance concerns professionally
- Embedding agentic AI governance into daily oversight routines
- Oversight discipline for approvals, reviews and performance monitoring
- Identifying and eliminating governance shortcuts that create exposure
- Personal governance discipline for AI related decisions
- Individual action plans and implementation commitments
- Upon successful completion of this training course, GLOMACS Certificate will be awarded to the delegates. Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance
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