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ART25

AI Governance Professional Training

Executive training for AI governance, risk, and regulatory implementation

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Practical, operational AI governance

A practical training focused on operational AI governance for senior professionals navigating AI risk, regulation, and lifecycle responsibilities. Not a technical AI engineering course or certification exam preparation.

The focus is on understanding AI risk, regulatory expectations, lifecycle governance, supplier oversight, accountability, and how to translate AI governance into operational controls across organisations.

Who it is for

  • 01Data Protection Officers, CISOs, and GRC professionals
  • 02Public sector bodies, data protection authorities, and accreditation bodies
  • 03AI developers, software engineers, and technical teams
  • 04Startups and scale-ups building AI solutions

A practical foundation for governing AI in regulated environments

  • 01Cross-domain understanding of AI risk
  • 02Practical AI governance and risk management
  • 03Alignment with the EU AI Act and emerging regulation
  • 04Curated peer cohort, capped at ten participants

Formats

Two ways to engage.

Half-Day Session

Executive Briefing

Half-day high-level session for leadership and decision-makers.

Three Half-Day Sessions

Professional Training

Three half-day sessions focused on operational implementation.

Private Organizational Delivery

Adapted to your context

Private delivery can be adapted to the organization's context, including:

  • Internal AI use cases
  • Governance maturity
  • Public sector or regulated environments
  • EU AI Act exposure
  • Supplier and procurement risks
  • Roles and responsibilities across teams

Programme

Seven modules covering the full scope of AI governance.

01Foundations of AI
  • Definitions of AI and common governance concepts
  • Different types of AI systems
  • Core concepts such as data, algorithms, models, and systems
  • AI system classification and context of use
  • Principles of responsible and trustworthy AI governance
02AI Impacts and Risks
  • AI harm taxonomy and how to identify AI risks
  • Individual risks such as bias, discrimination, and privacy harms
  • Organizational risks including reputational, operational, and legal exposure
  • Societal and systemic risks including misinformation and surveillance
  • Environmental and infrastructure-related AI impacts
03Regulatory Landscape
  • EU AI Act risk-based classification
  • High-risk AI obligations and governance expectations
  • Interaction with GDPR and existing legal frameworks
  • Roles of providers, deployers, and users
  • Public sector and regulated environment considerations
04AI Lifecycle Governance
  • Planning and design of AI systems
  • Data collection, quality, and preparation risks
  • Model development, testing, and validation
  • Deployment, monitoring, and incident handling
  • Decommissioning and lifecycle documentation
05AI Governance and Risk Management
  • Governance roles and accountability structures
  • Risk identification across legal, technical, operational, and security domains
  • Integration with existing GRC and compliance frameworks
  • Use of standards such as ISO 42001, ISO 42005, ISO 27001, and NIST AI RMF
  • Moving from policy to operational controls
06Operationalizing AI Systems
  • Embedding AI governance into projects and procurement
  • Supplier and third-party AI risk management
  • Monitoring, auditability, and evidence collection
  • Cross-functional collaboration between legal, risk, IT, security, and business teams
  • Practical implementation challenges and lessons learned
07Ongoing Risks and Concerns
  • Generative AI and agentic AI risk
  • Overreliance on predictive systems
  • Misuse scenarios including profiling, manipulation, and surveillance
  • AI risk across critical infrastructure and public services
  • Scaling governance as AI adoption increases

Participants will leave with

  • 01Practical ability to implement AI governance and risk management so that AI systems can be deployed with control and accountability
  • 02Alignment with EU AI Act, ISO 42001, and ISO 42005 so that regulatory expectations are translated into real operations
  • 03Ability to connect AI governance with risk management, data protection, and procurement so that decisions are made across domains, not in silos
  • 04Tools to challenge suppliers and conduct AI due diligence so that external risk is controlled before it enters the organisation
  • 05Capability to identify and classify AI risks across systems, processes, and governance structures so that governance becomes proactive rather than reactive
  • 06Stronger ability to procure, assess, and govern AI solutions so that long-term legal, operational, and financial risks are reduced

Trainer

Hummam Wasfi

Founder & CEO | AI Governance, Data Protection, GRC Strategy & Technology Advisor

Credentials
AIGP | FIP | CIPP/E | CIPM | CIPT | MBA
Applied across AI governance, data protection, and enterprise GRC environments.
Training
Assessor training delivered by SWEDAC (Sweden’s national accreditation authority), covering SS-EN ISO/IEC 17025:2018 and conformity assessment principles.

Bring this training to your organization.

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