Board and leadership
AI risk in business language: exposure, accountability, investment decisions, regulatory obligations and what management review must monitor.
People · Cross-cutting axis
All AI governance depends on people — board, leadership, technical teams, legal and the whole workforce. VGrid structures specific tracks for each audience, from the executive who has to decide on risk and investment to the employee who needs to know what may or may not be sent to a public LLM.
A single one-hour webinar does not change behaviour. Each audience needs a different depth and a different decision framing: leadership needs risk and investment criteria, technical teams need controls and secure development practices, legal and compliance need regulatory obligations and evidence, and the wider workforce needs concrete rules about acceptable use, sensitive data and which tools are authorised.
Same governance framework, different depth and decision framing.
AI risk in business language: exposure, accountability, investment decisions, regulatory obligations and what management review must monitor.
AI-specific threats and controls: LLM and agent attack surface, prompt injection, data leakage, logging, human oversight and documentation of models and systems.
Regulatory reading and evidence: ISO/IEC 42001 requirements, EU AI Act risk tiers, NIST AI RMF functions and the interface with data protection law.
Acceptable use awareness: what can be sent to an AI tool, what is prohibited, how to request authorisation and how to report an incident.
Content is adjusted to the organisation's real AI footprint.
Training programmes are delivered as consulting engagements, scoped to the organisation. They do not confer any official certification and are not a substitute for certification audits, which only accredited independent bodies can perform.
Tell us which audiences need to be covered and which AI uses already exist. VGrid proposes the tracks and the sequence.