Model Online / On-Site
Duration
Modules 5 modules

Course Objective & Scope

Subjecting an internal meeting-notes summariser and an automated credit-underwriting model to the same review process either paralyses delivery or leaves high-impact systems under-controlled. This course teaches how to build an enterprise AI risk classification methodology that places any use case into the right risk tier within minutes.

It combines the EU AI Act risk pyramid (prohibited, high-risk, transparency-regulated, minimal risk) with internal operational, financial, privacy and reputational criteria. Participants design an intake risk-tiering questionnaire and a tier-to-control mapping matrix tailored to their organisation.

Who Should Attend?

  • Enterprise risk management, compliance, internal control and InfoSec specialists
  • AI governance team members and AI CoE leads
  • Product managers and business analysts triaging new AI requests
  • Legal counsel and data protection specialists

Key Takeaways

  • Build an enterprise AI risk taxonomy blending regulatory rules and business risk appetite
  • Assign AI systems to risk tiers (Tier 1–4) based on autonomy, impact reversibility and data sensitivity
  • Detect when a change in deployment context elevates a low-risk tool into a high-risk tier
  • Map mandatory testing, documentation, human oversight and sign-off controls to each tier
  • Design a self-service intake questionnaire that calculates a use case's risk tier consistently

Curriculum

Building an Enterprise AI Risk Taxonomy
  • Fundamental rights, safety, operational continuity, financial loss, privacy and brand dimensions
  • How model architecture (predictive ML, LLM, autonomous agent) interacts with deployment context
  • Classifying on inherent risk before applying controls
Regulatory Classification: EU AI Act Risk Tiers
  • Screening against Article 5 prohibited AI practices
  • Annex I (safety components) and Annex III (HR, credit, education, essential services) high-risk checks
  • Procedural exemptions, profiling rules and GPAI transparency obligations
Multi-Dimensional Enterprise Risk Tiering Model
  • Target audience (internal staff vs external customers) and blast radius
  • Degree of autonomy: retrieval, recommendation/drafting, or autonomous execution
  • Decision materiality, reversibility and input data sensitivity
Mapping Risk Tiers to Mandatory Controls
  • Graduated control packages for Low, Medium, High and Critical risk tiers
  • When to mandate red teaming, bias audits, impact assessments or committee sign-off
  • Re-classification triggers when a system's scope or audience changes
Workshop: Designing the Intake Classification Questionnaire
  • Drafting a 12–15 question intake triage form and scoring logic
  • Calibrating the tool against real use cases from the organisation

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