AI Risk Classification
AI governance frameworks tell organisations what to do, but how do we actually make this work in the real world?
When teams try to apply frameworks such as the EU AI Act or sector guidelines, ambiguity quickly arises. Risk categories often depend heavily on specific use cases, making it difficult to classify internal copilots, workflow automations, or emerging agentic systems that do not fit neatly into predefined regulatory buckets.
Explore why existing approaches struggle to scale across real-world deployments and introduces a first-principles, Responsible AI-aligned, use-case agnostic risk classification framework designed for operational clarity.
What will be covered:
The limitations of risk classification models in leading frameworks (i.e. NIST AI RMF, ISO 42001, EU AI Act, MAS AIRG, SG MGF) and why consistent application is difficult
A structured framework with core AI risk dimensions and a transparent risk scoring methodology
A tier-based control catalogue for proportionate governance that integrates into your AI Risk Management Policy
Applying the framework to real scenarios through hands-on exercise
Through group discussions and collaborative exercises, explore practical applications of the framework, exchange insights, and consider how it might work in their own organisational contexts.
Whether you are building internal AI governance processes or operationalising regulatory requirements, learn how you can turn high-level principles into implementable systems.
*Note: Programme is still in development and may be subject to changes.
Facilitated by Chris Fong (The AI Governance Operational)
Chris Fong brings nearly two decades of experience in technology governance, risk and controls across Big Four advisory firms (KPMG, PwC), major financial institutions (Standard Chartered Bank, United Overseas Bank), Singapore's sovereign wealth fund GIC, and startups. He specialises in operationalising enterprise AI governance, developing practical "middle-layer" frameworks that translate regulatory expectations into implementable policies and lifecycle controls. His approach draws on leading standards including MAS AIRG, ISO frameworks, and NIST guidance. Chris shares his insights through his LinkedIn newsletter and advisory work under The AI Governance Operational (AIGO). He holds degrees from NUS and NTU, and maintains certifications including AIGP, AIGA, ISO/IEC 42001 Lead Auditor, CISSP, CISA, and AWS Certified AI Practitioner.
More About the Series
ThursTalks is Lorong AI's curated dialogue series featuring 1-2 spotlight speakers per session. Each session emphasizes focused perspectives, followed by an extended fireside chat or open discussion to encourage deeper understanding and meaningful exchange of ideas.
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