AI Risk Management Framework for Adtech
Tags: Frameworks
TL;DR
- NIST’s AI RMF provides a practical structure to inventory AI systems, assess risks, and monitor performance.
- It maps well to adtech needs: use‑case scoping, data‑flow mapping, bias/testing, and incident response.
Why it matters for HK marketers: A lightweight NIST‑aligned process unblocks vendor onboarding while satisfying global governance standards.
Key components to apply
- Inventory (Govern 1.6): Maintain an organized database of AI models/systems, purposes, data sources, owners, and change logs.
- Risk assessments: Extend existing DPIA/vendor questionnaires with AI‑specific items (LLMs, profiling, synthetic data, unlearning, training use of inputs).
- Data‑flow mapping: Diagram sources, destinations, and triggers for CRM, measurement, and model training pipelines.
- Monitoring & audits: Periodic output testing (deception, bias), privacy/security audits, and contracted third‑party audit rights.
- Recordkeeping: Purpose, inputs, deployer instructions, foreseeable uses/misuses, and discrimination assessments.
Standards to reference
- ISO/IEC 27701, ISO 42001:2023, ISO 5338 and NIST Privacy Framework can augment assessment methodology.
So what for marketers
Adopt a NIST‑style register and AI risk checklist; require vendors to answer AI‑specific questions and accept audit rights before deployment.
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