Insights

Practical notes on governing data and AI

Plain-language articles for CIOs, chief data officers, risk leaders and compliance teams on standards, regulation and the day-to-day mechanics of governing data and AI as one system.

Articles

Ten topics, in three groups

Standards and regulation, the links between data and AI, and the operating practices that keep governance current. Each article is general information, not legal advice.

Standards

ISO/IEC 42001 Readiness: Where to Start

Scope, inventory and risk method first: the evidence that makes the rest of an AI management system easier.

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Standards

NIST AI RMF in Practice: From Functions to Controls

Turning Govern, Map, Measure and Manage into owners, recurring activities and records.

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Standards

EU AI Act Obligations: An Overview by Role

Risk tiers, provider and deployer roles, and general-purpose models, explained at a high level.

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Data to AI

Data-to-AI Lineage Explained

What to capture from source data through features and models to a decision, and why it matters.

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Data to AI

Quality-Gated AI Release: Stop Bad Data Shipping

Data quality thresholds that gate model deployment, with evidence recorded at every release.

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Data to AI

Right to Be Forgotten Across Data and Models

Practical routes for erasure across stores, indexes and trained models, and what remains unsettled.

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Operations

Finding Shadow AI Without a Witch Hunt

Discovery methods that bring unsanctioned AI into view and give people a fast route to approval.

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Operations

Building an AI Inventory That Stays Current

What to record, what to include beyond in-house models, and how to keep entries accurate over time.

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Risk

Model Risk Governance Beyond the Validation Team

Extending tiering, independent challenge, monitoring and change control to modern AI.

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Operations

Governing Agents and RAG Systems

Source control, least-privilege tools, human approval and logging for retrieval and agentic systems.

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