Insights

Practical thinking for governing enterprise AI.

Analysis for security, risk, legal, data, technology, and executive leaders building durable AI operating models.

From AI policy to an operating model

Why responsible AI principles need ownership, workflow, evidence, and a cadence to become governable.

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Governing agentic access before autonomy scales

A practical security frame for authority, tools, identities, approvals, and blast radius.

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Building an enterprise AI inventory

A field guide to finding embedded, experimental, and employee-led AI use.

Planned

Extending third-party risk for AI

Questions conventional vendor review can miss when AI enters the service chain.

Planned

Start with clarity

Turn the ideas into an operating plan.

Start with a clear view of current use, ownership, exposure, and priorities.

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