AI Governance

Knowing which frameworks exist and where your organization sits on a maturity model still leaves an open question: what order do you actually do things in? The Shielded AI Governance Pathway is our own answer to that question — an original, six-phase implementation methodology developed from what we’ve seen work across engagements. It is not […]

Our main guide, AI Governance for Enterprises: A Practical Framework for IT, Cybersecurity, and Risk Leaders, makes a point worth repeating: not every framework in this space is the same kind of thing. Some are legally binding. Some are certifiable management standards. Some are voluntary guidance. Some are just practical security references. Treating them as

AI governance isn’t something an organization either “has” or “doesn’t have” — it develops in stages, the same way IT governance and cybersecurity programs matured over years, not overnight. This post lays out an original Shielded Networks maturity model for AI governance, plus a dedicated track specifically for AI cybersecurity maturity, since security capability tends

A practical, category-by-category AI governance checklist covering strategy, policy, inventory, risk, data, cybersecurity, vendors, and monitoring — useful for an initial gap assessment.

From shadow AI to ungoverned agents, these are the 12 mistakes that most often derail enterprise AI governance programs — and practical ways to avoid each one.

A practical guide to AI governance, AI IT governance, and AI cybersecurity governance — key frameworks, a maturity model, and where to start, in one 10-minute read.