Featured Recordings

A live conversation with Cheri Hotman of Hotman Group on why AI governance has to move from policy, testing, and monitoring toward control before consequence using the AI Admissibility framework.

In this live session Cheri Hotman and I go deep into some of the reasons we see AI security and operational challenges, and how AI Admissibility can help us regain control.

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Presentation Materials

Presentation slide titled 'The AI Admissibility Framework' with a subtitle 'Governing AI Behavior', dated June 2026, authored by Diane R. Jones from Strategic GRC & Security, LLC.

Presented to a local AI practitioner meetup, June 2026.
This deck introduces the Admissibility Framework, the Authority / Actions / Context / Evidence model, and why AI governance has to control systems before consequential action occurs.

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Downloadable Resources

Diagram of AI Admissibility framework.

A deeper explanation of the framework for making AI-enabled systems governable before consequential action occurs.

Read the paper

The Control Intent Engine

Flowchart of a Python script structure for the Control Intent Engine with sections for building parser, main routes, validation, evaluation, and related scripts.
Table comparing four AI Admissibility pillars: Authority, Actions, Context, and Evidence, with their associated questions and conditions.
Download the one sheet

An overview of my tool that maps system reality consistently and automatically to frameworks.

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Contact me for a demo

A practical checklist for evaluating Authority, Actions, Context, and Evidence before AI-enabled systems act.