A breakdown of what's inside the Core AI Policy Framework, and what each add-on actually includes.
This is the foundation document every engagement is built around, structured so your team can actually follow it day to day.
What AI tools are approved, what tasks they can be used for, and what's explicitly off-limits, written in plain language rather than legal boilerplate.
A simple classification of what counts as sensitive, confidential, or public data, and rules for what can and can't be shared with an AI tool at each level.
A defined workflow for how a new AI tool gets reviewed and approved (or rejected), including who owns the decision and how long it should take.
Practical guidance on checking AI-generated output for accuracy, bias, and appropriateness before it's used in a client-facing or decision-making context.
A clear, short procedure for what happens if an AI tool mishandles or exposes data, including who is notified and what the immediate steps are.
Who in your company owns AI governance day to day, what decisions they can make alone, and when something needs to be escalated.
A lightweight plan for making sure the team actually knows the policy exists and understands the parts relevant to their role.
A schedule for revisiting the framework as your AI stack, team, and the regulatory environment change, so it doesn't quietly go out of date.
The framework mapped specifically to your business rather than left generic, so it reflects how your company actually operates.
A live working session with your team to walk through the framework, answer real questions, and build genuine buy-in before rollout.
Regular check-ins so the framework keeps up with your company instead of sitting unused in a drawer after month one.
Most engagements start with a short call to understand your AI stack before anything is drafted.
Or check how pricing works first.