AI systems governance

Know every AI system your organisation depends on

Most organisations cannot yet list the AI tools their teams use, who owns them, what data they touch or where a human stays in the loop. We help you build that register and govern it.

9

Live AI systems

3

Approved for use

3

High-risk systems

5

Organisations covered

Live figures across client registers (retired systems excluded). Aggregates only.

Risk mix

How live systems are tiered by risk

89% of live systems have defined human oversight. Every high-risk system should have one.

Where AI is being used

Live systems by business category

  • Operations3
  • Productivity1
  • Risk & Compliance1
  • Data & Integration1
  • Clinical1
  • HR & People1
  • Customer Service1

The six controls

What good AI systems governance looks like

01

Inventory

A single register of every AI tool in use, including the ones staff adopt on their own.

02

Named ownership

Every system has a business owner accountable for its outcomes and its data.

03

Data classification

Public, internal, confidential or restricted, so the right safeguards apply from day one.

04

Risk tiering

Low, medium and high risk levels that decide how much review a system needs.

05

Human oversight

Defined points where a person reviews, approves or can override an AI decision.

06

Review cadence

Scheduled re-assessment as tools, vendors, data and regulation change.

The register lifecycle

From discovery to approval, in four steps

  1. 1

    Discover

    Find AI tools in use across teams and log them in the register.

  2. 2

    Classify

    Set the data sensitivity, risk level and an accountable owner.

  3. 3

    Pilot with controls

    Run a limited pilot with defined oversight and success measures.

  4. 4

    Approve or retire

    Approve systems that pass review; retire those that do not.

Start with a systems review

We inventory your AI and data systems, classify their risk and deliver an approved-tools register with guardrails.

Talk to our team