Every business is being told to adopt AI. Almost nobody is being told how to do it safely. REDD treats AI the way we treat every other system that touches your data: secured first, governed properly, and rolled out so your team actually uses it.
The part nobody mentions
Staff are already pasting company data into free AI tools. The question is not whether your business uses AI. It is whether you control where your data goes when it does.
Unapproved tools spread faster than any software in history. Without a policy and controls, your client data trains someone else's model.
Copilot surfaces everything a user can touch. If your permissions are a mess, AI turns quiet over-sharing into instant exposure.
Insurers, auditors and government buyers now ask how AI is governed. An answer of "we trust our people" does not pass.
The REDD approach
AI sits on top of everything you already have. Build the layers in this order and it multiplies your team. Skip one and it multiplies your exposure.
Permissions mapped and remediated before any AI tool sees them. What Copilot can reach, you decide first.
Approved tools, data boundaries and monitoring that proves the policy is followed rather than just published.
Copilot, automation and AI workflows deployed into real workflows, with training measured by usage rather than attendance.
Each layer rests on the one below. That is the whole point.
AI readiness check
Copilot surfaces everything a user can already reach. These six questions show whether that is a productivity win or a disclosure incident waiting to happen.
What your team gets
The gap between buying AI licences and getting value from them is training and workflow design. REDD deploys the tools inside the work your team already does, with the guardrails invisible until they are needed.
Doing it properly vs doing it fast
Both get you to Copilot. Only one of them survives an audit.
| Switch it on today | The REDD way | |
|---|---|---|
| Permissions | Inherited as-is, including the payroll folder shared in 2019 | Mapped and remediated before rollout |
| Policy | Written after the first incident | Signed off before deployment, tested against real use |
| Shadow AI | Staff keep using free tools quietly | Approved tools that are genuinely better than the free ones |
| Insurer question | No documented answer | Evidence pack ready |
| Outcome | Productivity gain, plus a new attack surface | Productivity gain, on a foundation that holds |
Scroll sideways to compare.
Common questions
It is safe when your permissions are clean, and risky when they are not. Copilot respects existing access exactly, so it surfaces anything a user could already technically reach, including the payroll folder nobody realised was shared. REDD fixes the permission layer before deployment, which is the whole difference between a productivity gain and a disclosure incident.
Shadow AI is staff using unapproved tools, usually free public chatbots, to get their work done. It matters because company data pasted into those tools may be retained and used for training, and because you cannot govern what you cannot see. The fix is not a ban that everyone ignores, it is providing approved tools that are genuinely better than the free ones.
Yes, and increasingly you will be asked to produce it. Insurers, auditors and government buyers now ask how AI use is governed. A workable policy names approved tools, sets data boundaries, and defines what must never be pasted into a model. REDD writes one your auditor will accept and your staff will actually follow.
The assessment itself is typically two to three weeks depending on tenant size. You get a report covering access and permission exposure, data classification gaps, and a prioritised remediation plan with indicative effort. Many businesses stop there for a quarter and fix the foundations before rolling anything out.
Not in the deployments we run. What it reliably removes is the repetitive work around the edges: summarising, drafting, formatting, searching. The productivity gain shows up when people stop hunting for information and start using it, which is a training and workflow problem more than a technology one.
There are two components: the readiness and governance work, which is a defined project, and the licensing, which is per user. Most clients find licensing is the smaller surprise. The bigger variable is how much permission remediation the readiness assessment uncovers, which is exactly why we assess before quoting the rollout.
Thirty minutes with a REDD engineer. You will leave knowing exactly what AI can safely reach in your environment today, and what needs fixing before it should.
Get in touch
Send the basics and a REDD engineer will come back to you within one business day. Prefer to talk? Call 1300 697 333.