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Real Bytes builds and deploys AI against the Australian AI Ethics Principles and the Voluntary AI Safety Standard. This page sets out the principles we hold to, the controls we run, and the assurance you can point to when your board, your customers or a regulator asks.
Why this page exists
Governance is not a brake on AI. It is the bit that makes it usable.
The tools have arrived faster than the practice around them. Most Australian businesses now have staff using AI whether the business has a policy or not, and most have at least one AI project on the roadmap. The question is no longer whether to use AI. It is whether the way you use it would survive a Privacy Act complaint, a customer question, or a board review.
We treat AI governance the same way we treat security. It is not a document. It is a set of controls, owners and review points that run for the life of the system. Done well, it lets you move faster, because you can say yes to a use case with confidence rather than saying no out of fear.
Our approach is built on the Australian AI Ethics Principles published by the Department of Industry, Science and Resources, the Voluntary AI Safety Standard, and the privacy and security obligations your business already carries. We do not invent a new framework. We apply the national one.
The eight Australian AI Ethics Principles
The principles, and what each one means when we do the work
These are the national principles. The line under each is how we actually apply it in a Real Bytes engagement, in plain English.
Human, societal and environmental wellbeing
We scope AI to a defined business problem and check it does not push staff, customers or the public toward harm. We will say no to a use case that is technically possible but careless.
Human-centred values
A person is accountable for every AI-assisted decision. We never let an model sign off on hiring, pricing, enforcement or clinical judgement on its own.
Fairness
Before rollout we ask who the model could disadvantage and how that surfaces in your data. We test outputs for bias against the groups your business actually serves.
Accountability
Every AI system we deploy has a named owner inside your business and a named owner inside ours. When something goes wrong, you know who to call and we know who answers.
Transparency and explainability
We document what the model is, what data it sees, where that data goes, and what its limits are. Your staff and your customers should be able to tell when AI was involved.
Contestability
If an AI output affects someone, that person has a path to query it and get a human review. We build that path into the workflow rather than leaving it to chance.
Privacy protection and security
AI does not bypass the Privacy Act. We minimise the data a model can reach, apply your existing sensitivity labels and DLP, and keep regulated data inside its approved boundary.
Reliability and robustness
We test before rollout and monitor after it. Outputs are checked for drift, hallucination and failure modes that matter in your context, not just in a vendor demo.
How we govern AI in practice
Six controls we run on every deployment
Principles on their own do not stop harm. These are the controls we put around an AI system so the principles hold up in production.
Data minimisation and boundary
We map what data the AI can reach before it is turned on. Sensitive stores are scoped out through permissions, sensitivity labels and Conditional Access. A model cannot learn from data it cannot see.
Human oversight by design
High-stakes outputs pass through a person before they act. We agree the decision matrix with you up front: which actions are automated, which need review, which need sign-off.
Transparency to staff and customers
We help you write the disclosure that tells people when AI is in the loop. Internal acceptable use, external privacy notices, and AI-specific terms where a regulator or contract requires them.
Accountability and ownership
Every deployment gets a RACI. A business owner inside your organisation holds the risk. A Real Bytes engineer holds the technical implementation. Neither role is shared into the model.
Security inherited from your tenant
AI sits inside the identity, data and logging controls you already run. It does not get a parallel estate. Entra ID, Conditional Access, Defender and your SIEM cover AI the same way they cover email.
Monitoring and review
Usage, prompt patterns and outputs are reviewed on a cadence. Drift, novel failure modes and shadow use are caught early. Access reviews include the non-human identities AI depends on.
Across the engagement
Governance runs through the whole job, not just the launch
The most common failure is governance bolted on at the end. We build it into each phase instead.
01
Discover
We start with the problem, not the tool. A use case is scored for value, risk and regulatory exposure before any licence is bought or any model is connected. If the answer is no, we say so.
02
Design
We design the data boundary, the human checkpoints, the disclosure, and the rollback. The governance shape is agreed with your risk owner before build starts, not bolted on at the end.
03
Deploy
Controlled pilot first. We measure real usage, document the prompts that work, and fix the failure modes that surface. Full rollout only after the pilot proves value and the controls hold.
04
Monitor
Ongoing review of usage, outputs and access. Periodic re-test against the original risk assessment. The model, the data and the permissions all get revisited as your business and the law move.
Standards and frameworks
The standards we design against
We do not invent a framework. We apply the Australian and international ones your business is already measured against.
Australian AI Ethics Principles
Department of Industry, Science and Resources
The eight principles we apply to every engagement, set out above.
Voluntary AI Safety Standard (VAISS)
Australian Government
The national standard for safe AI practice. We use its outcomes as a design checklist.
ISO/IEC 42001
ISO
AI management system standard. We work to its lifecycle and risk disciplines for clients pursuing certification.
Privacy Act 1988 and the APPs
OAIC
AI does not change your privacy obligations. We design against the Australian Privacy Principles and the coming small business reforms.
Essential Eight
Australian Cyber Security Centre
AI inherits your tenant security. We do not consider an AI rollout safe unless the Essential Eight baseline is in place.
What you walk away with
Assurance you can point to
A Real Bytes AI engagement leaves you with more than a working tool. It leaves you with the artefacts that let you answer the hard questions.
A use case register
Every AI system in scope, its owner, its data, its risk rating and its review date. The single source of truth for your AI footprint.
A risk assessment
For each use case, what could go wrong, who is affected, and what control closes it. Written in plain English for a risk owner to sign.
An acceptable use policy
Short, readable, and specific to your business. Covers sanctioned tools, disclosure expectations and what staff should never put into a public model.
A controls map
The Conditional Access, DLP, sensitivity labels, logging and access reviews that govern the system, mapped to the principles they satisfy.
A monitoring plan
What is reviewed, how often, by whom, and what triggers a rollback. Governance that keeps running after we leave.
A board-ready summary
A one-page position your leadership team can sign off and revisit, covering the principles, the risks and the decisions taken.
Common questions