Better HR practice. Better workplaces. Better careers.

When HR is done well at scale, it changes what the profession is capable of and what Australian employees experience at work. This page explains what O-HR and Nooma are doing to contribute to that outcome, and how we hold ourselves accountable to it.
The opportunity
Every HR decision affects a person.
HR decisions affect the livelihoods, careers, safety, and daily experience of every person in every Australian workplace. The quality of those decisions has always depended heavily on the capability, experience, and resources available to the people making them.
For most of the profession's history, access to expert HR capability has been unequal. Large, well-resourced organisations could afford senior HR leadership, specialist consulting, and enterprise-grade systems. Smaller organisations, independent practitioners, and consultants working at scale could not.
That gap has real consequences. Inconsistent HR practice means inconsistent outcomes for employees. Inconsistent fairness, inconsistent safety, inconsistent access to good management.
Nooma was built to close that gap. Not by lowering the standard, but by making the standard accessible to everyone who carries the responsibility for it.
Our social impact
commitments
These commitments apply across everything O-HR does: our consulting and advisory services, our on-demand HR leadership engagements, and the Nooma platform. Where a commitment is specific to one offering, we say so.
Representation and bias in AI
84% of HR practitioners in Australia are women. The profession that shapes how people are hired, managed, developed, and exited has been carried predominantly by women for decades. O-HR was built from inside that profession, by one of them.
AI adoption is currently skewed heavily toward male users. The tools being built to transform work are not being built by, or primarily for, the people who do this work. At the same time, research consistently shows that AI-driven automation is on track to disproportionately impact jobs held by women. The profession most responsible for managing that transition is itself at risk from it.
O-HR's response to that is not rhetorical. It is architectural and it is practical. Nooma is designed to augment HR practitioners, not automate them out of relevance. Our consulting work is delivered with the same intent: to build capability and confidence in the people we work with, not to create dependency on us.
We also commit to actively working to identify and reduce bias across our platform, our workflows, and our consulting delivery. AI systems can replicate and amplify existing biases. In HR, where decisions directly affect people's livelihoods and careers, that risk is unacceptable. We are building toward formal bias testing as a standing practice. In the interim, Nooma's workflows are underpinned by Australian human rights law, reviewed by certified employment lawyers, and validated by our Industry Council of experienced practitioners. We treat that as a floor, not a ceiling.
This is a profession that has long delivered more than it has been credited for. We are building the tools and delivering the advisory to change that.
Human rights and socially responsible AI use
O-HR takes a clear position on the organisations we align ourselves with, the technology we build on, and the engagements we take on.
In our consulting and advisory work, we will not take on engagements that require us to act against the interests of employees, facilitate unlawful workplace practices, or support organisations whose conduct is fundamentally inconsistent with fair and human-centred HR practice. Our consulting is guided by the same Charter principles that govern the platform. The practitioner accountability we ask of our clients is accountability we hold ourselves to.In our technology choices, we do not build on platforms provided by organisations whose practices are inconsistent with the protection of human rights. This includes organisations that develop or deploy AI for autonomous weaponry, mass surveillance, the suppression of civil liberties, or the manipulation of vulnerable populations.
We acknowledge that much of the foundational AI capability underpinning platforms like Nooma was built using human labour, often in low-cost countries and at conditions that raise legitimate questions about fair labour practice. We take this seriously. Our AI provider selection considers not only technical capability and security but the labour, ethical, and governance practices of the organisations behind the technology.
Our technology independence architecture means we are never locked into a single AI provider. If a provider's practices become inconsistent with our human rights commitments, we can move. That is a deliberate design decision.
We hold ourselves to Australia's AI Ethics Principles, published by the Department of Industry, Science and Resources, which include human-centred values, fairness, transparency, contestability, and accountability. These are not aspirations for O-HR. They are design requirements for the platform and practice standards for our consulting.
Impact on Australian business and the HR profession
Every HR decision made well is a better outcome for an employee somewhere. This is true whether the decision is supported by a Nooma workflow or guided by one of our consulting practitioners. Consistent, lawful, human-centred HR practice reduces the risk of unfair treatment, unsafe conditions, and unresolved conflict in the workplace.
Nooma embeds current Australian employment law obligations directly into HR workflows at the point where the work is being done. Our consulting engagements bring the same standard to bear: not as a compliance exercise but as a genuine commitment to the quality and defensibility of HR practice.
HR has always had the capability to shape how organisations perform. What it has lacked is the infrastructure to prove it. Nooma closes that gap for the platform. Our consulting work closes it in the room: building the governance-grade evidence, the capability, and the confidence that allows HR functions to demonstrate their contribution at board and executive level.
When HR is done well at scale, businesses perform better and the people within them benefit.
Environmental responsibility
AI systems carry an environmental cost that is rarely acknowledged by the organisations deploying them. So does consulting.
We believe transparency about both is part of operating responsibly.
Energy and water consumption
Generative AI inference consumes significant energy and water. While O-HR does not train foundational models from scratch, our use of AI for real-time workflow guidance and document generation contributes to the compute footprint of the providers we work with. We monitor this and factor environmental performance into our provider selection.
Model efficiency
We commit to choosing AI models and usage patterns that balance capability with resource efficiency. We do not use more compute than the task requires.
Digital-first, low-impact consulting
Our consulting model is designed to minimise unnecessary travel and physical resource use. We default to remote delivery where it serves the client equally well, use digital documentation throughout, and do not generate paper-based outputs unless specifically required. This reduces the environmental footprint of our consulting engagements relative to traditional models.
Provider practices
We consider the environmental commitments of our technology providers as part of our vendor assessment. Providers working toward renewable energy use and reduced water consumption in their data centres are preferred where capability and security requirements are otherwise equal.
Our commitment
Every HR decision affects a person.
O-HR is committed to building and delivering HR capability that is safe, fair, human-centred, and socially responsible. We will continue to prioritise equity, accountability, transparency, and environmental responsibility as our platform and consulting practice grow. Technology serves people and the practice of HR, not the other way around.
Last updated 18 July 2026