AI ETHICS & GOVERNANCE
CONTEXT
You have just read my application. This page is for the reader who wants more than a letter allows.
A cover letter argues fitness for a role. This page explains the question I have been asking for twenty-five years: who is accountable when a system that affects real people goes wrong? That question did not begin with AI. It has simply found its most consequential terrain here.
ORIGIN
The question predates the technology.
In 2001, I sat across a table from five trade unions in France's pulp and paper industry and negotiated one of the first workplace IT and privacy charters in that sector. The question was not technical. It was this: when a system changes how people work, who decides how it is used, and who carries responsibility when something goes wrong? I did not call it AI governance then. Nobody did. But the structure of the problem was identical.
Twenty-five years followed. I founded UNIDIS, a national employer organisation representing 2,450 member companies and 80,000 employees across France's pulp and paper industry. I negotiated more than forty national workplace agreements directly with government ministries and five major trade unions. I co-founded a joint training fund allocating more than €100 million annually. I sat on French and European boards and committees; not as an observer, but as the executive who designed the accountability structures and, in board capacity, the member who interrogated whether they held.
Then I built again in Australia: developing hospitality concepts and venues; co-founding OTOOL, an ERP solutions company serving manufacturing and logistics; advising Profluid, a precision engineering firm serving the mining and defence sectors; leading the French Australian Chamber of Commerce and Industry in Western Australia. Different sectors. The same underlying question. Systems that affect real people require governance structures that hold.
When you negotiate the terms of how technology enters someone's workplace, you are not writing policy. You are deciding what that person's Monday morning looks like. I have known that since 2001. It is why I am here.
POSITION
AI governance is a governance problem. Not an engineering problem.
Most organisations approaching AI governance are looking for technical expertise: risk matrices, algorithmic bias metrics, model documentation. These matter. They are not sufficient.
What holds when a regulator arrives or a system fails is not the technical specification. It is the accountability structure: who owns the decision, who can challenge it, what the escalation path looks like, and what the organisation is prepared to say when something goes wrong.
Building that structure is governance work. It requires someone who has built compliance environments under pressure, managed competing stakeholder interests, and understood that the cost of governance failure is not theoretical.
In 2024 I signed the Arborus International AI Charter. A commitment before a credential. In 2025 I co-founded Tricore Tech, a Perth AI laboratory focused on applied AI governance. In 2026 I completed the University of Oxford and UNESCO programme in AI and the Rule of Law. ISO 42001 Lead Implementer accreditation is in progress.
We are deciding what kind of society AI operates within. That is the civilisational question of this generation, dressed in regulatory language. I have spent twenty-five years building governance structures that protected real people in regulated environments. That preparation was not planned. But I am not wasting it.
VISION
The regulatory gap is closing. The governance gap is wider than most boards realise.
The EU AI Act is already partially in force. Prohibitions on unacceptable-risk AI have applied since February 2025. General Purpose AI obligations since August 2025. Transparency requirements arrive in the second half of 2026. High-risk AI obligations, now extended to December 2027 under the EU Digital Omnibus Regulation, are approaching faster than Australian organisations have been treating them.
Australia's regulatory picture is fragmenting simultaneously. Privacy Act amendments arriving in December 2026 require mandatory disclosure of automated decision-making that significantly affects individuals. The ACCC is actively pursuing AI-washing under consumer law. The DTA centralised AI transparency statements from all ninety-four Commonwealth entities in March 2026. New mandatory obligations under the updated AI policy came into force in June 2026, with further requirements arriving in December.
The organisations most exposed are those operating across both jurisdictions: Australian companies with EU clients, multinationals with Australian operations, and any organisation deploying AI in employment, credit, insurance, or essential services decisions. They need someone who understands both the European regulatory culture that produced these frameworks and the Australian operational context that must engage with them.
I am Franco-Australian. That combination is not incidental. It is the positioning.
HOW I CAN HELP
The organisation that has not yet created the role.
The organisations I am looking for are not those with a polished AI governance function already in place. They are the ones that know the question is coming for them and have no one in the room who owns it. No framework. No defined role. Not yet.
What I build in that situation: an accountability framework grounded in the organisation's existing risk appetite; a governance structure that practitioners actually use rather than file; a bridge between technical teams and executive leadership; and a regulatory map covering both the Australian obligations in force and the EU framework that may already apply.
This is not consultancy from the outside. It is executive governance from the inside. That is the only kind that holds.
If this is the conversation your organisation needs, I am available.
Contact me directly or connect on Linkedin.