Francine Hoo.

It started in audit, then moved into risk, compliance and operations. That gave me an early view of organisations through accountability: how decisions are made, what can go wrong, what good evidence looks like and what it means to be responsible for an outcome rather than simply advise on it.

Around 2015, my work moved increasingly into privacy and data.

At ASX, I worked across governance and compliance before taking carriage of the enterprise data governance function. It was a useful lesson in the difference between designing something on paper and making it work inside a real organisation.

Data governance was not really a data problem. It involved technology, ownership, regulation, risk, process, behaviour and competing organisational priorities. AI has many of the same characteristics, only amplified.

My work subsequently moved through enterprise data and transformation and into AI strategy, implementation and Responsible AI. At KPMG, I co-created and implemented its award-nominated AI Marketplace capability and led technical teams building AI-driven solutions. I have designed Responsible AI frameworks and impact approaches across Australia and Asia-Pacific and advised executives and Boards on AI, data, governance and transformation.

I have also been a Board Director and Compliance Committee Member.

Sitting on both sides of the table changes your perspective.

You think differently about a governance framework when you have had to operate one. You think differently about assurance when you have been accountable for what happens next. And you think differently about transformation when you know the organisation still has to function after the programme has finished.

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AI now brings many of the areas I have worked across into the same conversation. Business strategy and technology. Data and risk. People and process. Governance and economics. Innovation and accountability.

I do not see those as separate AI workstreams. I see the organisation they have to work inside.