On Thursday 27 August 2026, we hosted a sold-out seminar in Sydney, Financial Modelling in the Age of AI, bringing together industry practitioners from across the transaction lifecycle to explore how artificial intelligence is reshaping financial modelling. The seminar reached full capacity, and the room was buzzing with conversation that continued well after the formal discussion wrapped up.

How is AI being used in financial modelling today?

The seminar was built around a simple but pressing question: how is AI actually being used in financial modelling today, and what does that mean for the professionals who rely on it? Our discussion covered practical use cases of AI in model build, review and analysis, how AI is being integrated into existing transaction and operational workflows, and the governance, auditability and model risk considerations that come with it. Our panellists also spoke to the current limitations of AI tools and where professional judgement still can’t be replaced, drawing on real observations from live transactions. For a deeper dive into these themes, our recent report on why AI adoption in financial modelling is being paced by governance, not capability unpacks this in more detail.

AI and “verification debt”: what’s actually changing in the modelling process

One of the standout moments of the evening came from moderator Joshua Grimm, who introduced the audience to the concept of “verification debt”, a term he picked up from Jerome Brice. It describes how a fast, polished-looking AI output can appear finished long before it is actually reliable. Someone still has to reconcile the inputs, test the calculations, trace the information flows and be able to explain the result.

That distinction, between what AI can generate and who remains responsible for it, was arguably the central theme of the evening. It is a theme we have explored in depth before too, including in our experiment testing whether Claude can replace a financial model audit, where we hid 44 errors in a model to see what AI would actually catch.

Meet the panel: industry experts on AI in financial modelling

Our evening’s discussion was led by a panel of practitioners spanning modelling, banking, energy and corporate strategy.

The discussion was moderated by Joshua Grimm, Director, Forvis Mazars, who steered a thoughtful conversation across the transaction lifecycle, from live modelling environments to governance frameworks. Joshua has also shared his own observations from an earlier AI in financial modelling roundtable, including candid thoughts on where the technology falls short.

What’s next for our financial modelling seminar series?

The strength of the questions and the discussion that carried on after the seminar closed told us this is a conversation the industry wants to keep having. If you would like to explore these themes further before our next event, we would recommend our webinars, Prompting Excel and AI + Project Finance Models: Industry Update, or our upcoming session, AI Can Build the Model. Can You Review It?, live on Tuesday 3 November 2026. For teams wanting hands-on training, our AI in Project Finance Modelling course runs in both Sydney and Singapore later this year.