Our approach to AI

Switching on AI is not the same as having a strategy for AI.

AI is powerful, and that power carries both opportunity and risk. Pilots and tool purchases multiply quickly, yet none of them tell you where AI creates value or where it creates exposure. Answering that is the harder task. It depends on the governance around AI, the operating model it sits within, the quality of the underlying data, and the judgement to know where AI helps. That is the work we do.

What we work on

Where we work.

AI return on investment

AI spending is growing faster than the discipline around measuring what it returns. The costs are easier to hide than they are with traditional IT, accumulating quietly across licence fees, integration and governance overhead, and the compute underneath. The benefits are harder to pin down, because saved time and better decisions rarely show up on a single line. We help organisations work out what is actually being spent and what is being gained in return, then put a framework in place to track it over time.

AI strategy

An AI strategy is a set of deliberate choices about where AI is worth applying, what it should improve, what needs to be in place first, and where the organisation is better off not investing at all. Working with executive teams and boards, we build a position the organisation can stand behind, as clear about where AI does not belong as about where it does.

AI governance

AI governance sits where data governance, technology risk, and operational accountability meet. The questions are familiar in shape but new in scope. Who is accountable when AI informs a decision? What data sits behind it, and how are its outputs reviewed and retained? And where does human judgement stay in charge? Most organisations have gaps here, because the frameworks they rely on predate the technology. We bring AI governance into line with the way an organisation already manages risk and data, and make it stand up to a board or a regulator.

AI implementation

We are not a model-building firm. Our work is in the decisions that sit around the technology and decide whether it delivers value or creates exposure. That means how it connects to existing systems, who can access it and what data it can touch, whether it runs on shared or private infrastructure, which vendors are worth trusting, and how roles and skills change to support it. Those choices, more than the model itself, decide whether AI becomes part of how the organisation works, or just another shelf of tools.

AI adoption and the workforce

The hardest part of AI adoption is rarely the technology. People respond to it unevenly. Some worry about their roles or their job security; some take to the tools quickly while others hold back; and some reach for tools the organisation has never sanctioned, creating unmanaged risk for data and process. There is a slower problem too. As the tool takes on work people used to do themselves, the underlying skill and judgement can fade. Over-trust causes as much trouble as under-trust. We spend our time on the practical consequences: which roles change, how skills need to develop, what it takes to manage work that is part-human and part-AI, and how fast adoption can realistically go.

AI advisory sits within our broader Emerging Technology Adoption practice.

When to engage

When organisations come to us.

  • The organisation is making AI decisions through pilots and tooling choices, rather than from a deliberate position
  • Existing governance, risk, and data frameworks do not yet account for AI use
  • AI investment is increasing but the organisation cannot articulate what it is getting in return
  • A board or executive needs an independent position on AI strategy or risk
  • AI vendor proposals or platform decisions require independent review before commitment
  • Adoption is uneven, or the workforce implications of AI need to be worked through deliberately

Disclosure

Our own use of AI

We selectively use AI-assisted tools to support analysis, synthesis, and document review within engagements. The intent is to spend less time on mechanical tasks and more on judgement, stakeholder engagement and the parts of advisory work where experience matters most. Accountability for the advice we provide rests with our advisors. Client information is handled in line with the confidentiality and data handling commitments agreed at the start of each engagement.

Get in touch

Start with a conversation.

Whether you're facing a critical technology decision, a program in trouble, or a board that needs clarity, we can help.

[email protected]+61 2 9099 1621

201 Sussex Street, Sydney NSW 2000  ·  80 Ann Street, Brisbane QLD 4000