Services

AI leadership, strategy and delivery — from one senior partner

AI now covers a wide range of business activity: from Process AI that automates existing work, to Transformational AI that changes how a business creates value. They are not the same thing, and they deliver very different returns. My work is to help you choose deliberately, then make it happen.

Leadership

Fractional Chief AI Officer

A seat on your executive team. I own AI strategy, priorities, governance and delivery, work across the other chiefs, and report to the board in business language — part-time, without a full-time hire.

Direction

AI strategy

Six to eight weeks with your leadership team to establish where AI fits and where it doesn't, in what order, with what investment and under what governance. The output is a written strategic view you can act on, defer or shelve.

Delivery

Transformational AI platforms

When the strategy finds work worth doing, I lead the build: architecture, standards and security, with your developers becoming the builders. Prototypes in weeks, an MVP typically in 3–5 months and production in 8–12, depending on scope.

Governance

AI governance and security

Human accountability, audit trails and data controls designed in from day one — built by someone with cybersecurity experience from engineer to executive, so security becomes an enabler rather than a blocker.

Commercial

Commercial and product design

New revenue lines, pricing and subscription models, financial modelling for products, and go-to-market — designed together with the product, not separately.

Funding

R&D-ready AI builds

Building something genuinely new? I design the work as documented experiments from day one, so your R&D advisors have what they need to claim R&D tax incentives on it. How it works.

Where AI shows up

The AI Opportunity Radar

AI can show up in every part of a business — from back-office administration to the products you sell. Most businesses find their current AI activity sits on the left, in Process AI: useful, safer, and the smaller prize.

The strategic question is whether your next move is more depth there, or a shift to the right — to Transformational AI that changes what you sell, how you serve, and how easily customers leave.

Where to start

Where AI changes the business

Three phases — adoption, productionization, governance — and within them, the difference between Process AI and Transformational AI. The right place to start is rarely the obvious one: it's where AI compounds what you already have — your customers, your data, your know-how, your brand — and where the move is hardest for a competitor to copy.

Why Transformational AI, and why now

Process AI saves money.Transformational AI changes the business.

Both are useful. Only one creates a position competitors find hard to reverse.

Why now

Work that didn't justify the investment a year ago now does

Prototyped quickly enough to know what works, governed tightly enough for the board to sign off each step, and built so your business owns and runs the result.

R&D-ready AI builds

Let the build help pay for itself

Building a new AI product usually involves real technical uncertainty — and that uncertainty is exactly what R&D tax incentives are designed to reward, in Australia, the United States and many other countries.

Most businesses think about R&D incentives at year end, when the evidence is hard to piece together.

It starts with the right question. R&D has to create new knowledge: a technical uncertainty no expert could resolve in advance. The question is how to make something work, not whether customers will use it. The product needn't be new to the world: well over a hundred CRMs exist, yet a new one can still hold real technical unknowns.

From there, each uncertain piece of work runs as a documented experiment, with core activities kept distinct from supporting ones, in line with the OECD's Frascati Manual.

Where most of the value sits. The supporting work (building the platform the experiments run on) is often the largest part of the eligible spend, but only if its link to the core experiments is planned and recorded from the start.

Working with your advisors. I'm not an R&D tax advisor, and I don't prepare claims. I work alongside your advisors and make sure the business produces what they need.

Proven at scale. I led an eleven-person R&D program for an AI education business: around $30M of eligible R&D over three years, returning $13.5M through the R&D Tax Incentive. See the case study.

How an R&D-ready build runs

Eligibility and rates depend on each country's rules and on the work itself. Your R&D and tax advisors decide what is claimed.

Not sure which of these you need? That's a good first conversation.

Get in touch