Human-Centred AI
AI is now entering the work they do — the calls they make, the standards they hold. Ready or not.
The question isn't what AI can do. It's whether the people you're known for can trust it, challenge it, and shape it — without losing what made the work worth paying for.
A short, candid conversation for leadership teams facing a real AI decision.
Industries
Education
I'm brought in when the decisions get senior — for the board, the leadership team, and the experts whose standards are on the line.
Leadership needs to decide what to pursue, what to pause, and what to govern — and align senior stakeholders behind it.
Experts are wary that AI will dilute the work they're trusted for. The job is to amplify it, not erode it.
Teams can show AI working, but can't yet deploy it with the confidence to stand behind the output.
Three commitments that hold in every engagement.
I design from how people actually work — cautious, imperfect, accountable — not from the capability on the slide.
AI sharpens the craft your organisation is trusted for. The accountability — the name on the work — stays human.
I build the methods with your team, not for them — so the capability stays when the work ends, not a dependency on me.
Why clients bring me in
I teach this, not just advise on it. AI x Design Thinking at IDEO U; AI strategy at Imperial and Kellogg; guest speaker at MIT xPRO.
Forged where trust is non-negotiable. Three decades in high-stakes, regulated technology — former bank CIO through FCA/PRA authorisation, and global change leadership for 2,800 people at HSBC.
I stay in the work. I lead every engagement personally and stay hands-on throughout — not a senior pitch followed by a junior hand-off.
Most of my work is structured as focused phases rather than open-ended retainers.
A concentrated piece of work around one leadership question, one team, or one live use case — enough to create movement without drifting into theatre.
I work directly with a small number of organisations each year. That keeps the work senior, hands-on, and informed by what is happening across different sectors.
The output is not just advice. It is decision rules, working methods, and internal capability your team can keep using after the engagement ends.
Follow-on work happens when the scope expands — a new market, a new team, or a new workflow — not because you need a permanent adviser in the room.
Each engagement starts differently. Here are four that show the range.
How I use AI
I publish the boundaries, review standards, and commitments that shape how I use AI with clients and in my own practice.
See AI Use & Principles →In expertise-heavy sectors, AI commoditises the interpretive layer first — the advice, the analysis, the human read on the data. The defensible move isn't replacing your experts. It's sharpening the expertise behind them, because as AI spreads, trusted judgement gets scarcer, not cheaper.
Start a conversationA short, candid conversation for leadership teams facing a real AI decision.