What we do

Most organisations know they need to do something with AI. Few have a clear picture of where they actually stand – what's working, what's missing, and what to do first. This engagement answers those questions before committing to a full programme.

Two weeks of structured discovery – interviews with key stakeholders, review of current AI activity and governance posture, assessment against established frameworks – producing a maturity snapshot and a prioritised set of next steps tailored to the organisation's sector, risk profile, and strategic objectives.

Most organisations are deploying AI without a clear strategy for what problems it is solving, or the governance structures to know whether it is working – or causing harm. The cost of getting this wrong is not abstract. It shows up in failed programmes, regulatory exposure, and boards asking questions that no one can answer.

This engagement produces an AI strategy and governance framework that holds – in the organisation, at the board table, and under regulatory scrutiny. Grounded in 25+ years of executive experience, including direct governance of AI in life-critical clinical environments where the consequences were immediate.

Boards are being asked to govern AI without the context to do it well. The risk is not that they ask too many questions – it is that they ask the wrong ones, or none at all. This session gives boards and executive teams the grounding to govern AI with confidence.

A working session, not a lecture. Covers the AI governance landscape, how AI risk builds on, but also differs from conventional technology risk, what effective board-level oversight looks like in practice, and how to distinguish AI programmes that are under control from those that are not. Includes a practical case study.

The value of this engagement is perspective from having operated at both levels: as the technology executive accountable for delivery, and as the board director responsible for oversight. The questions that get asked, the risks that get surfaced, and the assumptions that get challenged look different from that vantage point.

Independent, experienced technology and AI advisory for boards, audit and risk committees, and executive leadership teams – translating technology strategy into board language, and board expectations into things a technology function can actually execute.

Large transformation programmes fail most often not because of technical problems, but because of unclear strategy, a target operating model that was never properly designed, and a roadmap that does not connect to real organisational capacity.

This engagement produces a transformation strategy that can be put in front of a board, approved, and actually executed – including what the organisation looks like on the other side.

Most organisations that have invested in cyber security assessments find themselves with multiple reports, competing priorities, and no consolidated view that a board or CEO can act on. This engagement synthesises existing work into a single board-visible risk picture with a clear, resourced programme behind it.

Fractional or interim CTO, CDO, or CIO for organisations navigating executive transitions, critical transformation programmes, or technology crises that cannot wait for a permanent hire. The distinction from a consulting engagement: this is operational leadership, not advice.

A clearly articulated technology strategy, or more precisely, the technology component of a business strategy, underpins any realistic plan to implement AI and translate it into business impact. With technology now a foundational cost and revenue driver, the real question isn't whether a strategy exists. It's whether it's current and appropriate, formally articulated, well understood, and consistently adopted across the organisation.

An independent engagement to build, or stress-test, a technology strategy: whether that means establishing the technology component of a business strategy from scratch, or assessing an existing strategy or roadmap for soundness, realistic resourcing, and real risk. Delivered by someone who has built and executed these strategies from the inside as CEO, CDO, and CIO, not just reviewed them from outside.

AI strategy fails at the handoff when the people responsible for executing it don't share a working understanding of what AI can and can't do. A strategy document doesn't fix that. The executive team does, once they have the shared literacy and judgement to apply it.

This engagement builds that capability directly: structured, practical education for an executive team, calibrated to the organisation's actual AI initiatives, not generic AI literacy training. Often follows an AI Strategy and Governance engagement, once the strategy exists and the team needs to be able to execute against it.

Technology and AI due diligence is often the least rigorous part of an acquisition process, treated as a checklist exercise rather than a genuine assessment of what's actually being acquired. For technology-dependent targets, that's where the real risk sits: technical debt, architecture that won't scale, AI systems built on shaky governance, or capability that doesn't survive the departure of one or two people.

Independent technology and AI due diligence for investment and acquisition decisions: assessing technology capability, architecture, AI systems, governance, and risk in a technology-dependent target. Delivered by someone who has built and been accountable for these systems from the inside, and who has personally carried out technology due diligence on investment opportunities, not just advised on the process.