I began this research — and this series — a while ago now, with an academic question and no commercial plan behind it: why do some SMEs make progress with GenAI while others stall? I genuinely did not set out to start anything. But somewhere across 20 interviews and the writing of these articles, a conviction formed that I have decided to act on — and that, honestly, is the only reason there is a tenth piece.
The finding itself was clear. GenAI adoption is not, at root, a technology problem. It is a leadership and meaning-making problem. The organisations that progressed were not those with the best tools or the largest budgets, but those whose leaders took responsibility for meaning under uncertainty — framing intent, legitimising experimentation, and helping people make sense of a technology none of them fully understood.
What kept nagging at me was the next question: who helps the leader do that? I have spent my career around the organisations that serve SMEs, and I have a lot of respect for them. But as I sat with the interviews, I kept coming back to the particular blend of skills this work demands — and to how rarely it sits in one place.
The skills the work actually needs
Helping a leadership team adopt GenAI well asks for three things at once. You need genuine fluency in the technology as it actually is this quarter — not the brochure, and not last year's version. You need a real understanding of how organisations and people make sense of change, because adoption is an interpretive act, not an install. And you need the judgement to match the shape of the help to a field moving this fast — knowing when a small experiment beats a three-year programme.
Plenty of excellent people and firms hold one or two of those. The managed service partner brings deep operational command of the estate. The reseller brings real product expertise and knows how to deploy it. The strategy consultant brings change and organisational craft. What my research kept surfacing is that this specific role needs the three together — the technical, the organisational, and the interpretive — and that combination is genuinely scarce. That is the gap I became convinced was worth filling.
So I am building it
Requisite Intelligence — AI counsel for business leadership. The name is the thesis: an organisation can only cope with the complexity GenAI introduces if it can call on enough interpretive capacity to match it, and most leadership teams do not have that capacity to spare while the technology is still in motion. The work is to supply it. These articles were never a sales funnel — they were me thinking in public, and the thinking led here.
The work from here
The nine articles before this one were diagnosis. This is where diagnosis becomes practice. Everything the research surfaced — that readiness emerges through use rather than arriving first, that constraints are design parameters rather than excuses, that momentum depends on leaders making uncertainty discussable — becomes the way Requisite Intelligence works with a leadership team. Not a methodology to be administered, but a way of thinking alongside the people actually carrying the decision. The offer is deliberately plain, and I hope a little rare: an honest read on where an organisation truly is, what is worth trying next, and what is not worth doing at all.