Services
Assess. Advise. Build. Embed.
Most AI advice comes from people who've never had to make it work inside a real organisation, with real constraints, real risk committees, and real budget owners. I've spent ten years inside manufacturing, FMCG, telematics, and regulated financial services, most recently leading technology through an AI adoption programme in wealth management.
I help leadership teams work out where AI is genuinely worth deploying, where it isn't yet, and how to get something running without creating a governance headache six months later.
Three ways to work together
Assess
An honest read of where you actually stand.
Most organisations don't need more AI ideas. They need to know whether their data, governance, and delivery capability can support the ones they already have. I run a structured assessment against your own constraints — not a vendor's maturity curve — and hand you an AI Readiness Report that tells you what's ready, what isn't, and what to fix first.
- –AI readiness assessment across data, governance, and delivery capability
- –Gap analysis benchmarked against your constraints, not an industry framework
- –An AI Readiness Report with a sequenced action plan — what to fix first and what can wait
Typically 2–4 weeks. Most clients start here — even the ones who think they already know.
Advise & Build
The strategy and the working system. Same person.
Once the assessment surfaces what needs to change, we redesign the operating model — who owns a use case, how a pilot gets funded past the demo, what governance signs off — and then I build it: agents and workflows integrated into the tools your team already uses, working alongside your engineers and data teams rather than around them. Working systems against your real data and your real constraints, not a deck that only survives the sales room.
- –Operating model redesign: ownership, funding, and governance for AI — not another framework diagram
- –Hands-on build: agentic systems built against your own data, working alongside your technical team
- –A defined handover point. The goal is a capable team, not a permanent retainer
Typically 8–16 weeks depending on scope. The big firms advise but don't build. The dev shops build but don't advise. I do both.
Embed
Your team learns AI by shipping it into their real work.
Most AI training fails the same way: a workshop, a slide deck, a prompt cheat-sheet, and everyone is back to old habits by Thursday. I embed with your team for six to eight weeks. We take their actual problems — the reports, the reconciliations, the drafting, the analysis — and solve them with AI, together, in the session. They keep what they build.
- –Weekly working sessions on real tasks from your team's backlog, not hypothetical exercises
- –Staff build their own agents and workflows alongside me, inside your existing tools and governance
- –A capstone session where everyone demos what they've shipped into their actual job
Six to eight weeks. The measure isn't attendance — it's whether your people are still using what they built a month after I've left.
If the above is not quite what you're looking for, let's chat about something more bespoke. I am also available for speaking at events, running training sessions, and fractional Chief AI Officer engagements.