§ 5.2 · /ai-transformation/discovery

AI Discovery — a structured way to find the real opportunities.

A 2–3 week engagement that gives you a prioritised roadmap, a realistic ROI model, and one specific first project ready to scope. Not a slide deck. Not a strategy document that dies in a shared drive.

What it covers.

Interviews with ops leaders

Across finance, order management, supply chain, and production — the functions where agentic AI has the most to offer mid-market operators.

Audit of existing workflows, data quality, ERP state, and integration surface

An honest read on what's ready for automation today, what needs cleaning up first, and where the integration work actually lives.

Assessment of agent-suitability per process

With explicit "not yet" calls where appropriate. Not everything should be agentic, and pretending otherwise wastes a year of budget.

ROI modelling

Cost of doing nothing vs. cost and benefit of automation. Numbers a CFO will defend, not marketing arithmetic.

Architecture recommendations

Cloud vs. local, autonomous vs. human-in-the-loop, build vs. buy — answered per process, not in the abstract.

A prioritised 12-month roadmap

With one project ready for immediate scoping. The output is a plan you can move on, not a framework you'll reread next quarter.

Who it's for.

CIOs and CTOs preparing a board-level AI plan
CFOs who've been told “find £500K of savings with AI”
MDs of PE-backed operators whose sponsors expect a credible AI thesis
Heads of Operations at businesses where the AI conversation keeps getting stuck in workshops

What it's not.

A generic “AI maturity assessment”
A capability audit against a vendor's product taxonomy
A piece of work that ends with a framework and no system

Commercial.

Fixed-fee engagement, sized to your operation and scope. Terms discussed on the discovery call. Deliverable in 2–3 weeks from kick-off.