AI adoption strategy
Where AI creates real payoff in your business, and where it is an expensive distraction.
- Engagement
- Fixed-scope engagement
- Typical timeline
- 4 weeks
- Starts with
- Interviews with one owner from each business function.
The board wants an AI plan, your team has tried a few tools, and nobody can separate the parts that would genuinely pay from the parts that make good screenshots. Meanwhile staff are pasting company data into consumer chatbots.
Clear go or no-go calls backed by cost, risk and impact modelling.
What we build
Concrete artefacts, handed over and documented.
Use-case register: every candidate scored on value, feasibility, data readiness and risk
A cost model per use case, tokens, infrastructure, review time, at realistic volume
Governance pack: acceptable-use policy, data-handling rules, approval and audit path
Two pilots specified to build level, with the accuracy bar each must clear
Twelve-month sequence separating pilots from production commitments
What changes
An AI plan the board can approve because it has costs and risks attached
Staff have a sanctioned route, so company data stops leaking into consumer tools
Pilots have a pass mark before they start
How it runs
- Weeks 1–2
01Register
We interview each function and collect every candidate use case, including the ones already running unofficially.
- Week 3
02Score and cost
Value, feasibility and running cost per case, with the data gaps named.
- Week 4
03Governance and pilots
The policy pack, and two pilot specifications with measurable accuracy targets.
Chosen per project. Named here so you can see the shape of it.
- OpenAI
- Anthropic Claude
- Azure OpenAI Service
- Microsoft Purview
Questions we get asked
Tell us the outcome, not the tooling.
Send us the situation you are in. We will tell you which discipline it belongs to, what we would do first and what it costs, including when the answer is to wait.