AI adoption
AI that earns its place in the operation.
Established companies do not need more AI pilots. They need a few that work, are measured against a baseline and are governed well enough to scale. Our method is deliberately meticulous: map before you build, prove before you scale.
The problem
Why most AI efforts stall
Pilots without a baseline
Nobody measured the process before the pilot, so nobody can show what it gained. The pilot ends as an impression, not a result.
Tools before workflows
Licences are bought and demos are impressive, but the work itself is unchanged. Value comes from changing how the work is done.
Governance at the end
Data protection, security and the EU AI Act surface just before rollout, and stop it. Designed in from the start, they make scaling safe.
The method
Five phases, each with a gate
No phase starts until the previous gate is passed. That is what makes the method slow at the start and fast at the end.
- 01
Map
Walk through the real workflows with the people who do them. Inventory the data. Measure time, cost and error rates as they are today.
OutputProcess map, data inventory and a measured baseline.
GateThe process owner agrees the baseline.
- 02
Prioritise
Score each use case on value, feasibility, data readiness and risk. Choose two or three, not twenty.
OutputA ranked portfolio of use cases.
GateEach chosen case has a business owner and a budget.
- 03
Prove
Build the smallest pilot that tests the riskiest assumption, in real work, for a fixed period, with a stop rule set in advance.
OutputA measured result against the baseline.
GateThe target is met, or the pilot is stopped.
- 04
Govern
Data protection under GDPR, risk classification under the EU AI Act, security, human oversight, model and vendor choice, documentation.
OutputA governance file and operating rules.
GateSign-off by the business owner, data protection and security.
- 05
Scale
Roll out, train people and change the process, not just the tool. Monitor quality and cost every month.
OutputRunning in production with agreed measures.
GateBenefits hold three months after rollout.
Principles
What “meticulous” means in practice
- 01
Measure before and after
Without a baseline there is no result, only an opinion. We measure first, even when it feels slow.
- 02
The people who do the work design the change
They know where the time goes and where errors creep in. Adoption follows when they shape the solution.
- 03
The smallest thing that proves value
A spreadsheet, a prompt and a review step often prove more in a fortnight than a platform does in six months.
- 04
Stop rules set in advance
Before a pilot starts we write down what result would end it. Otherwise every result looks like success.
- 05
Keep your options open
Models change monthly. We design so that models and vendors can be swapped and your data stays yours.
- 06
Agents under supervision
When AI takes actions, not just writes text, it gets clear permissions, full logs and a named person accountable.
Contact
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Whether you are weighing an investment, preparing your company for AI or building something new, we are glad to talk.