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AI implementation
We are an AI implementation consultant for UK organisations turning AI pilots into systems people use, with the controls, training and human checkpoints that make them stick.
In focus →
Where the line sits
Plenty of organisations have tried AI in a pilot.
Far fewer have a system in daily use, owned by the business and trusted by the people who rely on it.
The gap is rarely the model.
It is data, process, ownership, training and clear rules about when a person steps in.
That gap is the work of an AI implementation consultant, and it is where we focus.

What the AI takes on
Where people stay in the loop
Pilot to production
We start by auditing the pilot: what it does, what data it uses and how good it really is.
We test it against past decisions made by your people, so accuracy is measured rather than assumed.
Then we design the production workflow, including thresholds, review queues and escalation routes.
The government’s adoption research found only about a third of firms planning to use AI feel ready to implement it.
Our job as an AI implementation consultant is to close that readiness gap with a clear plan and working controls.
Illustrative batch with a typical confidence spread. Your real split comes from a pilot on your own work. Some decisions go to a person whatever the score.
Change management
Many AI projects stall because people do not trust the output or do not know when to overrule it.
We involve the people who will use the system from the first week, not the last.
Reviewers learn what the AI is good at, where it fails and how to escalate.
Managers learn how to read the monitoring reports and when to pause the system.
Where wider upskilling is needed, we connect the rollout with AI literacy training.
We also agree how staff can raise concerns about the system and how those concerns are answered.
Good adoption work makes the change stick after the consultants leave.
Controls
Going live is not the end of human involvement.
The UK government’s AI Playbook calls for meaningful human control at the right stages.
We make that concrete: who reviews which cases, how often samples are checked and who can switch the system off.
For a management system view, ISO/IEC 42001 gives a recognised structure for AI governance.
We map your controls to it where that helps, without treating a certificate as the goal.
If you want an independent view of those controls, see our AI assurance work.
Going live is not the end of human involvement.
How it works
Each system ships with a named person accountable for what it does.
01
We measure what the pilot really does against past human decisions.
02
We set thresholds, review queues, escalation routes and ownership.
03
We go live with one team, watch the overrides and fix what they reveal.
04
We train reviewers and owners, then hand over monitoring and change control.
Questions
Further reading
Keep reading
Next step
A 30-minute call. We map one workflow, what the AI could take, and where a person must stay in the loop.