Baseline the current work
Observed, not surveyed: steps, hand-offs, wait time, rework, volumes and the hours each stage consumes today. Without this there is nothing to measure against.
AI Services
The tools were never the problem. The workflow was.
Giving everyone a chat assistant produces a lot of experimentation and very little change. Augmentation is different: one process at a time, redesigned end to end, with the new way documented, trained and measured.
The pattern we keep seeing
Licences went up. Cycle times did not.
Adoption statistics are not outcomes. These are the symptoms of tools without workflow change.
- High licence uptake, no measurable change to throughput or cycle time
- Everyone uses AI slightly differently, so nothing can be standardised or reviewed
- The AI-assisted step is followed by the same manual checks as before, so the time saving evaporates
- Quality is now inconsistent and no one can say whether AI helped or hurt
- Your best people quietly built a good way of working and nobody else knows about it
How augmentation works
One process, redesigned properly
We take a workflow that matters, and we do the whole job on it before moving to the next one.
Redesign the steps
Which steps AI drafts, which it checks, which it should never touch, and which disappear entirely. The redesign is done with the people who do the work, because they know where the exceptions live.
Set the standard
The agreed prompts, templates, review criteria and escalation rules - written down, so the workflow is repeatable rather than personal.
Fit it to the tools
Configured in whatever you already run, with the assistance placed inside the flow of work rather than in a separate tab someone has to remember.
Train the team on the new way
Role-specific, on live work, not a generic prompt-writing course. People learn the redesigned process, including when to override the machine.
Measure and correct
Same measures as the baseline, taken again at 30 and 90 days. Where the gain did not appear, we find out why and adjust.
In practice
What working with us looks like
The engagement runs with the people who do the work, not around them. Sessions are short, scheduled around delivery, and every stage ends with something you can act on.
You get a named consultant for the whole engagement - the person in the room is the person doing the work.
How it runs
Six to twelve weeks per workflow
1
Choose the workflow
We pick one with real volume, a measurable outcome and an owner who wants it fixed. Ambition comes later; the first one has to succeed.
- Volume, hours and pain quantified before selection
- A named process owner accountable for the change
2
Baseline
Two weeks of observation and data collection so the before-picture is factual.
- Time and motion across the real process
- Quality and rework rates captured
3
Redesign and pilot
The new process runs with a small group on live work, adjusted weekly.
- Weekly iteration with the team doing the work
- Exceptions and edge cases documented as they appear
4
Roll out and measure
Standard published, training delivered, measurement repeated at 30 and 90 days.
- Written standard operating procedure
- Reported gain against the original baseline
Deliverables
What you leave with
What you get
- Baseline measurement of the workflow as it runs today
- Redesigned process with the AI-assisted steps defined
- Written standard: prompts, templates, review and escalation rules
- Configuration in your existing tools
- Role-specific training delivered on live work
- 30 and 90 day measurement against the baseline
- A repeatable method your team can apply to the next workflow
What we will not do
We will not report adoption as a result. Seats used is an input; hours recovered, cycle time and quality are results, and those are what we measure.
We will not automate a step whose output nobody checks. If a mistake there would be expensive or unfair, a person stays in the loop and the design makes their check fast.
We will not redesign a process that should simply be deleted. Sometimes the honest finding is that the report nobody reads should stop being produced.
Where this fits
Related services and sectors
Questions
Questions about ai workflow augmentation
Training changes what people know; augmentation changes how the work runs. We usually do both - the training lands better when it teaches a redesigned process rather than generic tool use.
That is a decision for you, and you should decide it before we start rather than after. In most engagements the recovered hours go back into work the team could never get to - backlog, quality, the things that were being skipped.
Then we report that, and we look at why: the wrong workflow, an unchanged downstream check, or a tool that cannot do what was assumed. This happens, and finding it in week eight of one workflow is much cheaper than finding it after an organisation-wide rollout.
Often not. Most organisations already own more capability than they use. Where a new tool is genuinely needed we will say so, with the reasoning and the cost.
Pick one workflow and prove it
The audit finds the workflows worth starting with, ranked by hours and tractability.