AI consulting for established UK firms

AI consulting that turns scattered tools into systems that pay back.

Your team is already using AI. The opportunity is to turn that activity into measurable value. I help you find the work worth changing, test the smallest useful approach, measure the result and build only what earns its place.

A decade of experiments for a UK bank, Vitality, RNLI and Farrow & Ball. Building production AI inside a UK bank since 2023.

Direct reply from me within two business days. No sales sequence.

Steve Quinlan
£33,150
saved a year at a UK bank, from one AI-supported review system.
Tested, not borrowed
What I mean by AI consulting

Decide where AI can create value. Prove it before you scale.

AI consulting is hands-on help to decide where AI can create measurable value in your business, then prove it before you scale. I map the real work, identify the bottlenecks and risks, quantify the opportunity, and set the next move. The output is a decision your team can act on, not a tool list or a strategy deck.

Where the value starts

The opportunity is already inside the work.

AI value rarely begins with a transformation plan. It begins with the person who knows a process is too slow, a decision is too hard, or a handoff keeps breaking. I work with the people closest to that work, map what actually happens and test the smallest change that can improve a real number.

Most firms have already started using AI. The missing piece is a way to learn across the business. Useful experiments stay on one person’s laptop. Bad ideas get repeated elsewhere. Leaders see activity, but cannot tell what is worth backing.

The consultancy turns that scattered effort into three things:

01
A ranked view of the opportunity.
Where AI could improve speed, quality or capacity, and where it is not worth the risk.
02
Evidence a decision can survive.
A baseline, a measured result and a value case built from your own numbers.
03
A system the team can own.
What works becomes repeatable. What does not gets stopped while it is still cheap.
One discipline, two scales

The scale changes. The test-and-learn discipline does not.

The Edge Loop is the principle behind the brand: pick, test, measure, keep, stack. For one person, it builds an advantage around their work. Inside a firm, the same discipline turns scattered use into shared evidence and repeatable systems.

The Edge Loop
AI Edge at work
Consulting at firm level
01 · Pick
Pick a real task
Choose a workflow that matters to the business
02 · Test
Test an AI approach
Run a bounded pilot against the way the work happens now
03 · Measure
Measure the result
Compare time, quality, risk, capacity and cash
04 · Keep
Keep what works
Decide to scale, change or stop from evidence
05 · Stack
Stack the gain
Turn the proven approach into a system the team owns

The Edge Loop shapes the judgement. The Sprint Method structures the AI Opportunity Roadmap.

Tested, not borrowed becomes a commercial rule: no AI initiative earns the next pound until it has proved a result.

Prove it first
Consulting routes

Start with the smallest engagement that can answer the question.

I do not ask you to pick an offer before we understand the problem. Start with the work that is stuck, slow or difficult to value. I will recommend the smallest useful route, including doing nothing if there is no credible value case.

Primary consulting engagement
3 to 4 weeks · Scoped per firm
The AI Opportunity Roadmap

For firms whose AI use has grown in pieces and needs a clear order. I interview leadership and the people doing the work, map the workflows in scope, cost the bottlenecks and opportunities in hours and cash, then rank the moves.

You leave with a costed, sequenced 90-day plan. It shows what to do now, what to test next and what to leave alone. It is built for a board decision and for the people who have to act on it.

Explore the AI Opportunity Roadmap →
A bounded session · Your real work
One measurable outcome
Practical AI Workshops

For a team with a real workflow or decision to work through together. The session uses your work, not generic prompt demonstrations. We map the problem, score the most credible opportunities and shape the next experiment.

You leave with two or three opportunities, an owner for the first test and a clear measure of success. Workshops are available when the team context and measurable outcome are clear.

Ask about a practical workshop →
A specific decision · A proposed build
A brief that needs challenging
Focused advisory and second opinions

For work that does not need a full Roadmap. I can pressure-test an AI proposal, challenge the value case, help shape a first experiment, or give a vendor-neutral view before you commit budget.

If there is a better route than bringing me in, I will say so.

Start a conversation →
For website or agent-experience questions, the AX Audit is available when the problem naturally calls for it. It is specialist work, not the main route into the consultancy.
What the business gets

Value you can defend, not activity you can count.

01
A clearer decision.
One ranked view of what to do now, next and not yet.
02
A number finance can question.
Baselines and value estimates built from your own frequency, time, cost and quality data.
03
A safer first move.
A bounded test with explicit quality and risk guardrails, plus a stop condition.
04
Capability that stays.
Your team owns the method, the evidence and the next decision. The consultancy does not become a permanent dependency.
Why this is my work

I have spent a decade finding what actually moves a number.

AI is a new context. The evidence discipline is not.

93%
less time per review

At a UK bank, I designed an AI-supported system for GEO and code reviews. It reduced each review from five hours across three roles to 20 minutes with one engineer: 93% less time, 486 hours and £33,150 saved a year at two reviews a week. The engineer now spends the time acting on the findings, not producing them.

486 hrs
saved a year, at two reviews a week.
£33,150
saved a year on the same work.

Before AI, the same approach produced

+28%
donation journey conversion at RNLI. That result helped make the case for the wider experimentation programme.
+14%
health quote leads at Vitality.
+162%
year-on-year colour consultant bookings at Farrow & Ball.

The contexts changed. The pattern did not: start with the real work, establish the baseline, test the assumption, measure the result and use the evidence to decide what happens next.

Read more about my experience →
Who I work with

Built for established UK firms without a dedicated AI team.

I work with CEOs, MDs and operations leads at established UK firms with £2m to £20m revenue. You are past the founder-only stage, but you do not have a large data or AI team. Sector matters less than the shape of the problem.

This is usually a good fit when:
  • People already use AI, but the results are scattered and hard to compare.
  • A repeated workflow is slow, expensive or limited by handoffs.
  • Leadership needs evidence before committing more budget.
  • The team wants to build internal capability, not outsource the judgement.
It is not the right fit when:
  • You want generic AI awareness training with no work outcome attached.
  • The tool has already been chosen and you only need someone to implement it.
  • The people, process or data needed to establish a baseline are unavailable.
  • The brief starts with “transform everything” rather than one result that can be measured.
The process

Start with the problem. Scope the work from there.

1
Step 1
Tell me what you are trying to fix.
A repeated task, a stuck decision, a proposed investment or a team problem is enough. You do not need a finished brief.
2
Step 2
We test the fit.
A short call establishes the outcome, the people involved and whether there is a credible route to value.
3
Step 3
I recommend the smallest useful engagement.
Roadmap, workshop, focused advisory, a specialist audit, or no engagement.
4
Step 4
We agree the measure before the work starts.
Scope, outcome, timeline, fee and boundaries are written down.
5
Step 5
You finish with a decision and ownership.
The evidence, artefact and next move stay with your team.

The first conversation costs nothing. There are no open-ended retainers by default and no invoice you have not agreed to in advance.

Common questions

Questions I get asked before we start.

AI consulting is hands-on help to decide where AI can create measurable value in a business, prove the result and turn what works into a repeatable system. My work starts with the workflow and the business outcome. It does not start with a preferred tool.
I interview the people involved, map how the work happens, establish a baseline, quantify the bottlenecks and opportunities, and shape the next test. Depending on the problem, that becomes a Roadmap, a workshop, focused advisory or specialist audit.
The AI Opportunity Roadmap runs across 3 to 4 weeks. A Practical AI Workshop is a bounded team session with preparation and a clear follow-up. Focused advisory is scoped around the decision. Every engagement has a defined start, finish and outcome.
The first conversation is free. The AI Opportunity Roadmap is scoped and quoted per firm because the workflows and depth of mapping vary. Workshops and advisory are priced against the agreed outcome and scope. You see the fee and boundaries before you decide.
The Roadmap is diagnostic and prioritisation work. I can help shape or test a first solution when that is the smallest useful next step. A larger implementation is scoped separately or handed to your internal team or delivery partner, with the evidence and requirements they need.
An agency usually builds against a brief. A training course teaches a general capability. My consulting starts one step earlier: deciding which work is worth changing, what result would count, and how to prove it before more budget is committed.
Yes, when the audience and outcome are clear. Workshops use the team’s real work and end with a measurable next move. Talks and keynotes focus on AI experimentation, building value from evidence and moving from scattered use to systems that work on repeat.
The specialist AX Audit is available when a website or agent-experience problem naturally calls for it. The former fixed-price AI Visibility Scorecard is parked and is not a bookable product.
My focus is established UK firms with £2m to £20m revenue. I will consider enquiries from outside the UK and be direct about whether the method fits the market and context.
Start here

Bring me the work that should be working better.

You do not need an AI strategy or a finished brief. If there is a repeated task, a stuck decision, a proposed AI investment or a team problem you think should be working better, tell me. I will reply within two business days and tell you whether I can help.

One enquiry, one reply. No autoresponder and no sales sequence.