Find Your
First
AI Win
Most enterprise GenAI pilots still don't show measurable P&L impact. We help you pick the one use case that pays for itself, launch it, and stop confusing motion with progress.
95%
OF GENAI PILOTS RETURN ZERO
1
USE CASE, PICKED PROPERLY
Days
TO FIRST PAYBACK
Most first AI projects are picked badly.
MIT Project NANDA analysed 300+ public AI initiatives in 2025 and found 95% had no measurable P&L impact. Gartner had already warned that at least 30% of GenAI projects would be abandoned after proof-of-concept by end of 2025. McKinsey's March 2025 State of AI says 78% of organisations use AI in at least one function, but only 17% say 5%+ of their EBIT is attributable to GenAI.
The pattern's familiar. A board asks for AI. Someone picks a use case that sounds interesting, not one that's worth building. The slide deck looks fine. Nothing changes on the invoice run.
The first one matters because it teaches the business what a useful AI project actually looks like.
TYPICAL FIRST PROJECT
- Chatbot on the website, nobody asked for
- "AI for everything" platform, six-figure licence
- Picked by IT, not by the team doing the work
- Data isn't ready, so the demo is faked
- No P&L owner, no number it has to move
- Quietly dies after the pilot
A FIRST WIN
- A task done daily, by a real team
- Bespoke build, sized to the saving
- Picked with the people who do the work
- Uses data you already have, cleanly
- One number it has to move, named up front
- Live in days, paid back the same quarter
A first AI win passes five tests.
We run every candidate through the same five questions. The ones that pass go on the build list. The ones that don't get killed before they cost anyone a quarter.
Visible on the P&L
Hours saved, deals closed, costs avoided. If finance can't point at the line it's moved, the project shouldn't be the first one.
Small enough to ship fast
If the first version can't ship fast, you've picked something too big. Split it down until it can, or pick a different one.
Data you already have
First wins use data that exists, in a system you already use. If it needs a new data warehouse first, it's a second-year project.
Safe to get wrong
A human checks the output, or the cost of an error is small. The team needs room to spot what's working without a board-level incident every Friday.
An owner who wants it
A named operator whose number it moves. Not IT, not a vague business owner. The person who's emailed about it on a Monday morning.
Where we come in.
A focused discovery, a scored shortlist, then we build the top one. No twelve-month roadmap, no PowerPoint deliverable. You see the first version running on your data before we send a second invoice.
We don't sell licences and don't earn referral fees from model providers. The right answer is whichever AI tool, or no AI at all, actually moves the number.
BOOK A DISCOVERY CALLDiscovery
We sit with three or four teams. Sales, ops, finance, support. We watch what they do, ask where the time goes, and read the systems they use. By the end we've got 15 to 25 candidate use cases written up the same way.
Score and shortlist
Every candidate's run through the five tests and plotted on value against feasibility, like Gartner's use-case prism. You get the full list with our reasoning, a top three, and a recommendation for which one to do first. If the right answer's no, we'll say so.
Launch the first one
Fixed scope, fixed price, fixed deadline. We build the chosen use case end to end. Real data, real users, the same systems your team already opens every morning. Live fast, measured against the number you said it had to move.
Hand over a real roadmap
After the first one's live, you've got proof, a measurement habit and a team that's seen it work. We write the next year's plan against the same five tests, so the second and third wins don't need us to pick them.
The first one really does decide the rest.
Four numbers from credible research. They all point at the same problem: the use case has to be chosen for value and feasibility before anyone builds.
95% return nothing.
MIT Project NANDA's State of AI in Business 2025 analysed 300+ public AI initiatives. 95% delivered no measurable P&L impact, despite $30bn to $40bn of spend.
30% killed after PoC.
Gartner: at least 30% of GenAI projects will be abandoned after proof-of-concept by the end of 2025. Cited reasons: poor data quality, weak risk controls, costs, unclear business value.
78% adopt, 17% see 5%+ EBIT.
McKinsey's State of AI (March 2025): 78% of organisations use AI in at least one function. 17% of respondents say 5% or more of their EBIT is attributable to GenAI.
14% of micro firms, 36% of large.
DSIT's AI Adoption Research: 36% of large UK businesses and 23% of mid-sized firms are using AI, against 14% of micro businesses. That's the adoption gap UK SMEs are dealing with.
Sources: MIT Project NANDA (State of AI in Business 2025); Gartner press release, 29 July 2024; McKinsey State of AI, March 2025; UK Department for Science, Innovation and Technology, AI Adoption Research.
It's 70% people, 20% data, 10% AI.
BCG puts the split at roughly 10/20/70. Ten per cent of the value comes from the algorithm. Twenty comes from the data and technology. Seventy comes from people and process.
If you've already paid a vendor for the ten per cent and nothing's moved, that's why. The other ninety per cent is what we pick for, and what we build around.
McKinsey's March 2025 numbers say the same thing: out of 25 attributes tested, workflow redesign had the biggest effect on EBIT impact from GenAI.
The model
The bit everyone talks about. Pick a sensible one, move on.
The data and plumbing
Get the inputs clean, the outputs into the system the team already uses.
The people and the workflow
Who does what, when. What gets cut, what gets kept, who checks the output. This is where first wins are won and lost.
The ones we get asked first.
We've already done a pilot. Is this for us?
Especially. A previous chatbot, Copilot rollout or no-code agent is useful evidence. The first win is the first one that actually moves a number, which is rarely the first one anyone tried. The previous attempt shows what your business will and won't use.
How is this different from a big consultancy engagement?
This is narrower. One working system, on your data, with a number it has to move. We do the discovery and the build ourselves, so the advice has to survive contact with the actual workflow.
What if AI is the wrong answer here?
Then that's what we say. A lot of the time the answer's a small internal tool, a tidied-up workflow, or a piece of automation that's barely AI at all. We aren't paid commission by model providers, so we'll happily recommend the cheapest thing that moves the number.
Our data's a mess. Should we sort that out first?
Not as a separate programme. The first win runs on the data you've got, with the cleaning that the use case actually needs. Fixing all the data first is how three-year AI programmes get started and quietly end.
What size of business is this for?
UK SMEs and mid-market firms, roughly £2m to £200m revenue. Big enough to have repeated workflows worth automating, small enough that one good first win shifts the company. If you're under £2m, we'll usually point you somewhere cheaper.
Who needs to be in the room?
One leader who can call it (CEO, MD or COO usually), plus two or three operators whose teams the work will land on. Not a steering committee. The whole discovery's eight to ten people, not fifty.
How much does it cost?
Discovery's fixed-fee. The first build is scoped against the chosen use case, fixed price per phase, usually a fraction of the saving it'll make in year one. You sign one phase at a time. No retainers.
What happens after the first win?
You've got the shortlist, the scoring, the team's confidence and a measurement habit. Most clients pick the next two off the same list and run them themselves. Some keep us on to build them. Either's fine. The point's that you don't need us picking for you anymore.
Pick one. Launch it. Then the rest.
Thirty minutes. Tell us what you've already tried, where the time goes, and which board number nobody can move. You'll come away with a clear view of what a first win looks like in your business, and whether you need us to build it.