AI CONSULTANCY IN LONDON AND SURREY

Depends who’s asking. CEOs usually want to talk strategy, COOs want bottlenecks fixed. We start with questions, not tools. Sometimes we’ll run through a case study, sometimes we just dig until the right use cases fall out. Only then do we talk about ai strategy or implementing ai, otherwise it’s just theory.

Look, it depends on the job. Automating reports? You don’t need perfect data. Forecasting demand? Then yes, data quality matters. We run a quick prototype and see what comes back. If it works, we move. If it doesn’t, you either fix the dataset or drop the use case. That’s how organisations avoid wasting money on ai adoption that was never going to scale.

Honestly, more than you first think, but usually less than the value it brings back. A small automation? Not much. Rebuilding part of the supply chain? That’s a bigger ai investment. The trick is staging: start with something that proves business value, then scale when the board can see the benefits. Otherwise you’re just writing blank cheques.

Start tiny. Test how artificial intelligence behaves with one process before rolling it anywhere else. Add guardrails: controls, monitoring, audit trails. Call it ai governance if you like, really it’s just good risk management. No project is risk-free, but if you break it into steps, boards stay in control and nothing runs away from you

Both. At the start it’s you, we can’t map anything without context. Then it’s mostly us, our team, the ai consultants and the data scientists doing the heavy work. At the end it swings back, because adoption doesn’t happen without you. And we always hand things over properly, knowledge transfer built in, so you’re not stuck with us forever.

Then the use case was wrong, or the design missed the mark. People don’t adopt tools that make life harder. AI should feel invisible, slotting into daily work. If ai implementation adds clicks or slows people down, it won’t stick. That’s on the design, not on the people.

No. It’s the hot thing, yes, and generative ai is useful. But not everything. Sometimes it’s forecasting, sometimes supply chain, sometimes just automating the boring stuff. Our job as an ai consultancy is to say “this is worth it, that’s not”, not to sell you whatever’s trendy this month.

Kill it. Don’t drag it out. Even global leaders like Amazon walked away from projects that didn’t pay back. If ROI’s not there, stop, pivot, try another. AI investment has to be staged, small bets, see results, double down only where the value’s real.

Depends. Small stuff, automating reports, streamlining a workflow, you’ll see wins in weeks. Bigger plays take longer. We always push for a quick pilot so the board can see business value early. No point waiting a year to find out. That’s how ai adoption builds momentum.

Start simple. Did it save money? Did it reduce overheads? Did customers notice? ROI isn’t just numbers on a slide, it’s real business value the organisation can feel. We run prototypes, measure outcomes, and if it doesn’t deliver, we stop. If it does, then we scale the ai implementation.

It’s about picking the right fights. Maybe it’s supply chain, maybe marketing, maybe customer experience. Not every use case gives you competitive advantage. Our experienced ai consultants help organisations spot where AI gives leverage. You don’t need to do everything, just the things that actually move the needle for your business goals.

You can hire another ai consulting firm, and you should talk to a few. What you get with us is simple: integrity, domain expertise, and a track record. We spend money like it’s ours. We’re business owners too, we know payroll pressure and reporting deadlines. We won’t sell things you don’t need. We judge ourselves the same way boards do, by delivery.