AI Consulting

Usually between 50 and 75% below the full cost of a comparable British hire, once salary, employer national insurance, pension, recruitment fees and overheads are all counted. We place UK-based AI consultants, though most clients choose Eastern Europe, the Philippines or Latin America instead, since quality matches and cost does not, with Eastern Europe suiting British teams well at roughly an hour from London. The aim is the strongest quality-to-cost ratio available, exceptional advice at a sustainable price. AI consulting carries a premium in Britain because credible, hands-on strategy experience is scarce.

AI consulting is the work of deciding where AI genuinely belongs in your business, and just as importantly where it does not, before serious money gets spent. It covers feasibility, whether your data can support what you imagine, build-versus-buy judgement, model and vendor selection, cost modelling and the governance questions that arrive once AI touches customers. Teams bring in a consultant because the field moves faster than any internal generalist can track, and vendor claims need an independent, technically fluent sceptic. Consulting produces clarity, not software; if you know what to build, hire engineers instead.

Shipping history and scepticism, together; the consultant worth hiring has built AI systems that reached production and can tell you which of their own past projects should never have been started. Look for evaluation literacy, insisting on defining what good output looks like before anything is built, fluency in the economics of tokens, latency and hosting, and data judgement to spot that the real blocker is data quality rather than model choice. They should use AI heavily in their own work, showing where human judgement overruled the tool. Beware fluent slide-makers with no production scars.

Ask them to tell you about an AI project they advised killing, and why; consultants who have never recommended against a build are salespeople with better vocabulary. A good consultant should start asking about your data, your users and what failure would cost, rather than reaching for a framework. Ask how they would measure success on a project you have in mind, and listen for evaluation thinking rather than enthusiasm. It is reasonable to expect them to use AI tools fluently in front of you; their craft is judgement about these systems.

Demand is intense and the market is noisy, which is exactly the combination that produces expensive mistakes. Every board wants an AI answer, so consulting supply has ballooned faster than genuine expertise, and the buyer's problem is telling them apart. If you face a real decision, a build, a vendor selection, a data strategy, then yes, because the cost of a wrong turn dwarfs the fee. If nothing concrete is on the table, an engagement will manufacture recommendations to justify itself, and a small internal experiment usually serves better first.

Constantly, and for a consultant that is close to a professional obligation, since advising on tools you do not use daily produces advice that ages in weeks. Our consultants prototype with AI, analyse with it and pressure-test vendor claims against hands-on experience rather than documentation. Soundness comes from the discipline around it; recommendations are grounded in evaluations you can rerun, prototypes are built to be measured rather than admired, and anything AI-drafted is reviewed by the person whose name is on it.

The same CTO-led process every engineer faces, with extra weight on production evidence, because AI consulting attracts more confident talkers than any field we hire for. Candidates go through a technical assessment, live pair programming with a senior engineer on a realistic problem, a cultural fit screen and a psychometric assessment we built for software engineers. We push for specifics on systems that shipped, what was measured and what they would refuse to build again. How they use AI tooling is assessed directly.

You are typically interviewing matched candidates within 7 working days of a requirements call, and developers are often embedded and pushing code within about two weeks. From there it is a rolling monthly contract with 30 days' notice, one monthly fee, and no placement charges. You can scale up or down as the work changes, and you pay nothing to interview.

There is a two-week money-back guarantee, and if you want to continue we replace the developer free of charge. In practice this rarely comes up, because you interview a shortlist of two candidates who have already passed a CTO-led technical assessment and a live pair programming session, so the fit question is largely settled before anyone starts.