Buyer guide

How to choose an enterprise AI consultancy in the UK

Choosing an enterprise AI consultancy in the UK comes down to four inspectable checks: who writes the code, one production workflow with measurements and their provenance, governance implemented as controls rather than documents, and what the client keeps when the engagement ends.

Enterprise AI consultancy. A consultancy that takes an organisation from AI strategy to governed systems running in production, combining architecture, hands-on engineering and implemented controls rather than advice alone.

Four checks, and how to read a pitch

  1. Ask who writes the code

    Meet the people who would deliver, not the people who sell. Firms where the same people write the strategy and the code cannot hide behind a handover.

  2. Ask for one workflow in production

    Ask for one real workflow taken to a system people use daily, with the measurements and their provenance stated. A demonstration is not that proof.

  3. Ask whether governance is implemented as controls

    Identity, permissions, deterministic checks and human gates are inspectable. Policy documents and committees are not.

  4. Ask what you keep when they leave

    The client should own the code, the architecture and the operating model, with a written handover, and be able to continue without the consultancy.

The four checks to use when choosing an enterprise AI consultancy in the UK, and what a pitch looks like against each one.
DimensionWhat a pitch looks like
Ask who writes the codeA partner sells the work and a separate bench builds it.
Ask for one workflow in productionA slide deck, unused seats, or a figure with no source.
Ask whether governance is implemented as controlsA governance workstream that produces a policy set and a steering committee.
Ask what you keep when they leaveA change-request route back to the firm, or knowledge that leaves with the team.

What production proof looks like, from work we have shipped

These four checks are answerable from production systems, not from a demonstration. The figures below are already published on our engagement files, each with its provenance. We are based in Stoke-on-Trent and deliver across the UK, the Gulf and the US.

Who writes the code
At 1AYM the people who write the strategy write the code. Every engineer is certified on the platforms we build on or has shipped inside a top-tier engineering organisation. Meta, Spotify, UBS, Starling Bank, S&P Global and Sky are former employers of our engineers, not clients.
One production workflow
A government-accredited EdTech's speaking assessment runs as a measuring instrument on the live estate: 3,141 live student records on 21 August 2026, counts from the production database, and an automated test estate grown from around 300 tests to more than 1,400. A PE-backed marketing agency's platform sessions cost 60% less on average after we re-architected its skills estate, by our own measurement. Identity provisioning for 1,000+ users across 600+ groups has been running for seven months.
Governance as inspectable controls
The pattern we implement is the model proposing and something deterministic deciding: an agent drafts, and validators, reconciliations and human gates decide what proceeds. Evaluation runs in CI. We hold no ISO or SOC certification; controls are evidence, not a substitute for a certificate.
What the client keeps
Architecture, code and operating model are documented and handed over. Nothing depends on us staying.
Vendor status is disclosure, not proof of fit
1AYM is an OpenAI Select Partner: a company status, not a certification, and not evidence of fit by itself. The founder holds Claude Certified Architect – Professional and Claude Certified Associate – Foundations, independently verifiable on Credly. 1AYM holds no partner status with Anthropic. Another client environment reached 91% adoption in North America, a figure published in the Anthropic customer case study.

The market is four different businesses wearing one label

Search for an AI consultancy in the UK and the results mix four kinds of firm that share a label and almost nothing else. Which one you need depends on the problem, and most bad engagements start by buying the wrong kind, not the wrong firm.

The Big Four and large systems integrators
Built for board-sponsored, multi-year transformation with global delivery and regulatory cover. Genuinely good at programme management at scale. The trade-off is a partner who sells, a bench that builds, and a cost structure that needs a large programme to justify itself.
Specialist consultancies
Senior practices where the people who scope the work deliver it. Suited to organisations that want a production system, a working operating model and their own capability at the end, without funding a programme office.
Staff augmentation
Sells individual engineers by the week. Useful when you already have the architecture and the leadership and simply need hands. It transfers no design responsibility: if the system is wrong, that is your problem.
Automation agencies
Assemble chatbots and workflow tools quickly for SME budgets. The right answer for small internal conveniences, and the wrong one for anything that touches a ledger, a regulator or a system of record.

What the market actually charges, from the only prices firms publish by name

No UK body publishes a genuine benchmark of consultancy fees. The Management Consultancies Association publishes market size rather than prices, Source Global Research publishes pricing sentiment with the detail behind a paywall, and the Crown Commercial Service publishes its consultancy framework's grade structure and the fact of contractual caps without the figures. The fee guides that circulate online cite nobody, which is why their numbers disagree with each other.

The only public, firm-attributable prices in the UK are the per-day fee schedules suppliers must publish to sell through the government's G-Cloud framework. G-Cloud 14 is in force until October 2026, with a successor announced in August 2026, and most of its cards were priced in April and May 2024. Read them as a floor rather than a quote: ONS figures put producer price inflation for professional, scientific and technical services at 3.5% in the year to the first quarter of 2026.

Suppliers price against SFIA, a seven-level seniority scale, which is what makes the cards comparable. The figures exclude VAT and assume an onshore person-day with professional indemnity cover included. At level 5, the senior specialist grade, published prices run from £800 to £2,380 a day across the eleven supplier fee cards read for this page on 1 September 2026, with a median of £1,500. The large firms sit at the top of that level: Accenture, Deloitte and KPMG publish £1,580 to £2,380 at level 5 and £1,880 to £2,855 at principal or partner level. Practices outside the large firms publish £800 to £1,400 for the same level, with Fusion AIX at the floor of that band. Whole engagements carry fixed prices too. On its G-Cloud 14 card Gartner prices whole engagements rather than days, publishing £70,200 for AI use case elicitation and prioritisation, £142,400 for an AI capability maturity assessment and £203,500 for an AI strategy and roadmap.

What surprises buyers in the catalogue is that the large firms do not simply price higher. Across whole listings their published bands are wider at both ends, typically holding lower floors as well as higher ceilings, and the floor is where the misreading happens.

None of which makes a published figure a quote. The useful question is not the price of a day but what a fixed scope delivers and who carries the risk when the work runs long. 1AYM sells three shapes: fixed-scope statements of work, a retained architecture engagement, and engineers embedded in a client's own programme. None of them is priced on this page, and the embedded engagement states its commercial terms on its own page. Four things in the same public record are worth more to a buyer than the bands themselves.

The headline low is not the specialist
Accenture's G-Cloud listing spans £95 to £2,240 a day. Its own fee card explains the spread: £95 buys a level 1 junior working offshore, while the onshore senior specialist at level 5 is £1,580. A quoted figure carries no information until you know who does the work and from where.
What a person is paid is not what a firm charges
Advertised interim figures for individual AI and machine learning specialists sit at a median of £560 to £600 a day, depending on the specialism (IT Jobs Watch, six months to September 2026). That is a multiple below firm pricing at comparable seniority, and the gap is overhead, cover, insurance and margin. A firm quoting at individual level is worth interrogating on what carries the delivery risk.
Paying for time is not paying for an outcome
The National Audit Office, reviewing government spending on external consultants, found that input-based pricing “often fails to deliver the best value for money”, and that outcome-based payment may offer better value where the outcomes are clearly measurable. That is third-party support for buying a fixed scope over open-ended time.
Nobody publishes the independent tier
There is no public, primary source for what a senior specialist working alone charges a client: G-Cloud publishes no headcount, and recruitment guides measure what a person is paid rather than what a client pays. Bands for that tier circulate widely and cite nothing, so this page does not invent one.

Ask who writes the code

The single most predictive question in selection. Firms where strategy and engineering are separate departments produce strategies that engineering quietly rewrites, and systems that drift from the deck that sold them. Firms where the same people write the strategy and the code cannot hide behind the handover, because there is none.

Ask to meet the people who would deliver, not the people who sell. Ask what they personally shipped in the last quarter. A practice that cannot answer that question with named systems is a broker.

Ask for one workflow in production, then read the proof properly

Demonstrations are cheap and production is expensive, so production is the evidence that matters. Ask every candidate for one real workflow they took from ambition to a system people use daily, and how long it took.

Then read the numbers with their provenance attached. A figure published by the client, a figure the consultancy measured, and a forecast are three different strengths of evidence, and a firm that blends them into one claim is telling you how it will report your programme too.

Governance you can inspect beats governance you can read

Every firm will say the word governance. The separating question is where it lives. If the answer is a policy document and a committee, the controls depend on people remembering them. If the answer is identity and permissions the system enforces, deterministic checks that gate what an agent may do, evaluation that runs on every change and human approval on consequential actions, the controls hold when nobody is watching.

The pattern to look for is the model proposing and something deterministic deciding: an agent drafts, and validators, reconciliations and human gates decide what proceeds. A consultancy that cannot describe its gating pattern in that level of detail has not built one.

Vendor position: partner status is disclosure, not proof of fit

Most AI consultancies hold some vendor relationship, and the honest ones state it plainly, because it shapes advice. A reseller attached to one vendor will recommend that vendor. A model-selective practice chooses by workload and production evidence, and can show you systems running on more than one stack.

Partner statuses are worth reading precisely. 1AYM, for example, is an OpenAI Select Partner: a company status that describes a relationship with the vendor, stated so a buyer can weigh it, not evidence by itself that the firm fits your problem. Treat any partner badge the same way, from any firm: as a disclosure to interrogate, not a shortcut past the four checks above.

Ask what you keep when they leave

The end state of a good engagement is that the client owns the code, the architecture, the operating model and the capability, and could continue without the consultancy. Ask directly: what do we own on the last day, who can run it, and what does it cost to keep running.

Firms whose commercial model depends on you being unable to leave will resist that question. That resistance is the answer.

When a consultancy is the wrong answer

If the problem is a well-served product category, buy the product. If you have strong engineering leadership and a clear architecture, hire or borrow engineers instead of buying design you already have. If nobody senior owns the outcome internally, fix that first, because no external firm can substitute for an absent owner.

A consultancy earns its fee where strategy, architecture and engineering have to move together and the organisation wants to keep the result: taking the first governed workflow into production, standing up the platform and controls around it, and transferring the capability to run it.

Sources

  1. [1]Crown Commercial Service, G-Cloud 14 framework RM1557.14 (2024)
  2. [2]Accenture (UK), G-Cloud 14 data science services listing (2024)
  3. [3]Accenture (UK), G-Cloud 14 SFIA fee card (2024)
  4. [4]Deloitte, G-Cloud 14 specialist pricing document (2024)
  5. [5]KPMG, G-Cloud 14 SFIA fee card (2024)
  6. [6]Faculty Science, G-Cloud 14 pricing document (2024)
  7. [7]Fusion AIX, G-Cloud 14 SFIA fee card (2024)
  8. [8]Gartner, G-Cloud 14 pricing document (2024)
  9. [9]National Audit Office, Lessons learned: the government's use of external consultants, HC 1381 (2025)
  10. [10]Office for National Statistics, Producer price inflation, UK: March 2026, including services January to March 2026 (2026)
  11. [11]IT Jobs Watch, Artificial intelligence: UK interim market pay (2026)

Frequently asked questions

What four checks should you use to choose an enterprise AI consultancy in the UK?

Choosing an enterprise AI consultancy in the UK comes down to four inspectable checks: who writes the code, one production workflow with measurements and their provenance, governance implemented as controls rather than documents, and what the client keeps when the engagement ends.

What does production proof look like for an enterprise AI consultancy?

Production proof is one real workflow people use daily, with measurements and their provenance stated. A client-published figure, a consultancy measurement and a forecast are three different strengths of evidence. A demonstration is not production.

Should we choose a Big Four firm or a specialist consultancy?

Match the firm to the shape of the work. A board-sponsored, multi-country transformation with heavy regulatory reporting suits a large integrator. A first production system, a platform build or an engineering-led adoption programme suits a senior specialist practice, because you are buying judgement and code rather than programme management.

What does a partner status with OpenAI or Anthropic actually tell you?

It tells you the firm has a formal relationship with that vendor, which usually means earlier access, direct support channels and co-delivery experience. It does not tell you the firm is right for your problem, and it is worth asking any partner firm to show work delivered on stacks outside that vendor.

How quickly should work reach production?

For a first governed workflow, weeks to a small number of months, not quarters. The honest constraint is usually access, data and approvals rather than engineering. A firm that cannot name what it would ship in the first month is planning a long discovery.

What should the contract say about ownership?

That the client owns the code, the architecture, the documentation and the operating model, with no licence back to the consultancy required to keep running the system. Handover, runbooks and capability transfer should be deliverables with acceptance criteria, not goodwill.

Does the consultancy need to be UK-based?

For UK organisations with data-residency, procurement or sector-regulatory constraints, a UK-headquartered practice working to UK GDPR and the Data Protection Act 2018 simplifies the compliance conversation. 1AYM is based in Stoke-on-Trent and delivers across the UK, the Gulf and the US. What matters more than the address is whether the firm architects for your residency requirements and can evidence it in production.

How much does an enterprise AI consultancy cost in the UK?

No UK body publishes a fee benchmark, so the only public, firm-attributable prices are the per-day fee schedules suppliers must publish to sell through the government's G-Cloud framework. On the G-Cloud 14 cards, a senior specialist at SFIA level 5 runs from £800 to £2,380 a day with a median of £1,500: £1,580 to £2,380 at the large firms, £800 to £1,400 at practices outside them. Whole engagements carry fixed prices too, with Gartner's card publishing £70,200 for AI use case prioritisation up to £203,500 for an AI strategy and roadmap. A headline low is not comparable until you read the fee card behind it: Accenture's listing starts at £95 a day, which its own card shows is a level 1 junior offshore, against £1,580 for the onshore senior specialist. Most cards were priced in April and May 2024 and are a floor rather than a quote. These are other firms' published prices, not 1AYM's; 1AYM's engagements are not priced on this page, and the question that decides value is what a fixed scope delivers and who carries the risk.

Further

We build these systems for a living. See the engagement files for what that looks like in practice, or write to us if yours is the next one.

Last reviewed · 1AYM