AI for consultancies and consulting firms.
AI for consultancies is the practical work of taking the repeatable tasks out of how a consulting firm wins, delivers and runs its business, so the same team can serve more clients without adding headcount. AssumeAI is a UK, founder-led AI consultancy and AI engineering firm that does this for management, specialist and boutique consultancies, from a pair of prioritisation workshops to working systems built inside the firm. Nothing is built without justification and nothing is deployed without safeguards.
- Hours a year found at The Litmus Partnership
- 9,672
- Hours a month now saved there
- 268
- Hours of IP in one AI board advisor
- 400+
- To set up a project in four systems
- 90 sec
Firms we have built with
What does AI for consulting firms actually involve?
A consultancy sells expertise, but a good part of the week can go on work that is not expertise at all: assembling proposals, re-keying data between systems, formatting reports, digging the same answers out of old documents. That work is where AI earns its place first. It is also where most firms stall, because AI tools are easy to buy and hard to fit to the way a particular firm actually operates.
Our work with consultancies follows a structured, risk-aware order. We start by finding where your hours go and putting a cost against each opportunity, ranked, so you can see the return before you commit to anything. We then put governance and safeguards in place, with clear policies, controls and training, so your team can use AI safely and consistently. Only then do we design and build production-grade AI that works in real environments and increases consultant output. You can take all three stages with us, or take one and run the rest yourself.
AssumeAI sits between the strategy firms that cannot build and the AI development firms that cannot advise. That matters in a consultancy more than almost anywhere else, because the people who will use the system are also the people who know whether its output is good enough to put in front of a client. We design with them, not around them.
- Step 01
Find and cost
Where the hours go, with a cost against each opportunity, ranked.
- Step 02
Govern
Policies, controls and training, so AI is used safely and consistently.
- Step 03
Build
Production-grade AI, built inside your firm and owned by you.
Where does AI pay back first in a consultancy?
Across our client work, the clearest returns so far have come from four places, and they are rarely the ones that make the headlines.
The first is the proposal. Clear AIMS asked us for a proposal generator, and it took the average proposal from what would have been two to three hours of work down to five to ten minutes. The second is the analytical grind inside delivery. At The Litmus Partnership we built a benchmarking platform that handles 2,000 lines in around 45 minutes, where 200 to 300 lines used to take eight hours, and monitoring work that took 30 to 40 hours now takes two to three.
The third is the back office that every consultancy runs and nobody chose: project set-up, finance and reporting. For Coaching Without Borders, one form now sets up a new project in four systems in about ninety seconds, survey responses become a finished slide report automatically, and the cash flow dashboard refreshes in two to three minutes.
The fourth is the firm's own intellectual property. The Consultancy Growth Network had built six years of proprietary tools, assessments, talks and articles. We made all of that knowledge accessible in an AI board advisor trained on more than 400 hours of the network's material, and it is now available to every member of the network.
What these have in common is that each one removes work a senior person should not be doing, and none of them asks the client to accept a lower standard of output.
What have consultancies achieved with AI so far?
The fullest example is The Litmus Partnership. Its senior leadership team already believed AI could improve efficiency across the business and had captured its ideas on a single page. What it lacked was clarity on what was practical, a defensible view on prioritisation and a sequenced approach to delivery. Our two-week strategy review ran surveys across senior leadership, consultants and the technical team, ten stakeholder interviews to find where time was being spent, and an opportunity map for each of seven departments. It identified twenty-six initiatives and 9,672 hours a year, in a roadmap sequenced over twenty-four months. Candice Finn, the firm's MD, said we “demonstrated a deep understanding of our business and articulated a prioritised roadmap which we can now execute, with sensible governance, training and risk controls built in.”
We then delivered an eight-month programme of AI and automation initiatives. The aim was to increase efficiency and capacity at the key bottlenecks, so that Litmus could price more competitively without increasing headcount or sacrificing margin. The programme covered internal and external AI policies and a tool impact assessment, ten training films, rebuilt and automated pre-selection questionnaires, the benchmarking platform, and a tenders application built from scratch for the web and for mobile. The firm now saves 268 hours a month, and every figure was collected from the people at Litmus who use the tools.
The same pattern, a review first and then the build, ran at Coaching Without Borders. A four-week review produced twenty-seven initiatives across fifteen platforms, and the automations that followed went live in June and July 2026, each with its own handover pack. You can see every project, with the figures, on our work page.
The Litmus Partnership
“AssumeAI are a pleasure to work with and delivered a clear, concise and practical AI strategy review. Within a short timespan, they demonstrated a deep understanding of our business and articulated a prioritised roadmap which we can now execute, with sensible governance, training and risk controls built in.
We look forward to continuing to work with Hugh and Rupert to drive differentiation and efficiencies throughout our consultancy with AI and automation.”
Is AI different for management, specialist and boutique consultancies?
The principles are the same. The starting point is not.
Boutique consultancies
A boutique consulting firm rarely has anyone technical in house, and that is usually the whole reason it has not started. The barrier is rarely the money; it is not having anyone who can build. In that case the building is our part, and afterwards we train your team, hand over the documentation and leave a roadmap you can run without us.
Specialist consultancies
A specialist consultancy usually sits on deep, proprietary knowledge: a library of methods, reports and frameworks built up over years. That is often the most valuable thing to put AI over, as The Consultancy Growth Network did. Marc Jantzen, its CEO, said we helped them “develop a genuinely differentiating asset”. Specialist firms in regulated sectors also answer to chartered or professional bodies, which changes the governance work; our page on AI for professional services covers that in more depth.
Management consultancies
In a management consultancy with several departments and a long list of competing ideas, the work is mostly prioritisation: an opportunity map for each department, a view of which systems are enablers and which are constraints, and a sequence the leadership team can agree on. That was the shape of the Litmus review across seven departments, and of the workshops we ran for i10, a firm that wins large public sector programmes and delivers them through an ecosystem of partners, but whose commercial processes still ran on spreadsheets, copy and paste and memory.
Where should a consultancy start with AI?
AI Priorities Workshop
If you are keen to move but want confidence you are starting in the right place, the AI Priorities Workshop is the lightest way in. It is one pain point workshop with your senior leadership team, a second within the department to surface the day-to-day frictions leadership does not always see, and a concise roadmap of the initiatives to focus on first. i10 came out of its workshops with seven initiatives in three layers and a sixteen-week plan to deliver them, from thirteen use cases assessed.
AI Strategy Review
If you want a considered, evidence-based plan before you spend, the AI Strategy Review takes about six weeks. It combines organisational surveys, stakeholder interviews and a full review of your tech stack, and hands you five practical documents: an AI implementation roadmap, an AI risk assessment, an AI readiness assessment, an AI audit report and an executive presentation to bring your leadership team with you.
30-day implementation sprint
If you already know the bottleneck you want gone, go straight to a 30-day implementation sprint: one week to agree what to build, three weeks to roll it out.
Free AI maturity assessment
And if you would like a benchmark before any of that, the free AI maturity assessment is nine questions and about two minutes, built for professional services firms of 20 to 200 staff, with your scored report in your inbox immediately.
What does AI consulting for a consultancy cost?
Every service has a published starting price. We will not quote a build before we know where your hours go, because the honest number depends on it. The first step is finding the leaks and putting a cost against each one, ranked; you then sign off exactly what gets built, with the number and the return it is based on in front of you.
| Service | Investment |
|---|---|
| AI Priorities WorkshopTwo pain point workshops and a concise roadmapTwo workshops, plus a roadmap | From £4,000 |
| AI Strategy ReviewSurveys, interviews, a tech stack review and five documentsAbout six weeks | From £12,000 |
| AI Governance ImplementationPolicies, impact assessments and audit trails2 to 4 weeks | From £3,000 |
| Tailored AI Team TrainingWorkshops across Claude, Cowork, Gemini and moreOne-off or a sustained programme | From £5,000 |
| 30-Day Implementation SprintOne use case, built and deployedAbout four weeks | From £6,000 |
| 90-Day Implementation SprintSeveral workflows built, deployed and embeddedAbout twelve weeks | From £15,000 |
| Enterprise AI DeploymentClaude Cowork or ChatGPT Enterprise, with six to twelve agents and skillsAgreed when scoped | £20,000 ex VAT |
| Managed ServiceHalf, one or two engineers embedded in your firmMonthly | From £5,500 per month |
Each service carries a guarantee. If the strategy review does not surface opportunities worth many times the fee, we keep working until it does. If a 30-day sprint is not live and delivering value in 30 days, we keep working at no extra cost until it is. We are not the cheapest option, and if you want a quick hack we are the wrong firm.
How do you keep client data safe?
For a consultancy, client confidentiality is not a compliance line; it is the product. We do not build on top of your business, we build inside it. Everything lives in your existing infrastructure and you own all of it, code included. We run our own firm's confidential data through the same systems every day, so if they were not secure we would be the first to know.
Governance comes before the build. AI governance implementation gives you internal AI policies for your teams, external AI policies for clients and partners, impact assessments so you understand what you deploy, and audit trails including a risk register and an incident log. It is aligned with EU GDPR, any SOC credentials you need to hold and the requirements of your chartered or professional bodies, and it typically takes two to four weeks. A blanket ban does not work; it just pushes usage underground. Clear guardrails let people use AI with confidence.
Where a firm wants one platform for everyone, Enterprise AI Deployment puts Claude Cowork or ChatGPT Enterprise on EU-based data hosting, configured to your data governance policies for access, permissions, retention and data handling. If you do not have a policy yet, the governance template we use with clients is free on our resources page.
Describe the defined business use case for this tool. What problem does it solve, and what outputs will it produce?
| Non-AI alternatives considered | |
|---|---|
| Why AI is more appropriate than alternatives | |
| Is this use of AI proportionate to the task? |
Governance pack · TemplateAI Tool Impact Assessment
Complete one per AI tool. Retain as a governance record.
| Tool name | |
|---|---|
| Vendor or provider | |
| Version or model | |
| Date of assessment | |
| Assessor | |
| Business owner | |
| Date of first use | |
| Next review date |
- Built inside your infrastructure
- You own all of it, code included
- EU-based data hosting
- GDPR, SOC and professional bodies
Should a consultancy build, buy or train?
Usually all three, in a deliberate order.
Train
Training is how a team gets value from tools it is already paying for. Tailored AI team training covers Claude, Cowork, Gemini and Prompt Engineering Fundamentals, built around your real work rather than generic demos, run remotely or on site. For Hillbreak, a specialist ESG and sustainability advisory firm, we ran three Claude Cowork workshops alongside its pilot and built six custom skills, from spreadsheets and slides to writing in the house voice, plus two worked use cases taken from brief to finished document.
Buy
Buying means putting an enterprise platform in everyone's hands. A licence on its own changes nothing if nobody knows what to do with it, which is why our enterprise deployments come with six to twelve agents and skills built around the workflows your teams run every week, such as drafting a proposal from your templates or summarising a client file.
Build
Building is for the work no product fits: the Litmus benchmarking platform, the Consultancy Growth Network advisor, the Clear AIMS proposal generator. We build around your processes rather than around one model, and because you own the code you can change what sits underneath it as the tools improve. If you want building capacity on tap rather than a single project, the managed service embeds half an engineer, one or two inside your firm on a monthly footing.
How long does AI implementation take in a consulting firm?
Our timelines are published on each service page. The standard AI Strategy Review takes about six weeks, depending on the size of the business; focused reviews have run faster, two weeks for Litmus and three for Hillbreak. A 30-day sprint puts one working solution live within a month. The 90-day implementation sprint runs two weeks to identify and prioritise, eight weeks to develop and deploy, and two weeks to embed the capability in your team. Governance work takes two to four weeks.
Larger programmes are sequenced rather than rushed. The Litmus programme ran over eight months, and the review we completed for Plan Ahead PM set out thirteen initiatives in a plan that runs over eight months, from the rollout of AI tools and training through to a finance dashboard. Much of the real work is agreeing what to build, which is why every engagement starts there.
- AI governance implementation2 to 4 weeks
Policies and controls · Up to four weeks
- AI Strategy ReviewAbout six weeks; focused reviews faster
Surveys, interviews, tech stack
- 30-day implementation sprintAbout four weeks
Agree · Roll it out
- 90-day implementation sprintAbout twelve weeks
Prioritise · Develop and deploy · Embed
- A full programmeSequenced, not rushed
Eight months at The Litmus Partnership
Who will actually do the work?
AssumeAI is founder-led from end to end, which means faster decisions, senior accountability and less friction throughout delivery. Rupert Wiseman, Managing Director and Principal AI Consultant, studied Law at Exeter and worked in corporate finance before co-founding the business, and has spent over two years leading AI transformation programmes; his legal background brings a rigorous focus on safety, governance and risk controls from day one. Hugh Dowling, Head of Development, completed a Master's in Software Engineering and makes sure everything we build is designed to operate in a secure, scalable, commercial environment.
Our AI engineers and consultants work alongside them, and behind the founders is an associate network of over ten AI consultants and AI engineers, so the work is never waiting on one person. We also teach this subject: we have run workshops for master's students at Green Templeton College, University of Oxford, on how AI is practically supporting consulting firms. You can meet the team on our about page and read our weekly writing on AI adoption on the blog.
Questions
Do we need someone technical in house?
No, and that is usually the whole reason firms of your size have not started. The barrier is rarely the money; it is not having anyone who can build. That is our part. Afterwards we train your team, hand over the documentation and leave you a roadmap you can run without us, because we do not want you dependent on us.
What is the least expensive way to start?
The free AI maturity assessment: nine questions, about two minutes, and a scored report benchmarked against comparable firms. The lightest paid engagements are AI governance implementation, from £3,000, if policy is the gap, and the AI Priorities Workshop, from £4,000, which gives you two pain point workshops and a concise roadmap.
Do we have to use you to build what the review recommends?
No. The plan is yours, and you are free to run it however you like. Many clients choose us to deliver it, but the roadmap, the risk assessment and the other documents belong to you either way, whoever does the building.
How quickly will we see results?
A 30-day sprint puts one working solution live within a month, and if it is not live and delivering value in 30 days we keep working at no extra cost until it is. Strategy work takes longer to pay back, but it tells you what to build first, so the money you spend on building goes to the highest-value work.
What if the tools improve and leave what we build behind?
They will improve. That is a reason to start rather than a reason to wait. We build around your processes, not around one model, and because you own the code you can change what sits underneath it. If better tools tomorrow are your reason not to act, you have chosen a reason that never expires.