Generative AI consultancy in London for SMBs
Get the productivity gains from generative AI without the data, quality and compliance risks, delivered on Microsoft by a London IT partner.
Book your free AI readiness review
Microsoft Direct CSP · Microsoft AI Cloud Solution Provider · Microsoft Support Service Designation · 24x7x365 MDR and SOC · 30+ years in IT
Generative AI consultancy is the work of helping a business use generative AI, the technology behind tools like Microsoft 365 Copilot and ChatGPT that can produce text, summaries, drafts and answers on demand, in a way that is safe, measurable and worth the money. Lanmark provides that consultancy to London SMBs in the 20 to 500 user range, and we do it as your Microsoft partner and IT provider, not as a slide deck.
Most of the businesses we meet already have generative AI in the building. Staff are pasting client emails into ChatGPT, drafting documents with free tools, and getting inconsistent results with no oversight. The question is no longer whether to use generative AI. It is how to use it deliberately, on infrastructure you control, with the data and quality risks handled properly. That is what this page is about.
What generative AI consultancy actually involves
Generative AI describes AI models that generate new content, a paragraph, a summary, a reply, a first-draft document, rather than simply classifying or predicting. Large language models, or LLMs, are the best known example. A generative AI consultancy helps you decide where these models can usefully be applied, chooses the right tools, deploys them on secure infrastructure, trains the people who will use them, and puts the governance in place to do so safely.
A good engagement is judged on business outcomes, not on how much AI tooling gets switched on. Our work with a client typically covers four things: identifying the handful of use cases where generative AI genuinely saves time or money, getting the underlying Microsoft 365 and security estate ready, deploying and training, and then measuring whether the return is real. If the return is not there, we say so before you spend.
For a broader view across all of AI, not just generative models, see our main AI consultancy in London hub. This page focuses specifically on generative AI.
Where generative AI pays back fastest for SMBs
Generative AI does not pay back evenly across a business. In our experience with London professional services, finance and legal firms, the return concentrates in work that is text-heavy, repetitive and currently done by expensive people. The clearest wins are:
- Drafting and summarising, first-draft engagement letters, proposals, reports and meeting notes, where a good prompt turns an hour into fifteen minutes.
- Knowledge retrieval, answering staff questions from your own documents, policies and past work, with the source cited, instead of asking a colleague.
- Correspondence, triaging and drafting replies to routine client and supplier email.
- Research and analysis, pulling the relevant points out of long documents so a fee earner reviews rather than reads.
The pattern is consistent. Microsoft 365 Copilot is, in our experience, worth between two and ten hours of saved time per user per week once it is deployed properly and people are trained, depending on role. The variation is almost entirely about deployment quality, not the technology. That is where consultancy earns its fee.
The risks generative AI brings, and how we contain them
Generative AI carries risks that older software does not, and they are the reason unmanaged use is dangerous. We contain each one before switching anything on.
Data leakage. Free consumer AI tools can retain what your staff paste into them. Client-confidential information should never leave your control. We deploy generative AI inside your Microsoft 365 tenant boundary, so your data stays governed by your own identity and security controls. We harden SharePoint and OneDrive sharing and apply Microsoft Purview sensitivity labels first, because most leakage risk comes from existing oversharing, not from the AI itself.
Hallucination. Generative models can produce confident, well-written answers that are wrong. We design deployments so that AI drafts and a person approves, never the reverse, for anything that matters. For knowledge assistants we use retrieval-augmented generation, a technique that grounds the AI’s answer in your actual documents and cites the source, so claims can be checked.
Inconsistency and quality drift. Left to individual staff, prompt quality varies wildly. We provide shared prompt patterns, guardrails and training so output is consistent and reviewable.
Governance and accountability. Someone has to own AI use. We work through data sensitivity, data residency (for most UK SMBs, EU or UK only), logging, access control and acceptable use during the readiness assessment, and translate the answers into policy and tooling. For managed clients, this sits alongside our enterprise-grade managed detection and response and security operations centre service, so the same team watching your email and identity also watches your AI estate.
The UK’s National Cyber Security Centre publishes practical guidance on the secure use of AI, which aligns with the baseline we apply. See the NCSC guidance on AI and machine learning security.
How we deploy generative AI on Microsoft
Microsoft gives SMBs a clear, well-governed route to generative AI, which is why it is our default. Four tools cover almost every case, and part of the consultancy is choosing the right one rather than over-buying.
Microsoft 365 Copilot, generative AI inside the Office apps your staff already use, for drafting, summarising and analysis across Word, Outlook, Excel, Teams and PowerPoint. This is the starting point for most firms. See our guide to Microsoft 365 Copilot for UK SMBs.
Microsoft Copilot Studio, a low-code way to build custom assistants and agents on your own content and processes, typically in one to four weeks to a first useful version.
Azure OpenAI and Microsoft AI Foundry, for custom generative AI applications that reach into your own data behind your tenant boundary, when an off-the-shelf tool cannot. Our plain-English Microsoft AI Foundry guide explains when this is the right step.
We are a Microsoft Direct Cloud Solution Provider and a Microsoft AI Cloud Solution Provider, which is Microsoft’s own designation for partners qualified to sell and deploy Azure AI and generative AI workloads. Microsoft is our default, but it is not a fixation. Where another model is genuinely the right answer, for example Anthropic’s Claude for long-document reasoning, we will say so and design for it.
Custom generative AI assistants and agents
When a generic tool cannot reach your data or your process, we build a custom generative AI assistant. An assistant answers questions and drafts content grounded in your own knowledge. An agent goes a step further and completes a defined task on your behalf, calling on tools and data to produce an output.
Examples we have built or scoped for London SMB clients, with a measured business case behind each one: a document-drafting assistant that produces first-draft engagement letters from a structured brief, cutting drafting time by around 60 per cent; an IT ticket triage agent that classifies, summarises and routes incoming requests, reducing first-response time by roughly 40 per cent; and a supplier-onboarding agent that reads supplier documentation, checks it against approved lists, and prepares the finance team’s review pack.
Every assistant and agent we build runs on your security baseline: Azure OpenAI in your own subscription, private endpoints, Purview labelling on source data, full prompt and response logging, and access controlled through your existing Entra ID groups. If the business case is not there, we tell you before we build anything.
Where generative AI fits on the AI Capability Ladder
We place every client on the AI Capability Ladder, a five-rung framework, so you always know your current position and the next step. Generative AI runs right through it. Rung 1, Aware, leadership understands what generative AI is and where it could apply. Rung 2, Active, Copilot is licensed for selected users. Rung 3, Adopted, Copilot is the default for productivity work, with governance in place. Rung 4, Augmented, custom generative AI assistants and agents handle defined tasks, with outcomes measured. Rung 5, AI-native, generative AI is part of how the business runs, justified by data.
Most London SMBs we meet are on Rung 1 or 2 for generative AI. The consultancy is about moving up one rung at a time, safely, with a measured return at each step.
Why Lanmark for generative AI consultancy
We run the Microsoft estate that generative AI sits on. AI is an extension of work we are already accountable for, not a new line bolted on.
Our accreditations are real and checkable: Microsoft Direct CSP, Microsoft AI Cloud Solution Provider, and the Microsoft Support Service Designation, which only a handful of firms worldwide hold.
Our delivery is security-led. Generative AI risks are security risks, and we deliver on the same 24x7x365 MDR and SOC baseline we provide to clients in regulated sectors.
We start with a free AI readiness review, not a paid discovery engagement, and we run a free Microsoft 365 licence review alongside any work so you only pay for the licences you need.
And we explain it in plain English. Our skill is turning generative AI from a buzzword into something a Managing Director, Finance Director or Operations Director can act on this quarter.
We work mainly with professional services, finance and legal firms, sectors that generate the volumes of text where generative AI pays back fastest and that face the regulatory constraints that demand careful governance. Related: IT support for law firms in London and IT support for financial services in London.
How to get started, the free AI readiness review
Before recommending any generative AI investment, we run a structured AI readiness review with your senior team. It is free, it takes 90 minutes, and it produces a written summary you can share at board level, a placement on the AI Capability Ladder, and three costed next-step options.
Typical timescales are two weeks from first conversation to the readiness review and recommendations, and three to four weeks from there to a first measurable pilot, usually a controlled Microsoft 365 Copilot rollout to one team.
Frequently asked questions
What is generative AI consultancy?
Generative AI consultancy is professional help to apply generative AI, the technology behind tools like Microsoft 365 Copilot that produce text, summaries and drafts, to your business safely and profitably. It covers choosing use cases, deploying the right tools on secure infrastructure, training staff, and putting governance in place. It is judged on business outcomes, not on how much AI is switched on.
Is generative AI safe to use with client-confidential data?
Yes, when it is deployed correctly. The risk comes from free consumer tools that can retain what staff paste in, and from existing oversharing in your document storage. We deploy generative AI inside your Microsoft 365 tenant boundary, apply Microsoft Purview sensitivity labels, tighten SharePoint and OneDrive permissions, and control access through your existing identity groups before anything is switched on.
How is generative AI different from Microsoft 365 Copilot?
Microsoft 365 Copilot is one product built on generative AI. Generative AI is the broader category, which also includes custom assistants, agents built in Copilot Studio, and bespoke applications on Azure OpenAI and Microsoft AI Foundry. Copilot is where most SMBs start; the others come into play when an off-the-shelf tool cannot reach your own data or process.
What generative AI use cases actually save money for an SMB?
The fastest returns are in text-heavy, repetitive work: drafting and summarising documents, answering staff questions from your own knowledge with sources cited, triaging and drafting routine correspondence, and pulling key points from long documents. Deployed properly, Microsoft 365 Copilot is worth between two and ten hours of saved time per user per week depending on role.
How do you stop generative AI making things up?
Generative models can produce confident but wrong answers, known as hallucination. We design deployments so AI drafts and a person approves for anything that matters, and for knowledge assistants we use retrieval-augmented generation, which grounds the answer in your actual documents and cites the source so it can be checked.
Do we have to use Microsoft, or can you work with other AI models?
Microsoft is our default because, for the SMBs we serve, the licensing economics, identity model and security controls usually line up best. Where another model is genuinely the right answer, such as Anthropic’s Claude for long-document reasoning, we will say so and design for it.
How much does generative AI consultancy cost?
The AI readiness review is free. Pilot engagements start at £8,000 for a single use case over four to eight weeks, and ongoing adoption programmes start at £3,500 per month. All exclude Microsoft licensing, which we optimise through our free licence review service.
How quickly can a London SMB get started?
About two weeks from the first conversation to a free readiness review and recommendations, and three to four weeks from there to a first measurable pilot, typically a controlled Microsoft 365 Copilot rollout to one team.
Book your free AI readiness review
A 90-minute conversation with our senior AI team. No cost, no obligation. You walk away with a written summary, a placement on the AI Capability Ladder, and three costed next-step options.
Book your free AI readiness review
Or call us on 020 7123 4910 and ask for the generative AI consultancy team.