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AI Strategy

AI strategy that survives a board meeting.

AI is crowded with hype and changes by the week. Our AI strategy consulting starts with an AI readiness assessment and gives you a grounded view of where generative AI genuinely strengthens your business today, prioritised, costed and sequenced, so the next conversation is about approval rather than possibility.

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The Problem With AI Strategy

The hard part is not ideas.
It is choosing between them.

Most organisations we meet already have twenty or thirty AI ideas floating around. What they do not have is a defensible way to say which three are worth funding, what each will cost, and which one goes first. That is what AI use case prioritisation is for.

Feasibility

Grounded in your data

An idea is only real if the data behind it exists, is accessible and is good enough. We check that before anything gets on a roadmap.

Cost

Costed, not estimated

Each prioritised use case comes with an architecture and a build cost, so the roadmap is a budget conversation rather than a wish list.

Sequence

Ordered for momentum

Early projects are chosen partly because they prove value quickly. Nothing kills an AI programme faster than eighteen months before the first result.

Governance

Safe to say yes to

Acceptable-use policy, data handling and review points, written so your risk and legal people can sign off rather than stall.

Our AI Strategy Services

Two engagements, depending on how big the question is.

AI Roadmap

For organisations that need an enterprise-wide plan: multiple departments, real governance requirements, and a board or executive group that has to approve the spend.

What you get

  • A governance framework covering acceptable use, data handling and review points
  • AI upskilling workshops to bring your people into the conversation
  • Structured use-case collection across departments
  • A prioritisation workshop that narrows the list against value and feasibility
  • Technical mapping of the top five use cases: architecture, data, integration, cost
  • A consolidated roadmap report written for an executive audience

What it is worth

  • One AI direction across the organisation instead of five departmental ones
  • Governance and risk addressed before the first build, not after an incident
  • A prioritised pipeline you can fund in stages
  • Costings accurate enough to budget against
  • A document that survives the board meeting it was written for

AI Kickstarter

For small and mid-sized teams that do not need an enterprise programme. They need to know what to do first, and to know it in weeks rather than quarters.

What you get

  • A leadership workshop on goals, constraints and current processes
  • Collection and prioritisation of candidate AI use cases
  • Technical mapping of the top three: cost, feasibility and architecture
  • A clear action plan for the first project

What it is worth

  • Immediate clarity on where to start
  • Fast filtering of high-impact opportunities from plausible-sounding ones
  • Technical confidence, because the solution is defined by people who build them
  • A roadmap you can act on straight away
Our Approach

How an AI Roadmap comes together.

Six stages. The order matters: governance first means nothing later gets blocked by a question that should have been settled at the start.

01

Governance

Establish the governance and readiness framework: acceptable use, data handling, and who decides what.

02

Training

Workshops that bring your teams up to a shared level, so the ideas that follow are grounded rather than speculative.

03

Prioritise

Collect use cases across the organisation, then narrow them against value, feasibility and data reality.

04

Map

Take the top use cases to technical detail: architecture, integration points, build cost and sequencing.

05

Deliver

Present a consolidated, board-ready roadmap with costings and a recommended order of work.

06

Move into delivery

Hand over to your team, to us, or to a mix of both. The roadmap is written to be executable either way.

What Delivery Looks Like

The systems a roadmap turns into.

Strategy work is only worth what gets built afterwards. These are systems we have delivered, the kind of work a prioritised roadmap leads to.

AI Marketplace Platform
AI DevelopmentMarketplace

AI Marketplace Platform

Support chatbot, live SEO analyser and a vector recommendation engine, all sharing one retrieval layer.

+10% GMV, 40% fewer support tickets
 Warehouse Intelligence
AI DevelopmentAI AutomationLogistics

Warehouse Intelligence

Demand forecasting, OCR-driven receiving and anomaly detection across 14 fulfilment centres.

47% fewer stockouts, 14 warehouses
 Visual Quality Inspection
AI DevelopmentComputer VisionManufacturing

Visual Quality Inspection

Custom-trained YOLOv8 models running on edge devices, replacing manual visual QA so the line can run around the clock.

99.2% accuracy, 38 FPS on the line
See all case studies
Common Questions

Before you get in touch.

We already have a list of AI ideas. Is that enough to start?

It is a good start, and it is usually where the AI Kickstarter begins. The work is not generating more ideas. It is filtering them against feasibility, data availability and actual return, then sequencing what is left.

How long does a roadmap engagement take?

An AI Kickstarter typically runs a few weeks. A full AI Roadmap takes longer because it includes governance work and technical mapping across more use cases, and because it depends on getting time with people across your organisation.

Do we have to build with you afterwards?

No. The roadmap is written so any competent engineering team can execute it, including your own. We would like to build it, but the deliverable stands on its own.

What if the answer is that AI is not worth it?

Then we say so, and you have saved considerably more than the engagement cost. That outcome is rarer than it used to be, but it still happens and we would rather tell you early.

What is an AI readiness assessment?

A structured check of whether your data, systems and processes can actually support an AI build before you fund one: where the data lives and what state it is in, which integrations are realistic, and which use cases have a measurable payoff. It is where an AI Roadmap engagement starts, and there is a short version you can run yourself in our AI readiness assessment post.

Talk to us about your AI strategy.

Bring the messy version. A rough sense that something should change is a perfectly good place to start. It is where most of these engagements begin.

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