AI Strategy & Enablement

The same strategy discipline, pointed entirely at AI.

What AI is already doing here, what is worth doing next, and the capability to actually do it.

Engagement

Advisory + enablement. Runs as a full AI strategy, or as the evaluation of a single opportunity.

Who it is for

CIOs and IT leaders, executives under pressure to have an answer on AI, and the teams being asked to deliver one.

When people call us

AI is arriving from every direction at once — the board, the vendors, the staff already using it — and there is no view of what is worth funding.

The practice

01

Current state evaluation

What is already in use across the business, sanctioned and not, what it costs, and what risk it carries today.

02

Idea capture and generation

Opportunities gathered from the people doing the work, and generated with them where the business has not yet seen what is possible.

03

Opportunity evaluation

Each idea assessed on value, feasibility, the AI capability it genuinely requires, and whether the data and process underneath it can carry it.

04

Roadmapping

A sequenced plan with dependencies and cost, built so the early items fund the argument for the later ones.

05

Policy and guardrails

What may go into these tools, who is accountable, and how an idea gets approved in a week. Sized to speed decisions up.

06

Capability enablement

The skills, roles, platform access and working patterns a business needs before AI work stops depending on one enthusiast.

07

Adoption and change

Rollout to real teams on real work, with usage measured rather than assumed.

08

Delivery

Where the roadmap calls for something built, it is built: agents, automation and integration, or custom software.

From noise to a funded plan

Evaluation before enthusiasm.

  1. 01
    Current state

    What is already in use here, sanctioned and not, and what it is touching.

  2. 02
    Capture

    Ideas from the people doing the work, and generated with them where the business has not seen what is possible.

  3. 03
    Evaluate

    Value, feasibility, the AI capability it needs, and whether the data and process can carry it.

  4. 04
    Roadmap

    Sequenced so the early items fund the argument for the later ones.

  5. 05
    Enable

    Skills, access, rules and a first team using it on real work.

Readiness reorders the list

A high-value candidate sitting on data nobody has cleaned is a later item. Saying so at evaluation is cheaper than proving it in a pilot.

We evaluate the AI already in use, capture and generate opportunities with the people doing the work, assess each on value and readiness, and build the roadmap. Then we enable the capability to deliver it, and build what the roadmap calls for.

Start with what is already happening

Before anything is ranked, find out what is in use, who is using it, what it is touching, and what it is costing. This is usually the most surprising document produced during the engagement, and it changes what the strategy has to address.

Evaluation before enthusiasm

Every idea gets tested on the same ground: what it is worth, what it would take, what AI capability it actually needs, and whether the data and the process underneath it are ready. A strong idea sitting on data nobody has cleaned is a later item, and saying so early is cheaper than proving it in a pilot.

Enablement is where it holds or fades

A roadmap does not deliver itself. The capability side is people who know how to scope this work, platform access that does not take a quarter to arrange, rules that let a good idea proceed, and a first team using something on real work. That is the difference between a strategy and a slide.

Work we have done

AI strategy and roadmap — energy services. The board and the executive were pushing, employees were asking, and some licences had already been bought before anyone had settled what they were for. We assessed more than twenty opportunities and ranked them on two axes: how hard each would be to implement, and what AI capability each actually required. The engagement was advisory — we built none of it. The client used the roadmap to decide what to pursue, how to scope it, and what their policy should say.

SharePoint audit for AI readiness — energy services and construction. The concerns were security and information risk, and there was no information architecture to implement against. We reviewed the estate, found a significant number of high-risk issues, and designed the information architecture along with the other remediation the estate needed. Our recommendation was to clean up and close the high-risk gaps before going near a rollout.

SharePoint audit for AI readiness. We reviewed a SharePoint estate against what an assistant would need from it — permissions, structure, and whether the content was current enough to answer from — before any rollout was committed to.

What you keep

The code and the data·Your existing relationships·Approval and control·The ability to stop·The off switchWhat that means

Start with a 45-minute briefing.

No pitch. We’ll map your situation against what actually works and tell you honestly where to start.