AI strategy & consulting

Turn AI ambition into a prioritised, funded roadmap

We assess where AI creates value across your business, prioritise every opportunity by value, feasibility and risk, and set out a 12–24 month roadmap with business cases, governance and the operating model to deliver it. Then, if you want, we build it.
Opportunity mapExample
Example impact and effort mapImpactEffortBuild firstLeave alone
  1. Invoice entryHigh impact · low risk
  2. Quote checksHigh impact · medium risk
  3. Ticket triageHigh impact · low risk
  4. Pricing exceptionsLeave alone for now

What you leave the first session withAn initial view of where AI could matter most, the questions to answer first, and what an assessment or full strategy would cover.

Why AI strategies stall

Most AI strategies stall between the board presentation and the first build.

We connect the two: a clear view of where AI creates value, a portfolio ranked by what it’s worth and what it takes, and a roadmap that balances quick wins against long-term advantage. The first wave is specified well enough to start building the week after sign-off.

  1. Horizon 1 · 0–3 months

    Prove value

    Two or three high-confidence initiatives go live and set the baseline for measuring the rest.

  2. Horizon 2 · 3–12 months

    Scale what works

    Extend proven patterns across functions, fix data foundations and stand up governance.

  3. Horizon 3 · 12–24 months

    Build advantage

    New AI-enabled capabilities, products and ways of working that competitors can't easily copy.

Diagnose

Start from an honest baseline

We score your organisation on six dimensions of AI maturity and agree the target for each. The gap between the two is what the roadmap has to close, and it shows where to invest first.
  • Strategy & valueUse cases tied to business goalsCurrent level 2 of 5, target 4 of 5.
  • Data & technologyQuality, access, integrationCurrent level 2 of 5, target 4 of 5.
  • Governance & riskPolicy, controls, complianceCurrent level 1 of 5, target 4 of 5.
  • People & skillsLiteracy, roles, adoptionCurrent level 2 of 5, target 4 of 5.
  • Operating modelOwnership, funding, deliveryCurrent level 1 of 5, target 3 of 5.
  • MeasurementKPIs and value trackingCurrent level 1 of 5, target 4 of 5.
IllustrativeExample profile. Yours comes from interviews, system reviews and a short survey.

Approach

Five phases, each ending in something leadership can act on

Run end to end as a full strategy, or start with the assessment and decide from there.
  1. Diagnose

    Maturity baseline

  2. Discover

    Sized use cases

  3. Prioritise

    Ranked portfolio

  4. Plan

    Roadmap + governance

  5. Mobilise

    First wave specs

Diagnose

AI maturity and readiness assessment

We assess where you stand across strategy, data, technology, governance, skills and operating model, through leadership interviews, system reviews and a short survey.

You get: a maturity baseline and the blockers to fix first.

Discover

Value opportunity assessment

We work function by function, from finance and operations to sales and service, to find where AI can move revenue, cost, risk or customer experience.

You get: a sized long-list of use cases tied to business goals.

Prioritise

Portfolio prioritisation and business cases

Each opportunity is scored on value, feasibility and risk, and the strongest ones get a business case leadership can fund.

You get: a ranked portfolio and business cases for the first wave.

Plan

Roadmap and operating model

We sequence the portfolio over 12 to 24 months, decide what to build, buy or partner on, and set out ownership, governance and funding.

You get: a board-ready roadmap, governance framework and operating model.

Mobilise

Mobilisation and change

Strategy only counts once something ships. We turn the first wave into delivery specs with KPIs, and plan the training and change your teams need.

You get: delivery-ready specs, a KPI framework and a change plan.

Prioritise

Every opportunity scored on value, feasibility and risk

Value covers revenue, cost, risk and customer impact. Feasibility covers data, systems, skills and change effort. The top-left quadrant becomes the first wave; the bottom-right is what we advise you not to fund yet.

Build first

  • Invoice entry · hours saved high, risk low · top 3
  • Ticket triage · hours saved high, risk low · top 3
  • Quote checks · hours saved high, risk medium · top 3

Plan

  • Contract review · hours saved high, risk high

Quick win

  • Weekly reporting · hours saved low, risk low

Leave alone

  • Pricing exceptions · hours saved low, risk high
IllustrativeExample workflows, not client data. Your map is built from your own processes.

Why ATI Lab

Strategy you can actually execute

Enterprise view, grounded in delivery

The same structured approach as a top-tier strategy engagement: maturity, value, portfolio, roadmap, governance. But the estimates come from people who have shipped production AI.

We tell you what not to pursue

Some ideas are too early, too risky or not worth the money. Saying so protects your budget, your data and your credibility with the board.

From strategy to first release

The first wave is written as build specs with KPIs, so delivery can start the week after sign-off, with our team or yours.

What the strategy includesTypical strategy deckATI Lab AI strategy
Enterprise-wide view of where AI creates valueYesYes
Portfolio ranked by value, feasibility and riskOftenYes
Business case for each first-wave initiativeSometimesYes
Governance framework and operating modelYesYes
Cost and effort estimates from shipped workNoYes
First wave specified and ready to buildNoYes

FAQ

AI strategy questions

What does an AI strategy engagement include?

Five phases: a maturity and readiness assessment, a value opportunity assessment across your functions, prioritisation with business cases, a 12–24 month roadmap with governance and an operating model, and mobilisation of the first wave. Each phase ends with a deliverable leadership can act on.

How is this different from a large consultancy's AI strategy?

The structure is similar: maturity, value, portfolio, roadmap, governance. The difference is that ATI Lab also designs, builds and runs AI systems, so feasibility and cost estimates come from shipped work, and the first initiatives can move straight into delivery instead of stalling after the final presentation.

Does the strategy cover governance, risk and compliance?

Yes. The roadmap includes an AI governance framework: policies, approval and review points, data handling, model risk and the regulatory obligations that apply to your sector and markets, sized to your organisation rather than copied from a template.

How long does it take?

It depends on the size of the organisation and how many functions are in scope. A focused assessment for one business unit is much shorter than an enterprise-wide strategy. We fix scope, timeline and fee after the first conversation.

Who needs to be involved on our side?

An executive sponsor, the leaders of the functions in scope, and the owners of your key systems and data. We keep the time asks short and structured: interviews, a short survey and a few working sessions.

Do we have to build with you afterwards?

No. The roadmap and specs stand on their own and are written so any competent team can deliver them. Many clients continue with us because the team that scoped the work is the fastest path to production, but that is a choice, not a requirement.

Next step

Get an AI roadmap your board will fund and your teams can deliver

Start with a 30-minute strategy session. We'll discuss your goals, where AI could matter most, and what an assessment or full strategy would cover for an organisation your size.