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Know exactly where AI pays back, before you spend

A short, evidence-led engagement that maps where AI will reduce cost or recover time in your business, ranks the options by return and risk, and gives you a sequenced plan you can budget against.

Right for you if
You know AI matters but every vendor pitch sounds the same.
Outcome
A ranked, costed plan you can take to your board.
Timeline
2–3 weeks.
Pricing
Fixed fee, scoped to your systems and volumes after a discovery call.
Two people planning on a whiteboard
The problem

Why this keeps going wrong

AI decisions get made on the wrong criteria: whoever demoed most convincingly, whatever a competitor announced, whichever tool someone already pays for.

The fix is not complicated. Apply the same discipline you would apply to any other capital decision. Know the baseline, compare options on one scale, and be explicit about what you will not do this year.

Signs this is you

  • You have been asked for an AI strategy and do not know where to start.
  • You are evaluating vendors with no way to compare their claims.
  • A pilot has stalled and nobody can say why, or what it returned.
  • Different teams are buying different tools independently.
  • You suspect you already spend on AI but cannot total it.
The engagement

What happens, week by week.

  1. Week 1

    Find out what is actually happening

    Short interviews across functions, kept non-punitive so people tell you which tools they really use.

    You get: A current-state map: tools in use, owners, data touched, spend to date.

  2. Weeks 1–2

    Measure the processes, not the technology

    Volume, time and cost baselines for the processes that matter.

    You get: A baseline you can measure future change against.

  3. Week 2

    Score every opportunity on the same scale

    Time or cost recovered, effort, dependency risk and governance risk.

    You get: A ranked opportunity register with the scoring shown, not hidden.

  4. Week 3

    Sequence it, cost it, and say what to avoid

    A phased plan with indicative cost, and an explicit "not this year" list.

    You get: A sequenced roadmap and a six-page board summary.

Deliverables

What you walk away with.

Current-state assessment

What is in use, by whom, touching which data, at what cost.

Opportunity register

Every candidate use case, scored and ranked.

Sequenced roadmap

Phases, dependencies, indicative budget and owners.

Board-ready summary

Six pages in commercial language, not a technical specification.

Included

  • Interviews across functions
  • Discovery of unsanctioned AI tool use
  • Baseline measurement
  • Scoring and ranking
  • Indicative cost and effort per phase
  • A board presentation with live Q&A

Not included

  • Building anything
  • Vendor procurement or contract negotiation
  • A full data warehouse or architecture review
  • Change-management delivery (we flag it, we do not run it)
What we measure

How you'll know it worked.

  • AI tools discovered vs. previously known
  • Baseline hours and cost per process
  • Top three use cases costed to ±30%
  • A decision made by leadership. A document alone counts as failure.

Questions we hear a lot

Is three weeks really enough?

For most businesses, yes. A longer engagement produces a thicker document, not a better decision.

What if the answer is that we should not invest yet?

The report says so. It happens in a minority of engagements, usually because the data or process is not ready.

Do we need our data ready first?

No. Assessing it is part of the work.

Who needs to be involved from our side?

A sponsor with authority, and six to ten hours of people's time in total.

Will you then quote to build what you recommended?

If you want us to. You are free to take the plan elsewhere.

Start with a conversation, not a proposal.

Thirty minutes with someone who has built this before. If we're not the right fit, we'll say so and point you to who is.