AI · Deep dive 01
AI Opportunity Mapping
Before a single line of code, we scan your operations, products and ambitions for the places AI actually compounds value. What to build, what to buy, what to skip — ranked by impact, not hype.
The scope
A short, focused engagement that produces a ranked opportunity list: where AI is worth investing, where it isn't, and what each build would cost. An honest map, not a pitch for more engagements.
Does this sound familiar?
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The board keeps asking what the AI strategy is and the team doesn't have a good answer.
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Every department has a 'we should use AI for this' idea and none of them have been costed.
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Vendors are pitching AI features daily; nobody has the framework to evaluate them.
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You've built AI demos that never shipped because 'production' was scarier than anyone admitted.
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Leadership wants 'an AI roadmap' and the team doesn't know where to start.
The customer payoff
The payoff
What you feel once it’s running.
A ranked shortlist of AI opportunities with impact and effort honestly estimated.
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Build-vs-buy recommendations per opportunity.
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The 'not worth it' list — equally valuable.
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A shared language in leadership for evaluating the next 12 months of AI pitches.
Phases
⏱ 2–4 weeksHow AI Opportunity Mapping actually runs.
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01
Listen
Interviews with every function: product, ops, support, sales, marketing. What's slow? What's manual? What keeps breaking?"
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02
Score
Each opportunity scored on impact (hours saved, revenue uplift, quality gain), cost (build + ongoing), risk (model, data, compliance)."
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03
Triage
Short workshop with leadership to walk the list and rank. We facilitate; you decide."
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04
Write it up
One-page opportunity register + one-pager per opportunity with scope, rough cost, and dependencies."
The hand-off
You walk away with
What lands in your hands — every artefact, nothing hidden.
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AI opportunity register — all ideas, scored and prioritised
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One-pager per top-5 opportunity
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Build-vs-buy recommendation per opportunity
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'Not worth it' list with reasoning
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Suggested sequencing for the next 12 months
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Shared evaluation framework for future AI pitches
Questions we get
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Q·01 Do we need to have data ready?
No. Part of the engagement is evaluating data-readiness per opportunity. Data gaps are findings, not blockers."
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Q·02 What if none of the opportunities are worth it?
That's a valid finding. We've told multiple clients 'wait six months' and they've thanked us later. The point of the engagement is honest answers, not manufactured demand."
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Q·03 Can we combine this with an AI build?
Yes — many clients use this as the scoping phase for a downstream build engagement. We'll tell you upfront if we recommend doing the build."
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Q·04 Who should we involve?
At minimum: CEO / COO, product lead, engineering lead, the operators who actually do the work that might be automated. Roughly 8–12 interviews."
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Q·05 What's the output format?
A working document (Notion / Google Docs), plus a 1-hour walkthrough. PDF version available on request but nobody reads PDFs."
Ready to start
Get a map, not a pitch.
Two to four weeks to an honest ranked list of where AI compounds for you — and where it doesn't. Let's walk the ground together.
Start an opportunity mapThe wider map
Every service page at a glance.
Each link below opens a dedicated page on that specific piece of one of our four service pillars. Jump sideways — different service, same way of working.
Digital Product Strategy
Service overview →Web & Mobile Development
Service overview →Business Automation
Service overview →AI Integration
Service overview →- 01 AI Opportunity Mapping — you’re here
- 02 AI-Driven Product Features
- 03 AI-Powered Automation
- 04 Evaluations, Guardrails & Observability
- 05 Vendor-Neutral Integration