AI Discovery
Find where AI will actually move your numbers — before you commit a budget.
The problem
"Every vendor starts with their product. We start with your numbers."
The 200-slide deck
Big 4 AI assessments produce extensive frameworks nobody acts on. By the time a recommendation reaches a board, the market has moved.
The pilot that never scales
AI pilots succeed technically and stall commercially. Missing: an honest feasibility assessment and a business case built for the CFO's question, not the engineer's.
Starting with the wrong problem
Most organisations begin with the most visible AI use case — not the highest-value one. The difference between the two can be the difference between a tool and a transformation.
Method
Four phases. One decision.
Kick-off & context
Understand the business model, priority metrics, existing data, current pain points. Map the organisational landscape.
Process discovery
Interviews with 5–10 business stakeholders (process owners, sales, operations, IT). Map processes, decision flows, data availability, volume of repetitive tasks. Generate a long list of AI candidates.
Scoring & prioritisation
Score all candidates against value (impact on your priority metric), feasibility (data, integration, timeline), and time-to-value. Build a ranked opportunity map.
Output & delivery
Business cases for the top 3 candidates. Decision brief for CEO/board. Ready to present, ready to decide.
What you get
Facts, not recommendations.
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AI Opportunity Map
Full candidate list with scoring rationale — positioned on a value × feasibility matrix.
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Top-5 ranked opportunities
Each with scoring rationale, business impact estimate, and feasibility assessment.
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One-page business case (top 3)
What it is, what it delivers, what it costs, what it requires. Built for the CFO question.
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CEO/board decision brief
3–5 slides. No technical jargon. Ready to present.
Who it's for
The decision owner.
Owns the revenue or cost line AI would affect. Needs a ranked list and a business case — not a technology roadmap.
Owns the digital agenda. Needs AI opportunities tied to business metrics, not to model architectures.
Owns operations. Needs to know where repetitive, high-volume decisions can be safely augmented.
What comes next
AI Discovery opens the door.
Intent Architecture Workshop
→Define what your AI systems should optimise for — before you build them.
Business Case Validation Canvas
→Test the financial and operational assumptions behind your top opportunity before committing to build.
Tech Feasibility
→Validate that the architecture for your top-priority opportunity is buildable, at the estimated cost, with your actual data.
Ready to find out where AI will actually move your numbers?
Every engagement starts with a short conversation. No commitment, just specifics.
Let's talk →