AI Product Strategy
Most AI projects fail before a line of code is written — unclear use cases, poor data readiness, no measurable goal. This engagement applies the first four stages of the Business-First AI™ methodology to identify where AI genuinely moves the needle, and build the roadmap to get there.
Built on Business-First AI™
This service applies stages D1–D4 of the 7D methodology: Discover → Diagnose → Define → Design. The output is a validated AI product strategy your team can execute — not a slide deck.
The 4-Stage Process
Discover — Problem Definition
Identify where AI can create measurable business value. Not where it's technically possible — where it changes a real outcome that your organisation cares about.
Diagnose — Readiness Assessment
Score your organisation across 5 dimensions: Data Quality, Process Maturity, Team Capability, Leadership Alignment, and Technology Infrastructure. Surface blockers before committing budget.
Define — Use Case Prioritisation
Apply RICE scoring (Reach × Impact × Confidence ÷ Effort) against data availability and strategic alignment. Produce a ranked shortlist your leadership can act on.
Design — Roadmap & Requirements
Translate the prioritised use cases into a phased roadmap with detailed requirements — everything engineering needs to build the right thing, first time.
What You Get
- AI Opportunity Map — 5–8 prioritised use cases with business case
- AI Readiness Scorecard — 5 dimensions scored 0–5 with gap analysis
- Use Case Prioritisation Matrix with RICE × strategic alignment scores
- Phased Implementation Roadmap (0–3 months, 3–9 months, 9–18 months)
- Build vs. buy vs. partner recommendation per use case
- Success metrics and measurement framework (D7 — Drive)
Common Questions
What is Business-First AI™ and how does it apply here?
Business-First AI™ is the methodology behind this service. It's a 7-stage framework that starts every AI initiative with a validated business problem (not a technology bet), runs through structured diagnosis, definition, and design, and ends with a measured business outcome. AI Product Strategy is the consulting application of the first four stages: Discover, Diagnose, Define, and Design.
How do I know if my organisation is ready for AI?
Readiness depends on five dimensions: Data Quality, Process Maturity, Team Capability, Leadership Alignment, and Technology Infrastructure. An AI Readiness Assessment scores each of these (0–5) and produces a prioritised blocker list — so you know exactly what to fix before committing to any AI initiative.
Do you implement AI, or just advise?
I focus on strategy and requirements — defining what to build and why, selecting the right approach or vendor, and writing the specifications your engineering team needs to execute. I bridge the gap between business vision and technical delivery without writing production code.
How long does an AI strategy engagement take?
An AI Readiness Assessment typically runs 2 weeks. A full AI Product Strategy engagement from Discover through Design usually takes 4–6 weeks depending on the complexity of your data landscape and stakeholder ecosystem.
Let's talk AI
Book a free 30-minute discovery call
Bring your AI challenge — unclear use cases, a stalled initiative, or a blank slate. We'll figure out the right next move together.