Accelerator · AI Strategy
AI ideas aren't scarce. Captured value is.
Most AI strategies lose the link back to business strategy and the value proposition customers pay for. The AI Value Canvas puts it back: one page per use case, from strategic priority to P&L line.
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AI is a good trigger to review how everything is done, cut operating costs and implement known use cases better. That is useful. It is also what every competitor is doing with the same tools.
Three patterns show up again and again:
- Pilots stall. Success was never defined, so "it worked" can always be argued.
- Value is never banked. The old way keeps running alongside the new one, and the P&L never moves.
- Portfolios take the easy path. It is easier to solve problems that are well understood than the ones the strategy has tasked us with, where no one has blazed the trail. The easy path ends in parity.
The question worth asking: if a competitor bought the same models tomorrow, what would they still not have?
What the AI Value Canvas is
A one-page canvas for a single AI use case. It forces the questions that decide whether value is captured, before anyone writes code:
- What decision or workflow are we changing, and what does it replace today?
- What does success look like, measured how, against what baseline?
- Who owns the value, and on which P&L line does it land?
- What are the biggest risks, and how are they contained?
Every box comes with scoring criteria, so a canvas can be judged as well as filled in. Weak boxes show you where the use case is likely to fail.
How to use it
- Step 1
Start from the strategy, not the idea list.
Before any canvas is filled, write down the three to five strategic priorities and the value proposition customers pay you for. Every use case should trace back to one of them. If it can't, it isn't aligned, however attractive it looks.
- Step 2
Scan quickly to prioritise.
Fill a canvas for each shortlisted idea in 20 to 30 minutes, with business, technical and risk people in the same room. "Unknown" is a valid answer. The unknowns become your design work plan, and blockers show up before weeks are spent in design.
- Step 3
Complete it with evidence to prove value.
For the use cases you take forward, complete every box with real data: a measured baseline, a target agreed before the pilot runs, and the evidence that it worked. Set the bar before you jump.
- Step 4
Carry it forward.
The canvas doesn't get filed away. Its boxes become the gate criteria, the KPIs and the review items once the solution is live. That is what keeps one thread from strategy to the P&L.
Two canvases, one method
Traditional AI
For prediction and optimisation: churn, demand, risk scoring, next best action, truck roll avoidance.
Covers: The decision to optimise, the process it replaces, prediction target, data and features, implementation plan, team, value statement and biggest risks.
Generative and agentic AI
For assistants, copilots, document processing and agents that take actions.
Covers: The task or workflow, the process it replaces, context, tools and action space, autonomy and human checkpoints, success definition, evaluation and assurance, value statement, and risks and guardrails.
Not sure which one? If the output is a prediction or a score, use Traditional AI. If it is generated content or an action taken on someone's behalf, use Generative and agentic.
What the canvas won't do on its own
A canvas makes a use case honest. It doesn't build a portfolio. Choosing which use cases deserve a canvas, sequencing them, and making sure the value actually reaches the P&L is the harder part.
That is what the full AI Value Playbook covers: four phases, four gates, and one thread from strategy to captured value. It also includes companion sheets for organisational impact and for decisions and differentiation, which are used with clients in workshops.
Questions every AI portfolio should answer
- 1.Which strategic priority does each initiative move, and would a customer notice?
- 2.Who owns the value, by name, on which P&L line?
- 3.What will we stop doing when it works?
If your team can't answer all three for every AI initiative you are funding, we should talk.