AI Value Canvas public guide

One practical reading path for stronger AI decisions.

Start with the purpose and framework, work through the four domains, then use the scenarios, templates, and closing guidance to decide what should happen next.

01 · Start here

Why the AI Value Canvas Exists

Why an AI idea needs more than technical possibility before commitment.

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02 · Framework

The AI Value Canvas at a Glance

See the ten elements, four domains, and decision context that make up the Canvas.

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03 · Desirability

Customer Understanding: Start with the Work, Not the AI

Start with the people, work, pains, gains, and adoption conditions that matter.

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04 · Feasibility

AI Opportunity & Solution

Test whether AI is proportionate to the task and design the interaction responsibly.

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05 · Sustainability

Data, Model & Risk: Build and Maintain Responsibly

Establish the data, model, safeguards, and operating conditions needed to proceed.

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06 · Viability

Value & Cost: Make the Viability Case

Define credible outcomes, costs, unit economics, and build-buy-partner choices.

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07 · Portfolio

Portfolio Decisions and Scaling AI Initiatives

Choose, sequence, and scale initiatives with evidence and accountable ownership.

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08 · Examples

Worked Scenarios and Evidence Vignettes: Applying the AI Value Canvas

Apply the Canvas through worked scenarios and bounded evidence vignettes.

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09 · Working template

AI Value Canvas Working Template

Use the detailed prompts, thresholds, and decision records for one initiative.

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10 · References

References and Further Reading

Review the sources and further reading that support the public guide.

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11 · Next decision

Closing: Use the AI Value Canvas on Your Next Decision

Close the loop with practical next steps, human support, and accountability.

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12 · About

About the Author

Meet the creator of the AI Value Canvas and the intent behind the resource.

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