The AI Marketing Canvas: A Five-Step AI Plan for Marketers
One book, placed in its field — what Rajkumar Venkatesan, Jim Lecinski's book gets right, where it goes further than the rest, and what the rest of the field adds.
Mike West, Editor · Leading With Data · marketingleader.guide/guides/profile-ai_marketing_canvas
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The AI Marketing Canvas: A Five-Step AI Plan for Marketers
One book, placed in its field — what Rajkumar Venkatesan, Jim Lecinski's book gets right, where it goes further than the rest, and what the rest of the field adds.
Mike West, Editor · Leading With Data · marketingleader.guide/guides/profile-ai_marketing_canvas
The problem
Business Growth and Marketing ROI erodes when it is left to instinct instead of method.
You were taught the moves piecemeal, never the whole model.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
The model
- 01Clean Customer-Focused Data Foundation
- 02AI Experimentation with Vendor Tools
- 03In-House AI Capability Expansion
- 04AI Marketing Champion
- 05Full Transformation and Automation
- 06AI-First Organizational Culture
- 07Personalization Capability at Scale
- 08Customer Trust in AI and Brand
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
Step 1 of 5 · Clean Customer-Focused Data Foundation
A foundation is defined by identity resolution and freshness, not by storage volume.
Misconception
That having lots of data — a data lake, a CDP purchase, years of transaction logs — means you have a foundation ready for AI.
Reality
Volume is not readiness; models need data that is connected at the individual-customer level and continuously cleaned, and most organizations hold their richest data in function-shaped silos (campaign, service, commerce) that never resolve to a single person.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
Step 2 of 5 · AI Experimentation with Vendor Tools
Aim for one attributable win in one moment, not a broad tool evaluation.
Misconception
That experimentation means testing many tools broadly to see what sticks, or that a pilot should aim to prove a large transformative use case.
Reality
The point is not to survey the vendor landscape but to attack one identified value pocket in a specific customer moment with a rented tool, so learning is fast and the win is attributable.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
Step 3 of 5 · In-House AI Capability Expansion
Insourcing competency, not adding tools, is the defining move of this stage.
Misconception
That expansion means signing bigger vendor contracts and replicating the successful pilot everywhere at once.
Reality
Expansion is a deliberate insourcing of capability — hiring data science talent, appointing a champion, and reducing external reliance — even if you keep some vendors, so that the strategic knowledge accrues to you.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
Step 4 of 5 · AI Marketing Champion
The champion's core skill is translation between domains, not depth in either one.
Misconception
That the champion is a senior data scientist, or alternatively a marketing generalist who 'gets' AI.
Reality
The role is a bilingual technologist whose value is translation and orchestration — turning marketing problems into ML problems and ML outputs into business cases — not personally building models or running campaigns.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
Step 5 of 5 · Full Transformation and Automation
AI-first is a workflow redesign, not a task-automation exercise.
Misconception
That transformation is automating individual tasks faster — replacing manual steps one by one within the existing workflow.
Reality
AI-first means redesigning the workflow itself around what machines do well, not bolting automation onto human-shaped processes; and it forces explicit build-versus-buy decisions on your most strategic capabilities.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
The cheat sheet
- Clean Customer-Focused Data FoundationA foundation is defined by identity resolution and freshness, not by storage volume.
- AI Experimentation with Vendor ToolsAim for one attributable win in one moment, not a broad tool evaluation.
- In-House AI Capability ExpansionInsourcing competency, not adding tools, is the defining move of this stage.
- AI Marketing ChampionThe champion's core skill is translation between domains, not depth in either one.
- Full Transformation and AutomationAI-first is a workflow redesign, not a task-automation exercise.
- AI-First Organizational CultureCulture gates every downstream construct — it must lead the technology, not trail it.
- Personalization Capability at ScalePersonalization at scale is real-time and generative, distinct from templated segmentation.
- Customer Trust in AI and BrandTrust moderates the payoff of every customer moment — high capability with low trust underperforms.
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data
Sources
- The AI Marketing Canvas: A Five-Step AI Plan for Marketers — Rajkumar Venkatesan, Jim Lecinski
The AI Marketing Canvas: A Five-Step AI Plan for Marketers · Mike West, Editor · Leading With Data