Use when AI Marketing Canvas Assessment is needed to produce a scored assessment for social-media or digital-marketing work; use `ai-readiness-diagnostic` when its narrower outcome is requested.
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Use when AI Marketing Canvas Assessment is needed to produce a scored assessment for social-media or digital-marketing work; use `ai-readiness-diagnostic` when its narrower outcome is requested.
Use this skill when the requested outcome is specifically a scored assessment and the supplied brief falls within ai marketing canvas assessment.
Do Not Use When
Use ai-readiness-diagnostic when its narrower output is the real deliverable; do not use this skill as a generic substitute.
Do not use it to publish, send, spend, alter a live account, or make unsupported legal, platform, performance, or certification claims.
Required Inputs
Artefact
Source/provider
Required?
If absent
AI marketing use-case brief, intended human control point and success measure
Requester or approved brief
Yes
Stop and request the missing decision context.
Brand voice, offer facts, constraints and approvals
Client source pack or authorised owner
Conditional
State assumptions; do not invent names, prices, results or approvals.
Performance, platform or research evidence used for claims
Traceable export, URL, document or named source
Conditional
Issue a qualified finding and identify the evidence needed.
Capability and Permission Boundaries
Default to read-only: inspect supplied material and report findings. Editing, publishing, contacting people, spending, or changing live systems requires separate explicit authority. Minimum capabilities are read access to supplied files and search across the authorised evidence set. Use only the files, tools, accounts and evidence made available for the engagement, expose every unassessed check, and obtain explicit authority before any mutation.
Degraded Mode
Fallback: if files, network access, platform data, language review or production tools are unavailable, return the narrowest useful qualified scored assessment; mark unavailable checks not assessed and never convert them into a pass.
Decision Rules
Choice
Action
Failure or risk avoided
Data readiness, AI maturity and risk support the proposed operating level
Choose the lowest viable automation level and define its human approval gate.
Automating an unsafe or unevaluable marketing process.
A required fact or approval is missing
Stop that claim or action; request it or use an explicit placeholder.
Fabricated facts, implied consent or unauthorised publication.
Evidence is partial but a useful draft is possible
Deliver a qualified draft with gaps and the next verification step.
Treating an unassessed requirement as passed.
Workflow
Confirm the exact scored assessment, consumer, market, channel and approval boundary; route to ai-readiness-diagnostic if it is the closer match.
Inventory supplied facts, source provenance, constraints and missing inputs; stop if the objective, audience or authority is unknowable.
Select the domain method and record the material decision behind it before drafting.
Produce the smallest complete scored assessment; keep facts traceable and placeholders visibly unresolved.
Test the result against the decision table, domain quality criteria and anti-slop gate; recover by narrowing or qualifying unsupported portions.
Deliver the artefact with evidence, assumptions, unassessed checks and the next approval or verification step.
Outputs
Artefact
Consumer
Observable acceptance condition
Scored assessment
Requester, client reviewer or delivery team
The scored assessment addresses the named audience and objective, records assumptions, and passes the skill's domain checks without invented facts.
Decision and gap note
Approver or next workflow
Names the chosen route, evidence used, unresolved inputs and any action requiring authority.
Evidence Produced
Evidence
Format
Acceptance condition
Finding-to-source register and unassessed-check list
Inline table, checklist or linked source note
Every material claim, decision and unavailable check is traceable.
Quality Standards
Preserve the domain guidance and East African market context below; replace it only when the requester names another market.
Use British English unless the target language or market requires otherwise, and verify names, figures, quotations and platform rules before use.
Make the key choice visible, cover failure and edge cases, and keep the result ready for its named consumer.
Run the repository's anti-ai-slop ship gate; a blocking factual, cultural, safety or permission defect stops release.
Anti-Patterns
Writing before the objective and audience are known. Fix: stop and obtain the missing brief fields.
Reusing a neighbouring skill's template because the headings look similar. Fix: route by the requested scored assessment, not vocabulary overlap.
Adding a price, result, quotation, platform limit or cultural claim without a traceable source. Fix: verify it or qualify/remove it.
Treating missing access, evidence or native-language review as approval. Fix: mark the check not assessed and narrow the result.
Publishing, sending, spending or changing a live account from drafting authority alone. Fix: obtain explicit action-specific authority and retain the approval record.
Most businesses talk about AI in marketing without knowing where they actually stand or what
"progress" looks like for their size and context. This skill produces a completed AI Marketing
Canvas — a structured diagnostic and roadmap grounded in Venkatesan and Lecinski's (2026)
five-step model — that tells a client exactly what step they are on, what they should do in each
of the four customer moments, and what their next 12 months should look like.
For the full 41-item AI readiness diagnostic, use the sister skill ai-readiness-diagnostic.
This skill focuses on canvas completion and roadmap output.
Framework source: Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd ed.
Stanford Business Books.
Required Input
Before generating any output, ask for the following:
Client business name — the trading name used in all deliverables.
Industry — what sector is the client in (e.g., retail, hospitality, financial services, NGO)?
Country / city — where is the business based and where is its primary audience?
(Default: Uganda / East Africa)
Primary marketing goal — what is the single most important marketing outcome this year?
Current tools in use — list any CRM, content tools, scheduling platforms, and analytics
tools currently in use. If none, say so.
Team size — solo operator, 2–5, 6–20, or 20+ people in the marketing function.
Monthly marketing budget range (UGX) — approximate band: under 500k, 500k–2M, 2M–10M,
10M+. If a different currency applies, note it.
Step 1 — Run the Canvas Diagnostic
Ask the client the following nine questions. Record yes/no answers.
#
Diagnostic Question
Step Indicator
1
Does the client have a centralised customer database (CRM or equivalent)?
Step 1
2
Is there a named person responsible for data and analytics?
Step 1
3
Has the client used any AI tools for content creation, scheduling, or analytics?
Step 2
4
Have any AI experiments shown measurable results (e.g., time saved, engagement lift)?
Step 3
5
Is AI integrated into more than two marketing functions?
Step 3
6
Does the client have a documented AI use policy?
Step 3
7
Is there real-time personalisation in any channel?
Step 4
8
Does AI inform budget decisions or campaign strategy?
Step 4
9
Are any revenue streams enabled or substantially transformed by AI?
Step 5
Diagnosis logic — count total yes answers:
Yes count
Current Step
Label
0
Step 1
Foundation
1–2
Step 2
Experimentation
3–5
Step 3
Expansion
6–7
Step 4
Transformation
8–9
Step 5
Reinvention
State the diagnosed step clearly at the top of the canvas output. Be honest: most East African
SMEs will land at Step 1 or Step 2. Do not inflate the diagnosis.
Step 2 — Complete the AI Marketing Canvas
The canvas has five steps (rows) and four customer moments (columns), producing 20 cells.
Populate every cell for the client's current step and next step in full. Summarise the
remaining steps in one sentence each.
The Five Steps
Step 1 — Foundation
AI is not yet deployed. The focus is data infrastructure and organisational readiness.
AI identifies and creates new revenue streams from existing customer relationships
Full data platform
New business model lines
Advocacy
Community AI — AI tools that advocates use to create and share content
Community platform data
Advocate-led growth at scale
Step 3 — Produce the 12-Month Roadmap
Structure the roadmap by quarter. Every action must include a named tool or channel, a named metric,
and a Q assignment.
Standard roadmap template — adapt to client's diagnosed step and context:
Q1 — Diagnose and Establish
Confirm current step based on diagnostic results.
Complete a data audit: identify where customer data lives, who owns it, and what is missing.
Set up or clean the customer contact list (CRM, spreadsheet minimum standard).
Launch 1–2 low-risk AI experiments appropriate to current step (e.g., AI caption writing in
ChatGPT, scheduling via FeedHive or Buffer).
Metric: baseline content output volume, time spent on content creation per week.
Q2 — Measure and Scale One Experiment
Review Q1 experiment results against baseline.
Select the single most successful experiment and scale it (increase frequency, apply to more
channels, or expand to a second content type).
Begin mapping the customer journey for the retention moment.
Metric: time saving from AI tools, engagement rate change, WhatsApp open or reply rate.
Q3 — Integrate and Expand
Integrate AI into one additional marketing function beyond content creation.
For EA context: consider WhatsApp automation for retention or sentiment monitoring for advocacy.
Draft and publish an internal AI use policy (see playbook-ai-content-workflow for guidance).
Metric: functions using AI (target: 3+), policy in place (yes/no).
Q4 — Review Canvas Progress and Set Year 2 Targets
Re-run the nine-question diagnostic to check step progression.
Update the canvas: complete the next step's cells for any moment where Q1–Q3 work is confirmed.
Set SMART objectives for Year 2 based on confirmed capabilities.
Metric: step movement (did the client advance one step?), Year 2 AI investment recommendation
in UGX.
Step 4 — Write the Plain-Language Summary
After the canvas and roadmap, produce a section titled "What This Means for Your Business".
This section must:
State the diagnosed step in plain language ("You are at Step 2 — Experimentation").
Explain what that means in one paragraph without jargon.
Name the single highest-impact action the client can take in the next 30 days.
Be honest about the gap between current state and transformation — do not promise shortcuts.
Be written as if speaking directly to a business owner, not a marketing professional.
Step 5 — Monetisation
At this stage, AI capabilities become a source of competitive advantage and new revenue:
AI-powered products or services sold to customers (e.g. a personalisation engine licensed to partners)
Proprietary audience data monetised through partnerships
AI-driven efficiency gains reinvested into market expansion
Brand reputation as an AI-first organisation attracts premium clients and talent
Consultancy note: Most EA clients will not reach Step 5 within a 12-month engagement. Frame it as a 3–5 year horizon goal and use it to demonstrate the long-term value of starting the Canvas journey now.
East Africa Context Notes
Apply these adaptations throughout the canvas and roadmap:
Data scarcity — most EA SMEs have no CRM; customer data lives in WhatsApp groups,
spreadsheets, or paper records. Step 1 must address this before any AI deployment.
WhatsApp first — WhatsApp is the primary channel for retention and advocacy in Uganda and
across East Africa. Prioritise WhatsApp automation at Step 2–3 over email sequences.
Mobile Money — MTN Mobile Money and Airtel Money are transaction platforms; personalised
promotions tied to Mobile Money behaviour are a Step 4 opportunity.
Step 2 tools for EA context — ChatGPT or Claude for captions and blog briefs; FeedHive or
Buffer for scheduling; Canva Magic Write for short-form copy; Google Alerts for brand monitoring.
Step 3 tools for EA context — Africa's Talking for WhatsApp and SMS automation; Hootsuite
Insights or Brandwatch (if budget allows) for sentiment monitoring.
Most EA SMEs are at Step 1–2 — calibrate ambition accordingly. A Step 2 roadmap executed
well is more valuable than a Step 4 roadmap that cannot be implemented.
Agile Sprint Approach (Venkatesan and Lecinski, 2026)
AI marketing initiatives fail when treated as annual strategic plans. Recommend monthly sprint cycles:
Sprint planning (Day 1): Select one AI use case to test this month
Pilot execution (Days 2–20): Run the experiment with a defined audience segment
Measurement (Days 21–25): Compare AI-assisted results vs human-led baseline
Review (Days 26–28): Replicate, iterate, or abandon based on results
Next sprint (Day 30): Select next use case based on learnings
KPI for each sprint: measure lift vs human-led control. A 10% improvement justifies scaling.
AI-to-AI Marketing Readiness (Venkatesan and Lecinski, 2026)
As consumers increasingly use AI agents (ChatGPT, Perplexity, Google Gemini) to research, compare, and purchase, brands must be readable by machines as well as humans. Assess:
Are product pages structured with clear, machine-parseable pricing and features?
Are brand values explicitly stated in factual, accessible language?
Is content well-sourced and factually accurate (LLMs avoid citing inaccurate sources)?
Does the website use structured data markup (Schema.org)?
This is a 2–5 year horizon for most EA markets but should inform content architecture decisions now. Brands that are not AI-readable risk becoming invisible as AI-native search and AI shopping agents become mainstream.
Quality Criteria
Output meets standard when it:
Diagnoses the client's step based on evidence from the nine questions, not aspiration or
optimism — step inflation is a failure mode.
Addresses all four customer moments for both the current step and the next step in full, with
named AI capabilities, required data, and expected results.
Produces a roadmap that is concrete: every action names a tool, a channel, and a metric.
Reflects East African context throughout — WhatsApp, Mobile Money, and data scarcity are noted
where they affect the recommended approach.
Assigns every roadmap action to a specific quarter (Q1, Q2, Q3, or Q4).
Includes a plain-language "What This Means for Your Business" summary written for a business
owner, not a marketing specialist.
Is honest about step progression — a realistic Step 1–2 plan is better than an inflated Step 4
plan the client cannot execute.
Cites Venkatesan and Lecinski (2026) on first use of the framework.
References
Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd ed. Stanford Business Books.
Chaffey, D. (2024) Digital Marketing: Strategy, Implementation and Practice. Pearson.
Bodnar, K. and Cohen, J. (2012) The B2B Social Media Book. Wiley.
Related skills:
ai-readiness-diagnostic — the full 41-item AI readiness diagnostic; run this before or
alongside the canvas assessment for a more detailed organisational audit.
playbook-ai-content-workflow — execution playbook for AI-assisted content production.
playbook-ai-automation-workflow — automation and tool integration guidance.
05-social-media-strategy — full social media strategy; the canvas roadmap feeds into this.
