AI Readiness Diagnostic

Use when

Conducts a 41-item diagnostic to assess a client's AI marketing maturity, identify their current AI Marketing Canvas step (1–5), and produce a scored maturity profile with a prioritised action plan. Invoke this skill when a client wants to understand where they stand on AI adoption, before beginning any AI strategy, tool selection, or training investment. Based on Venkatesan and Lecinski (2026) The AI Marketing Canvas, 2nd edition, Stanford Business Books.
Use this skill when it is the closest match to the requested deliverable or workflow.

Do not use when

Do not use this skill for graphic design, video production, software development, or legal advice beyond the repository's stated scope.
Do not use it when another skill in this repository is clearly more specific to the requested deliverable.

Workflow

Collect the required inputs or source material before drafting, unless this skill explicitly generates the intake itself.
Follow the section order and decision rules in this SKILL.md; do not skip mandatory steps or required fields.
Review the draft against the quality criteria, then deliver the final output in markdown unless the skill specifies another format.

Anti-Patterns

Do not invent client facts, performance data, budgets, or approvals that were not provided or clearly inferred from evidence.
Do not skip required inputs, mandatory sections, or quality checks just to make the output shorter.
Do not drift into out-of-scope work such as code implementation, design production, or unsupported legal conclusions.

Outputs

An AI-focused strategy, audit, system design, or prompt asset in markdown with human review and control points.

References

Use the inline instructions in this skill now. If a references/ directory is added later, treat its files as the deeper source material and keep this SKILL.md execution-focused.

Purpose

Assess a client's current AI marketing maturity across five domains, calculate their AI Marketing Canvas step, and produce a practical, prioritised action plan that reflects their actual starting point. Output is structured for a non-technical business owner to read and act on immediately.

After completing this diagnostic, refer the client to the sister skill ai-marketing-canvas-assessment for full canvas completion and strategic roadmap development.

Required Inputs

Ask for the following before beginning:

Business name — trading name of the client organisation
Industry — sector and nature of the business
Country / city — primary operating location (default: Uganda/East Africa)
Primary marketing goal — what the client most wants marketing to achieve
Team size — approximate number of people in the marketing function

Then walk through all 41 diagnostic questions together with the client, recording Y (Yes) or N (No) for each item. Do not skip questions. If the client is genuinely uncertain, default to N and note it for follow-up.

The 41-Item Diagnostic

Domain 1: Data Foundation (8 items)

Do you have a single, centralised customer database?
Is customer data cleaned and deduplicated at least quarterly?
Do you track customer behaviour across more than one channel?
Do you have explicit customer consent for data collection and use?
Can you segment your customers by behaviour, not just demographics?
Do you have a named person responsible for data quality?
Do you have a documented data governance policy?
Can you link online and offline customer data?

Domain 2: Technology Stack (8 items)

Do you have a CRM system in active use?
Do you use a social media scheduling tool?
Do you use an email marketing platform?
Do you have website analytics in place (GA4 or similar)?
Do you use any AI-powered content creation tools?
Do you use any marketing automation (Zapier, Make, or similar)?
Do you use any AI analytics or reporting tools?
Do you have a documented tech stack with assigned owners?

Domain 3: Team Capability (8 items)

Has your marketing team used ChatGPT or a similar LLM in the last 30 days?
Does anyone on your team understand prompt engineering basics?
Has your team received any AI tools training in the last 12 months?
Do you have a documented AI use policy for staff?
Is there a senior leader who champions AI adoption?
Does your team feel comfortable experimenting with new tools?
Do you regularly review how AI tools are being used?
Does your team know the difference between AI-generated and human-created content?

Domain 4: AI Deployment (9 items)

Do you use AI for any content creation (captions, blogs, emails)?
Do you use AI for social media scheduling or posting?
Do you use AI for customer segmentation or targeting?
Do you use AI-powered chatbots or automated messaging?
Do you use AI for sentiment analysis or social listening?
Do you use AI for paid advertising optimisation?
Do you use AI for performance reporting or forecasting?
Do you have real-time personalisation in any marketing channel?
Has AI changed how you make budget or strategy decisions?

Domain 5: Business Impact (8 items)

Has AI reduced time spent on content creation by at least 25%?
Have AI experiments produced measurable ROI?
Has AI improved audience targeting or engagement rates?
Has AI enabled you to produce more content at the same cost?
Has AI created new revenue streams or business models?
Do you have AI-specific KPIs in your marketing plan?
Do senior stakeholders receive regular AI performance updates?
Has AI changed your competitive position in your market?

Scoring

Step 1: Calculate domain scores

Count the number of YES answers in each domain:

| Domain | Items | Max Score | |---|---|---| | 1. Data Foundation | 1–8 | 8 | | 2. Technology Stack | 9–16 | 8 | | 3. Team Capability | 17–24 | 8 | | 4. AI Deployment | 25–33 | 9 | | 5. Business Impact | 34–41 | 8 | | Total | 1–41 | 41 |

Step 2: Identify the AI Marketing Canvas step

| Total Score | Canvas Step | |---|---| | 0–8 | Step 1 — Foundation | | 9–16 | Step 2 — Experimentation | | 17–24 | Step 3 — Expansion | | 25–32 | Step 4 — Transformation | | 33–41 | Step 5 — Reinvention |

Step 3: Interpret domain scores

Apply these thresholds to identify specific gap areas:

| Domain | Score | Interpretation | |---|---|---| | Data Foundation | 0–3 | Critical gap — no AI programme can succeed without this | | Technology Stack | 0–3 | Tool gaps limit what AI can do | | Team Capability | 0–3 | Training is the priority before any tool investment | | AI Deployment | 0–4 | Experimentation is the immediate priority | | Business Impact | 0–3 | Either early stage or AI is not yet being measured |

Output Structure

Produce the following five sections in order.

Section 1: Score Summary Table

Present a clean table showing:

Each domain name
Domain score (e.g., 3/8)
A one-word status: Strong, Developing, or Critical
Total score and Canvas step

Example format:

| Domain | Score | Status | |---|---|---| | Data Foundation | 3/8 | Critical | | Technology Stack | 5/8 | Developing | | Team Capability | 4/8 | Developing | | AI Deployment | 2/9 | Critical | | Business Impact | 1/8 | Critical | | Total | 15/41 | Step 2 — Experimentation |

Section 2: Canvas Step Diagnosis

Write one paragraph in plain English explaining:

Which step the client is at and what that means in practice
What characterises organisations at this step
What is typically holding them back
What the realistic next step looks like

Be honest. If the client is at Step 1, say so directly and explain what that means without softening the message into vagueness.

Source: Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd edn. Stanford Business Books.

Section 3: Top 3 Priority Gaps

Identify the three most urgent gaps based on domain scores and individual question responses. Rank them most urgent first. For each gap:

Gap title — name the specific weakness
Why it matters — one sentence on the business consequence
What is missing — the specific Y/N items that are N
First action — the single most important thing to do about it

Section 4: 90-Day Action Plan

Structure three 30-day blocks. Include exactly three named, specific actions per block. Actions must be concrete (name a tool, name a process, name a person or role).

Days 1–30: Stabilise the Foundation

Action 1
Action 2
Action 3

Days 31–60: Build Capability

Action 1
Action 2
Action 3

Days 61–90: Begin Deployment

Action 1
Action 2
Action 3

Calibrate ambition to the client's step. A Step 1 client's 90-day plan is about getting basic data and tools in place — not deploying AI-powered personalisation.

Section 5: Recommended Tools

Recommend tools appropriate to the client's current Canvas step and the East African market. Prioritise:

Free tiers before paid subscriptions
Tools accessible from Uganda without VPN or restricted payment
UGX pricing or USD pricing with local payment options where available

Step 1–2 tool recommendations to consider:

| Need | Tool | Tier | |---|---|---| | CRM | HubSpot CRM | Free | | Email marketing | Mailchimp | Free up to 500 contacts | | Social scheduling | Buffer | Free (3 channels) | | Website analytics | Google Analytics 4 | Free | | AI content creation | ChatGPT (GPT-4o) | Free / Plus at ~UGX 130,000/month | | AI content creation | Gemini | Free | | Automation | Zapier | Free (5 zaps) | | WhatsApp automation | Africa's Talking | Pay-as-you-go, UGX-compatible | | SMS automation | Africa's Talking | Pay-as-you-go |

Step 3–4 tool recommendations to consider:

| Need | Tool | Tier | |---|---|---| | CRM with automation | HubSpot Starter | From ~USD 20/month | | AI writing at scale | Jasper or Copy.ai | From ~USD 39/month | | Social listening | Brandwatch Lite or Mention | From ~USD 29/month | | Reporting | Looker Studio | Free | | AI analytics | Polymer or Akkio | From ~USD 20/month | | Chatbot | Tidio or Landbot | Free tier available |

Note the WhatsApp advantage: if the client is already using WhatsApp for customer communications, this counts toward the Technology Stack domain and can be formalised quickly via Africa's Talking or similar APIs.

East African Market Context

Most Ugandan and East African SMEs score between 4 and 12 on this diagnostic, placing them at Step 1 or early Step 2. This is not a failure — it reflects the market's current stage of AI adoption.

Common patterns to look for:

No CRM: Customer contacts held in Excel spreadsheets or WhatsApp groups. Recommend HubSpot Free as the immediate priority.
WhatsApp already in use: Formalise this into the tech stack. Africa's Talking enables automated WhatsApp and SMS flows at low cost.
Team capability gap: Many teams have experimented with ChatGPT informally but have no policy, no training, and no structured prompting practice. The training-client-team skill provides a structured training programme.
Budget sensitivity: Lead with free tiers. Demonstrate value before recommending any paid subscription.

AI Use Case Matrix (Venkatesan and Lecinski, 2026)

Once the diagnostic score is known, map the client's AI readiness to the 2×2 Use Case Matrix:

| | Internal | External | |---|---|---| | Productivity | Automate internal workflows: reporting, content briefs, data analysis | Scale customer-facing functions: chatbots, FAQs, WhatsApp automation | | Growth | Build proprietary data and algorithmic advantages | Deliver personalised customer experiences at scale |

Recommendation by score: (Convert raw score to percentage: total ÷ 41 × 100)

Score 0–25%: Start in Internal/Productivity quadrant only
Score 26–50%: Internal/Productivity + begin External/Productivity pilot
Score 51–75%: All four quadrants in scope; prioritise highest-ROI cell
Score 76–100%: Full AI transformation; consider Monetisation (Canvas Step 5)

AI Maturity Wave Assessment (Nayebi, 2025)

Identify which wave the client currently operates in:

Wave 1 — Automation: Rules-based workflows, scheduled posts, canned responses, basic chatbots. Most EA SMEs are here.
Wave 2 — Predictive ML: Customer segmentation, engagement prediction, A/B test optimisation, sentiment analysis. Achievable for EA mid-market clients.
Wave 3 — Agentic AI: Autonomous agents that perceive, reason, act, and learn without human prompts. Horizon planning for EA; immediate for multinational clients.

Ask the client: "Which wave best describes your current AI marketing activity?" Use their answer to calibrate the roadmap in the final section.

Quality Criteria

All 41 items are addressed — no question is skipped or estimated without a reason recorded
The total score is calculated accurately and the Canvas step is stated clearly
Domain breakdown reveals specific gap areas and is not reduced to a single total score
The 90-day plan contains specific, named actions — not generic advice such as "improve data quality"
Tool recommendations match the client's step and are accessible in the East African market, with free tiers prioritised
Language is honest: if the client is at Step 1, the diagnosis says so clearly and explains what that means in practical terms
Output is structured so a non-technical business owner can read it without a consultant present and know exactly what to do next
The score summary table is the first thing the client sees — context and explanation follow the data

References

Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd edn. 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.

Nayebi, F. (2025) Foundations of Agentic AI for Retail. Gradient Divergence.

For full canvas completion and strategic roadmap development, use the sister skill ai-marketing-canvas-assessment after completing this diagnostic.

AI Readiness Diagnostic

Use when

Conducts a 41-item diagnostic to assess a client's AI marketing maturity, identify their current AI Marketing Canvas step (1–5), and produce a scored maturity profile with a prioritised action plan. Invoke this skill when a client wants to understand where they stand on AI adoption, before beginning any AI strategy, tool selection, or training investment. Based on Venkatesan and Lecinski (2026) The AI Marketing Canvas, 2nd edition, Stanford Business Books.
Use this skill when it is the closest match to the requested deliverable or workflow.

Do not use when

Do not use this skill for graphic design, video production, software development, or legal advice beyond the repository's stated scope.
Do not use it when another skill in this repository is clearly more specific to the requested deliverable.

Workflow

Collect the required inputs or source material before drafting, unless this skill explicitly generates the intake itself.
Follow the section order and decision rules in this SKILL.md; do not skip mandatory steps or required fields.
Review the draft against the quality criteria, then deliver the final output in markdown unless the skill specifies another format.

Anti-Patterns

Do not invent client facts, performance data, budgets, or approvals that were not provided or clearly inferred from evidence.
Do not skip required inputs, mandatory sections, or quality checks just to make the output shorter.
Do not drift into out-of-scope work such as code implementation, design production, or unsupported legal conclusions.

Outputs

An AI-focused strategy, audit, system design, or prompt asset in markdown with human review and control points.

References

Use the inline instructions in this skill now. If a references/ directory is added later, treat its files as the deeper source material and keep this SKILL.md execution-focused.

Purpose

After completing this diagnostic, refer the client to the sister skill ai-marketing-canvas-assessment for full canvas completion and strategic roadmap development.

Required Inputs

Ask for the following before beginning:

Business name — trading name of the client organisation
Industry — sector and nature of the business
Country / city — primary operating location (default: Uganda/East Africa)
Primary marketing goal — what the client most wants marketing to achieve
Team size — approximate number of people in the marketing function

The 41-Item Diagnostic

Domain 1: Data Foundation (8 items)

Do you have a single, centralised customer database?
Is customer data cleaned and deduplicated at least quarterly?
Do you track customer behaviour across more than one channel?
Do you have explicit customer consent for data collection and use?
Can you segment your customers by behaviour, not just demographics?
Do you have a named person responsible for data quality?
Do you have a documented data governance policy?
Can you link online and offline customer data?

Domain 2: Technology Stack (8 items)

Do you have a CRM system in active use?
Do you use a social media scheduling tool?
Do you use an email marketing platform?
Do you have website analytics in place (GA4 or similar)?
Do you use any AI-powered content creation tools?
Do you use any marketing automation (Zapier, Make, or similar)?
Do you use any AI analytics or reporting tools?
Do you have a documented tech stack with assigned owners?

Domain 3: Team Capability (8 items)

Has your marketing team used ChatGPT or a similar LLM in the last 30 days?
Does anyone on your team understand prompt engineering basics?
Has your team received any AI tools training in the last 12 months?
Do you have a documented AI use policy for staff?
Is there a senior leader who champions AI adoption?
Does your team feel comfortable experimenting with new tools?
Do you regularly review how AI tools are being used?
Does your team know the difference between AI-generated and human-created content?

Domain 4: AI Deployment (9 items)

Do you use AI for any content creation (captions, blogs, emails)?
Do you use AI for social media scheduling or posting?
Do you use AI for customer segmentation or targeting?
Do you use AI-powered chatbots or automated messaging?
Do you use AI for sentiment analysis or social listening?
Do you use AI for paid advertising optimisation?
Do you use AI for performance reporting or forecasting?
Do you have real-time personalisation in any marketing channel?
Has AI changed how you make budget or strategy decisions?

Domain 5: Business Impact (8 items)

Has AI reduced time spent on content creation by at least 25%?
Have AI experiments produced measurable ROI?
Has AI improved audience targeting or engagement rates?
Has AI enabled you to produce more content at the same cost?
Has AI created new revenue streams or business models?
Do you have AI-specific KPIs in your marketing plan?
Do senior stakeholders receive regular AI performance updates?
Has AI changed your competitive position in your market?

Scoring

Step 1: Calculate domain scores

Count the number of YES answers in each domain:

Step 2: Identify the AI Marketing Canvas step

Step 3: Interpret domain scores

Apply these thresholds to identify specific gap areas:

Output Structure

Produce the following five sections in order.

Section 1: Score Summary Table

Present a clean table showing:

Each domain name
Domain score (e.g., 3/8)
A one-word status: Strong, Developing, or Critical
Total score and Canvas step

Example format:

Section 2: Canvas Step Diagnosis

Write one paragraph in plain English explaining:

Which step the client is at and what that means in practice
What characterises organisations at this step
What is typically holding them back
What the realistic next step looks like

Be honest. If the client is at Step 1, say so directly and explain what that means without softening the message into vagueness.

Source: Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd edn. Stanford Business Books.

Section 3: Top 3 Priority Gaps

Identify the three most urgent gaps based on domain scores and individual question responses. Rank them most urgent first. For each gap:

Gap title — name the specific weakness
Why it matters — one sentence on the business consequence
What is missing — the specific Y/N items that are N
First action — the single most important thing to do about it

Section 4: 90-Day Action Plan

Structure three 30-day blocks. Include exactly three named, specific actions per block. Actions must be concrete (name a tool, name a process, name a person or role).

Days 1–30: Stabilise the Foundation

Action 1
Action 2
Action 3

Days 31–60: Build Capability

Action 1
Action 2
Action 3

Days 61–90: Begin Deployment

Action 1
Action 2
Action 3

Calibrate ambition to the client's step. A Step 1 client's 90-day plan is about getting basic data and tools in place — not deploying AI-powered personalisation.

Section 5: Recommended Tools

Recommend tools appropriate to the client's current Canvas step and the East African market. Prioritise:

Free tiers before paid subscriptions
Tools accessible from Uganda without VPN or restricted payment
UGX pricing or USD pricing with local payment options where available

Step 1–2 tool recommendations to consider:

Step 3–4 tool recommendations to consider:

East African Market Context

Most Ugandan and East African SMEs score between 4 and 12 on this diagnostic, placing them at Step 1 or early Step 2. This is not a failure — it reflects the market's current stage of AI adoption.

Common patterns to look for:

No CRM: Customer contacts held in Excel spreadsheets or WhatsApp groups. Recommend HubSpot Free as the immediate priority.
WhatsApp already in use: Formalise this into the tech stack. Africa's Talking enables automated WhatsApp and SMS flows at low cost.
Team capability gap: Many teams have experimented with ChatGPT informally but have no policy, no training, and no structured prompting practice. The training-client-team skill provides a structured training programme.
Budget sensitivity: Lead with free tiers. Demonstrate value before recommending any paid subscription.

AI Use Case Matrix (Venkatesan and Lecinski, 2026)

Once the diagnostic score is known, map the client's AI readiness to the 2×2 Use Case Matrix:

Recommendation by score: (Convert raw score to percentage: total ÷ 41 × 100)

Score 0–25%: Start in Internal/Productivity quadrant only
Score 26–50%: Internal/Productivity + begin External/Productivity pilot
Score 51–75%: All four quadrants in scope; prioritise highest-ROI cell
Score 76–100%: Full AI transformation; consider Monetisation (Canvas Step 5)

AI Maturity Wave Assessment (Nayebi, 2025)

Identify which wave the client currently operates in:

Wave 1 — Automation: Rules-based workflows, scheduled posts, canned responses, basic chatbots. Most EA SMEs are here.
Wave 2 — Predictive ML: Customer segmentation, engagement prediction, A/B test optimisation, sentiment analysis. Achievable for EA mid-market clients.
Wave 3 — Agentic AI: Autonomous agents that perceive, reason, act, and learn without human prompts. Horizon planning for EA; immediate for multinational clients.

Ask the client: "Which wave best describes your current AI marketing activity?" Use their answer to calibrate the roadmap in the final section.

Quality Criteria

All 41 items are addressed — no question is skipped or estimated without a reason recorded
The total score is calculated accurately and the Canvas step is stated clearly
Domain breakdown reveals specific gap areas and is not reduced to a single total score
The 90-day plan contains specific, named actions — not generic advice such as "improve data quality"
Tool recommendations match the client's step and are accessible in the East African market, with free tiers prioritised
Language is honest: if the client is at Step 1, the diagnosis says so clearly and explains what that means in practical terms
Output is structured so a non-technical business owner can read it without a consultant present and know exactly what to do next
The score summary table is the first thing the client sees — context and explanation follow the data

References

Venkatesan, R. and Lecinski, J. (2026) The AI Marketing Canvas, 2nd edn. 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.

Nayebi, F. (2025) Foundations of Agentic AI for Retail. Gradient Divergence.

For full canvas completion and strategic roadmap development, use the sister skill ai-marketing-canvas-assessment after completing this diagnostic.

Adoption

peterbamuhigire/ai-readiness-diagnostic

$ install --global

Security Scan Results

SKILL.md

AI Readiness Diagnostic

Use when

Do not use when

Workflow

Anti-Patterns

Outputs

References

Purpose

Required Inputs

The 41-Item Diagnostic

Domain 1: Data Foundation (8 items)

Domain 2: Technology Stack (8 items)

Domain 3: Team Capability (8 items)

Domain 4: AI Deployment (9 items)

Domain 5: Business Impact (8 items)

Scoring

Step 1: Calculate domain scores

Step 2: Identify the AI Marketing Canvas step

Step 3: Interpret domain scores

Output Structure

Section 1: Score Summary Table

Section 2: Canvas Step Diagnosis

Section 3: Top 3 Priority Gaps

Section 4: 90-Day Action Plan

Section 5: Recommended Tools

East African Market Context

AI Use Case Matrix (Venkatesan and Lecinski, 2026)

AI Maturity Wave Assessment (Nayebi, 2025)

Quality Criteria

References

Related Skills

peterbamuhigire/training-social-media-fundamentals

peterbamuhigire/training-smartphone-video-production

peterbamuhigire/training-diy-content

peterbamuhigire/training-client-team

peterbamuhigire/ai-readiness-diagnostic

$ install --global

Security Scan Results

SKILL.md

AI Readiness Diagnostic

Use when

Do not use when

Workflow

Anti-Patterns

Outputs

References

Purpose

Required Inputs

The 41-Item Diagnostic

Domain 1: Data Foundation (8 items)

Domain 2: Technology Stack (8 items)

Domain 3: Team Capability (8 items)

Domain 4: AI Deployment (9 items)

Domain 5: Business Impact (8 items)

Scoring

Step 1: Calculate domain scores

Step 2: Identify the AI Marketing Canvas step

Step 3: Interpret domain scores

Output Structure

Section 1: Score Summary Table

Section 2: Canvas Step Diagnosis

Section 3: Top 3 Priority Gaps

Section 4: 90-Day Action Plan

Section 5: Recommended Tools

East African Market Context

AI Use Case Matrix (Venkatesan and Lecinski, 2026)

AI Maturity Wave Assessment (Nayebi, 2025)

Quality Criteria

References

Related Skills

peterbamuhigire/training-social-media-fundamentals

peterbamuhigire/training-smartphone-video-production

peterbamuhigire/training-diy-content

peterbamuhigire/training-client-team