Personal Action Plan Worksheet
Personal Action Plan: Applying AI Investment Frameworks to Your Organisation
Take-home exercise – Complete within 7 days of the masterclass
Instructions
You’ve spent today practicing AI investment frameworks on RetailFlow. Now translate those lessons to YOUR organisation. This worksheet is designed to be completed thoughtfully after the course, when you have time to reflect and access organisational data.
Recommended time: 45-60 minutes (in a quiet space, not rushed)
When to complete: Within 7 days of the masterclass, while the frameworks are fresh
Goal: Create a concrete action plan for improving YOUR AI investment decisions
Privacy: This is private—for your eyes only (unless you choose to share with your team)
Before You Begin
Gather these materials: - [ ] Today’s course materials (Framework Reference Sheet, AI Investment Checklist) - [ ] Your organisation’s current AI initiatives list (if available) - [ ] Recent AI proposals or business cases (if available) - [ ] Your strategic plan or innovation roadmap (if available) - [ ] A quiet 45-60 minutes without interruptions
Set your intention:
This isn’t a test. There are no wrong answers. The goal is honest self-assessment that leads to better AI investment decisions. Be realistic, not aspirational.
Part 1: Your AI Maturity Assessment (10 minutes)
A. Where are you on the Data Value Pyramid?
Check ONE level that best describes your current state:
-
- Example: Recording transactions, but data sits in siloed systems
-
- Example: Sales + inventory + customer data in one place, can create dashboards
-
- Example: Analysing trends, segmenting customers, identifying demand patterns
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- Example: Churn prediction, demand forecasting, fraud detection models in production
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- Example: Dynamic pricing, automated inventory ordering, autonomous systems
My organisation is at Level: ____
Key insight from today: You CANNOT skip levels. If you’re at Level 2, don’t fund Level 5 projects.
B. What’s your biggest data readiness gap?
Use the 0-10 scoring system from today. Rate your organisation:
| Data Dimension | Score (0-10) | Notes |
|---|---|---|
| Data Availability (sufficient volume of historical data) | ||
| Data Quality (accurate, complete, consistent) | ||
| Data Access (can integrate necessary sources) | ||
| Data Bias (representative, not discriminatory) | ||
| AVERAGE DATA READINESS SCORE |
If your average is <7: You need data infrastructure investment BEFORE AI projects.
My #1 data readiness action: _________________________________________________________________
Part 2: Your AI Portfolio Balance (10 minutes)
A. Map your current AI investments across Three Horizons
Think about your current or planned AI initiatives. Estimate % of AI budget in each:
| Horizon | Focus | Target | Your Current % |
|---|---|---|---|
| Horizon 1: Optimize (0-12 months, improve core operations) | Low risk, proven tech, >200% ROI | 70% | ___% |
| Horizon 2: Build (1-3 years, grow adjacent opportunities) | Medium risk, scaling challenges, >150% ROI | 20% | ___% |
| Horizon 3: Transform (3-5+ years, new business models) | High risk, high potential, >100% ROI | 10% | ___% |
| TOTAL | 100% | ____% |
B. What does your portfolio reveal?
Common patterns:
- >80% in Horizon 1: You’re optimizing into obsolescence. Not enough transformational bets.
- >30% in Horizon 3: You’re taking too much risk. Not enough quick wins to fund experiments.
- <60% in Horizon 1: You might not have enough near-term revenue to sustain long-term bets.
My portfolio is: - [ ] Balanced (close to 70/20/10) - [ ] Over-invested in Horizon 1 (need more transformational bets) - [ ] Over-invested in Horizon 3 (need more quick wins) - [ ] Under-invested in AI overall
My #1 portfolio rebalancing action: _________________________________________________________________
Part 3: Learning from RetailFlow (10 minutes)
What did RetailFlow teach you?
The key decision: RetailFlow had to choose between: - Chatbot: 92% ROI, low risk, data ready, fits budget - Dynamic Pricing: 253% ROI, high risk, ethical concerns, over budget - Inventory: 264% ROI, medium risk, slightly over budget - Fraud Detection: 315% ROI, data not ready, high bias risk
Which ONE RetailFlow lesson applies most to YOUR current situation?
Check the lesson that resonates:
Why this lesson matters to me: _________________________________________________________________ _________________________________________________________________
How I’ll apply it: _________________________________________________________________ _________________________________________________________________
Part 4: Your #1 AI Investment Decision (15 minutes)
This is the most valuable part—take your time.
Evaluate a real AI project using today’s frameworks
Think of ONE specific AI initiative you’re currently evaluating (or will be soon).
Project name: _______________________________________________
Budget: $_____________ Timeline: ________ months
Traditional Criteria (Quick Check)
| Criterion | Yes/No | Notes |
|---|---|---|
| Strategic fit: Aligns with business priorities? | ⬜ | |
| Financial ROI: >150% over 3 years? | ⬜ | |
| Feasible: Have resources and capabilities? | ⬜ |
AI-Specific Criteria (THE CRITICAL ONES)
| Criterion | Pass/Fail | Score/Notes |
|---|---|---|
| 1. Data Readiness (0-10 score, need 7+) | ⬜ Pass ⬜ Fail | Score: ___ If <7, what data work is needed first? |
| 2. Continuous Learning Plan (30-50% annual costs budgeted?) | ⬜ Pass ⬜ Fail | 5-year TCO: $_______ (not just Year 1!) |
| 3. Accuracy vs. Risk (AI accuracy matches business risk tolerance?) | ⬜ Pass ⬜ Fail | Required accuracy: % AI achieves: % |
| 4. Explainability (Can explain decisions? Regulatory requirement?) | ⬜ Pass ⬜ Fail | High/Med/Low need? Cost impact? |
| 5. Ethical Risk (Bias testing? Diverse teams? Legal review?) | ⬜ Pass ⬜ Fail | High/Med/Low risk? Mitigation plan? |
The Verdict
Traditional criteria only: Would you fund this? ⬜ Yes ⬜ No
Traditional + AI-specific criteria: Should you fund this? ⬜ Yes ⬜ No ⬜ Yes, but only after addressing: _______________________
If NO or conditional, what needs to change? _________________________________________________________________ _________________________________________________________________
Part 5: Your Monday Actions (10 minutes)
What will you DO differently this week?
Be specific. Make it actionable. Commit to 3 things.
Action 1: Data/Infrastructure
What I will do: _________________________________________________________________
Who needs to be involved: ___________________________________
Deadline: ________________
Action 2: Process/Evaluation
What I will do: _________________________________________________________________
Who needs to be involved: ___________________________________
Deadline: ________________
Action 3: Specific Project
What I will do: _________________________________________________________________
Who needs to be involved: ___________________________________
Deadline: ________________
Part 6: Your Commitment (5 minutes)
The one thing I’m committing to change about how I evaluate AI investments:
The one question I’ll ask about EVERY AI proposal from now on:
The one RetailFlow lesson I’ll share with my team:
Part 7: Accountability & Follow-Up (Optional)
Share Your Plan (Optional)
Consider sharing this plan with: - [ ] Your direct manager (for alignment and support) - [ ] Your executive team (to elevate AI evaluation rigor) - [ ] Your AI/data team (to collaborate on data readiness) - [ ] A peer from the masterclass (for mutual accountability)
Schedule Follow-Up
Put these on your calendar NOW:
Connect with the Facilitator (Optional)
If you’d like a follow-up conversation:
Email: ____________________________________________
Best time for a 20-min call: _________________________
Topic: _____________________________________________
OPTIONAL: In-Class Quick Start (5 minutes)
If time permits at the end of class, start your action plan with these quick wins:
Quick Win 1: Capture Your Top Insight (1 minute)
The one RetailFlow lesson I’m taking home: _________________________________________________________________
Quick Win 2: Identify Your #1 AI Decision (1 minute)
The specific AI project I need to evaluate using today’s frameworks: _________________________________________________________________
Quick Win 3: Flag Your Biggest Gap (2 minutes)
Quick self-assessment—which is your weakest area? - [ ] Data readiness (don’t have AI-ready data) - [ ] Portfolio balance (over-invested in one horizon) - [ ] Evaluation rigor (not using AI-specific criteria) - [ ] Organisational buy-in (executives don’t see the need)
My #1 priority to address: _________________________________________________________________
Quick Win 4: Set Your Calendar Reminder (1 minute)
Right now, pull out your phone and: - [ ] Set calendar reminder for 3 days from now: “Complete AI Action Plan” - [ ] Set calendar reminder for 7 days from now: “Review AI Action Plan progress”
Resources to Take Home
✅ AI Investment Checklist – Use for every AI proposal ✅ Framework Reference Sheet – Quick lookup for the 5 frameworks ✅ Digital Templates – ROI calculator, Tech Radar template, Transformation Matrix ✅ Pre-Readings – Share with your team as primers ✅ This Action Plan – Complete within 7 days while today’s insights are fresh
Post-Course: Complete Your Full Action Plan
Now that you’re back in your regular environment, set aside 45-60 minutes to complete this full worksheet.
Best practices for completion: - Schedule it as a calendar block (treat it like a meeting with yourself) - Find a quiet space without interruptions - Have your organisational data available - Be honest, not aspirational - Focus on actionable next steps, not perfect answers
Final Reflection (Complete at home)
Before today’s masterclass, I evaluated AI investments by:
After today, I will evaluate AI investments by:
The biggest shift in my thinking:
One thing I’ll do differently on Monday:
Your Commitment Statement
I commit to completing this action plan by: _____________ (date)
I commit to implementing at least ONE change to how I evaluate AI investments.
Signed: _________________________ Date: __________
Congratulations! You now have a framework for bringing AI investment rigor to your organisation.
Remember: - RetailFlow showed you what rigorous AI evaluation looks like - Today’s frameworks work for any industry, any AI project - The AI-specific criteria (data, learning, accuracy, explainability, ethics) separate leaders from laggards - You don’t need to be perfect—just more intentional than you were yesterday
Next steps: 1. Complete this action plan within 7 days (while frameworks are fresh) 2. Apply the AI Investment Checklist to your next AI proposal 3. Share one framework with your team 4. Revisit this plan in 30 days and assess progress 5. Contact the facilitator if you want to discuss your plan
You’ve got the frameworks. You’ve got the checklist. You’ve got the plan.
Now go make better AI investment decisions.