🔒 Exercise 3 Facilitator Guide

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Exercise 3: Dragon’s Den - Facilitator Guide

Duration: 70 minutes (2:45 PM - 3:55 PM) Core Learning: AI-specific criteria (data readiness, ethical risk, bias, ongoing costs) change which projects to fund. Traditional ROI analysis would fund WRONG projects.

Setup (Before 1:45 PM)

Divide participants into 4 project teams (ideally 3-4 people each): - Team 1: Customer Service Chatbot pitch - Team 2: Dynamic Pricing pitch - Team 3: Inventory Optimization pitch - Team 4: Fraud Detection pitch

Each team gets: - Pitch scenario (5-page document with detailed financials) - 1 hour prep time (1:45-2:45 PM) - AI tools available (optional)

Committee (remaining participants): - Gets AI Investment Checklist, Investment Calculator, pitch materials - Sits front row, takes notes on each pitch

The Four Initiatives (Quick Ref)

Initiative	Year 1 Cost	ROI	Key Challenge
Chatbot	$450K	92% (lowest ROI)	Safest, but lowest returns
Dynamic Pricing	$850K	150%	HIGH ethical risk (price discrimination)
Inventory	$1.1M	163% (best H1)	Over $1.2M cap
Fraud Detection	$650K	169% (highest)	6-month data prep delay, bias risk

Budget constraint: $2M total, at least 2 initiatives, max $1.2M per initiative

Phase 1: Team Prep (1:45 - 2:45 PM)

Your role: - Brief teams on pitch structure (7 min pitch + 5 min Q&A) - Point them to pitch scenarios for facts/numbers - Mention: “AI tools available if you want to stress-test your assumptions” - Don’t coach—let teams decide how to position their initiative

What teams typically do: - Chatbot team: Positions as “safe, reliable, fits budget” - Pricing team: Highlights ROI, downplays ethics question - Inventory team: Claims it’s “worth the premium investment,” justifies exceeding cap - Fraud team: Focuses on “highest ROI,” tries to minimise 6-mo delay impact

Don’t interfere. Teams naturally advocate for their projects. That’s the point.

Phase 2: Pitches (2:45 - 3:30 PM)

Structure: - Each team: 7 min pitch + 5 min Q&A - Order: Chatbot → Pricing → Inventory → Fraud - Committee takes notes using AI Investment Checklist

Your role: - Timekeep strictly (7 min warning at 6 min) - Direct Q&A to committee, don’t answer yourself - Take notes on what committees prioritize in questions

What you’ll observe: - Early questions focus on ROI (traditional thinking) - Gradually, questions shift toward risks (ethical, bias, data prep) - By Fraud pitch, committee often asks: “But what’s the data delay risk?”

Phase 3: Committee Deliberation (3:30 - 3:50 PM)

Your setup (2 min): “Committee: You have $2M. You heard four pitches. Now decide: Which initiatives to fund? You must: - Fund at least 2 initiatives - Stay under $2M - Use the AI Investment Checklist (5 AI-specific criteria) to decide, not just ROI

You have 20 minutes to debate and decide. I’m listening, not coaching.

Go.”

Your role during deliberation: - Sit back. Let them argue. - If they go silent: “What’s the debate here? What makes this hard?” - If they only look at ROI: Don’t correct—let them notice the flaw - If someone says: “But what about the ethical risk?” → Say: “Good question. Discuss.” - Observe: What criteria do they naturally prioritize?

What typically emerges: - Traditional committee: Funds Inventory + Fraud (highest ROI, exceeds budget) - Risk-averse committee: Funds Chatbot + Fraud (safe + highest ROI) - Balanced committee: Funds Chatbot + Inventory (safe + transformational) - Ethical committee: Rejects Pricing (ethical risk), funds others

All are legitimate. There’s no single “right” answer.

Phase 4: Decision & Debrief (3:50 - 3:55 PM)

Ask committee (1 min): “What did you decide? Quick recap.”

Then ask (3 min): “Why that decision? What criteria mattered most?”

Listen for: - ROI-focused? “We picked highest returns” - Risk-focused? “We avoided projects with ethical/bias risks” - Portfolio-focused? “We balanced transformational + safe” - Data-focused? “We rejected Fraud because 6-mo delay kills momentum”

Your debrief (2 min):

If they picked Inventory + Fraud (high ROI): “Interesting. Highest returns. But notice: - Inventory: $1.1M means ONLY funding 2 projects (tight) - Fraud: 6-month delay means no revenue for 6 months - You gave up the ‘quick win’ (Chatbot) for ‘long payoff’ - Question for next time: Can you afford to wait 6 months?”

If they picked Chatbot + something: “You chose the safe + growth play. Lower overall ROI, but: - Chatbot: Quick win, builds capability, funds itself - Which other initiative? That shows your risk appetite”

If they rejected Pricing: “You eliminated Pricing on ethical risk. That’s AI-specific thinking: - Traditional IT projects: Ethics usually secondary - AI projects: Unethical AI is worse than no AI - You’re making a strategic judgment, not just an ROI calculation”

Key teaching points (weave in naturally): 1. “Notice how AI-specific criteria changed your thinking vs. pure ROI analysis?” 2. “Data readiness and ongoing costs matter more for AI than traditional IT” 3. “Ethical risk isn’t a ‘nice to have’—it’s decision-making material” 4. “Teams always argue for their own project. Committee’s job: see the whole portfolio”

Decision Archetypes (What You Might See)

Four common decision patterns emerge. Recognize them:

Archetype 1: Conservative (Risk-Averse)

Decision: Chatbot + Fraud Reasoning: “Chatbot is proven, fits budget, quick ROI. Fraud has highest ROI despite delay.” Tradeoffs: Lowest overall portfolio risk, but sacrifices transformational opportunity

Archetype 2: Growth-Focused (ROI-Maximizer)

Decision: Inventory + Fraud (or Pricing + Fraud) Reasoning: “Maximize returns. Inventory is transformational, Fraud has highest ROI.” Tradeoffs: Exceeds budget cap, requires deferring one initiative, higher risk concentration

Archetype 3: Balanced Portfolio

Decision: Chatbot + Inventory Reasoning: “One ‘safe quick win’ + one ‘transformational.’ Respects budget, spreads risk.” Tradeoffs: Misses highest ROI options, but most defensible to board

Archetype 4: Data-First (Ethical/Long-term)

Decision: Chatbot + Inventory (explicitly rejecting Fraud’s delay) Reasoning: “Can’t afford 6-month data prep delays. Pricing has ethical risk we won’t accept.” Tradeoffs: Explicitly deprioritizing highest individual ROIs for strategic discipline

All are defensible. None is “wrong.”

What Makes This Exercise Powerful

Morning: Participants learned frameworks (Three Horizons, portfolio balance)

This afternoon: They discover frameworks create DIFFERENT decisions than gut feel - Team pitches emphasize ROI (traditional thinking) - Committee questions gradually shift to risk/ethics (AI-specific thinking) - Final decision often CONTRADICTS highest ROI project

The “aha!” moment: Committee member: “Wait, we’re not funding the highest ROI project?” Other: “Because it has ethical risk. AI is different.” You: “Exactly. That’s the whole point.”

Common Facilitator Moves

If committee is silent: “What’s the real debate here? Someone likes Fraud. Someone likes Inventory. Why?”

If they ONLY look at ROI: Don’t say “use the checklist.” Instead: “What worries you about any of these? Risk-wise?”

If they say “Fraud’s highest ROI, fund it”: “True. But notice the 6-month delay. What does that cost you strategically?”

If they reject Pricing for ethics: “That’s AI-specific thinking. Traditional IT: ethics secondary. AI: Ethics can be deal-killer.”

Backup Plan (If Pitches Run Long)

If pitches still going at 3:30: - Skip individual deliberation question round - Go straight to group vote: “Raise hands: Fund Inventory? Fraud? Chatbot? Pricing?” - 1 min discussion of results - Debrief on why those choices

Still teaches the learning, just faster.

Post-Exercise

Final reflection (3:55-4:10): “What did this exercise teach you about AI investment decisions?”

Listen for: - “AI needs data, traditional IT doesn’t” - “Ethical risk matters more with AI” - “Ongoing costs are higher than expected” - “ROI alone isn’t enough—you need frameworks”

If you hear: “I’m using this at work Monday” You’ve succeeded.

Facilitator Checklist

Before 1:45: - [ ] Divide into 4 teams - [ ] Distribute pitch scenarios - [ ] AI Investment Checklist ready for committee - [ ] Timer for pitches (strict)

During prep (1:45-2:45): - [ ] Brief teams on pitch structure - [ ] Don’t coach teams - [ ] Make AI tools available

During pitches (2:45-3:30): - [ ] Timekeep strictly - [ ] Don’t answer questions, direct to committee

During deliberation (3:30-3:50): - [ ] Sit back, listen - [ ] Only intervene if silent - [ ] Observe: What criteria do they prioritize?

During debrief (3:50-3:55): - [ ] Ask what they decided - [ ] Ask why - [ ] Connect to AI-specific thinking

This is the capstone. Teams pitch (ego invested). Committee decides (frameworks applied). Learning: How AI changes investment logic.