Chapter 6: AI Opportunity Mapping | Quanskill AI Program

🎯 Chapter Objectives

Learn a systematic framework for identifying AI opportunities in your department
Evaluate and prioritize AI initiatives by impact, feasibility, and cost
Create your personal AI Opportunity Map
Finalize your personal prompt library (5-10 reusable prompts)

🖼️ Visual Summary — Chapter 6 Theory

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6.1 The AI Opportunity Framework

Not every process benefits from AI. Use this 4-step framework to identify the RIGHT opportunities:

IDENTIFY — Find repetitive, data-heavy, or error-prone tasks

EVALUATE — Score by impact (time saved, errors reduced, cost cut)

PRIORITIZE — Rank by feasibility (data available? Tool exists? Low risk?)

PLAN — Define the solution, timeline, and success metrics

6.2 Where to Look for AI Opportunities

AI works best on tasks that are:

🎯 High-Impact AI Candidates:
Repetitive: Done frequently with little variation (daily reports, data entry)
Data-heavy: Involves analyzing large amounts of information (inspection logs, supplier data)
Time-consuming: Takes hours that could be spent on higher-value work
Error-prone: Human mistakes have significant consequences (quality records, compliance)
Template-based: Follows a consistent structure (emails, SOPs, reports)

⚠️ Poor AI Candidates: Tasks requiring physical presence, complex human judgment, emotional intelligence, novel creative decisions, or those with insufficient data.

6.3 Priority Matrix

Score each opportunity on two dimensions to prioritize:

Score	Impact (What's the benefit?)	Feasibility (Can we do it?)
3 — High	Saves 5+ hours/week OR reduces errors by 50%+	Free/low-cost tool, data available, low risk
2 — Medium	Saves 2-5 hours/week OR reduces errors by 20-50%	Moderate cost, some data preparation needed
1 — Low	Saves <2 hours/week OR marginal error reduction	High cost, significant data/integration work

Priority = Impact × Feasibility

Score 9 (3×3) = 🟢 DO FIRST — Quick win, high impact

Score 6 (3×2 or 2×3) = 🟡 PLAN — Good opportunity, needs some preparation

Score 4 or below = 🔴 DEFER — Consider for later phases

6.4 Department Quick-Win Examples

💰 Finance: Invoice Processing Assistant ▼

Current: Manual invoice data entry, 3 hours/day

AI Solution: GenAI extracts invoice data from photos/PDFs, categorizes expenses

Impact: 70% time reduction, fewer data entry errors

Feasibility: High — free tools available, no integration needed

Priority Score: 3 × 3 = 9 🟢 DO FIRST

📦 Procurement: Supplier Comparison Matrix ▼

Current: Manual comparison of 5+ supplier quotes, 4 hours per RFQ

AI Solution: Structured prompt to analyze and compare quotes on weighted criteria

Impact: 60% time reduction, more consistent evaluation

Feasibility: High — use ChatGPT/Claude with CRAFT prompt

Priority Score: 3 × 3 = 9 🟢 DO FIRST

🏭 Operations: Daily Production Report ▼

Current: Manually compiling data from multiple sources, 1.5 hours/day

AI Solution: Template prompt that generates report from key metrics you input

Impact: 50% time reduction, standardized format

Feasibility: High — GenAI prompt template

Priority Score: 3 × 3 = 9 🟢 DO FIRST

6.5 Your AI Seeder Journey

This program identifies AI Seeders — department champions who will lead AI adoption in Phase 2.

Level	Score	Role
🏆 PLATINUM	90-100	AI Champion — leads initiatives, mentors others
🥇 GOLD	75-89	AI Seeder — implements solutions, measures ROI
🥈 SILVER	60-74	AI User — applies tools daily, identifies opportunities
🥉 BRONZE	Below 60	AI Aware — understands basics, ready for growth

📝 Chapter 6 Summary

Key Takeaways:Use the 4-step framework: Identify → Evaluate → Prioritize → Plan
Look for repetitive, data-heavy, template-based tasks
Score opportunities by Impact × Feasibility
Start with quick wins (Score 9) — they build momentum and credibility
Your AI Opportunity Map is your roadmap for Phase 2

🔬 Continue to Final Lab →