beginnersinai AI Mapping Audit Skill
This skill provides the framework and knowledge for performing AI Mapping Audits — systematic evaluations of where AI creates value across a business's production functions.
When This Skill Activates
Use this knowledge when the user:
- Asks "where should I use AI in my business?"
- Wants to find new AI use cases beyond content/writing
- Mentions the "mapping problem" or AI adoption bottlenecks
- Asks how other companies are using AI
- Wants to audit their AI usage
- Is planning AI strategy for a venture
The Research Foundation
Paper: "Mapping AI into Production: A Field Experiment on Firm Performance" Authors: Hyunjin Kim (INSEAD), Dahyeon Kim (INSEAD), Rembrand Koning (Harvard Business School) Date: March 30, 2026 Program: INSEAD AI Founder Sprint / AI Venture Lab
Key Findings
The Mapping Problem: The central friction in AI adoption is not AI capability — it's discovering WHERE and HOW AI creates value within a firm's production process.
The Experiment: 515 high-growth startups. Treatment group received information about how OTHER firms had reorganized production around AI, prompting them to search for use cases across a BROADER set of firm functions.
Results:
- 44% more AI use cases discovered (concentrated in product development and strategy)
- 12% more tasks completed
- 18% more likely to acquire paying customers
- 1.9x higher revenue
- 39.5% less demand for external capital investment
- No increase in labor demand — firms did more with less
- Gains largest at 90th percentile — AI expands the ceiling, not the floor
What This Means Practically
- Most firms only use AI for content creation and chatbots — they have a mapping problem
- The highest-value AI applications are in product development and strategy
- Simply SHOWING firms how others use AI causes them to discover more use cases
- AI reduces capital requirements — you can do more without hiring or raising money
- The biggest gains go to already-strong ventures — AI amplifies winners
The 10-Function Framework
Read ${CLAUDE_PLUGIN_ROOT}/skills/ai-mapping-audit/references/ten-functions.md for the complete framework.
Examples From Other Firms
Read ${CLAUDE_PLUGIN_ROOT}/skills/ai-mapping-audit/references/examples-from-other-firms.md for examples of how real firms have reorganized around AI across all 10 functions.
Case Studies From the Research Paper
Read ${CLAUDE_PLUGIN_ROOT}/skills/ai-mapping-audit/references/case-studies-from-paper.md for the 4 actual case studies shown to the treatment group — Gamma (process redesign), RyzLabs (parallel prototyping), FazeShift (eliminating glue work), and Ranger (sell first, build AI second). These caused firms to discover 44% more use cases.
How to Apply
Quick Assessment (2 minutes)
Ask the user: "Which of these 10 functions does your business use AI for?" Then identify the gaps.
Full Audit (30-60 minutes)
Run the /map command to scan their workspace automatically.
Single Venture (10-20 minutes)
Run /map-venture [name] for a focused analysis.
Scoring (5-10 minutes)
Run /map-score after a map to prioritize opportunities.
The Anti-Pattern
If a user's AI usage is concentrated only in:
- Content writing
- Social media posts
- Email drafting
- Image generation
...they have the mapping problem. The highest-value applications are in:
- Product development (synthetic testing, feature prioritization, automated QA)
- Strategy (competitive monitoring, market analysis, scenario modeling)
- Finance (revenue attribution, pricing optimization, cash flow forecasting)
- Customer development (segmentation, churn prediction, personalization)
- System optimization (analyzing AI system performance, self-improvement loops)
Always guide users toward these higher-value functions.