Ai mapping audit

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

1. Most firms only use AI for content creation and chatbots — they have a mapping problem
2. The highest-value AI applications are in product development and strategy
3. Simply SHOWING firms how others use AI causes them to discover more use cases
4. AI reduces capital requirements — you can do more without hiring or raising money
5. 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.