The AI Competency Paradox

This book explores how artificial intelligence disrupts the cognitive foundations of human expertise. It introduces the AI-Competency Ceiling and the Procedural Memory Paradox concepts that explain how AI-assisted performance accelerates early skill acquisition while impeding mastery. Drawing from neuroscience, skill acquisition theory, and over 150 years of technological disruption, the book presents a revised Dreyfus model, and case studies from Netflix to Toyota demonstrating the core messages of the book. It offers strategic frameworks for preserving cognitive capital, including Strategic Workforce Management, Meta-Intelligence Development, and mechanisms for sustainable AI adoption. More than a guide to adaptation, it challenges readers to consider whether thinking remains fundamentally human when cognition is outsourced.

An essential reading for executives, strategists, policymakers, and educators navigating the tension between operational excellence and cognitive resilience.

Part 1: The Myth of AI Replacing Jobs Why AI s Impact Is Misunderstood. - Chapter 1:
The Automation Fallacy
Why AI doesn t function as a simple job killer. . - Chapter 2:
AI & the Competency Shift
The difference between job elimination and job transformation. - Chapter 3:
The Evolution of Work & Intelligence
How AI disrupts skill acquisition rather than just employment. - Part 2: The AI-Competency Paradox How AI Challenges Traditional Skill Development. - Chapter 4:
The Dreyfus Model & Competency Theory
Why AI impacts different skill levels in unique ways. - Chapter 5:
Intrinsic vs. Extrinsic Competencies in the AI Era
The hidden cost of AI automation in skill erosion. - Chapter 6:
The AI-Augmented Workforce
How organisations can realign skill development in an AI-driven economy. - Part 3: The Business Strategy Imperative How Leaders Must Rethink AI Adoption. - Chapter 7:
Porter s Strategy Lens: Cost Efficiency vs. Competitive Advantage
How AI-driven cost-cutting strategies backfire. - Chapter 8:
Success vs. Failure in AI Workforce Integration
Case studies of Tesla (failure) vs. Toyota (success). - Chapter 9:
Rethinking AI Workforce Planning
Practical strategies for sustainable AI-human collaboration. - Part 4: The Future of Work & Human Competence What Comes Next. - Chapter 10:
AI & The Future of Expertise
How AI transforms the definition of human intelligence & skill. - Chapter 11:
The Ethical & Economic Considerations of AI Workforce Transformation
Implications for society, policymakers, and education systems. - Chapter 12:
AI as a Democratising Force or a Capitalist Tool?
Examining whether AI is a force for democratic knowledge-sharing or a capitalistic tool for economic consolidation. - Part 5: The Strategic Responses and Cognitive Sustainability. - Chapter 13:
Building AI-Resilient Organizations
A roadmap for business leaders to navigate the next decade of AI-driven work.