This chapter presents a comprehensive theoretical framework for understanding the systematic tensions created by technological disruption in workforce transformation, with artificial intelligence serving as the contemporary case study. Through analysis of the World Economic Forum’s Future of Jobs reports and historical technology adoption patterns spanning five centuries, we introduce the Orthogonal Technology Principle and Economic-Societal Impact Matrix as conceptual tools for predicting when technological innovations create mounting societal tensions despite apparent economic benefits. Our analysis reveals that current AI adoption patterns exhibit characteristics historically associated with disruptive technology cycles that systematically undermine foundational human capabilities while optimizing for narrow economic metrics. Using comparative historical analysis—from the printing press (1450s) through contemporary GPS and calculator adoption—we demonstrate recurring patterns of competency displacement and societal adaptation challenges. This chapter provides a predictive assessment framework and intervention strategies applicable across technological domains, establishing a foundation for evidence-based technology policy in an era of accelerating innovation.