Predictions of a fully automated, workless society within two decades have captured public imagination and policy attention. This article examines the empirical evidence and theoretical frameworks surrounding large-scale technological displacement, arguing that rather than eliminating work entirely, AI and automation are more likely to hollow out middle-skill occupations while preserving demand for high-touch human services and augmented knowledge work. Drawing on labor economics, organizational psychology, and technology adoption research, we identify three emerging workforce segments: AI-augmented super-workers, human-essential service providers, and a potentially marginalized middle tier facing structural displacement. The article evaluates organizational responses including skills development programs, hybrid human-AI work design, and social safety net innovations. We conclude that preventing a bifurcated "stipend society" requires proactive intervention in education systems, labor market institutions, and the psychological contract between workers, employers, and the state. The central challenge is not whether society can afford economic security for displaced workers, but whether existing political and cultural frameworks can accommodate such a transformation while preserving human agency and meaning.

Abstract: See minimalism represents a fundamental shift in how professionals—particularly Generation Z and millennials—conceptualize work's role in their lives. Rather than pursuing traditional upward mobility at all costs, career minimalists prioritize stability, boundaries, and fulfillment through secure employment, clear work-life separation, and diversified skill development. This article examines the emergence of career minimalism as a response to chronic workplace burnout, economic volatility, and evolving generational values. Drawing on organizational psychology, human resource management, and labor economics literature, we analyze the individual and organizational consequences of this philosophy and identify evidence-based practices for supporting sustainable career approaches. We argue that career minimalism is not withdrawal from work but strategic energy allocation—a recalibration of the psychological contract between employees and employers that prioritizes long-term resilience over short-term advancement. Organizations that understand and accommodate this shift stand to benefit from improved retention, reduced burnout, and access to diverse talent seeking meaningful but bounded employment relationships.

As artificial intelligence tools become ubiquitous in higher education, management educators face the challenge of integrating these technologies while maintaining pedagogical rigor and teaching critical evaluation skills. This article examines an experiential exercise that uses AI as both a learning tool and object of study in teaching cross-cultural management, specifically Hofstede's Cultural Dimensions framework. Drawing on experiential learning theory, constructivist pedagogy, and emerging research on AI literacy in business education, we analyze how structured AI interactions can simultaneously develop cultural competence and critical AI literacy. The article presents evidence-based design principles, documented implementation experiences from business schools, and forward-looking recommendations for educators seeking to balance technological innovation with foundational learning objectives. This pedagogical approach addresses the dual imperative of preparing students for AI-augmented workplaces while cultivating the analytical skepticism necessary to evaluate AI-generated information.