Generative Change Management :A Pedagogical Proposal for Human-AI Hybrid Productivity and Competitiveness

The integration of generative artificial intelligence (AI) into work raises three interdependent questions for people who lead teams and processes: how professional contribution is redefined when cognitive capabilities are shared with AI; how production is reorganized when parts of a workflow are delegated to AI with different degrees of autonomy; and how AI-generated outputs participate in organizational decisions, knowledge, and relationships. Generative Change Management (GChM) addresses these questions through three pedagogical dimensions that correspond to the framework's core capabilities: professional value develops expanded professional capability; productive agility develops hybrid production architecture; and organizational relationships develop hybrid organizational intelligence. Their deliberate articulation supports hybrid productivity. Algorithmic language operates as a cross-cutting professional competency, while symbolic-algorithmic linkage describes the organizational process through which AI-generated outputs acquire meaning, legitimacy, and practical authority. The proposal works with situations drawn from participants' professional practice. Through analysis, design, application, reflection, and redesign, participants learn to configure digital production units, distinguish delegation of execution from delegation of judgment and criteria, define verification and process reconstruction, preserve accountability, and integrate human and AI capabilities without weakening professional judgment or collective learning. Hybrid competitiveness is treated as a downstream strategic effect that may emerge when hybrid productivity becomes an organization-specific and difficult-to-replicate capability.