Generative Change Management: Emergent Intelligence and Hybrid Competitiveness

Generative Change Management (GChM) is a conceptual and methodological framework for managing human–algorithmic coexistence in organizations. Its central claim is that, when we work with artificial entities capable of engaging in dialogue, what we do and who we are at work change together. This change can be observed in the contributions a person can make, the recognition those contributions receive, and the person's participation in the organizational project. From a relational perspective, GChM examines how new cognitive and operational capabilities arise through exchanges between people and responsive artificial entities. The attributional bond explains how people's expectations of these entities shape their exchanges. Intervention combines three operations: capability expansion within this relationship, innovation in the production workflows that integrate these capabilities, and responsible traceability, that is, the ability to reconstruct how results were produced and who is accountable for them. These operations are organized into three dimensions—augmented agency, agentic architecture, and algorithmic strategy—and nine intervention axes. Three emergents take shape in the relationships among the dimensions: the innovation core, professional transformation, and symbolic-algorithmic culture. Intervention follows a fractal logic: the same pattern applies at the scale of a person, a team, or several units, and what develops through each intervention changes the conditions for the next. The framework's objective is hybrid competitiveness: an innovative capability that arises from this coexistence and enables distinctive, relevant responses for specific recipients.