A Three-Layer Model for Training Conflict Management and Negotiation in Hybrid Human–Artificial Intelligence Environments

Abstract: Developing conflict management and negotiation capabilities in complex, dynamic environments remains a central challenge for scholars and practitioners. While traditional approaches have relied on face-to-face instruction, case analysis, and human-led simulations, these formats are increasingly constrained in supporting sustained managerial judgment and adaptability under uncertainty. Building on recent developments in hybrid learning and AI-supported training, this paper presents a design-oriented three-layer training model that reframes conflict training as an adaptive, multi-stage process rather than a single instructional intervention. The proposed architecture integrates three complementary layers: engagement through narrative-based learning, reflective insight enabled by diagnostic processes that surface individual conflict patterns, and adaptive practice through AI-based simulation. The contribution of this work lies in articulating a coherent training architecture grounded in accumulated development and implementation experience. The model offers a conceptual framework for conflict management and negotiation training that leverages hybrid human–AI environments while preserving human agency.

Keywords: AI-Supported Training; Negotiation Simulation; Hybrid Human–AI Learning.