HUMAN–AI COLLABORATION AND MANAGERIAL DECISION-MAKING A FRAMEWORK FOR AI-ASSISTED INFORMATION SYSTEMS

The rapid adoption of Artificial Intelligence (AI) in organizational information systems is significantly transforming the nature of managerial decision-making. AI-assisted information systems can process large and complex datasets, identify hidden patterns, generate predictions, and provide recommendations that support managers in strategic and operational decisions. However, the effectiveness of AI-supported decision-making depends not only on technological capability but also on how managers understand, trust, evaluate, and collaborate with AI-generated recommendations. Excessive reliance on AI may lead to automation bias, while insufficient trust may result in the rejection of valuable AI insights. In this context, the present study proposes an integrated framework for examining Human–AI collaboration in managerial decision-making. The framework establishes relationships among AI capability, AI explainability, human trust in AI, Human–AI partnership, decision quality, and organizational outcomes. AI capability represents the analytical and predictive strength of AI systems, while explainability enables managers to understand and evaluate AI-generated recommendations. Human trust is positioned as a key mechanism through which technological capabilities influence effective Human–AI collaboration. The framework further emphasizes human oversight and organizational AI readiness to ensure appropriate managerial control and responsible use of AI. The proposed model suggests that effective collaboration between human expertise and AI intelligence can enhance decision accuracy, timeliness, strategic alignment, and overall organizational performance. The study provides a structured foundation for empirically examining AI-assisted managerial decision-making and offers practical implications for organizations seeking to implement AI as a collaborative decision-support capability rather than a replacement for managerial judgment.