Generative Artificial Intelligence Empowering Knowledge Work: The Impact of Human-AI Collaboration on the Efficiency and Quality of Managerial Decision-Making

Abstract

The rapid iteration and industrialization of Generative Artificial Intelligence (GenAI) have thoroughly changed the paradigm of knowledge work in modern organizations, and thus the process of managerial decision-making has evolved from heuristic judgment dominated by human managers to the new paradigm of human-AI collaborative creation. This paper seeks to investigate how GenAI-assisted human-AI collaboration would affect the effectiveness and quality of organizational managerial decision-making. Based on the knowledge-based view and collaborative intelligence, a theoretical framework including the technology of GenAI, modes of human-AI collaboration and decision-making performance is established in this paper. By quantitative simulation experiments and empirical analysis with Python, the impacts of GenAI assistance on decision-making time cost, information processing comprehensiveness, decision accuracy and risk identification ability are verified in this paper. It can be found that moderate human-AI collaboration will contribute to managerial decision-making effectiveness and quality; too much or not enough GenAI assistance may weaken the positive impacts of human-AI collaboration on managerial decision-making. GenAI contributes to managerial decision-making effectiveness and quality mainly through reducing information searching costs, improving data analysis efficiency and compensating human cognitive limitations.