Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges

TL;DR

This paper explores how deep learning algorithms can enhance organizational decision-making by improving information processing and supporting employees, highlighting principles, promises, and challenges involved.

Contribution

It provides a comprehensive overview of deep learning's potential to augment decision-making in organizations, emphasizing theoretical insights and practical considerations.

Findings

Deep learning can improve decision support systems.

DL algorithms assist employees in complex information processing.

Challenges include data quality and ethical considerations.

Abstract

The current expansion of theory and research on artificial intelligence in management and organization studies has revitalized the theory and research on decision-making in organizations. In particular, recent advances in deep learning (DL) algorithms promise benefits for decision-making within organizations, such as assisting employees with information processing, thereby augment their analytical capabilities and perhaps help their transition to more creative work.