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

arXiv: https://arxiv.org/abs/2011.02834 · HTML: https://mlsanity.com/paper/2011.02834/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Nov 2020.

## Built on by (most cited first, 4 of 4)

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- [A categorical error sensitivity index (ISEC): A preventive ordinal decision-support measure for irrecoverable errors in manual data entry systems](https://mlsanity.com/paper/2605.12328/) (2026)

## Abstract (arXiv)

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.