Next-Generation Management on Exploring AI-Driven Decision Support in Business

Abstract

Algorithmic decision support (ADS), driven by AI fueled by machine learning, is increasingly becoming an essential element in diverse processes across sectors. Organizations implement Advanced Decision Support (ADS) systems to improve the efficiency of decision-making and make the most use of data. Nevertheless, the advancement of ADS entails a multitude of human choices that can inject intricacies and ambiguities into the procedure. These decisions encompass the selection of areas to use ADS, as well as the choices made during its creation and the subsequent utilization of its outputs for decision-making. Conclusions derived from ADS outputs are typically applied in organizational settings without adequately assessing the consequences of the decision support. This study explores the difficulties related to the creation and implementation of ADS, with a focus on the significance of taking behavioural aspects into account while adopting ADS in businesses.

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