AI-Empowered business decision-making: Cross-industry applications, challenges, and implementation strategies

Department of CHASS, University of California, Riverside, USA

^* Corresponding author: ychen1192@ucr.edu

Abstract

This article sheds lights on the influence and obstacles that AI may face in the process of corporate decision-making. It recognizes that AI has been extensively employed in market forecasting, customer behavior analysis, supply chain optimization, financial risk control, and other areas, with the intention of not only increasing efficiency, but also of making the activities more accurate. Besides, it still has to overcome challenges stemming from data governance, cost-benefit, talent development, and compliance, along with transparency. The writer identifies data governance, interpretable AI, stepwise changes, and interdepartmental cooperation as the main implementation paths and confirms their practicability through examples of retail, manufacturing, and finance. The article focuses on the irreplaceable role of human-machine collaboration and cultural transformation. Besides, it addresses the need for going research into aspects like international legal regulations, AI model safety, and explainability to be able to establish trust in AI as the main tool in high-risk industries.