AI-Powered Decision Making in Management: A Review and Future Directions
Authors:
- 12 May 2023
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 82-86
Abstract
Artificial intelligence (AI) tools have developed to the point where they are now integrated into systems that support decision-making in practical settings and have a significant influence on that decision-making. This paper discusses decision-making theories, artificial intelligence (AI) technologies, and the sensible decision systems that derive fromthe blending of these ideas. This paper reviews the current state of AI-powered decision making in management and discusses future directions for research in this area. The review covers various applications of AI in management, including decision support systems, predictive modeling, and optimization. The benefits and limitations of using AI in decision making are also discussed. The paper concludes with a discussion of future research directions, including the integration of AI with other technologies, the use of explainable AI, and the need for interdisciplinary research.Keywords
This publication has 14 references indexed in Scilit:
- Unsupervised Hyperspectral Microscopic Image Segmentation Using Deep Embedded Clustering AlgorithmScanning, 2022
- Bi-level energy optimization model in smart integrated engineering systems using WSNEnergy Reports, 2022
- Intelligent ecofriendly transport management system based on IoT in urban areasEnvironment, Development and Sustainability, 2022
- Application of deep learning and machine learning models to detect COVID-19 face masks - A reviewSustainable Operations and Computers, 2021
- Predictive Analytics for Smart Parking: A Deep Learning Approach in Forecasting of IoT DataACM Transactions on Internet Technology, 2021
- Artificial Neural Networks in AgricultureAgriculture, 2021
- Intelligent Chatbot for Lab Security and Automation2020
- Formulation and application of quantum-inspired tidal firefly technique for multiple-objective mixed cost-effective emission dispatchNeural Computing and Applications, 2019
- iRAF: A Deep Reinforcement Learning Approach for Collaborative Mobile Edge Computing IoT NetworksIEEE Internet of Things Journal, 2019
- A novel LMS algorithm for ECG signal preprocessing and KNN classifier based abnormality detectionMultimedia Tools and Applications, 2018