Proceedings of the 2024 2nd International Conference on Management Innovation and Economy Development (MIED 2024)

A Novel Management Decision Method with Artificial Intelligence Algorithm

Authors
Zikang Zhang1, *
1College of Letter and Science, University of California-Berkeley, Berkeley, CA, United States
*Corresponding author. Email: zhangzikang0204@163.com
Corresponding Author
Zikang Zhang
Available Online 15 October 2024.
DOI
10.2991/978-94-6463-542-3_10How to use a DOI?
Keywords
Artificial Intelligence; Financial Technology; Decision-Making; Data Model; Decision Support System
Abstract

In contemporary management practices, decision-making processes are critically influenced by the efficiency and accuracy of the underlying methodologies. Traditional decision-making approaches are often challenged by the complexity and scale of data involved, leading to delays and potential inaccuracies. Artificial Intelligence (AI), particularly through large-scale model training, offers a promising alternative by enabling more rapid and precise decision-making frameworks. However, the adoption of AI in management decisions is not without its limitations, including issues related to data privacy, model transparency, and integration with existing systems. In this research, we will introduce an innovative approach utilizing large AI models to enhance management decision-making processes. By leveraging advanced algorithms and substantial data training sets, our methodology not only addresses the shortcomings of traditional systems but also capitalizes on the speed and scalability of modern AI technologies. The implementation of our approach in several enterprise environments demonstrates significant improvements in decision-making efficiency and organizational performance. The findings suggest that large-scale AI models can be effectively integrated into management frameworks, providing a robust tool for enhancing decision accuracy and operational efficiency. These results are indicative of the substantial benefits that such technologies can bring to management practices, making them a valuable reference for organizations aiming to improve their decision-making systems. The practical implications of this research underscore the transformative potential of AI in management, advocating for broader adoption and continued innovation in this field.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 2nd International Conference on Management Innovation and Economy Development (MIED 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
15 October 2024
ISBN
978-94-6463-542-3
ISSN
2352-5428
DOI
10.2991/978-94-6463-542-3_10How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Zikang Zhang
PY  - 2024
DA  - 2024/10/15
TI  - A Novel Management Decision Method with Artificial Intelligence Algorithm
BT  - Proceedings of the 2024 2nd International Conference on Management Innovation and Economy Development (MIED 2024)
PB  - Atlantis Press
SP  - 70
EP  - 75
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-542-3_10
DO  - 10.2991/978-94-6463-542-3_10
ID  - Zhang2024
ER  -