EconPapers    
Economics at your fingertips  
 

AI-Based Enterprise Notification Systems and Optimization Strategies for User Interaction

Qianru Xu

European Journal of AI, Computing & Informatics, 2025, vol. 1, issue 2, 97-102

Abstract: In modern enterprises, notification systems play an important role as key tools for information exchange and user interaction. However, the current notification system faces various challenges such as data confidentiality, security protection, message quality, development costs, and technical difficulties. The introduction of artificial intelligence (AI) technology has brought new solutions to these problems. For example, AI can enhance data confidentiality, use deep reinforcement learning to improve content distribution, utilize cloud computing to reduce development costs, and incorporate fairness principles into model training, thereby improving the performance and user satisfaction of notification systems. This study explores the problems existing in current notification systems and proposes targeted improvement solutions based on AI technology, providing theoretical support and practical guidance for enterprises to create efficient, secure, and highly intelligent notification systems.

Keywords: enterprise level notification system; artificial intelligence; user interaction; data privacy; content optimization (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://pinnaclepubs.com/index.php/EJACI/article/view/227/234 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dba:ejacia:v:1:y:2025:i:2:p:97-102

Access Statistics for this article

More articles in European Journal of AI, Computing & Informatics from Pinnacle Academic Press
Bibliographic data for series maintained by Joseph Clark ().

 
Page updated 2025-10-02
Handle: RePEc:dba:ejacia:v:1:y:2025:i:2:p:97-102