Year: 2025
Type: article
Abstract: Modern digital systems that rely heavily on data collection have made user privacy the key operational challenge. Private or sensitive information needs data anonymization through identifier removal or encryption to protect it across healthcare, financial and e-commerce operations. Implementing Artificial Intelligence (AI) technology created new procedures to automate data anonymization processes. Privacy preservation remains uncertain when using AI-based anonymization systems since these technologies might introduce privacy vulnerabilities. The article examines how AI interacts with data anonymization by reviewing framework capabilities supported by related advantages and inherent restrictions. The article discusses whether AI solutions yield improved privacy security or if they give rise to novel exposure risks because of de-anonymization features and algorithmic bias vulnerabilities. This paper analyzes the academic and industrial development of AI applications for privacy preservation through an organized review process establishing an essential evaluation of AI's influence on future privacy techniques.
Author: Meghasai Bodimani
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4410029607