Download PDFOpen PDF in browser

Overcoming Challenges: Integrating AI/ML with Legacy Systems and Addressing Data Privacy Concerns

EasyChair Preprint 12626

8 pagesDate: March 20, 2024

Abstract

Integrating Artificial Intelligence (AI) and Machine Learning (ML) with legacy systems poses significant challenges for organizations seeking to leverage these technologies in their operations. Additionally, data privacy concerns present a formidable obstacle to the adoption of AI/ML, particularly in industries dealing with sensitive information. This research paper explores the complexities of integrating AI/ML with legacy systems and addresses data privacy concerns. It examines strategies for overcoming these challenges, including data anonymization techniques, secure integration protocols, and regulatory compliance measures. By exploring real-world case studies and best practices, this paper offers insights into effective approaches for integrating AI/ML with legacy systems while safeguarding data privacy.

Keyphrases: Integration Challenges, Legacy Systems, Machine Learning (ML), data privacy

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:12626,
  author    = {Hiromi Morita and Kiswah Noor},
  title     = {Overcoming Challenges: Integrating AI/ML with Legacy Systems and Addressing Data Privacy Concerns},
  howpublished = {EasyChair Preprint 12626},
  year      = {EasyChair, 2024}}
Download PDFOpen PDF in browser