Download PDFOpen PDF in browserOvercoming Challenges: Integrating AI/ML with Legacy Systems and Addressing Data Privacy ConcernsEasyChair Preprint 126268 pages•Date: March 20, 2024AbstractIntegrating 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
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