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Theoretical and Conceptual Frameworks for Understanding Artificial Intelligence in Records and Information Management
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Author(s): Dhara Ashish Darji (Ganpat University, India), Pooja D. Pancholi (Ganpat University, India), Shital Bhagubhai Patel (Ganpat University, India), Sonal J. Patel (Ganpat University, India)and Jagruti N. Patel (Ganpat University, India)
Copyright: 2025
Pages: 32
Source title:
Artificial Intelligence in Records and Information Management
Source Author(s)/Editor(s): Samson Mutsagondo (Sorbonne University, Abu Dhabi, UAE)
DOI: 10.4018/979-8-3693-9795-4.ch007
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Abstract
Artificial Intelligence has transformed the RIM arena by changing how organizations create, store, and retrieve records. What was once left to traditional approaches now uses data analytics, pattern recognition, automation, and NLP capabilities through AI to redefine efficiency, accuracy, and scalability in handling records and information. Although these changes can provide better processes that comply with the new standards, there are challenges of ethics, technology, and the organization. This chapter delves into how AI might help reduce the complexity involved in handling large volumes of data by providing theoretical frameworks as well as concrete methodologies to integrate AI with RIM. It also explores trends like intelligent automation and predictive analytics and their applications in subdomains such as archive management and digital preservation. By touching upon problems such as data privacy and ethics, the chapter provides an overarching framework for adoption of AI, giving valuable insights to practitioners, researchers, and policymakers alike.
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