IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Leveraging Artificial Intelligence for Enhanced Public Records Security in Zimbabwe

Leveraging Artificial Intelligence for Enhanced Public Records Security in Zimbabwe
View Sample PDF
Author(s): Constance C. Nhambura (University of South Africa, South Africa)
Copyright: 2025
Pages: 26
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.ch002

Purchase

View Leveraging Artificial Intelligence for Enhanced Public Records Security in Zimbabwe on the publisher's website for pricing and purchasing information.

Abstract

This chapter explores the potential of leveraging Artificial Intelligence (AI) to enhance the security of public records in Zimbabwe. Using systematic literature review, the chapter aims to establish how AI can be leveraged to enhance the security of public records in Zimbabwe. By integrating AI technologies such as anomaly detection, automated compliance monitoring, and intelligent document management, public institutions can significantly reduce the risks of data breaches, unauthorized access, and mismanagement of records. The chapter highlights the current challenges faced in records security, including inadequate infrastructure and limited resources. The findings suggest that adopting AI technologies cannot only bolster the security of public records but also improve operational efficiency and transparency in public administration.

Related Content

Frederic Andres. © 2027. 14 pages.
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar. © 2027. 27 pages.
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran. © 2027. 24 pages.
Swetha Margaret T. A., Renuka Devi D.. © 2027. 31 pages.
Maurice Saluschke, Michael Schulz. © 2027. 30 pages.
Mirjam Sepesy Maučec, Gregor Donaj. © 2027. 16 pages.
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo. © 2027. 21 pages.
Body Bottom