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eISSN: 2581-9615 || CODEN (USA): WJARAI || Impact Factor: 8.2 || ISSN Approved Journal

The Role of Artificial Intelligence in predictive cyber threat detection: Opportunities and risks in U.S. federal and private sectors

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Salami Edward O *

Westcliff University, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 27(03), 990-1004

Article DOI: 10.30574/wjarr.2025.27.3.3200

DOI url: https://doi.org/10.30574/wjarr.2025.27.3.3200

Received on 05August 2025; revised on 14 September 2025; accepted on 17 September 2025

The introduction of artificial intelligence (AI) and machine learning (ML) technologies into cybersecurity has become a pivotal change of paradigm to respond to the changes in the environment of cyber threats. This extensive literature review summarizes how AI can be used to detect predictive cyber threats and evaluates the opportunities and risks of such applications by the federal and private industries in the U.S. The paper is a synthesis of the existing literature on AI-based detection methodologies, an analysis of the performance of different machine learning strategies, and the evaluation of sector-specific implementation issues. This article shows that AI technologies bring both new opportunities and new threats and challenges, even though they offer unprecedented opportunities in terms of their predictive and detection capabilities in threats. The results suggest that the successful implementation of AI in the field of cybersecurity must be attentive to industry-specific needs, regulations, and emerging threats. The study makes a contribution to the concept of the transformative power of AI in the field of cybersecurity, as well as outlining key areas that need further research and strategic formulation.

Artificial Intelligence; Cybersecurity; Threat Detection; Machine Learning; Federal Sector; Private Sector; Predictive Analytics

https://journalwjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-3200.pdf

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Salami Edward O. The Role of Artificial Intelligence in predictive cyber threat detection: Opportunities and risks in U.S. federal and private sectors. World Journal of Advanced Research and Reviews, 2025, 27(03), 990-1004. Article DOI: https://doi.org/10.30574/wjarr.2025.27.3.3200.

Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0

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