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

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.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17759187
Primary Topic
Information and Cyber Security
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Information and Cyber Security
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Information and Cyber Security
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