Enhancing Human-Machine Cooperation through the Integration of Empathetic AI into Corporate Cybersecurity and Forensic Operations

Radoslav Baltezarević Marko Stanojević Danilo Izgarević Miloš Azdejković

Журнал: International Journal of Cognitive Research in Science, Engineering and Education @ijcrsee

Статья в выпуске: 2 vol.14, 2026 года.

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In order to strengthen the cooperation between humans and machines, empathic artificial intelligence is increasingly emerging as a key player. This cooperation is particularly evident in corporate cybersecurity and digital forensics. Today, thanks to the inclusion of emotional awareness in artificial intelligence systems, many organizations can more easily monitor the cognitive load of their analysts during critical security situations. Empathic artificial intelligence in corporate cybersecurity is a new force for proactive threat detection, compliance and risk management. It helps analysts to respond to constant cyber threats more effec-tively, and in forensic investigations it offers great support in emotional and behavioral analysis. In this way, in cybercrime inves-tigations, through the observation of anomalies and their patterns, decisions are made with a higher degree of accuracy. How-ever, this technology still faces numerous challenges, such as accurately reading emotional cues, protecting sensitive data, and ensuring ethical management. In any case, well-defined frameworks that promote cooperation between artificial intelligence and humans are the necessity of the present, in order to remove these barriers. It is undeniable that empathic artificial intelligence has the potential to create security ecosystems that are more adequate, reliable and above all focused on human needs. Therefore, in the near future, it will revolutionize the field of corporate cybersecurity operations and digital forensics, but only if it is smartly implemented.

empathetic artificial intelligence \ human–machine collaboration \ corporate cybersecurity \ forensic operations \ cybercrime investigation

Короткий адрес: https://sciup.org/170213612

IDS: 170213612   |   УДК: 343.9:004.8   |   DOI: 10.23947/2334-8496-2026-14-2-373-384