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Artificial Intelligence (AI), Cyberpsychology, Human-Centric, Cybersecurity Defenses, Behavioral Insights, Cognitive Biases, Emotional Triggers, Phishing Prevention, Insider Threat, Mitigation, Adaptive Systems.

Artificial Intelligence (AI) has become a cornerstone of modern cybersecurity, enabling systems capable of detecting, mitigating, and responding to cyber threats with remarkable efficiency. Despite these advancements, a critical gap remains in addressing the human element is a major factor in cybersecurity vulnerabilities. Studies reveal that over 85% of breaches are attributable to human error, including cognitive biases, emotional triggers, and habitual behaviors. Traditional AI systems primarily focus on technical vulnerabilities, such as malware or network breaches, often neglecting these human dimensions. This oversight leaves organizations vulnerable to sophisticated attacks that exploit psychological weaknesses, including phishing, social engineering, and insider threats. Integrating cyberpsychology, the study of human behavior in digital environments, into AI systems offers a transformative approach to addressing these challenges. By leveraging insights into how individuals interact with technology, human-centric AI systems can predict and mitigate errors, guide users in real-time, and foster secure behaviors. For instance, emotion-aware AI can detect user frustration during password resets and offer tailored assistance, thereby reducing user errors and boosting satisfaction. Similarly, gamified training platforms incentivize engagement, enhancing awareness and long-term adherence to secure practices. Behavioral threat modeling, informed by cyberpsychology, further strengthens security by identifying anomalies, such as unusual login activity, and proactively addressing potential risks before incidents occur. This research explores the theoretical foundations, empirical evidence, and practical applications of human-centric AI in cybersecurity through a qualitative case study approach examining three distinct organizational contexts. The findings demonstrate substantial improvements in security outcomes when psychological principles are integrated into AI-driven systems, including a 48% reduction in phishing incidents, 92% accuracy in identifying potential insider threats, and significant improvements in security awareness through gamified training. These improvements highlight how merging technical innovation with psychological understanding enables adaptive, user-centered defenses that empower individuals while significantly reducing organizational risk. The human-centric approach establishes a new benchmark for resilient and effective cybersecurity strategies that address both technical and human dimensions of security.