Artificial Intelligence in Cybersecurity: An Agent-Based Model for Nist and Sox Compliance

The rise in complexity of cyber threats demands advanced security systems that utilize Artificial Intelligence (AI) to improve protection and ensure compliance. This paper introduces an AI-based agent model created to assist cybersecurity operations while maintaining compliance with the National Institute of Standards and Technology (NIST) and the Sarbanes-Oxley Act (SOX). The suggested model incorporates machine learning, behavioral analysis, and automated decision-making to identify anomalies, counter threats, and apply regulatory controls in real time. By using intelligent agents, the system perpetually observes network activities, detects potential security incidents, and guarantees adherence to established cybersecurity regulations. The research assesses how effective AI-driven automation is in minimizing compliance risks, simplifying audit procedures, and strengthening cybersecurity resilience. The results indicate that AI-enabled agent-based models can greatly enhance compliance enforcement and threat response, thereby fortifying organizational security measures.