AI-Driven Cybersecurity in IT Project Management: Enhancing Threat Detection and Risk Mitigation

Abstract

With increasingly sophisticated and common cyberattacks these days, conventional cybersecurity solutions in IT project management tend to fall short. As the sophistication of cyberattacks increases, the demand for fresh ideas that can best protect IT systems and information continues to rise. This research examines the adoption of Artificial Intelligence (AI) in cybersecurity solutions in IT project management. In particular, it examines how AI technologies, such as machine learning, deep learning, and anomaly detection, can be utilized to augment threat detection, respond automatically, and enhance risk management in IT initiatives. The study follows a mixed-methods framework with an amalgamation of systematic literature review along with case studies. Statistical instruments like SPSS v25 were used to test data from 40 IT initiatives that adopted AI-based cybersecurity systems. Key performance measures like time to detect threats, effectiveness in mitigating risk, and security results were measured before and after integrating AI solutions. Findings reveal that there was a 35% decrease in time to detect threats, a 25% increase in the effectiveness of mitigating risk, and a 45% increase in the accuracy in detecting threats, which overall contributed to a tremendous reduction in cybersecurity breaches. These results emphasize the revolutionary influence of AI in cybersecurity practices of IT project management. The research concludes that AI-based cybersecurity models provide a viable avenue to address risks proactively and improve the security stance of IT projects. It is highly recommended that IT project managers embrace AI-driven solutions to enhance their cyber defenses against current and impending threats and guarantee the successful and secure delivery of projects in today’s connected world.