Evaluating the Integration of AI-Driven Cybersecurity Frameworks in Agile Program Management for Medium and Large Organizations

Abstract

The increasing complexity of cybersecurity threats, combined with the widespread adoption of AI technologies, necessitates robust program management frameworks in medium and large organizations. This study evaluates the integration of AI-based cybersecurity solutions within Agile program management practices, focusing on the balance between operational speed, assurance, and compliance. A mixed-method approach is employed, combining quantitative analysis of open-source cybersecurity datasets with qualitative survey insights from program managers. The research examines adversarial attacks and the effectiveness of AI-driven defense mechanisms, including Recurrent Neural Network (RNN) models for anomaly detection. Results indicate that organizations adopting AI-integrated frameworks achieve higher threat detection accuracy and maintain compliance standards without compromising program delivery speed. The findings provide actionable guidance for embedding security-first practices into Agile program lifecycles, offering valuable insights for program managers, cybersecurity teams, and organizational leadership.