The Transitioning from Individual Implementation of Zero Trust Architecture to AI-driven Tools : Reducing Manual Workloads and Increasing Efficiency through AI in ZTA

Zero Trust Architecture (ZTA) has emerged as a fundamental security framework for Information Technology (IT) companies seeking to enhance their cybersecurity posture. Nordic based IT companies, such as Atea, face challenges in manually implementing ZTA due to its complexity and the time required for individuals. As AI-driven security tools like Microsoft Security Copilot continue to gain traction, companies are increasingly examining their potential for integration into ZTA implementation to enhance security and efficiency. This study examines the perspectives of five IT security professionals' knowledge on ZTA, its implementation and the role of AI-driven tools in streamlining security processes. Through semi-structured interviews, participants shared their insights regarding ZTA definitions, implementation strategies, challenges, and the impact of AI tools on security workflows. A thematic analysis approach was conducted to identify the occurring patterns and categorized within the research questions. Findings show that AI enhances efficiency by reducing manual workload and enhancing threat detection, but human expertise is still crucial for security management. Participants raised concerns about vendor reliance, compliance restrictions, costs, and data leak risks, emphasizing the need to protect sensitive information in AI-driven ZTA. Furthermore, IT security implementations are unique to each organization, as they depend on the specific needs and goals of the organization. The study concludes that each organization has different security needs, resources, and goals which means ZTA implementation must be flexible. Companies should tailor their security strategies to fit their specific situation while still following core security principles.