Tenzai’s Pavel Gurvich Discusses the Impact of Agentic AI on Application Security and Testing Efficiency
In a rapidly evolving technological landscape, the integration of artificial intelligence (AI) into software development processes has become increasingly prominent. Pavel Gurvich, co-founder and CEO of Tenzai, elaborated on how AI-driven development accelerates application delivery while posing significant challenges to traditional security testing models. During an insightful interview at the RSAC Conference 2026, Gurvich underscored the pressing need for security teams to adapt to the accelerated pace of code creation, emphasizing that the speed of development often outstrips the capacity of manual testing procedures.
Gurvich articulated this dilemma, noting that while organizations strive for swift application delivery, they must also consider the accompanying risks of potential vulnerabilities. The challenge lies in balancing the desire to release applications rapidly with the necessity to safeguard them against security threats. He acknowledged that manual testing cycles are becoming increasingly inadequate in addressing these vulnerabilities. As a solution, automated agents have emerged as vital tools, capable of conducting testing at machine speed. These agents not only enhance testing efficiency but also ensure comprehensive coverage across diverse and constantly changing environments, which is critical in today’s complex technological landscape.
The implications of employing agentic AI in application security extend beyond mere speed. According to Gurvich, these intelligent systems can significantly augment traditional security methodologies. By leveraging agentic AI, organizations can enhance their testing capabilities, compensating for the limitations of limited human resources and expertise. This technology allows for a more thorough evaluation that encompasses not just the source code but also the deployment, configuration, and integration layers of applications. Such comprehensive visibility enables teams to identify potential risks that conventional static analysis often overlooks, thus enhancing overall application security.
Gurvich made a compelling assertion during the interview, stating, “You better have an agent of your own testing your applications before somebody else does.” This warning highlights the critical importance of proactive testing measures in an era where AI-generated code can inadvertently introduce new security gaps and vulnerabilities. It is essential for organizations to adopt a proactive stance, leveraging AI-driven tools to anticipate and mitigate potential security issues before they can be exploited by malicious actors.
Throughout the discussion, Gurvich outlined key themes related to the use of agentic AI in cybersecurity. He highlighted the emergence of new security challenges stemming from AI-generated code, which can create overlooked vulnerabilities and edge cases that traditional approaches might miss. Additionally, he emphasized the role of agentic AI in facilitating penetration testing expertise across different teams within an organization. By integrating this technology, organizations are better equipped to conduct continuous and parallel testing, effectively replacing the slower, sequential review cycles that have historically characterized application testing.
Gurvich’s leadership at Tenzai has focused on developing AI-native cybersecurity strategies tailored to help enterprises protect their code and enhance resilience. Drawing from his extensive background, which includes co-founding Guardicore and directing Akamai’s enterprise security business, Gurvich brings a wealth of experience to the forefront of cybersecurity innovation. His military background, including 12 years in Israeli military cyber roles, further informs his understanding of the intricacies involved in safeguarding digital infrastructures against evolving threats.
In summary, Gurvich’s insights shed light on the transformative potential of agentic AI in application security. As organizations increasingly adopt AI technologies for development purposes, the pressing need for robust security measures becomes undeniable. By employing automated agents to conduct proactive, comprehensive testing, organizations can significantly improve their security posture, enabling them to navigate the complexities of modern application development with greater confidence and resilience. As the digital landscape continues to evolve, it is clear that the integration of agentic AI will play a pivotal role in redefining how organizations approach application security and testing methodologies.