Six countries, six conversations, one critical question: What does the future of security operations look like in the age of AI?
Qevlar AI recently completed a series of intimate dinner gatherings across six European countries to address this pivotal question facing cybersecurity leaders today.
The company's leadership team traveled to the UK, Italy, France, Sweden, Germany, and Spain to convene small groups of top cybersecurity minds, including CISOs from leading organizations and security operations experts. The format was deliberately simple: no slides, no pitches, just focused dialogue around the practical challenges of integrating AI into security operations.
The conversations revealed several critical themes shaping the future of AI-driven security operations:
Practical AI Implementation Over Hype: CISOs consistently emphasized their focus on making AI practical and impactful rather than pursuing technology that merely appears impressive on paper. The focus was on real-world applications that solve actual operational challenges.
Trust and Orchestration Trump Speed: Effective AI adoption in security operations depends fundamentally on trust and thoughtful orchestration rather than simply accelerating existing processes. Security leaders stressed the importance of AI systems that can be relied upon to make sound decisions autonomously.
Analyst Time Protection: A clear priority emerged around protecting analyst time, reflecting the ongoing talent shortage in cybersecurity and the need for AI solutions that genuinely augment human capabilities rather than create additional overhead.
The learnings gathered from these European conversations will inform Qevlar AI's continued development of autonomous AI SOC analysts, which currently serve leading Managed Security Service Providers (MSSPs) and enterprises across the globe.
As the cybersecurity landscape continues to evolve rapidly, the company's commitment to understanding the practical needs of security operations teams through direct engagement with industry leaders demonstrates the importance of human insight in developing effective AI solutions.