Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Adversaries are using AI to attack with unprecedented speed and precision. This trend, coupled with the rapidly growing use of agentic AI, means it is now necessary to use AI to protect and defend the modern tech stack. It is timely that on June 2, 2026, President Trump signed Executive Order 14409 on Promoting Advanced Artificial Intelligence Innovation and Security. At a high level, this EO validates that security is fundamental to reaping the benefits of AI.

Frontier AI is poised to change cybersecurity faster than most organizations can adapt. It’s accelerating vulnerability discovery, which puts new pressure on security teams to handle more vulnerabilities, in less time, with workflows built for much slower technology. The primary challenge of the frontier AI era is not the increase in vulnerabilities. It’s understanding which exposures are most critical and how to address them before adversaries target them.

Identity security has long been built around a simple premise: Authenticate a user, grant access, and trust that decision until their next login. While for many this model worked well enough when identities were primarily human and access patterns were predictable, that’s no longer the case for humans and definitely not the case for AI agents.

Across enterprises, a familiar pattern is emerging. A business unit identifies an AI tool with a clear upside in productivity or revenue. Their proposal moves into procurement. Security raises concerns, and the legal team asks new questions about the tool. Compliance starts hesitating and the momentum slows. Finally, the project stalls. This friction is not due to resistance to innovation. It reflects a deeper structural issue: Most enterprise governance models were not designed for AI.

We're proud to announce that Frost & Sullivan has named CrowdStrike a Leader for the second consecutive time in the 2026 Frost Radar: Cloud and Application Runtime Security (CARS). Building on last year's recognition, CrowdStrike scored highest on both the Growth and Innovation indices.

CrowdStrike has joined the OpenID Foundation as a Sustaining Corporate Member, its highest level of membership, and is also now a member of IDPro. Together, these commitments reflect a focused effort to help shape the future of identity-first security through both standards leadership and real-world deployment and a shift beyond static authentication toward more dynamic, interoperable, and effective identity security.

Modern adversaries are accelerating attacks across identities, endpoints, cloud environments, and SaaS applications, often moving faster than security teams can respond. Identity has become a primary attack vector as attackers leverage credential abuse to evade detection and expand their foothold. Stopping today’s threats requires visibility and context across every domain to accurately assess risk before adversaries can move laterally.

AI is moving from experimentation to execution. What started as copilots is quickly evolving into autonomous AI agents that can make decisions, execute tasks, and operate across enterprise environments. As organizations accelerate adoption of agentic AI, they’re expanding their attack surface in ways traditional security models weren’t built to handle.

As organizations accelerate adoption of AI systems, the scope of data security has dramatically expanded. Sensitive data is no longer simply stored. It is continuously accessed, transformed, and moved across cloud services, APIs, and AI pipelines. For use cases from model training to inference, AI systems depend on dynamic data flows that introduce new and often unseen risks.

AI is reshaping the modern workplace. From automating tasks to generating in-depth research in seconds, AI tools are enhancing productivity at a lightning pace. GenAI assistants, agentic browsers, and automation platforms are everyday tools that employees are interweaving into their daily workflows. However, with this powerful new capability comes the serious risk of data loss.