Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Security teams face a new imperative: act fast, or risk losing the vulnerability battle. The average enterprise faces thousands of vulnerabilities across a sprawling hybrid attack surface. Adversaries are using AI to discover and exploit weaknesses independently, at machine speed, making traditional disclosure timelines increasingly irrelevant. Scan-and-ticket workflows weren't built for this reality, and neither are the teams asked to execute them with finite headcount and growing board-level scrutiny.

Agentic AI is rewriting the rules of enterprise risk, operating across distributed systems at a speed and scale that most security architectures weren’t designed to handle.

CrowdStrike is introducing AI Discovery and Governance for CrowdStrike Falcon for IT, a new capability that helps organizations identify, assess, and govern AI technologies across enterprise environments. Enterprise IT infrastructure is the control plane for modern organizations. It determines how systems communicate, how identities authenticate, and how workloads execute across endpoints, servers, and clouds. This foundation supports the rapid implementation of AI across businesses.

CrowdStrike has once again been named a Leader in the 2026 Gartner Magic Quadrant for Endpoint Protection.

Companies and employees are racing to capture the value and efficiencies offered by AI, but security is often an afterthought. Employees are using unauthorized GenAI tools to summarize documents, draft emails, and analyze potentially sensitive or proprietary data. Developers are adding AI capabilities before security teams can review them. SaaS platforms are adding AI features that may process sensitive business data by default.

Two recent industry reports validate CrowdStrike’s leadership in the identity threat detection and response (ITDR) market: Identity is the front line of modern cyberattacks. Today’s adversaries log in and use legitimate identities to move laterally, escalate privileges, and operate inside legitimate sessions as trusted users.