The 2025 State of Ransomware Survey from CrowdStrike paints a concerning picture of the modern threat landscape, revealing that a vast majority of organizations are falling behind in the race against Artificial Intelligence (AI)-driven adversaries. A striking 76% of 1,100 IT and cybersecurity leaders surveyed admit their organizations cannot defend at the speed of AI-powered attacks. The report also uncovers a significant disconnect between perception and reality, with high leadership confidence in ransomware readiness despite high rates of successful attacks. The findings serve as a clear call to action for businesses to abandon legacy security models and embrace AI-powered defensive technologies to stand a chance against today's hyper-accelerated threats.
While this is a survey report and not a regulation, it outlines the de facto requirements for modern cyber defense in an AI-driven world. The key findings imply a new standard of care for organizations:
The survey included 1,100 senior IT and cybersecurity decision-makers from a wide range of industries across the globe, including the United States, United Kingdom, France, Germany, India, Singapore, and Australia. The findings are broadly applicable to any medium-to-large enterprise.
To align with the realities presented in the report, organizations must pivot their security strategies. The implied requirements are:
The primary impact highlighted by the survey is the widening gap between attacker capabilities and defender readiness.
To address the challenges raised by the CrowdStrike report, organizations should take the following steps:
Accenture report confirms widespread unpreparedness for AI-powered cyberattacks, with 90% of firms unready and 77% lacking AI security practices.
Deploy AI-powered EDR solutions that can detect and block malicious behaviors in real-time, matching the speed of automated attacks.
While AI makes phishing more convincing, ongoing user training is still a critical layer of defense to reduce the success rate of initial access attempts.
Given that paying a ransom is ineffective, robust and tested backup and recovery capabilities are the most reliable way to respond to a successful ransomware attack.
To counter the speed of AI-powered attacks, organizations must fight fire with fire by implementing AI-based Process Analysis. Legacy, signature-based antivirus is obsolete. Modern EDR and XDR platforms that use machine learning models can analyze process behaviors, command-line arguments, and API calls in real-time. These models are trained on vast datasets to recognize malicious patterns at machine speed, enabling them to detect and terminate an AI-driven attack chain before it achieves its objective. This is the core technological shift required to close the response gap identified in the CrowdStrike report.
Since AI makes phishing lures more convincing, organizations must assume that initial compromise will occur. User Behavior Analytics (UBA) provides a critical post-compromise detection layer. By baselining normal user and entity behavior, UBA systems can detect anomalies that signal an attack, such as a user account suddenly accessing sensitive data, logging in from an unusual location, or using novel administrative tools. This allows security teams to detect a compromised account being used by an attacker, even if the initial entry point was missed.

Cybersecurity professional with over 10 years of specialized experience in security operations, threat intelligence, incident response, and security automation. Expertise spans SOAR/XSOAR orchestration, threat intelligence platforms, SIEM/UEBA analytics, and building cyber fusion centers. Background includes technical enablement, solution architecture for enterprise and government clients, and implementing security automation workflows across IR, TIP, and SOC use cases.
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