Over 75% of Orgs Can't Keep Pace with AI-Powered Attacks, Survey Finds

CrowdStrike Survey: 76% of Organizations Lag Behind AI-Driven Cyberattacks, Revealing Critical 'Confidence Illusion'

INFORMATIONAL
October 22, 2025
November 9, 2025
5m read
Threat IntelligenceRansomwarePolicy and Compliance

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Full Report(when first published)

Executive Summary

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.


Regulatory Details

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:

  • Speed is Paramount: The core challenge is the speed of attack. Adversaries use AI to automate reconnaissance, develop malware, and craft convincing phishing lures, collapsing the 'breakout time'—the window defenders have to react—to mere minutes.
  • AI Defense is Essential: An overwhelming 89% of security leaders now view AI-powered protection as an essential capability, not a luxury. This indicates a market consensus that traditional, signature-based defenses are obsolete.
  • Ransom Payments are Ineffective: The survey reinforces that paying a ransom is a losing strategy. 83% of organizations that paid were attacked again, and 93% had their data stolen regardless, confirming the untrustworthiness of cybercriminals.

Affected 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.

Compliance Requirements

To align with the realities presented in the report, organizations must pivot their security strategies. The implied requirements are:

  1. Adopt AI-Powered Defenses: Implement security platforms that use AI and machine learning to detect and respond to threats in real-time. This includes next-generation antivirus (NGAV), endpoint detection and response (EDR), and identity protection tools that can analyze behavior at machine speed.
  2. Focus on Proactive Threat Hunting: Shift from a reactive posture to proactive threat hunting, using intelligence and technology to find adversaries in the network before they can execute their final attack.
  3. Align Leadership and Technical Teams: Bridge the 'confidence illusion' by providing boards and executive leadership with realistic, data-driven metrics on cyber readiness, rather than subjective confidence scores.

Impact Assessment

The primary impact highlighted by the survey is the widening gap between attacker capabilities and defender readiness.

  • Increased Breach Velocity: AI allows attackers to move through the attack lifecycle faster than human-led security teams can respond, leading to more frequent and more damaging breaches.
  • Ineffective Security Spending: Organizations clinging to legacy security tools are investing in technology that is fundamentally incapable of stopping modern threats, resulting in wasted budget and a false sense of security.
  • The 'Confidence Illusion': 76% of respondents reported a disconnect between leadership's perceived readiness and the organization's actual preparedness. This dangerous gap means strategic decisions are being made based on flawed assumptions, leaving organizations exposed.

Compliance Guidance

To address the challenges raised by the CrowdStrike report, organizations should take the following steps:

  1. Benchmark Your Response Time: Measure your organization's mean time to detect (MTTD) and mean time to respond (MTTR). Compare this against the breakout times of modern adversaries. If your response time is measured in hours or days, you are critically vulnerable.
  2. Invest in an AI-Native Security Platform: Evaluate and invest in a consolidated security platform that leverages AI across endpoints, cloud workloads, identity, and data. This is essential for achieving the speed and visibility needed for modern defense.
  3. Re-evaluate Your Ransomware Policy: Based on the data showing the ineffectiveness of paying ransoms, boards should re-evaluate their stance. Focus investment on prevention, detection, and recovery capabilities rather than budgeting for ransom payments.

Timeline of Events

1
October 21, 2025
CrowdStrike releases its 2025 State of Ransomware Survey.
2
October 22, 2025
This article was published

Article Updates

November 9, 2025

Accenture report confirms widespread unpreparedness for AI-powered cyberattacks, with 90% of firms unready and 77% lacking AI security practices.

MITRE ATT&CK Mitigations

Deploy AI-powered EDR solutions that can detect and block malicious behaviors in real-time, matching the speed of automated attacks.

Mapped D3FEND Techniques:

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.

D3FEND Defensive Countermeasures

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.

Article Author

Jason Gomes

Jason Gomes

• Cybersecurity Practitioner

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.

Threat Intelligence & AnalysisSecurity Orchestration (SOAR/XSOAR)Incident Response & Digital ForensicsSecurity Operations Center (SOC)SIEM & Security AnalyticsCyber Fusion & Threat SharingSecurity Automation & IntegrationManaged Detection & Response (MDR)

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AIartificial intelligenceCrowdStrikeransomwarethreat landscapecybersecurity survey

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