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Organizations Lag in AI Governance as Shadow AI and AI-Powered Threats Expand Attack Surface

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A survey of 3,400 digital trust professionals reveals widespread adoption of AI tools in organizations with insufficient governance controls. Fewer than half (38%) have formal AI policies, while 25% lack any AI policy. Shadow AI usage risks exposing sensitive data to unmanaged large language models (LLMs), and 56% of respondents cannot estimate the time required to halt AI systems during a security incident. AI-powered cyber threats—particularly phishing, social engineering, and misinformation—are perceived as harder to detect and authenticate, with 71% reporting increased difficulty in identifying such attacks. Only 20% of organizations have processes to override malicious or compromised AI systems, and 43% acknowledge AI-based cybersecurity tools have improved detection capabilities, but governance gaps persist despite escalating risks.

Timeline

  1. 05.05.2026 14:10 1 articles · 15h ago

    ISACA survey identifies governance and security gaps in enterprise AI adoption

    A survey of 3,400 digital trust professionals reveals that 90% of organizations report employee use of AI tools, but only 38% have formal AI policies in place. 25% lack any AI policy, and 56% cannot estimate the time required to halt AI systems during a security incident. Only 20% have processes to override malicious or compromised AI systems. AI-powered phishing and social engineering attacks are perceived as harder to detect (71%), and authenticating digital information has become significantly more difficult (58%). 38% report declining trust in traditional threat detection methods, while 43% acknowledge improvements in detection and response due to AI-based cybersecurity tools.

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