Topic

AI Security

AI security encompasses the practices, tools, and frameworks used to protect AI systems from adversarial attacks, data breaches, model theft, and unauthorized access or manipulation. It is critical for enterprise AI governance because vulnerabilities in AI systems can lead to compromised model integrity, exposure of sensitive training data, and unpredictable model behavior that violates compliance requirements. Organizations must implement AI security measures to ensure their systems remain trustworthy, maintain regulatory compliance, and protect intellectual property and customer information from emerging threats specific to machine learning environments.

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ResearchGlobal2026-05-06

AI Governance Gaps Persist Across Global Enterprises, Cloud Security Alliance and Google Find

The Cloud Security Alliance, commissioned by Google, released 'The State of AI Security and Governance,' a data-driven research report examining how enterprises are adopting generative and agentic AI. The report documents significant gaps in AI governance maturity, security integration practices, and data exposure controls across global organizations. It also finds that multi-model AI strategies are concentrated among a small number of providers, and that security teams are among the earliest enterprise adopters of AI in cybersecurity workflows.

Cloud Security Alliance Google AI governance AI security enterprise risk data exposure generative AI agentic AI risk management transparency