The EU AI Act introduces a comprehensive legal framework for regulating artificial intelligence, focusing on safety, transparency, and public trust. It categorizes AI systems by risk level, establishing specific obligations for organizations operating within the EU or selling AI-based products to ensure compliance and accountability.
AI coding tools like GitHub Copilot significantly enhance productivity but introduce serious security risks, including phantom dependencies and vulnerable code. Without proper governance and validation, organizations may face unseen threats and accumulating technical debt.
As enterprises increasingly integrate AI capabilities into their operations, they must address the evolving risks associated with cybersecurity. A comprehensive approach that unifies AI security with traditional enterprise cybersecurity practices is essential for mitigating these threats while ensuring the trustworthiness of AI systems.
In the era of rapidly advancing AI technologies, organizations are increasingly adopting AI Security Posture Management (AI-SPM) solutions to protect sensitive data and ensure regulatory compliance. This article outlines five critical questions organizations should consider when selecting an AI-SPM solution to effectively manage risks and enhance security.
A recent report highlights that AI adoption in enterprises is significantly outpacing data governance, leading to serious security and privacy concerns. With many organizations lacking real-time monitoring and effective controls, AI is over-accessing sensitive data, which can result in regulatory violations and data breaches.
As AI and machine learning evolve, they are reshaping the landscape of cybersecurity, introducing both new threats and opportunities for defense. Organizations must adapt to these changes by integrating AI into their security strategies while developing robust governance frameworks to mitigate the risks associated with generative and agentic AI.
A new report warns that the U.K. government lacks the necessary emergency powers to respond effectively to AI-enabled disasters, such as critical infrastructure disruptions or terrorist attacks. It calls for giving officials the authority to compel tech companies to share information and restrict public access to AI models during emergencies.
Generative AI security requires strong governance from the C-suite to mitigate risks such as data breaches and compliance failures, making it a boardroom imperative. As organizations rapidly adopt generative AI, they must prioritize security measures to prevent unauthorized tools and ensure proper oversight.
This guide offers a framework for CISOs to secure AI agents and non-human identities as they become integral to enterprise environments. It highlights the need for AI Identity Governance (AI-IG) to address the security risks posed by these autonomous digital workers.
The rise of “shadow AI” refers to the unsanctioned use of AI tools by employees, which poses significant risks for organizations regarding security and compliance. A recent report indicates that 90% of IT leaders are concerned about these unauthorized practices, leading to potential financial losses and data breaches.