The ASEAN digital economy is set to approach nearly $1 trillion by 2030, highlighting the urgent need for robust data protection measures. Countries in the region, including Indonesia and Vietnam, are enhancing their legal frameworks to secure citizen data and attract investment, while Singapore leads with its advanced AI governance initiatives.
This article outlines the specific cybersecurity requirements outlined in the EU AI Act for high-risk AI systems, which become enforceable in August 2026. Key requirements include documented risk management systems, data governance protocols, and the necessity for human oversight to ensure accuracy and robustness throughout the AI lifecycle.
This article clarifies the differences between AI governance and information security (InfoSec), emphasizing the need for both a secure framework and responsible operational guidelines in AI initiatives. It highlights the importance of integrating AI governance with InfoSec to manage risks effectively, ensuring that AI systems are not only secure but also ethical and compliant.
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.
Deepfake technology has evolved into a significant threat, necessitating operational readiness and governance mandates for enterprises to combat risks such as fraud and reputational damage. As regulations tighten globally, organizations must integrate detection capabilities to maintain trust and compliance in the digital age.
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.
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.
Agentic AI is revolutionizing cybersecurity by autonomously analyzing threats and automating responses, significantly enhancing efficiency in the face of rising cyber threats. However, the autonomy of these systems introduces new vulnerabilities, necessitating robust governance to balance their benefits and risks.
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.