Securing AI: The Rising Threat of Data Breaches

Rapid AI adoption presents significant security challenges, as these intelligent systems learn from, store, and potentially leak sensitive data.

A recent GenAI report highlights that a large majority of organizations have already experienced data breaches, indicating current security measures are insufficient for AI environments. 

This crisis is fueled by the exposure of sensitive data in AI models, the uncontrolled use of "Shadow AI" by employees, and the inadequacy of traditional security approaches. 

To address these vulnerabilities, organizations must adopt a data-centric security strategy embedded throughout the AI lifecycle, foster collaboration between IT and security teams, and invest in AI-specific security solutions to build resilience against inevitable breaches. Ultimately, integrating robust security measures is crucial for enabling sustainable AI innovation and reducing risk exposure.

Om Podcasten

Decoding AI Risk explores the critical challenges organizations face when integrating AI models, with expert insights from Fortanix. In each episode, we dive into key issues like AI security risks, data privacy, regulatory compliance, and the ethical dilemmas that arise. From mitigating vulnerabilities in large language models to navigating the complexities of AI governance, this podcast equips business leaders with the knowledge to manage AI risks and implement secure, responsible AI strategies. Tune in for actionable advice from industry experts.