Mitigating the hidden risks of Shadow AI

VentureBeat examines the risks associated with the unauthorised use of artificial intelligence (AI) tools and applications when organisations implement restrictive policies to block access. Such policies have proven ineffective, as they merely drive Shadow AI underground. Employees will find workarounds, whether through personal devices, private accounts, or screenshots, resulting in a critical lack of visibility for IT and security leaders. Moreover, as the article highlights, this approach stifles innovation while failing to manage cybersecurity and data protection risks.

The article outlines several key steps required to achieve effective mitigation, focusing on visibility, governance, and employee skills development. The first step involves gaining a complete understanding of AI usage within the organisation. From here, tailored policies should be developed, avoiding blanket bans in favour of context-aware controls. This could include browser isolation techniques to prevent sensitive data from being uploaded to public AI models or redirecting employees to sanctioned, enterprise-approved AI platforms. Next, robust data loss prevention (DLP) mechanisms are essential for identifying and blocking attempts to share sensitive information, serving as a safety net against accidental disclosure. Finally, comprehensive employee education is vital, providing practical guidance on responsible AI use and clear communication about the consequences of exposing sensitive data.

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