Combating IP Leaks into AI Applications with Free Discovery and Risk Reduction Automation

Combating IP Leaks into AI Applications with Free Discovery and Risk Reduction Automation

January 17, 2024 at 09:57AM

Wing Security introduces a free discovery and a paid tier for automated control over AI SaaS applications, aiming to enhance intellectual property and data protection. 83.2% of companies use GenAI applications, with 99.7% employing AI-powered SaaS. Their solution offers steps to Know, Assess, and Control AI risks while automating workflows for effective risk reduction.

From the meeting notes, it is clear that Wing Security has announced a new offering that includes free discovery and a paid tier for automated control over thousands of AI and AI-powered SaaS applications. This is aimed at helping companies better protect their intellectual property and data against the evolving risks of AI usage.

Wing Security’s research revealed that a high percentage of organizations use SaaS applications integrating AI capabilities, with a majority utilizing GenAI applications. However, the security implications of using these applications go unnoticed by both security teams and users.

The potential risks associated with data usage in AI-powered SaaS applications include data storing, model training, and human validation. To address this, Wing Security has introduced a solution that follows the “Know, Assess, Control” approach, enabling security teams to discover, assess, and manage the risks associated with AI-SaaS applications. By automating these processes, Wing Security aims to save time and reduce risks.

Furthermore, Wing Security’s automated workflows aim to facilitate better communication and collaboration between users and administrators of AI-SaaS applications, fostering a stronger security culture.

In summary, Wing Security’s new approach empowers organizations to navigate and control the increasing use of AI within their operations, while involving end users in the security process. The comprehensive understanding of how AI applications utilize organizational data and know-how allows for clear risk prioritization and user involvement.

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