Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Enterprise workers are eager to take advantage of AI tools — whether their employer likes it or not. This unapproved use, what’s known as shadow AI, is increasing dramatically: As much as 96% of the work employees do with AI is through non-corporate accounts. Whether done inadvertently or maliciously, this can leak an enterprise’s highly sensitive and proprietary data. Security platform Cyberhaven says it can solve this problem by tracking data lineage, or data lifecycles across different users and endpoints. The company has specific large lineage models (LLiMs) for this task, and today is announcing Linea AI, the next generation of it platform intended to help stop shadow AI and predict what flagged incidents may be most dangerous. “It manifests itself in this form of lineage: You understand where data is coming from, who has had access to it, across all the different endpoints, across all your users,” Nishant Doshi, Cyberhaven’s chief product and development officer, told VentureBeat in an exclusive interview. 90% reduction in incidents requiring manual reviewAccording to Cyberhaven’s analysis of the workflows of 3 million workers, AI usage grew 485% between March 2023 and March 2024, and employees are increasingly sharing sensitive data: Nearly 83% of legal documents and around 50% of source code, research and development materials and HR and employee records that employees share with AI are going to non-corporate AI accounts. To help prevent this unsanctioned use and protect sensitive company data, Linea AI uses an LLiM trained on billions of real enterprise data flows

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn MoreSecurity leaders and CISOs are discovering that a growing swarm of shadow AI apps has been compromising their networks, in some cases for over a year.They’re not the tradecraft of typical attackers. They are the work of otherwise trustworthy employees creating AI apps without IT and security department oversight or approval, apps designed to do everything from automating reports that were manually created in the past to using generative AI (genAI) to streamline marketing automation, visualization and advanced data analysis. Powered by the company’s proprietary data, shadow AI apps are training public domain models with private data.What’s shadow AI, and why is it growing?The wide assortment of AI apps and tools created in this way rarely, if ever, have guardrails in place. Shadow AI introduces significant risks, including accidental data breaches, compliance violations and reputational damage.It’s the digital steroid that allows those using it to get more detailed work done in less time, often beating deadlines. Entire departments have shadow AI apps they use to squeeze more productivity into fewer hours