As software development teams increasingly adopt AI-driven coding tools, there’s a parallel rise in governance measures to mitigate risks associated with shadow AI in the software supply chain. JFrog’s Shadow AI Detection tool provides essential visibility by inventorying internal AI models and third-party API access, thereby enhancing governance. Nightfall’s Data Loss Prevention platform aims to prevent sensitive data leaks into unauthorized AI tools through innovative classifiers and policies tailored for unique business needs. Palo Alto Networks, via its Prisma SASE services, focuses on securing data flows and monitoring both approved and unapproved generative AI applications. The shadow AI detection market is expanding, with other players like Netskope, BetterCloud, and Reco offering solutions to manage AI governance and security risks. Organizations are urged to establish clear policies and conduct regular audits to address shadow AI challenges effectively, ensuring a balance between innovation and risk management to protect data integrity.
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