Netskope , a leader in modern security and networking, today released new research showing a 50 spike in genAI platform usage among enterprise end-users in the three months ended May 2025 . Despite an ongoing shift toward safe enablement of SaaS genAI apps and AI agents, the growth of shadow AI-unsanctioned AI applications in use by employees-continues to compound potential security risks, with over half of all current app adoption estimated to be shadow AI.
The new data was published within the companys latest Netskope Threat Labs Cloud and Threat Report . It examines the ongoing employee shift to genAI platforms, whether they are delivered from the cloud or on-premises, amid expansive interest to develop AI apps and autonomous agents, creating a new set of cybersecurity challenges that enterprises must address.
The Rise of genAI Platforms GenAI platforms, which are foundational infrastructure tools that enable organizations to build custom AI apps and AI agents, represent the fastest growing category of shadow AI given their simplicity and flexibility for users. In the three months ended May 2025 , users of these platforms increased by 50. GenAI platforms expedite direct connection of enterprise data stores to AI applications with the popularity in usage creating new enterprise data security risks that place added importance on data loss prevention DLP and continuous monitoring and awareness. Network traffic tied to genAI platform usage also increased 73 over the prior three month period. In May, 41 of organizations were already using at least one genAI platform. Approximately 29 of organizations are utilizing Microsoft Azure OpenAI, followed by Amazon Bedrock 22, and Google Vertex AI 7.2 respectively.
The rapid growth of shadow AI places the onus on organizations to identify who is creating new AI apps and AI agents using genAI platforms and where they are building and deploying them, said Ray Canzanese , Director of Netskope Threat Labs. Security teams dont want to hamper employee end users innovation aspirations, but AI usage is only going to increase. To safeguard this innovation, organizations need to overhaul their AI app controls and evolve their DLP policies to incorporate real-time user coaching elements.
The Many Facets of On-Premises AI Innovation From deploying genAI locally through on-premises GPU sources, to developing on-premises tools that interact with SaaS genAI applications or genAI platforms, organizations are evaluating many options to innovate quickly using AI, and, increasingly, they are turning to Large Language Model LLM interfaces.