As AI adoption accelerates across enterprises, employees are installing coding agents, desktop assistants, browser extensions, local models and other AI-powered tools without formal IT approval. This growing ecosystem of shadow AI creates new security and compliance challenges, particularly as organizations struggle to determine which tools are running, who is using them and what sensitive information they can access.
While traditional shadow IT was largely associated with unauthorized SaaS applications, AI introduces a more complex situation at the endpoint. AI agents and tools can interact directly with corporate systems, source code and sensitive data, often operating outside established security monitoring and governance processes.
Fleet Device Management aims to address this challenge by integrating AI governance directly into its existing device management platform, allowing organizations to oversee AI tools alongside software, vulnerabilities, browser extensions and developer applications.
Bringing AI Visibility and Governance to the Endpoint
Fleet’s new capabilities provide organizations with a centralized approach to managing AI adoption across their device fleets.
The platform introduces an AI inventory that identifies installed agents, tools, skills, plugins and MCP servers across operating systems, with filtering by publisher, version and device. Additional capabilities include tracking token usage and AI-related spending by user, tool and device, helping organizations understand adoption patterns and associated costs.
Fleet is also introducing AI session context visibility, enabling security and compliance teams to examine what information employees submit to AI tools and how those tools respond. This is designed to help identify potential exposure of customer information, corporate data and proprietary source code.
Rather than requiring a separate AI security product, Fleet integrates these capabilities with existing policies, reporting and remediation workflows. Organizations can identify unmanaged AI applications, enforce governance decisions and manage changes through infrastructure-as-code (IaC) and GitOps workflows, making actions reviewable, auditable and reversible.
Fleet’s open-source approach also provides transparency into the information collected by its endpoint agent. AI inventory and visibility are included in Fleet Free, positioning basic AI oversight as a fundamental component of modern device management.
“Every company we talk to has the same problem. They have dozens of AI agents running on employees’ laptops and no clear picture of what’s there, who’s using it or what data is moving through it,” said Mike McNeil, CEO and co-founder of Fleet. “Shadow AI shouldn’t require another point solution. You should govern your AI agents in the same place you govern your plugins, extensions, software and developer tools.”
Viktor Filipsson, Senior IT System Engineer at Sonos, emphasized the importance of endpoint-level oversight.
“Endpoints are where AI risk actually shows up,” Filipsson said. “You can’t govern what you can’t see. You need to know which AI tools and packages are running on your devices, what people are feeding them, and whether you can trust them.”
Fleet Announces Virtual Summit on the Future of Device Management
Alongside the AI governance launch, Fleet announced its first virtual summit, scheduled for November 10, 2026, at 11 a.m. ET.
The two-hour event will bring together IT, security, development and AI leaders from organizations including but not limited to Pinterest, Red Hat, Sonos, SandboxAQ, Proton, Block and Nubank.
Hosted by McNeil, the summit will examine the role of AI agents in device management, the adoption of infrastructure as code, the importance of open-source technologies and how enterprise device management could evolve by 2030.
For more information, visit Fleet Device Management. Registration for the Fleet Virtual Summit is available online.
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