Omnissa has launched Elara, a new AI governance platform designed to detect and control unauthorized AI applications operating across enterprise networks, alongside three new AI agents that automate IT troubleshooting and patching. The announcements, detailed in a recent company release, target what the company calls "shadow AI"—artificial intelligence tools, models, and agents that employees use outside approved policies—while creating opportunities for managed service providers to expand into AI oversight and automated IT management. Elara, now available in beta, gives IT and security teams visibility into how digital work tools are deployed throughout their organizations, enabling them to apply policies informed by broader business context.
The new Elara platform offers several core capabilities for managing enterprise AI activity. It provides shadow AI detection that discovers AI applications, large language model systems, agents, and other tools operating across the enterprise, including technology outside approved policies or standard application inventories. The platform features an AI Gateway that governs how users, applications, and agents access AI models, with the ability to authorize model access, apply usage guardrails, and meter token consumption across providers. Elara also includes change management capabilities that evaluate modifications against conflicts, freezes, and dependencies before execution, either clearing the action, binding it, or routing it to the appropriate approver. The system records the full decision chain in real time, including what occurred, who authorized it, and what it affected, to maintain an audit-ready record. Separately, Omnissa introduced three new IT agents: a Digital Employee Experience agent that helps investigate employee experience issues and recommends resolutions, a Workspace ONE Vulnerability Defense agent that autonomously reviews and prioritizes vulnerabilities while preparing patching actions, and a Windows App Lifecycle agent that packages and tests applications before presenting them to administrators.
"Elara, which is now in beta, gives our partners an opportunity to address a challenge that is quickly becoming a priority for enterprises: understanding and governing the AI applications, models, and agents showing up across their organizations," Renu Upadhyay, chief marketing officer at Omnissa, told Channel Insider. According to Upadhyay, managed service providers can now shift from managing employees' devices to running secure environments where people and AI agents work together. The company also announced Omnissa Cloud PC, a turnkey cloud PC service that includes underlying compute along with unified endpoint management and Horizon Cloud DaaS services, initially running on AWS with additional hyperscaler options planned, and Horizon Delegate, a new agent for Horizon virtual desktop users that operates as a co-pilot and can continue working when the user isn't actively connected.
The announcements highlight an emerging opportunity for managed service providers to expand beyond traditional endpoint management into AI governance and oversight. As AI agents become more embedded in business environments, the report explains, customers will need help understanding what those tools can access, what actions they can take, and how to keep them operating securely. AI-driven troubleshooting and remediation could allow MSPs to support more customers without proportionally increasing staffing, though providers will need to demonstrate value through business outcomes rather than ticket volumes. "Customers aren't necessarily interested in how many tickets an MSP resolves," Upadhyay said. "They want fewer disruptions, better employee experiences, and stronger security." The opportunity could be particularly significant for smaller MSPs serving small and medium business customers that lack dedicated security teams, as automation could help these providers deliver more sophisticated services with limited staff. "AI and automation won't eliminate the need for expertise, but they let smaller providers compete based on the quality of their service, not the size of their business," Upadhyay noted. Providers that position themselves as strategic partners in AI adoption—defining policies and boundaries for AI agents while preventing problems proactively—may find recurring revenue streams that replace traditional break-fix models. The success of this shift will likely depend on whether service providers can translate technical automation into demonstrable improvements in employee experience and risk reduction.