The evolution of EUC: From static workloads to agentic AI

The digital workspace is undergoing an exciting transformation. For years, end-user computing (EUC) focused on delivering static desktops and core enterprise applications to remote employees. Today, as artificial intelligence (AI) becomes the operational core of modern business, virtual environments are evolving into dynamic, high-performance hubs where employees and autonomous agents co-work seamlessly.

As enterprises adopt agentic AI workflows, real-time collaboration tools, and local AI models, virtual workspaces require dedicated hardware acceleration. Equipping virtual environments with graphics processing unit (GPU) resources and accelerated computing unlocks key advantages:

• Dedicated developer sandboxes give developers and data scientists isolated, GPU-accelerated environments to build, test, and fine-tune AI models without risking local endpoint data exposure or host system conflict
• Seamless multitasking keeps user apps running at peak performance while background AI agents process complex workflows
• Instant local inference allows teams to run specialized large language models (LLM) and generative AI tools locally with near-zero latency
• Elevated experience & scalability deliver flawless graphics on any device while giving IT a flexible compute foundation to roll out future AI innovations

Modernizing and reshaping your virtual desktop infrastructure (VDI) into an agile, future-ready engine empowers both human talent and AI assistants to perform at their best.

A distinct synergistic partnership: Omnissa Horizon and NVIDIA vGPUA

NVIDIA and Omnissa have partnered to re-engineer how virtual environments scale, enabling enterprise IT to do more with less by maximizing their existing VDI investment. By pairing Omnissa Horizon with NVIDIA RTX Virtual Workstation, part of the NVIDIA virtual GPU (vGPU) software, and data center GPUs, the joint solution transforms virtual workspaces into an accelerated, cost-effective engine for human workers and AI agents alike.

This integrated solution addresses key strategic priorities across three critical pillars:

1. Unmatched performance for AI workloads: Offloading graphics rendering, video encoding, and AI matrix math directly to NVIDIA GPUs dramatically boosts host performance. This delivers the necessary compute density to run localized LLM inference, background agentic tasks, and modern collaboration tools concurrently without degrading the end-user experience.
2. Superior cost efficiency (optimized cost-per-token): Relying on public cloud AI application programming interfaces (API) or equipping every employee with a high-end physical AI PC quickly becomes cost-prohibitive. Shared GPU virtualization allows IT teams to slice physical GPUs across multiple virtual desktops and background agents, dramatically driving down the overall total cost of ownership (TCO) and cost-per-token for local model execution compared to standalone hardware or unconstrained cloud consumption.
3. Zero-trust security for AI assets: Running local AI models and agentic workflows on physical endpoints expose sensitive corporate data and intellectual property to risk. Omnissa and NVIDIA ensure that proprietary data, model weights, and sensitive enterprise prompts remain strictly isolated within the centralized, secure perimeter of the virtual data center.

Grounded customer outcomes: Driving workforce velocity and maximizing ROI

Consider a modern enterprise scaling AI capabilities across its entire organization, from customer service reps using live AI copilot assistants to autonomous agents running background analytics. Equipping thousands of employees with high-end physical AI laptops introduces high upfront hardware costs, prolonged deployment cycles, and underutilized compute assets outside of working hours.

By deploying the joint solutions from Omnissa and NVIDIA, enterprise IT replaces rigid physical infrastructure with dynamic, GPU-accelerated virtual workspaces. Knowledge workers gain immediate access to AI-assisted productivity tools, while background software agents receive the dedicated compute needed to process multi-step enterprise workflows seamlessly.

When employees log off at the end of the day, those same virtual GPU resources are automatically reassigned to run overnight batch processing or heavy background agentic tasks. This elasticity maximizes host density, eliminates hardware idle time, and dramatically lowers operational overhead while empowering both human workers and autonomous agents to operate at peak efficiency.

Living up to the Omnissa ONE 2026 theme

At Omnissa ONE 2026, the industry focus centers on a crucial premise: "Trust is built. Autonomy follows." As enterprises grant more operational freedom to both human employees and autonomous AI agents, IT leadership must first establish a predictable, secure, and observable infrastructure layer. You cannot trust an autonomous AI agent or an AI-assisted workflow if the underlying virtual environment suffers from lag, resource bottlenecks, or security blind spots.

By standardizing joint NVIDIA and Omnissa solutions, enterprise IT teams centralize GPU-accelerated workloads to gain total visibility and operational control. This trusted EUC layer makes workspace autonomy safe to scale, ensuring your digital workspace platform remains fast, secure, and ready to adopt whatever AI innovations emerge next. Adding GPU acceleration is no longer a luxury reserved solely for 3D CAD designers—it is the baseline required to future-proof your digital work foundation for everyday collaboration, local model execution, and agentic automation.

Visit the NVIDIA team at the Omnissa ONE 2026 Expo to see live product demonstrations of AI agent-assisted virtual workspaces and learn how to future-proof your existing infrastructure.