NVIDIA and ServiceNow Partner on New Autonomous AI Agents for Enterprises
Source: NVIDIA AI Blog
The Next Phase of Enterprise AI
Early agent systems have shown what’s possible—moving beyond simple prompts to tackle complex tasks. The next step is to embed those capabilities into enterprise environments, where agents must operate with context, control, and consistency across real workflows.
At ServiceNow Knowledge 2026, NVIDIA founder and CEO Jensen Huang joined ServiceNow chairman and CEO Bill McDermott in the opening keynote to discuss this evolution.
A Full‑Stack Collaboration
The two companies are expanding their partnership across the entire stack:
- Specialized autonomous AI agents that are safe and easy to adopt.
- Powered by NVIDIA accelerated computing, open models, domain‑specific skills, and secure agent‑execution software.
- Integrated with ServiceNow Action Fabric (workflow context) and ServiceNow AI Control Tower (governance).
Introducing Project Arc
Project Arc is a long‑running, self‑evolving autonomous desktop agent designed for knowledge workers, including developers, IT teams, and administrators.
What sets Project Arc apart?
- Native connection to the ServiceNow AI Platform via ServiceNow Action Fabric.
- Provides governance, auditability, and workflow intelligence for every action the agent takes.
- Can access local file systems, terminals, and installed applications to complete complex, multistep tasks that traditional automation can’t handle—with the controls enterprises need to deploy AI at scale.
Core Requirements for Autonomous Agents
- Open models & domain‑specific skills – customizable to each organization’s needs.
- Robust security – agents act without exposing sensitive data or systems.
- Efficient tokenomics – powered by AI factories that optimize token usage.
Learn more about tokenomics: AI Tokens Explained (NVIDIA Blog)
Secure Execution with NVIDIA OpenShell
Project Arc runs on NVIDIA OpenShell, an open‑source, secure runtime that enables autonomous agents to operate in sandboxed, policy‑governed environments.
- Enterprise‑grade control: define what an agent can see, which tools it may use, and how each action is contained.
- Collaboration: ServiceNow is both building on and contributing to OpenShell, advancing a common foundation for secure agent execution.
Executive Perspective
“Project Arc represents the next step in our ongoing collaboration with NVIDIA, bringing autonomous execution to the desktop,” said Jon Sigler, Executive Vice President and General Manager of AI Platform at ServiceNow.
“By combining OpenShell’s runtime layer with ServiceNow AI Control Tower, and powered by ServiceNow Action Fabric, we’re delivering the governance and security that enterprise AI requires.”
Open Models and Agent Skills Scale Enterprise AI
Enterprise AI must be adaptable to meet the unique needs of each organization. NVIDIA and ServiceNow are creating an open ecosystem that lets companies tailor models and applications to their specific domains and data.
Key Components
| Component | Description | Links |
|---|---|---|
| NVIDIA Agent Skills | Specialized agents (e.g., ServiceNow AI Specialists) that deliver targeted capabilities across enterprise workflows. | — |
| NVIDIA AI‑Q Blueprint | A blueprint for building deep‑research agents that can gather context, synthesize information, and support complex decision‑making. | AI‑Q Blueprint |
| NVIDIA Agent Toolkit | A collection of open models and building blocks—including NVIDIA Nemotron—for creating customized AI applications. | Nemotron |
| NOWAI‑Bench | An open benchmarking suite for enterprise AI agents, integrated with the NVIDIA NeMo Gym library. | — |
| EnterpriseOps‑Gym | One of the industry’s most challenging enterprise‑agent benchmarks; Nemotron 3 Super currently ranks #1 among open‑source models. | EnterpriseOps‑Gym |
Why These Elements Matter
- Real‑World Performance: NOWAI‑Bench evaluates multistep workflows—the scenarios where enterprise AI systems most often stumble.
- Reliability in Production: By focusing on end‑to‑end processes rather than isolated tasks, teams can build agents that behave predictably in live environments.
- Open Ecosystem: All tools and benchmarks are openly available, encouraging collaboration and rapid iteration across the AI community.
Bottom line: Leveraging NVIDIA’s open models, toolkits, and benchmarking suites enables ServiceNow (and other enterprises) to create highly specialized, reliable AI agents that scale with business needs.
Efficient AI Factories
As AI agents become long‑running and always‑on, scaling them across millions of workflows requires not just capability but efficiency—making token economics central to enterprise AI.
NVIDIA AI factories are built to deliver the lowest‑cost, most‑efficient tokenomics for production AI. The NVIDIA Blackwell platform provides >50× greater token output per watt than NVIDIA Hopper, resulting in ≈35× lower cost per million tokens. For enterprises running agents across millions of workflows, that efficiency can determine how quickly AI moves from pilots to broad production use.
ServiceNow AI Control Tower integrates with the NVIDIA Enterprise AI Factory validated design, extending governance and observability to large‑scale AI workloads. With added agent‑observability capabilities, organizations can:
- Monitor agent behavior in real time
- Manage AI systems across the full lifecycle—from deployment to optimization
AI is becoming a new way that work gets done. What’s changing now is that the core pieces required to deploy it at scale—capable agents, built‑in guardrails, and proven performance—are all coming together.
The companies that move fastest will be the ones that give agents:
- The infrastructure to act
- The context to make decisions
- The governance to keep every action accountable
NVIDIA and ServiceNow are making this a reality for the world’s enterprises.