Agentic AI isn’t just the latest AI hype cycle, it’s real technology that can make a big difference for enterprise workflows. That’s the big bet that ServiceNow has been making and is now doubling down on in a bid to bring higher return-on-investment to enterprise AI efforts.
ServiceNow is in the business of enterprise workflow solutions, helping its over 8,000 global customers with all manner of processes ranging from human resources to IT service management (ITSM). Over the past two years, the company has been incrementally adding AI services through its Now Assist technology. In 2024 its first agentic AI services debuted, with a library of AI agents in the Now Assist Skill Kit. While the underlying technology is sophisticated, ServiceNow’s approach emphasizes invisible integration — AI agents working behind the scenes to enhance enterprise productivity without requiring direct user interaction.
So how do you make agentic AI even more useful? That’s where AI orchestration comes in.
Today ServiceNow is announcing its new AI Agent Orchestrator and AI Agent Studio, marking a significant shift from basic generative AI assistance to comprehensive, end-to-end task automation.
What the ServiceNow AI orchestrator is all about
The AI Agent Orchestrator is the “brain” that coordinates and manages the interactions between different AI agents to accomplish complex tasks. The AI Agent Studio is the development and management platform that gives customers the tools to create, deploy and maintain their own custom AI agents.
The company plans to release thousands of specialized AI agents designed to handle complex enterprise workflows across IT, HR and customer service functions.
Early adopters report significant efficiency gains, according to ServiceNow. One early user is achieving a 70% reduction in ticket resolution time — cutting average handling time from 30 minutes to seven to eight minutes. The key to getting a better outcome is to fully realize the promise of agentic AI. And the promise of agentic AI workflows isn’t about just using a single agent, but rather a series of them to achieve a business goal.
“You can have all these single AI agents being specialized in a specific task, but bringing in the AI agent orchestrator, it’s bringing order to the chaos,” Dorit Zilbershot, vice president of AI experiences and innovation at ServiceNow, told VentureBeat. “It’s making sure that there is some kind of supervision on all these AI agents and that there’s an understanding of what’s the end-to-end goal or business problem that we’re trying to solve.”
Why agentic AI needs more than just agents
There is no shortage of interest in agentic AI in 2025. Many large enterprise technology vendors including big players like Salesforce with its Agentforce platform and Microsoft have been emphasizing the technology.
ServiceNow isn’t all that different in recognizing the value of agentic AI for enterprises. Where it differs is in the application. ServiceNow is all about workflows for enterprise processes, which can often involve many different steps. An agent can help to automate components within a specific domain, while AI agent orchestration can coordinate multiple agents across domains in a complicated workflow.
An example of how the AI agent orchestrator can help with a complex enterprise workflow might be onboarding a new employee. This involves several steps and tasks that need to be coordinated, such as: setting up the employee’s IT accounts and equipment, enrolling them in HR systems and benefits, scheduling training and orientation sessions and granting access to necessary business systems.
With the AI agent orchestrator, ServiceNow can create a team of specialized AI agents to handle each of these tasks. For example, an IT agent would provision the laptop, an HR agent would enroll the employee in HR systems, and a training agent would schedule onboarding sessions.
The AI Agent Orchestrator coordinates the handoffs and communication between the agents. It understands the overall onboarding workflow, monitors progress and ensures all the necessary steps are completed successfully. If any issues arise, the orchestrator can troubleshoot, re-assign tasks, or escalate to human intervention as needed. The system also provides end-to-end visibility and management of the onboarding process.
How agentic AI orchestration works
The idea of chaining together different AI processes or LLMs is not new either.
There are technologies like LangChain that allow organizations to “chain” together multiple LLMs. There are also LLM router technologies that allow different queries to be routed. Zilbershot said that ServiceNow’s orchestrator is built entirely on its proprietary platform and is not relying on external frameworks.
She explained that the system incorporates both short-term and long-term memory capabilities. The memory helps to provide context for the AI agents.
Within the orchestrator platform there are also multiple types of models. The orchestrator uses larger language models for decision-making and planning. It then uses smaller LLMs for specific actions like summarization or email generation.
Agentic AI workflows need data
ServiceNow’s strategic positioning at the intersection of AI and enterprise automation hinges on data, and specifically the company’s Workflow Data Fabric.
The Workflow Data Fabric is a foundational technology for ServiceNow. It enables cross-system data access, consistent context maintenance, secure data handling across workflows and integration with existing enterprise systems.
“We want to drive agentic AI and conversational experiences across the board, and we’re driving everything with the Workflow Data Fabric at its core,” Zilbershot said. “We’re able to access any data systems as well as any systems for actions, and really create the single place where our customers can manage and orchestrate all their enterprise processes and workflows with the ServiceNow platform.”
Published by: Sean Michael Kerner
