ServiceNow Launches a Control Tower for AI Agents
LAS VEGAS — Given that ServiceNow is, at its core, all about automating workflows for enterprises, it’s no surprise that the company has gone all-in on AI agents. At its Knowledge 2025 conference in Las Vegas, the company is launching new tools for managing and connecting AI agents across the ServiceNow platform and third-party services, as well as a more powerful version of its Apriel Nemotron model for building agentic systems.
ServiceNow’s (and NVIDIA’s) New Reasoning LLM
The Apriel Nemotron 15B model, which is based on NVIDIA’s recently launched Nemotron family and which ServiceNow is releasing in partnership with NVIDIA, is a reasoning model trained using NVIDIA’s NeMo framework. ServiceNow used NVIDIA’s Nemotron post-training dataset and its own domain-specific data to train the model.
Previously, ServiceNow launched two smaller 5B models in its Apriel family, which performed roughly on par with Llama 3.1 8 B. ServiceNow and NVIDIA say they will expand on their existing partnership and continue to co-innovate with these models and bring accelerated computing to other parts of ServiceNow’s stack.
“With this new Apriel Nemotron 15B reasoning model, we’re powering intelligent AI agents that can make context-aware decisions, adapt to complex workflows, and deliver personalized outcomes at scale,” said Jon Sigler, EVP of Platform and AI at ServiceNow. “But the model is just one part of the innovation. Our collaboration building a data flywheel — powered by Workflow Data Fabric and NVIDIA NeMo — enables a virtuous cycle of learning and improvement. This helps us build AI agents that are contextually aware, deeply personalized, and aligned to the real-time needs of the enterprise.”
The new model will become available in the second half of the year, which is likely why ServiceNow hasn’t released any detailed benchmarks yet beyond saying that the model shows “promising results for the model’s size category, reinforcing its potential to power agentic AI workflows at scale.”
Agent Fabric
The fact that ServiceNow is focusing so acutely on agents is no surprise. They do, after all, promise to make it easier to build complex automated workflows and extend upon what previous automation frameworks were able to achieve.
ServiceNow and others are already talking about how these agents are now essentially company employees, but just like employees sometimes have to talk to people outside of their own company, many agents, too, will need ways to interact with other agents across company silos. Various protocols and frameworks like the Google-backed Agent2Agent (A2A) and Cisco-backed AGENTCY with its Agent Connect Protocol are looking to tackle this problem — and vying to become the de facto standard for agent-to-agent communication.
Today, ServiceNow is launching its AI Agent Fabric, which was built upon Google’s A2A and Anthropic’s Model Context Protocol (MCP). The idea here is for the Agent Fabric to act as “the communication backbone for entire AI ecosystems — enabling native collaboration between agentic systems,” as the company describes it. It supports agent-to-agent, agent-to-tool and agentic system-to-agentic system communication using A2A and MCP.
“If you look at the true vision of agentic AI, it’s the capabilities to be able to stitch multiple agents together, to be able to take an action,” ServiceNow’s Chief Innovation Officer Dave Wright said during a press conference ahead of today’s announcement. “And the one thing the ServiceNow platform is really good at is being able to take that logic and then be able to apply action to that logic — and no one else does that, all sitting within one platform.”
As Dorit Zilbershot, ServiceNow’s Group Vice President of AI Experiences and Innovation, noted, the focus here is more on the capabilities the Agent Fabric enables than the protocols themselves.
“At this point, we really look at ourselves as an open platform, and we will be able to support all the common protocols that are available out there and make sure that our customers can benefit from all these great innovations,” Zilbershot said when asked how Agent Fabric is different from similar projects. “So if a system is only supporting a specific protocol, that should not block our customers, we’ll still be able to connect with that system — and that’s why it’s a Fabric. It really includes everything.”
Some of the partners involved in today’s announcement include Accenture, Adobe, Box, Cisco, Google Cloud, IBM, Jit, Microsoft, Moonhub, RADCOM, UKG, and Zoom, who will make Agent Fabric integrations available for their customers.
At the core of ServiceNow’s plan here is, of course, to get enterprises to use its AI agents in concert with third-party agents across this partner ecosystem.
“To unlock maximum business value, AI agents must operate seamlessly across diverse applications, data, and clouds,” said Rao Surapaneni, VP, General Management, Business Applications Platform at Google Cloud. “Our collaboration with ServiceNow empowers customers to unify AI agents across their entire IT estates, speeding up business decisions with tools like ServiceNow’s new AI Agent Fabric.”
A Control Tower for Agents
As part of today’s announcement, ServiceNow is also launching what it calls the AI Control Tower, which takes the company’s previously announced AI Agent Orchestrator and extends it to include monitoring, compliance and governance, lifecycle management and more. As the name implies, it’s a centralized command center for managing agents from ServiceNow and third-party AI agents, models and workflows, bringing all of them under a single umbrella.
“With AI Control Tower, businesses can oversee AI workforces in the same way the human workforce is managed, ensuring each agent is aligned, coordinated, optimized, and delivering impact at scale,” said Amit Zavery, president, chief product officer, and chief operating officer at ServiceNow.
Most enterprises are still in the process of figuring out how they can extract value from AI and many aren’t even thinking about agents yet. At first glance, this question of how multiple agents will operate across platforms may seem premature. Yet, the number of companies that are putting agents into production is growing rapidly.
ServiceNow, in its recent Enterprise AI Maturity Index, says that 55% of organizations using agentic AI have improved their gross margins, compared to 22% of those who are merely considering using this technology. The company isn’t necessarily a neutral player, but despite a steady undercurrent of AI skepticism among many technologists, it’s exactly the kind of workflow automation tools like ServiceNow that stand to benefit from putting agents into production.
