ServiceNow has already delivered thousands of AI agents; when customers deploy them along with third-party and custom-built agents, management and interoperability challenges can arise.
To address those challenges, ServiceNow is rolling out a wave of agentic management and control technology at Knowledge25 including:
- AI Agent Fabric for native interactions with other systems
- AI Workflow Data Network, leveraging alliances with 100 prominent data partners to ensure cohesive access to, and views of, enterprise data
- AI Control Tower for governing and managing agents at enterprise scale
The company’s overarching goal, according to Chief Innovation Officer Dave Wright, is to help customers unify a wide range of AI agents, data, and workflows on one platform. “It should be any agents in any workflow for any industry, on any cloud with any data, all on one platform,” Wright said in a briefing previewing the Knowledge25 announcements.
This analysis provides details into the new products outlined above, as well as enhancements to the company’s CRM software.
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AI Agent Fabric
ServiceNow executives referred to AI Agent Fabric as a “dynamic connected layer” that’s built to enable customers’ AI agents to natively interact with ServiceNow and third-party systems — while also enabling those agents to communicate, coordinate, and learn from each other.
AI Agent Fabric standardizes communication from agent to agent, orchestrator to orchestrator, and agent to other software and tools for timely exchange of information, according to Dorit Zilbershot, Group Vice President, Product Management, AI Experiences & Innovation at ServiceNow.
Providing an example of how AI Agent Fabric will help customers, Zilbershot described an e- commerce system running on Microsoft Azure infrastructure that experiences downtime and therefore must be restarted.
Resolution requires interaction between ServiceNow and Azure AI agents, with the Microsoft agents ultimately initiating testing, diagnostics, and a restart of the service. “I still need to, as a human, as a support agent, approve the restart of that service, so nothing bad is going to happen,” she explained. “So I can click on restart and just like that, the Azure AI agent starts doing the work.”
To ensure interoperability between agents, ServiceNow is working to support Google and its Agent 2 Agent (A2A) protocol, as well as the widely embraced Model Context Protocol. “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, noting that as an open platform, AI Agent Fabric will provide connectivity on an agnostic basis.
AI Workflow Data Network
This network of 100+ software partners is key to ensuring the value and impact of initiatives including AI Agent Fabric, as ServiceNow and its partners will collaborate to connect their AI systems and tools. The network will make data actionable across interconnected systems from partners including Microsoft, Google, Oracle, Databricks, and Snowflake, to name a few key enterprise software players that are part of the data network ecosystem.
ServiceNow demonstrated the power of the Workflow Data Network, which taps into the underlying Workflow Data Fabric it introduced last year. In the demo, a data analyst or user seeking inventory data made a request without needing to know where the data resides. Workflow Data Fabric connects to the right systems while helping the user retrieve the data, understand the context, and automate action.
“We are hiding the complexity of that data, setup, mapping, and understanding, all behind the scenes using Workflow Data Fabric and Workflow Data Network,” said Amit Saxena, Vice President and General Manager of Workflow Data Fabric at ServiceNow. “Because customers really care about outcomes…So workflow Data Fabric enables you to connect, understand, and take action.”
AI Control Tower
Responding to the burgeoning presence of AI and agents in the corporate software stack, AI Control Tower gives visibility into all of an enterprise’s AI assets, with views tailored to the function and responsibility of an individual — CIO, CFO, CHRO, and so on. They can gain insights including:
- Number of users onboarded by AI application
- Number of users by department
- Risk and compliance factors
The user can start at a high-level overview of systems then drill down into individual AI assets to understand systems by provider, by type, and by department. The control tower software also enables customers to arrive at a value metric to quantify the benefits from AI software.
The AI Control Tower discovers non-ServiceNow agents through use of the company’s Configuration Management Database (CMDB) as the system of record where customers register third-party agents; CMDB serves as the AI inventory data model.
CRM Upgrades and ServiceNow Lens
With its CRM software, ServiceNow aims to provide 360-degree customer views across channels while also orchestrating the most difficult part of customer interactions: resolution and fulfillment, whether that pertains to a dispute in banking or managing a manufacturing recall.
A demo of ServiceNow CRM showed how the software supports customers through sales and order management, field service management, and industry extensions. This would come into play in a scenario where AI agents identify a telco outage and initiate a series of tests to determine whether a human needs to be dispatched on-site. A person is required to confirm that step, including initiating a field service work order.
The company’s product rollouts at Knowledge25 also include ServiceNow Lens, which uses natural language prompts to understand on-screen data and move end users into the ServiceNow platform without requiring them to enter data, accelerating their ability to understand and use data in an AI context.
Closing Thoughts
With its AI Agent Fabric, Workflow Data Network, and AI Control Tower, ServiceNow embarks on an ambitious plan to deliver maximum AI-driven automation by orchestrating agent connections and actions through the broadest possible range of systems and platforms. This inclusive approach is necessary to fully leverage agentic AI’s promise because customers have multi-vendor software stacks that could otherwise serve as barriers to fully capitalizing on AI.
With its new and existing software, ServiceNow is delivering on this agenda across data, AI, and workflows. “All those three pieces come together, and that’s how you make sure you have high-quality agentic AI in the enterprise,” Zilbershot concluded.
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