Cognizant announced June 18 that ServiceNow AI Agents now interoperate with the Cognizant Neuro AI Multi-Agent Accelerator, creating a single orchestration layer for enterprises to coordinate AI agents across ServiceNow, custom-built systems, and third-party platforms. For customer support teams running workflows across multiple tools, the integration eliminates the manual connectors and piecemeal coordination that have kept agents from different vendors siloed.
AI agents from separate providers have largely operated in isolation, each demanding its own integration path. The Neuro AI Multi-Agent Accelerator changes that by bringing them into one environment where cross-platform workflows can run with less manual intervention. ServiceNow AI Agents can now participate in broader, automated processes that span the systems enterprises already use.
"Multi-agent systems are the future of enterprise AI," said Babak Hodjat, Chief AI Officer at Cognizant. "The value is in networks of agents working together rather than any single agent, platform or vendor. By bringing ServiceNow's AI agents into the Neuro AI ecosystem, our joint customers can build end-to-end, cross-platform AI workflows that drive real business outcomes at enterprise scale."
How the orchestration works
The integration uses the Model Context Protocol (MCP), an open standard that ServiceNow supports, so Neuro AI can discover and invoke ServiceNow AI Agents without custom connectors. New agents register automatically as they come online, and Neuro AI maps each request to the right agent in real time. The same approach extends to other third-party agent systems, with all activity operating within ServiceNow's existing access controls and audit logging.
Teams can stand up working multi-agent pipelines quickly. One path is generating an agent network from a prompt for a specific use case. Another is pulling from Neuro AI's library of prebuilt agent networks covering sales, finance, supply chain, customer service, and other domains. The accelerator is open source and available at github.com/cognizant-ai-lab/neuro-san-studio.
What industry analysts are seeing
IDC research shows that more than 70 percent of enterprises expect to invest in prebuilt standalone AI agents, custom agents, and agents embedded in existing software applications. "As a result, enterprises are best supported by an agent orchestration framework like Cognizant's Neuro SAN AI that enables organizations to manage and orchestrate agents in one place," said Jason Bremner, Research Vice President at IDC. "Cognizant's Neuro AI Multi-Agent Accelerator now allows customers to orchestrate ServiceNow agents, a big benefit given ServiceNow's popularity for managing IT and business process workflows. Customers can orchestrate ServiceNow agents through Neuro AI Multi-Agent Accelerator without costly integrations or custom connectors."
Amit Zavery, President, Chief Product Officer and Chief Operating Officer at ServiceNow, described the direction plainly: "The future of agentic AI is orchestrated, governed networks of agents working securely across the enterprise to coordinate work that once took complicated systems and manual overrides to achieve. By combining ServiceNow's AI agents and orchestration capabilities with Cognizant's Neuro AI Multi-Agent Accelerator, customers can connect data, AI and workflows across their business with context and control."
For support organizations already using ServiceNow for case management and IT workflows, the integration means those agents can now act inside larger, coordinated workflows that span other platforms. End-to-end processes that once required significant engineering effort can be configured to run across systems without custom connectors. This approach to AI Agents & Automation reflects a broader shift toward orchestrated networks rather than standalone deployments.
Why this matters for customer support teams
Customer support operations rarely live inside a single platform. Teams juggle ticketing systems, knowledge bases, CRM tools, and communication channels. When AI agents in each of those systems operate independently, the result is still a patchwork that requires human coordination. The Neuro AI Multi-Agent Accelerator gives support leaders a way to orchestrate agents across those boundaries. Prebuilt agent networks for customer service mean teams can start with patterns that already map to common support workflows-routing, escalation, knowledge retrieval, and post-resolution follow-up-then adapt them. The open-source nature of the accelerator also means in-house teams can inspect and modify the orchestration logic rather than treating it as a black box. For professionals building or managing AI for Customer Support Courses, this shift toward multi-agent coordination changes what skills matter: less focus on individual agent configuration, more on designing workflows where agents from different vendors collaborate to resolve a case from end to end.
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