Like many enterprise application platform vendors, ServiceNow has been on a journey over the past year to bring the power of agentic AI to users.
The company first introduced AI agents in its Xanadu platform release in 2024, The initial release enabled companies to build, test and deploy generative AI skills and prompts that can be assigned to AI agents. Today ServiceNow is out with its latest platform iteration as part of the company's Zurich release.
The update, available to current ServiceNow customers bundled with certain plans, introduces three major capabilities designed to move enterprises from AI experimentation to production deployment: natural language app building through vibe coding, enterprise-grade AI security consoles and autonomous workflow automation.
The timing addresses a critical enterprise bottleneck. While companies have invested in AI pilots, many still struggle to scale these projects beyond individual departments. Gartner predicts 60% of enterprises will adopt AI agent development platforms by 2029. ServiceNow is positioning itself to capture this transition in a very competitive space.
Vibe coding not for hobbyists but for enterprise applications
Vibe coding has been an emerging paradigm over the past few years, enabling users to build entire applications with natural language prompts. Multiple vendors are in the space including Cognition, Bolt, Lovable and Replit. ServiceNow is now entering the space, with a specific focus on enterprise workflow application enablement.
ServiceNow's new Build Agent transforms simple English commands into production-ready enterprise applications. Tell it "create an onboarding app that assigns tasks to HR, IT and Facilities" and it builds the entire system in minutes.
Like other enterprise IT platforms, ServiceNow has had low-code capabilities for years, providing users with the ability to assemble applications without code. The new Build Agent is something a bit different.
Build Agent performs comprehensive testing, handles version control and ensures compliance with enterprise standards. Every application includes audit trails, security controls and governance checking built-in. The platform leverages ServiceNow's 20-year accumulation of enterprise workflow data. This institutional knowledge helps AI agents understand business context automatically.
"In a matter of minutes, the Build Agent not only got the requirements, looked through all the aspects of building, found the errors before deploying, debugged it and also pushed the app into production, " Jithin Bhasker, global vice president and general manager of creator workflows at ServiceNow explained during a demo with press.
New security consoles built for enterprise AI scale
Another common pitfall that can significantly impact enterprise agentic AI deployments is security. To that end, ServiceNow's Zurich release introduces two entirely new security consoles specifically designed for enterprise AI deployment.
The new Machine Identity Console monitors all API connections and automatically flags high-risk integrations. The system automatically flags accounts inactive for over 100 days and identifies weak authentication methods like basic authentication.
"Machine identity console identifies any high risk integrations and provides a guided experience for our customers to help them improve the security," Amanda Grady, vice president and general manager of AI platform security explained in a press briefing.
ServiceNow also launched the new Vault Console, which builds on vault capabilities the company introduced in its Tokyo release two years ago. The enhanced console uses AI to discover sensitive data across workflows and applies protection policies automatically
"Now not only do you have humans and machines accessing the data, but now we also have AI agents accessing the data," Grady said during the briefing.
These new security capabilities build on ServiceNow's existing AI Control Tower, which the company announced in May 2025. The Control Tower provides enterprise-wide visibility and governance for AI systems. The new consoles extend this governance specifically to API integrations and data protection.
ServiceNow treats AI agents as a distinct identity type requiring specialized protocols.
"We consider AI agents to really be a new type of identity, distinct from humans and distinct from machines," Grady noted.
Market position against platform giants
ServiceNow's unified approach directly challenges Microsoft and Salesforce's low-code and agentic AI tools.
The key differentiator is the platform itself and integration with the existing ServiceNow enterprise workflows. The company's 20-year accumulation of enterprise workflow data provides a significant competitive advantage and gravity for existing users.
This institutional knowledge helps AI agents understand business context automatically. The enhanced process mining identifies automation opportunities instead of requiring manual discovery.
"We want to make sure that all the inefficiencies the customers have today can be solved by agentic scenarios," Nirankush Panchbhai, Senior vice president of AI platform at ServiceNow commented during the press briefing.
Why this matters for enterprise strategy
ServiceNow's Zurich release forces a fundamental strategic choice: platform consolidation versus best-of-breed AI tools. The company is betting that enterprises will choose integration simplicity over vendor flexibility.
The evidence suggests this bet may pay off. Tasks requiring weeks of development work now complete in minutes, according to ServiceNow. More importantly, the platform eliminates the integration complexity that kills many enterprise AI projects before they reach production scale.
The strategic question for enterprises becomes: accept platform lock-in for operational simplicity, or maintain vendor flexibility while managing integration complexity internally? For most organizations struggling to move beyond AI pilots, ServiceNow's unified approach may prove decisive.
The market signal is clear. As Panchbhai noted, enterprises are "pivoting from legacy automations to proactive automations across all workflows." Organizations still building point AI solutions with tools from multiple vendors may find themselves architecturally disadvantaged if the industry consolidates around integrated platforms.