ServiceNow has achieved a significant milestone in handling its own employee IT requests, with 90% of them being resolved autonomously, resulting in a 99% faster resolution rate compared to human agents. The company has now announced its plans to offer this capability to other enterprises through its new product technology.
According to ServiceNow, many organizations have been struggling to implement autonomous IT request handling due to governance and workflow continuity issues, rather than capability. The company’s solution, called Autonomous Workforce, includes a new employee-facing product called EmployeeWorks, built on its acquisition of Moveworks, and an underlying architectural approach called “role automation.” This approach treats AI as a worker operating inside workflows, rather than a feature sitting on top of them. ServiceNow has been building towards this for two decades, evolving from a ticketing system to a workflow automation engine, and layering AI onto that foundation through its Now Assist product.
The announcement has three key parts: ServiceNow EmployeeWorks allows employees to describe a problem in plain language and have it fixed without filing a ticket; Autonomous Workforce executes work end to end; and role automation is the architectural layer that governs how AI specialists operate inside existing enterprise permissions. ServiceNow is making a specific architectural bet about how to get to a point where AI can execute tasks autonomously, and it’s different from the agents most enterprises are already running. Bhavin Shah, founder of Moveworks and now SVP at ServiceNow, highlighted the problem of fragmented tools and disconnected AI experiences in many organizations.
ServiceNow is proposing a new architectural layer it calls role automation, which differs from conventional AI agents. With role automation, an AI specialist inherits permissions and governance rules, rather than reasoning its way into them. This approach creates a more secure and trustworthy AI system, as it cannot exceed its defined scope or self-escalate privileges. The company draws a three-tier distinction: task agents handle individual automation steps, agentic workflows mix deterministic and probabilistic execution, and role automation sits above both as a fully virtualized employee role with defined responsibilities and pre-inherited governance.
Alan Rosa, CISO and SVP of infrastructure and operations at CVS Health, has seen the importance of AI governance in healthcare. He emphasizes the need for responsible, explainable AI with clear guardrails and a focus on operational use cases with real ROI. Rosa’s approach requires governance to be embedded in the deployment architecture from the start, which is precisely the claim ServiceNow is making about role automation.
The implications of ServiceNow‘s announcement are significant for enterprises evaluating agentic AI. The key question is whether AI governance lives inside the execution layer or is sitting on top of it as a policy document. ServiceNow is trying to solve this problem by baking governance and workflow context directly into the agentic layer. For practitioners, the starting point is governance architecture, not capability. As Rosa said, “Scale and trust go together. If you lose trust, you lose the right to scale.”
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