ServiceNow plans automation of L1 Service Desk roles, promises more AI ‘specialists’ to come

ServiceNow plans to unleash the first member of its Autonomous Workforce, the Level 1 Service Desk AI specialist, next quarter.

The agent will autonomously diagnose and resolve common IT support requests such as password resets, provisioning of software access, and network troubleshooting. It will base its actions on information from enterprise knowledge bases, historical incident data, and defined workflows, and will be available 24/7, freeing humans to work on more strategic tasks as the agent executes mundane tasks with the scope, authority, and governance required for enterprise work, the company said.

ServiceNow is already using the agent internally, and claims that it is handling more than 90% of employee requests, and is almost twice as fast as human agents in performing these tasks, while still maintaining the necessary business context and governance required by an enterprise.

ServiceNow AI specialists like the Level 1 Service Desk agent are designed to work alongside humans, operating within a clearly defined scope governed by the same permissions that a human agent in that role would have.

“AI specialists, by default, cannot exceed their authority nor self-escalate permissions in memory based on the outcomes of reasoning that occurred during the first step of the AI powered decision and execution flow,” said John Aisien, SVP central product management at ServiceNow, during a media briefing. “Instead, these AI specialists ground decisions in live enterprise data, drawing in real time information about assets, access, ownership, real time permissions, and previous resolution patterns through our enterprise data foundation and our context graph.”

By combining probabilistic intelligence with deterministic workflow orchestration, ServiceNow said, the AI specialists can interpret requests, use business context to determine the right action to take, and execute that action while being overseen by ServiceNow’s AI Control Tower. They then notify the affected employee and update the knowledge base. And if they can’t resolve the issue, they pass it on to a Level 2 or Level 3 human agent for further investigation.

This is different to the historical approach. For the last two years, said Greyhound Research Chief Analyst Sanchit Vir Gogia, most vendors have competed on interface intelligence, with copilots summarizing, suggesting, and predicting. But, he said, “that phase is now saturated. What enterprises are evaluating in 2026 is whether AI can operate as a governed execution layer inside production workflows. Autonomous Workforce signals that ServiceNow understands this shift.”

This, he said, is architecturally meaningful: “AI … is being structured as a delegated participant in defined job roles. That changes accountability,” he said. “This is why ServiceNow’s emphasis on deterministic workflow orchestration is strategically aligned with enterprise demand. Models are probabilistic by design. Enterprises require outcomes that are predictable, auditable, and bound by policy.”

ServiceNow, however, didn’t say who would be accountable if one of its AI specialists went off the rails.

EmployeeWorks

ServiceNow also announced EmployeeWorks, available today, which it calls “a conversational front door to the enterprise.” It works as a personal assistant, pulling together conversational AI and enterprise search from Moveworks, which ServiceNow recently acquired, and from ServiceNow’s own unified portal and autonomous workflows, said Bhavin Shah, founding CEO of Moveworks and now general manager for Moveworks and AI at ServiceNow.

“Employees don’t need to know what agent to invoke, or where to go, or ask ‘should I use this system or that system?’” he said. “It just works.” The service supports protocols such as MCP and A2A to enable a “secure, scalable coordination between agents and business systems,” he said.

EmployeeWorks understands organizational structure, approvals, and authorization so it can execute tasks that require multi-system coordination, ServiceNow said, yet it can still maintain governance and audit trails. It can, for example, pull information from a document in SharePoint, then reference a Slack thread and pull together the information to create an action, or it can route and handle approvals, orchestrate workflows, or update systems, all while following enterprise policies.

Shah said EmployeeWorks is vendor-agnostic, can answer employee questions without them needing to switch to a different tool, and provides out-of-the-box integration and enterprise search.

Reservations about automations

Analysts approved of ServiceNow’s overall direction, but have reservations about the announcements.

Moveworks’ built-in governance mechanisms sound “amazing,” said Info-Tech Research Group Advisory Fellow Scott Bickley, but implementing EmployeeWorks will need considerable groundwork, including documenting workflows, updating knowledge bases, cleaning data and defining approval paths, with limitations and exceptions in place to cover all possibilities.

Gogia agreed. “ServiceNow is moving in the right direction because it is anchoring AI inside workflow control,” he said. “However, correctness of direction does not guarantee maturity of execution. The credibility of this strategy will be measured in regulated, exception-heavy, cross-system environments, not in idealized service desk queues.”

Moor Insights & Strategy Principal Analyst Melody Brue said, “the concern is that AI agents could become a new layer that routes around many of the apps people use today. ServiceNow aims to sit above that, coordinating agents and workflows across systems rather than just being another tool they might end up replacing.”

It’s no longer enough for AI to drive incremental efficiency, she said. Now, “it must help unlock value trapped in enterprise data and workflows. By tying AI into systems of record and orchestrated workflows, ServiceNow aims to move from static reports to agents that act on insights.”

Gogia takes it as a given that enterprises will adopt autonomous AI. The key question, he said, is whether they can govern it without destabilizing operational trust.

Another concern, said Bickley, is how enterprises will pay for it all. SaaS vendors each charge for AI services using their own variety of usage-based “AI credits”, but it’s difficult to accurately model and predict consumption of AI credits in a way that permits accurate budget forecasting, he said.

“There needs to be a clear path for legacy seat subscriptions to be migrated into AI credits,” Bickley said. “CFOs will not tolerate a variable pricing model that destroys budget predictability, and this pain point seems to go unaddressed by ServiceNow, and for that matter, the broader SaaS ecosystem as they double down on their aggressive AI launch initiatives.”