AI has passed the point of simply helping IT professionals get work done faster. Now AI agents can triage incidents, fulfill service requests, diagnose outages, and sometimes take action to resolve issues autonomously.
Deploying AI agents across IT operations can be relatively straightforward. The harder part is deciding which actions to delegate to AI, how much authority agents should have, and when people need to step in.
ServiceNow partners help organizations make these decisions. They point to some practical tips for enabling AI agents to act more autonomously across the IT ecosystem.
Wherever a team starts, the first step is to clearly define the purpose: the specific IT problem it wants to solve, such as faster resolution or fewer repeat incidents. Autonomy follows from that.
“It’s important to remember the objective and not get lost in the investments of the technology,” says Saurabh Singh, director of presales and technical lead at ServiceNow partner Fujitsu.
A good place to begin is in recurring IT processes where the desired outcome is clear and the path to resolution is well understood. Service requests, recurring incidents, and repeatable remediation can give IT teams practical opportunities to test whether AI can successfully diagnose issues and autonomously resolve them.
ServiceNow partner Capgemini worked with a grocery retailer on a multi-agent autonomous solution to address a recurring problem: malfunctioning cash registers. An agentic AI system now handles cash register errors automatically. Approximately 25% of cash register outages are resolved with zero touch. For an additional 35%, time to resolution has dropped significantly.
It’s important to note that autonomy isn’t always the right solution. Existing architecture, workflows, and AI maturity set the enterprise baseline, but each IT process must also be ready for agentic execution.
In the cash register example, for instance, stores were seeing a significant volume of recurring errors with a clear outcome, and AI agents could draw on a well-maintained knowledge base to solve problems. When a process isn’t ready, flows and scripted automation can lay the necessary foundation for deploying agents later.
ServiceNow partner Crossfuze observes that many of its customers aren’t at the right maturity level for agentic workflows. They lack well-defined processes and a well-maintained knowledge base for AI to draw on. As a result, they often focus on deploying virtual agents or standard scripted workflow automation.
“The flows and scripts that we build out will serve as the tools that we will use in agentic capabilities down the line,” says Oliver Nowak, AI practice lead at Crossfuze.
Identifying the cause of an incident, initiating remediation, and making a configuration change each carry a different level of risk. As AI is assigned more work across IT operations, organizations must decide how much authority it should have and when it’s authorized to act.
AI agents deliver the best outcome when workflows are clear, permissions are explicit, and rules define what actions they can take without a human in the loop. Capgemini recommends defining confidence thresholds for autonomous action to decide when a person needs to step in and when AI can act independently.
Understanding the environment AI operates in also helps organizations set effective boundaries. Before customers add more AI, ServiceNow partner Plat4mation assesses their existing processes and how they use the ServiceNow AI Platform. The assessment flags problems to fix before granting greater autonomy and shows where autonomous action makes sense.
Centralizing governance can provide better control as more AI agents are added to the IT ecosystem. Fujitsu stresses the importance of using a platform that provides visibility and governance over agents.
ServiceNow Super Intelligence Control Tower can help IT leaders understand how often AI is being used, where it’s useful, and what its return on investment is. That oversight also helps keep autonomous action aligned with company priorities and customers’ interests.
Expanding autonomy too quickly introduces unnecessary risk, so it's important not to hand AI every IT task or decision at once. Let it prove it can handle defined work within specific boundaries. As confidence builds and outcomes are validated, extend its authority deliberately, one process at a time, and always within clear limits.
As autonomy frees employees from repetitive, draining tasks, leaders can evaluate what new value those employees can create. Imagine a cashier with fewer register outages to work around, supported by contextual intelligence that suggests products based on a customer’s basket.
Find out how ServiceNow can help you stay ahead of business needs with autonomous IT.
