ServiceNow has unveiled thousands of pre-configured AI agents for customer service, IT, HR, and other enterprise functions.
These agents will be available on the ServiceNow Platform, which acts as the "control tower". From there, customers may scout, implement, and manage organization-wide AI agent deployments.
Yet, alongside modifying and implementing prepackaged agents, ServiceNow also provides a new AI Agent Studio for fully customized deployments.
While that may sound like a lot of work, the vendor promises a no-code design experience and a language-based interface.
So, simply put, if the user can describe the task they want the agent to complete – alongside their desired outcomes – the AI Agent Studio can build an agent for it.
However, while having thousands of AI agents run across enterprise systems, automate processes, and – ultimately - self-learn may seem utopian, it could also prove chaotic.
After all, perhaps a business installs an agent that influences how another operates. That could cause breakdowns or a nasty chain reaction that disrupts the enterprise.
Thankfully, ServiceNow has released an AI Agent Orchestrator to combat such concerns. It helps coordinate and stitch agents together to mechanize complex, multi-step flows.
In doing so, it gives those in the control tower new powers to monitor and extend the AI workforce.
For Amit Zavery, President, Chief Product Officer, & Chief Operating Officer at ServiceNow, that’s critical. "Agentic AI without unification creates more complexity within an enterprise," he said.
The ability of ServiceNow AI Agents to work together on tasks that draw from multiple systems and departments truly stands out.
"With a single location to orchestrate agents and prevent sprawl, our AI agents collaborate like active participants at work, acting as true extensions of their human counterparts," he concluded.
While there are thousands of possible examples of that collaboration in action, consider a network issue.
With Orchestrator, a business may develop custom agents that draw from network management, application performance monitoring, security information, and event management systems.
From there, the agents can work together to overcome the problem by isolating the cause, creating a resolution plan, and – upon human review – executing it.
Similarly, look at this through a CX lens. Perhaps this network issue is impacting customers, too.
Recognizing this, an agent could go into a CRM – or CSM in ServiceNow’s case – and create a segment of customers impacted by the outage.
From there, another agent may utilize an outreach tool to proactively notify that customer segment of the issue and send regular updates.
These are excellent examples. Yet, with the AI Agent Studio and Orchestrator, the possibilities are practically boundless.
Why Should Brands Trust ServiceNow with Agentic AI?
In developing agentic AI offerings, many businesses are shifting tact. Previously, they had only considered specific business functions; now, they’re serving the enterprise.
