ServiceNow has rolled out its Zurich release, expanding its platform with several “breakthrough” innovations.
Agentic Playbooks is one of those innovations. It allows teams to break down complex, cross-enterprise processes into step-by-step guides.
Indeed, it offers an interface for teams to map out workflows across enterprise systems, like whiteboard sketches.
To further boost this capability, ServiceNow announced it’s combining Process and Task Mining insights on one platform. As such, companies can better understand how work gets done, identify opportunities for AI agents, and spot where a human touch is critical.
From there, brands can return to their Agentic Playbooks and apply that intelligence to recreate those workflows.
The Playbook can then guide AI agents as they do some of the work and prompt humans when they’re needed to step in.
Here’s an example of how this could work in customer support. Consider someone calling up their bank regarding a lost credit card. Following a Playbook, the AI agents could verify the customer, freeze their card, and send a replacement, while keeping the customer in the loop. Meanwhile, businesses can clearly define exit rows if the customer wishes to escalate to a human.
As such, the brand can deliver an efficient, end-to-end, and governed resolution flow. All the while, it has taken process data and turned it into action.
ServiceNow Breaks More Barriers to Building Apps & Multi-Agent Flows
Many brands using AI agents have deployed them in isolation, as they build confidence in the technology. Yet, the future is multi-agent flows that mechanize multi-step, cross-system processes. That’s where the big bucks will be won.
IT needs more time to make that big picture a reality. Recognizing this, ServiceNow has unveiled two other new solutions, so teams can more efficiently work with AI.
First is its Build Agent, which turns ideas, written in natural language, into “production-ready” apps. In doing so, the agent handles the design, logic, integrations, and, of course, the “build” of the app.
For instance, a business may say: “Build me an onboarding app for customer service that automatically assigns tasks to HR, IT, and facilities.” It will then build it.
As it does so, the Build Agent leaves an audit trail, so IT has the blueprint, can put the icing on the cake, and run the app through rigorous testing.
While IT undergoes that testing, they may use the second standout solution: the Developer sandbox, which offers a space where the new apps and agents may make mistakes.
That space is collaborative, so IT can collaborate with other teams to experiment with, test, and optimize new solutions before putting them live.
As AI Scales, ServiceNow Expands the Scope for Security
As brands leverage Agentic Playbooks, AI agents will communicate, run across new enterprise integrations, and share data. To make this vision a reality, security processes must catch up quickly.
Enter the new ServiceNow Vault Console, which offers users a guided experience to protect sensitive data across the workflows they build.
Again, let’s take a customer service example. An admin could use the console to spot how personal data moves across tickets, recommend protection policies, and monitor compliance activity.
Additionally, it offers a central dashboard to monitor data flows and surface intelligent insights, like suggestions for protecting newly-discovered, sensitive data.
Alongside the innovation, ServiceNow is launching a Machine Identity Console to secure API integrations by actively managing what information AI agents can access.
The console also offers visibility into an enterprise’s integrations, isolates weak authentication methods, and provides steps to bolster security.
Indeed, if an integration is still following basic authentication protocols or is no longer active (for over 100 days), the Console will flag it and suggest steps to solve it.
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Amit Zavery, President, CPO, & CPO at ServiceNow, celebrated the Zurich release as “a turning point for enterprise AI.”
He continued: “ServiceNow is delivering multi-agentic AI systems in production that are not just powerful, but governable, secure, and built for scale.
We are transforming the enterprise tech stack to be AI-native, from autonomous workflows that act on data with precision, to developer tools that democratize high-velocity innovation.
“With built-in controls for security, risk, and compliance, we’re helping organizations move beyond experimentation and into a new era of intelligent execution,” concluded Zavery.
In doing so, ServiceNow continues establishing and expanding key partnerships with adjacent tech providers, including its strengthened collaboration with Genesys.
Genesys leads the cloud contact center space in its revenue. The latest advancements in its ServiceNow partnership aim to help service teams scale intelligent automation. As such, they may take further steps to orchestrate, implement, and automate end-to-end resolution flows.
Yet, alongside Genesys, ServiceNow has strengthened various other partnerships as its ambitions to become the ultimate AI platform for business advance.
For instance, it has strengthened collaborations with Cisco, NiCE, and Zoom over recent months, as its influence over the CX and broader enterprise space expands.
