Autonomous workflows are fast becoming the next enterprise AI battleground as companies move beyond copilots and enter the agentic AI platform era, where software can act on its own. That shift is redefining how work gets done, but it is also forcing a harder conversation about governance, identity and measurable value.

That tension is especially acute for platforms already embedded in core business processes. At ServiceNow Inc., the move toward autonomous workflows depends on treating agents as a new identity class with tightly scoped permissions, according to Amanda Grady (pictured, left), vice president and general manager of platform foundations and AI platform products at ServiceNow.

“We really think about agents as a new type of identity. They’re not machines, they’re not humans — they’re kind of somewhere in between,” Grady told theCUBE. “If it’s a fully autonomous agent, then [the agent] needs its own distinct identity and its own distinct set of permissions for what data it can access.”

Grady and Marcelle Howard (right), director of the AI Platform Foundry at ServiceNow, spoke with Christophe Bertrand at the RSAC 2026 Conference, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the operationalization of an agentic AI platform, the importance of traceability and how to achieve tangible return on investment through methodical deployment. (* Disclosure below.)

Scaling value through an agentic AI platform

The next challenge is operational, not conceptual. Most enterprises should resist broad rollouts and start autonomous workflows in narrow domains where the data is strong, the process is defined and ROI can be measured, Howard explained. That measured start matters because research has regularly shown many companies still struggle to turn AI activity into real business value.

“We see organizations starting with IT-centric use cases like email triage or resolution routing, things of that nature,” Howard said. “We have organizations that take something that’s two days [of effort] and reduce it to two minutes, where they start to see upwards of 13% meantime to resolution savings across the enterprise.”

With that speed, governance then becomes a runtime discipline. ServiceNow is using its AI Control Tower to log agent actions, collect traces and monitor whether outcomes drift from intent across both its own platform and outside AI systems, according to Grady. That model is designed to preserve least-privilege access, separate human-directed agents from fully autonomous ones and protect personally identifiable information as autonomous workflows scale. Those security concerns are not theoretical — they are quickly becoming the fault line between AI programs that scale and those that stall.

“AI is going to dramatically change the way we all work,” Grady said. “It’s going to bring amazing productivity gains. Those that do it with security in mind will ultimately be the ones that move faster in the long run. CIOs are under tremendous pressure to see value realization from their AI investments and security can sometimes end up taking a back seat. But I do believe those that are thinking about security will, in the end, ultimately be the ones that move fast.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the RSAC 2026 Conference:

(* Disclosure: TheCUBE is a paid media partner for the RSAC 2026 Conference. Sponsors of theCUBE’s event coverage do not have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE