Manual Operations to Agentic Intelligence with CSI

[Akash Bhardwaj]

One of the most recurring challenges I’ve seen across large-scale ServiceNow programs is how operational excellence tends to fade once the platform stabilizes.
The first few months after go-live are full of energy — dashboards are built, tickets drop, improvements are discussed — but six months later, that same rhythm disappears.

The reason is simple: continuous service improvement (CSI) isn’t built into the operations model.
We often rely on manual reviews, reactive problem solving, and ad-hoc automation instead of embedding a cycle that continuously learns, improves, and evolves.

Over the past year, I’ve seen how integrating Generative AI and Agentic AI into operations can change that equation completely (please note that the Generative AI and Agentic AI use cases are in the POC state with only being used by the CoE team at the moment for our implmentation, so I can not provide you the tangible outcome metric)

1. Continuous Service Improvement Framework: Laying the Foundation

Every sustainable improvement starts with visibility.
We began by building a CSI framework that didn’t just track incidents and SLAs, but analyzed them for patterns — which requests were recurring, which workflows had human dependencies, and where automation could realistically help.

Regular reviews of incident and request data became part of the operational cadence.
This data was then layered with end-user feedback and SLA trend analysis to identify meaningful

2. Generative & Agentic AI: Turning Data into Action

Generative AI changed the game for operations.
Initially, the goal was simple — reduce effort for L1 and L2 teams through:

• Intelligent search and knowledge deflection to help agents find relevant resolutions faster.

• Auto-summarization of incidents so shift handovers were consistent and context-rich.

But where it got truly interesting was when we moved from Generative AI to Agentic AI — where AI agents didn’t just summarize or suggest, but acted.

3. Adoption in Daily Operations: Making AI Part of Everyday Work

AI adoption is only real when it blends seamlessly into normal work.
We focused on automating L1-level repetitive tasks first — password resets, access provisioning, master data updates — all powered by ServiceNow’s automation engine with light AI intervention.

Soon after, we integrated AI-driven triage that analyzed the context of incidents and routed them to the right group instantly — a massive improvement in ticket handling time.