Research Question for Experienced ServiceNow System Administrators

neilswrts41 · 3 weeks ago

Good day, everyone.

My name is Neil, and I'm currently a student in the RiseUp with ServiceNow program.

I'm doing some personal research (outside of my official RiseUp coursework) to better understand the day-to-day challenges experienced by ServiceNow System Administrators. With ServiceNow rapidly expanding its AI capabilities, I'm curious to hear from professionals working in real-world environments.

If an AI assistant could permanently eliminate one repetitive task from your daily work as a ServiceNow System Administrator, what would it be?

I'd love to hear your thoughts on any of the following:

What repetitive task takes up the most time?
Approximately how many hours per week does it consume?
Why do you think automation hasn't completely solved this problem yet?
What would your ideal AI-powered solution look like?

I'm hoping to learn from your real-world experiences and better understand where the biggest opportunities for innovation exist.

Thank you in advance to everyone who takes the time to share their insights—I really appreciate it!

sungulelo41 · 2 weeks ago

Hey Neil,

This is a great query to put to the community!

If I had to pinpoint one of the biggest daily headaches for a SysAdmin, it’s managing and updating custom-heavy instances, specifically dealing with years of legacy scripting (like bad current.update() calls in Business Rules or outdated Client Scripts) that override Out-Of-The-Box (OOTB) capabilities.

Here is a quick breakdown of how that impacts the day-to-day:

1. The Repetitive Task & Time Sink

The Task: Troubleshooting unexpected downstream breakage during updates, patch deployments, or when implementing new features over legacy code.
Time Consumed: Easily 5 to 8 hours a week spent purely on impact analysis, unwinding custom scripts, and testing dependencies across sub-prod environments.

2. Why Full Automation Hasn't Solved It Yet

Automation relies on predictable rules. In custom-heavy instances, years of stacked scripts create hidden dependencies that standard automated flows can't anticipate. Even as platforms advance with innovations like ServiceNow Otto and Now Assist coming into play there’s a boundary:

Context & Intent: AI can read code and suggest clean OOTB replacements, but it can't always guess the original business intent behind a 6-year-old custom script.
Governance & Risk: While AI can streamline workflow execution, critical compliance checks, Segregation of Duties (SoD), and final testing on legacy infrastructure still require explicit human validation to prevent breaking downstream production logic.

3. The Ideal Solution

The ideal AI-powered solution wouldn't just write new code; it would act as an Architectural Risk Engine. It would proactively scan an instance, map out every dependency linked to a legacy script, highlight standard OOTB migration paths, and run automated sandbox stress tests before any code is touched.

Innovations like Otto shift our role from manual script execution to platform governance, but untangling custom technical debt is still very much a human-led effort!

Hope this gives you some good fuel for your research. As a recent RiseUp Alumni I am also curious like you, best of luck with your RiseUp program.

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svobodajan89 · yesterday

Hello Neil,

I am quite new on the ServiceNow CSA journey, so I am just gonna add my five cents.

I agree that heavily customized ServiceNow instances are a pain. I worked for a company which was customized a ServiceNow instance, and the regression testing with each release was painful, since not all of the testing could be automated. And I was not even an admin. Moreover, some of the customizations were later released by ServiceNow. So it would be great if the agent could compare the customizations with existing features and suggest where the customizations could be deprecated and replaced by the out-of-the-box options.