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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!
Solved! Go to Solution.
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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instances, specifically dealing with years of legacy scripting (like bad current.update() calls in Business Rules or outdated Client Scripts) that override Out-Of-The-Box (OOTB) capabilities.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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3 weeks ago
Hi Neil,
Great initiative! It's always valuable to see students digging into the practical, day-to-day realities of ServiceNow administration beyond the coursework.
Best of luck with your research and the RiseUp program! Feel free to reach out if you have any follow-up questions.
Best regards,
David
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3 weeks ago
Hi David, thank you so much for the reply, truly appreciate it. I will keep in touch.
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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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12 hours ago
Hi Sungulelo41
Thank you so much for the time and effort spent in shedding light on my question. I truly appreciate it. This insight definitely gave me proper fuel and something to look into. Stay curious my friend and keep well 😎