NowAssist in practice: what GenAI actually does in ServiceNow
A working guide to NowAssist and the GenAI capabilities that lift productivity and user experience across the platform.
What NowAssist is
NowAssist brings generative AI directly into everyday ServiceNow workflows. It changes how employees and IT teams interact with the platform: less typing, less searching, and fewer handoffs that lose context.
The capabilities that matter
1. Text-to-code generation
NowAssist generates ServiceNow scripts and workflows from plain language descriptions. Development cycles shorten and platform customization opens up to more of the team.
2. Case summarization
Long case histories become concise summaries on demand. Handoffs get faster and support teams stop re-reading threads.
3. Virtual agent enhancement
Conversational agents that understand context and intent. Self-service success rates climb when the agent actually follows the conversation.
4. Knowledge article generation
Case resolutions turn into polished knowledge articles automatically, so what one engineer learned is available to everyone.
Implementation practices
- ▸Start with high-impact use cases: put AI where it pays back first
- ▸Establish governance: clear review and approval for AI-generated content
- ▸Train your users: teams need to know how to prompt and when to trust
- ▸Monitor and refine: measure performance and adjust continuously
NowAssist has changed our service desk operations. Our agents are 50% more productive and customer satisfaction is up 25%.
A result from the field
Financial services firm
A major bank rolled NowAssist out across an IT service desk serving 15,000 employees:
- ▸60% reduction in average handling time
- ▸45% fewer escalations
- ▸85% virtual agent resolution rate
- ▸40% improvement in CSAT
Getting started
We have taken dozens of organizations through NowAssist implementations. The engagement typically covers:
- ▸Readiness assessment
- ▸Use case identification
- ▸Implementation roadmap
- ▸Change management
- ▸Ongoing optimization
Talk through your use cases with people who have deployed this in production.
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