Why It Matters
AI Suggestions help agents review new tickets faster by recommending ticket fields, generating summaries, and suggesting relevant knowledge base articles.
Agents can use these suggestions as a starting point while still reviewing and updating ticket details before taking action.
How to Set It Up
Go to Assistance → Tickets and open a ticket from the ticket listing page.
When a ticket is created, AssetSonar can suggest values for the following fields:
- Category
- Tonality
- Priority
- Urgency
AI-suggested fields are highlighted with a border so agents can identify values filled in by AI. If you manually change an AI-suggested value, the border is removed. If you change the field back to the AI-suggested value, the border appears again.
The Tonality field identifies the requester’s tone. It can include the following values:
- Neutral
- Inquisitive
- Frustrated
- Friendly
- Casual
- Happy
The Urgency field shows values from Very Low, Low, Medium, High, to Very High. Review the suggested urgency and update it if needed before prioritizing the ticket.
To generate a ticket summary, open the Conversation tab and click Summarize with AI. This opens an expandable summary section. The summary uses ticket context such as ticket content, requester details, urgency, priority, and associated devices.
Click Regenerate if you want to regenerate the summary.
To view suggested knowledge base articles, go to the ticket’s Knowledgebase tab. The KB Article Suggestions section shows relevant articles based on the ticket context.
On the Employee Portal, requesters can also view suggested KB articles from the ticket detail page.
For deeper troubleshooting, use Smart Diagnosis to review AI-generated diagnostic steps, possible root causes, and similar ticket patterns.
Note: Review AI-suggested fields, summaries, and KB articles before using them in your workflow.
Next Steps
Go to Assistance → Tickets, create or open a test ticket, review the AI-suggested Category, Tonality, Priority, and Urgency fields, then generate a summary and check whether the suggested KB articles match the request.
