It support · Production

Artificial Intelligence in Jira Service Management: AI-powered support workflows and AIOps

The problem

Support and IT operations teams face high volumes of manual ticket sorting, fragmented knowledge bases, and time-consuming post-incident review compilation that slow resolution and cause organizations to miss out on crucial learnings.

Workflow diagram · grounded in source
1
Help-seeker submits request
trigger
“the Jira Service Management help center, Slack, Microsoft Teams, email, and embeddable widget”
2
AI answers from knowledge base
ai_action
“AI answers uses AI to search across your linked knowledge base spaces and answer your customer questions”
3
Escalation routing decision
routing
“It can also determine whether a request should be escalated based on SLAs, customer interactions, urgency, etc.”
4
AI triage and prioritization
ai_action
“AI triage analyzes tickets in your queue and makes recommendations for appropriate request types and associated fields”
5
AI summarizes ticket activity
ai_action
“AI can quickly summarize ticket activity so you can get up to speed”
6
AI drafts agent reply
ai_action
“AI will generate a reply based on responses added by agents while resolving similar work items in the past”
7
Agent inserts or refines reply
output
“You can then insert the comment or refine it.”
Reported outcome

Jira Service Management's AI features enable ticket deflection via a virtual service agent, accelerate agent response through AI summaries and draft replies, and predict the top five most likely ticket assignees with 86 percent accuracy.

Reported metrics
Predictive assignee accuracy86 percent
Time spent on manual ticket sortingsignificantly reduce the time spent on manual sorting
Incident detection and recovery timereduce the time required to detect, respond to, and recover from incidents
Reported stack
Jira Service ManagementRovoNLPConfluenceWorkatoWorkdaySlackMicrosoft Teams
Source
https://www.atlassian.com/software/jira/service-management/product-guide/tips-and-tricks/artificial-intelligence
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Jira Service Management's AI features enable ticket deflection via a virtual service agent, accelerate agent response through AI summaries and draft replies, and predict the top five most likely ticket assignees with…

What tools did this team use?

Jira Service Management, Rovo, NLP, Confluence, Workato, Workday, Slack, Microsoft Teams.

What results were reported?

Predictive assignee accuracy: 86 percent; Time spent on manual ticket sorting: significantly reduce the time spent on manual sorting; Incident detection and recovery time: reduce the time required to detect, respond to, and recover from incidents (source-reported, not independently verified).

How is this it support AI workflow structured?

Help-seeker submits request → AI answers from knowledge base → Escalation routing decision → AI triage and prioritization → AI summarizes ticket activity → AI drafts agent reply → Agent inserts or refines reply.

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