It would be incredibly useful if Magic AI could recognize a technician’s job role within the company and use that information in two areas: ticket routing decisions and snippet phrasing.

Primary Use Case: Role-Aware Ticket Routing

Right now, ticket routing decisions are typically based on things like category, priority, and keywords. If Magic AI could also factor in the job role of the person routing or escalating the ticket, it would help us enforce process standards, improve queue management, and maintain SLA integrity.

A few examples where this would be valuable:

• Escalations from managers could bypass Level 2 queues and go directly to Level 3.

• AI could restrict certain routing actions for non-manager roles (like moving tickets to Projects, DevOps, or Leadership queues).

• If a Service Desk Manager escalates a ticket, Magic AI could automatically increase priority or flag it for immediate review.

• For routine misroutes, AI could warn Level 1 techs of improper routing but allow managers to bypass the warning.

• Tickets requiring leadership approval could be auto-tagged ‘Pending Manager Review’ if routed by a technician.

This would help clean up routing mistakes, prevent SLA risks, and make escalations run smoother while respecting team roles and responsibilities.

Secondary Use Case: Role-Aware Snippet Phrasing

Additionally, having Magic AI adjust phrasing in suggested snippets based on the sender’s role would improve client perception and communication clarity.

Some examples:

• Ticket closure confirmations sounding different if sent by a manager vs. a technician.

• Escalation notices reflecting the sender’s authority.

• Service restoration or outage notifications adjusting tone and phrasing depending on job role.

• SLA warnings or fast-tracks coming from leadership carrying the appropriate urgency.