AN INTERPRETABLE AI MODEL FOR INTELLIGENT IT SUPPORT TICKET PRIORITIZATION IN DIGITAL ORGANIZATIONS
Keywords:
artificial intelligence, information technology, IT support, explainable AI, ticket prioritization, digital organization, service continuity.Abstract
Digital organizations rely on stable information systems, cloud services, learning platforms and internal communication tools. When a technical incident is reported, the speed and correctness of IT support ticket prioritization affects service continuity. This paper proposes an explainable artificial intelligence model for intelligent ticket prioritization. The model combines textual complaint analysis, service impact, urgency, service-level agreement pressure, user history and support-team workload into a transparent priority score. Unlike simple first-come-first-served or keyword-based rules, the proposed approach produces both a priority class and a short explanation of the main causes for routing or escalation. A scenario-based analytical evaluation shows that the model improves urgent-ticket recognition and supports more balanced distribution of IT support resources.
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