From Automation to Autonomy: Exploring Agentic AI in IT Service Management

Agentic Artificial Intelligence represents a transformative paradigm in Information Technology Service Management (ITSM), fundamentally redefining operational capabilities through autonomous decision-making and action execution. This article explores the evolution from traditional automation toward agentic autonomy in ITSM environments, examining both theoretical foundations and practical applications. The transition from human-driven workflows to autonomous systems capable of contextual awareness, adaptive learning, and independent action execution marks a significant advancement beyond conventional rule-based automation. By integrating sophisticated machine learning algorithms, natural language processing capabilities, and predictive analytics, agentic systems address complex service management challenges including incident resolution, problem identification, resource optimization, and user support. While demonstrating substantial operational benefits in classification accuracy, resolution timeframes, service availability, and cost efficiency, agentic implementation presents significant challenges regarding technical integration, organizational adaptation, security governance, and ethical frameworks. The article addresses these multifaceted considerations while exploring transformative applications across self-service transformation, predictive analytics, dynamic resource allocation, continuous learning, and integration with existing ITSM frameworks. Through comprehensive examination of both opportunities and implementation considerations, this article provides insights into how agentic AI is reshaping service management paradigms and establishing new operational models for delivering IT services in increasingly complex digital environments.