Autonomous Enterprise AI Copilots for End-to-End ITSM Workflow Optimization
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V6I4P133Keywords:
Autonomous AI Copilots, Enterprise IT Service Management (ITSM), Cognitive Automation Frameworks, AI Assistants Vs. AI Copilots, Decision Autonomy Levels, ITSM Orchestration Architectures, Event-Driven Service Pipelines, Cross-Silo Workflow Automation, Intelligent Service Operations, AI-Driven Incident And Change Management, Enterprise Integration Patterns, ITSM Cockpit Architecture, Interoperable Service Platforms, Security-By-Design In ITSM, Measurable Service Performance Outcomes, Deployment Strategies For AI In IT Operations, End-to-End Workflow Automation, Cognitive Decision Support Systems, Scalable ITSM Modernization, Digital Service Governance ModelsAbstract
In 2025, autonomous AI copilots will support enterprise IT Service Management (ITSM) across functional silos and into adjacent domains, automating end-to-end workflows and complex use cases that lie beyond the capabilities of existing AI Assistants. Preparation requires an evidence-based strategy that addresses technical enablers, deployment approach, organizational implications, and measurable outcomes. The full exploration of autonomous AI copilots in ITSM begins with a definition that differentiates them from AI Assistants, delineates supporting capabilities and implementation boundaries, and describes four degrees of decision autonomy in cognitive automation and orchestration. Two reference architectures identify the core components of an autonomous ITSM cockpit and their interconnectionsdata flows, integration patterns, event-driven pipelines, security, and interoperability across tools and platformstogether with the measurable ITSM outcomes that can be achieved when pilot deployments progress to scale.
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