ISSN (Online): 2321-3418
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Engineering and Computer Science
Open Access

Agentic AI in Predictive AIOps: Enhancing IT Autonomy and Performance

DOI: 10.18535/ijsrm/v12i11.ec01· Pages: 1631-1638· Vol. 12, No. 11, (2024)· Published: November 2, 2024
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Abstract

The integration of Agentic Artificial Intelligence (AI) within Predictive AIOps (Artificial Intelligence for IT Operations) is revolutionizing the management of IT systems, significantly enhancing IT autonomy and performance (Smith & Johnson, 2023). This article explores the potential of Agentic AI to empower AIOps platforms in proactively predicting, identifying, and resolving system issues. By leveraging predictive analytics and machine learning, AIOps not only enhances operational efficiency but also minimizes downtime and supports autonomous decision-making in complex IT environments (Lee et al., 2022).

We examine the key roles that Agentic AI plays in improving performance metrics, optimizing resource allocation, and reducing the reliance on human intervention in critical system operations (Garcia & Patel, 2024). Additionally, this study investigates the implications for IT infrastructure scalability, long-term resilience, and the evolution toward self-governing systems (Chen, 2023). The findings underscore the transformative impact of Agentic AI on future IT operations, showcasing its potential to foster higher levels of automation and operational intelligence.

Keywords

Agentic AIPredictive AIOpsIT autonomyAnomaly detectionResource optimizationProactive

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Author details
Shanmugasundaram Sivakumar
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