AI-Driven Knowledge Management Systems for Enterprise IT Operations
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V4I4P116Keywords:
Cross-Border E-Commerce Data Governance, Cloud Computing, Data Localization And Residency, Data Sovereignty, Service-Oriented Architecture, Scalable Architectures, Third-Party Risk Management, Trusted Identity Management, Unified-Consent FrameworkAbstract
Artificial Intelligence (AI) is increasingly being integrated into Knowledge Management (KM) systems to provide enhanced decision-making support to Information Technology (IT) operations teams. AI-driven systems are empowering these teams to reduce service resolution times, streamline troubleshooting processes, and share knowledge more effectively by improving the speed, relevance, and contextual accuracy of knowledge retrieval and understanding. Alongside these advantages, such AI-powered capabilities are redesigning the nature of knowledge work, augmenting the collaborative aspect of KM efforts, and shifting the composition and skill requirements of IT operations teams. Fundamental considerations for developing AI-driven KM systems for IT operations are explored, including a discussion of deployed architectural patterns, data quality and governance concerns, and deployment and processing options. Further, the impact of these systems and capabilities on the KM aspect of IT operations teams is examined. Together, these insights provide a foundation for the adoption of AI capabilities within KM systems used by IT operations teams.
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