Agentic AI and the Future of Knowledge Management Systems

Abstract

The rapid evolution of Artificial Intelligence (AI) is transforming Knowledge Management Systems (KMS) from passive repositories of information into intelligent, adaptive, and autonomous ecosystems. This article explores the emergence of Agentic AI—AI systems capable of autonomous goal-setting, reasoning, planning, and action—and its implications for the future of knowledge management. Unlike traditional AI tools that operate reactively, Agentic AI can proactively curate, synthesize, validate, and distribute knowledge across organizational contexts. The paper examines how agent-based architectures enhance decision-making, enable dynamic knowledge orchestration, and foster continuous organizational learning. It further analyzes the integration of large language models, retrieval-augmented generation, multi-agent collaboration, and human-in-the-loop governance within next-generation KMS. Opportunities such as personalized knowledge delivery, automated expertise mapping, and cross-domain knowledge synthesis are discussed alongside challenges related to trust, transparency, ethical governance, data quality, and organizational readiness. The article concludes by proposing a conceptual framework for Agentic Knowledge Management Systems (AKMS) that balances autonomy with accountability, positioning Agentic AI as a strategic enabler of adaptive, resilient, and knowledge-driven enterprises.

Keywords: Agentic AI; Knowledge Management Systems (KMS); Artificial Intelligence; Autonomous Agents; Organizational Learning; Intelligent Automation; Human-in-the-Loop Governance; Knowledge Orchestration; Digital Transformation.