A COGNITIVE ENTERPRISE INTELLIGENCE FRAMEWORK FOR AUTONOMOUS KNOWLEDGE DISCOVERY, ORGANIZATIONAL LEARNING, AND ADAPTIVE BUSINESS DECISION SUPPORT

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

C ontemporary organizations generate vast and heterogeneous volumes of data across enterprise resource planning systems, customer relationship management platforms, unstructured documents, and operational sensors, yet most business intelligence (BI) architectures remain reactive, depending on predefined dashboards and static pipelines that require constant human interpretation. This paper surveys the emerging shift from static BI toward cognitive enterprise intelligence: systems capable of autonomously discovering knowledge, continuously updating an institutional memory, and supporting adaptive decision-making with minimal human intervention. We organize the survey around three cognitive layers reported in the literature — Knowledge Discovery, which extracts entities, relationships, and events from structured and unstructured enterprise sources using representation learning, knowledge-graph construction, and natural language understanding; Organizational Learning, which maintains an evolving knowledge graph while detecting concept drift and avoiding catastrophic forgetting through continual-learning mechanisms; and Adaptive Decision Support, which translates accumulated knowledge into interpretable recommendations through hybrid symbolic-statistical reasoning. For each layer we review representative techniques, compare their strengths and limitations, and identify open challenges around uncertainty quantification, provenance tracking, and evaluation methodology for organizational learning. The survey concludes that while individual components — knowledge-graph construction, continual learning, and neuro-symbolic reasoning — are maturing rapidly in isolation, their integration into a single closed-loop cognitive architecture for enterprise decision support remains an open and underexplored research direction

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Keywords

Cognitive Business Intelligence, Knowledge Graph, Continual Learning, Concept Drift, Neuro-Symbolic Reasoning, Organizational Learning, Explainable Decision Support.