The Evolution and Architecture of Agentic Open Source Intelligence
Abstract
This comprehensive review paper examines the ontological shift in Open Source Intelligence (OSINT). For decades, the field was strictly defined by the extraction of actionable intelligence from publicly accessible data, operating on a linear, highly manual pipeline that relied entirely on human cognitive processing. The advent of Agentic Artificial Intelligence (AI) fundamentally displaces this foundational paradigm. By transitioning the discipline from reactive data aggregation to proactive, autonomous execution, agentic architectures redefine the intelligence lifecycle, shifting the cognitive burden of data processing, correlation, and initial synthesis from human operators to autonomous algorithmic systems. To clarify the academic boundaries and methodological intent of this document, it must be explicitly stated that this is a comprehensive review paper rather than a presentation of singular novel empirical research. The objective of this review is to systematically aggregate, synthesize, and critically evaluate the theoretical, mathematical, and architectural state-of-the-art across the rapidly expanding domain of Agentic AI in cybersecurity and OSINT. By analyzing recent academic frameworks published across leading repositories—such as the Institute of Electrical and Electronics Engineers (IEEE), the Association for Computing Machinery (ACM), Springer, and Elsevier—this paper provides a definitive structural analysis of the current landscape. This review specifically addresses the mathematical foundations of autonomous reasoning through Bayesian probabilistic updating, constructs structural models of multi-agent collaborative topologies, evaluates the operational efficacy of specialized cybersecurity frameworks, and thoroughly examines the profound socio-technical friction generated by this paradigm shift, specifically focusing on the barrier of algorithmic trust, legal accountability deficits, and the emerging defensive imperative to track Non-Human Identities (NHIs).