Al-Driven Financial Intelligence and Digital Knowledge Ecosystems: A Conceptual Framework for Institutional Decision-Making and Research Support
TL;DR
An interdisciplinary conceptual framework that links the fields of Artificial Intelligence, Financial Management and Library & Information Science to explore how financial intelligence and scholarly communication through Al-enabled systems are engaged in digital libraries and institutional governance is presented.
Abstract
The rapid proliferation of various artificial intelligence (Al) technologies in both organisational and academic ecosystems has irrevocably transformed the way institutions produce, interpret, and leverage information for decision-making. Paradoxically, the increasing complexity of financial systems, research environments and knowledge infrastructures has strained fragmented disciplinary approaches. This paper presents an interdisciplinary conceptual framework that links the fields of Artificial Intelligence, Financial Management and Library & Information Science (LIS) to explore how financial intelligence and scholarly communication through Al-enabled systems are engaged in digital libraries and institutional governance. From the paper; Al should not simply be understood as a technological tool but rather also as a strategic and epistemic force capable of determining what we consider risk, how we allocate resources, who has access to knowledge, how users interact with these systems, and ultimately, evidence-based decision-making. Based on theories in financial governance, technology adoption and usage, knowledge management, and information behavior the paper a) synthesizes major scholarly streams to propose an innovative conceptual model that ties together Al capability, digital knowledge infrastructure, information trust, decision intelligence and institutional performance The piece goes on to explain that the future of research support, funding strategy, and institutional performance will increasingly depend upon how institutions can harness intelligent systems in combination with ethical governance, human expertise, and knowledge shareability. At a conceptual level, the paper contributes by connecting three pieces that researchers rarely connect and providing a publication-oriented resource for future empirical research. This research speaks to academics, financial professionals, librarians, policymakers and leaders in higher education who strive to construct resilient, data-informed or ethical institutions amid an age of intelligent automation.