BEYOND TECHNOLOGY: UNPACKING ORGANIZATIONAL BARRIERS IN AI-DRIVEN FINANCIAL DECISION SUPPORT SYSTEMS - A SYSTEMATIC REVIEW AND BIBLIOMETRIC ANALYSIS

Abstract

This systematic literature review examines organizational barriers in AI-driven decision support systems (AIDSS) adoption within financial services through bibliometric and thematic analysis. Following PRISMA 2020 guidelines, 183 articles were screened, yielding 67 high-quality publications (2019-2024) for analysis. Keyword co-occurrence analysis using VOSviewer identified ten core concepts forming four distinct clusters:  implementation challenges (barriers, implementation, systematic review, clinical decision support), financial sector applications (artificial intelligence, financial services, banking), organizational adoption dynamics (adoption, organizational), and healthcare sector transferability. Findings reveal a critical research-practice gap:  while "artificial intelligence" dominated with 63 occurrences, "barriers" (23) and "adoption" (22) surpassed sector specific keywords, indicating a paradigm shift from technical capabilities toward organizational challenges.  Temporal analysis shows emerging focus on organizational factors (average publication year 2024.00 vs. 2022.78 for financial services). However, absence of granular barrier constructs (culture, leadership, skills) and limited cross-sectoral knowledge transfer from healthcare CDSS literature represent conceptual underdevelopment.  Results underscore that organizational readiness not technical sophistication constitutes the primary adoption constraint, requiring integrated change management strategies alongside technology deployment.