The Determinants of Artificial Intelligence Capabilities; A Systematic Review

Abstract

Purpose: This review examines determinants of organizational artificial intelligence (AI) capability while distinguishing antecedent conditions from constitutive resources, developmental processes, AI readiness, and downstream outcomes. Design/methodology/approach: A structured evidence map and construct-sensitive narrative synthesis were developed from targeted scholarly discovery. The accompanying register contains 56 distinct candidate bibliographic records, provisionally classified into antecedent/formation, constituent/measurement, and adjacent or unresolved categories. Eleven empirical publications are discussed as analytic exemplars, alongside four prior reviews. Title-term network, temporal-overlay, and density maps describe the candidate register. Findings: The empirical exemplars identify strategic and institutional conditions, learning processes, and resource-orchestration mechanisms relevant to capability formation. However, studies differ in their outcome definitions and analytic designs, preventing a valid pooled ranking of determinants. Originality/value: The review separates explanatory predictors from components used to measure capability and places visual title-term patterns alongside, rather than in place of, empirical evidence. Limitations: The candidate register is not a final included-study sample; a reproducible database-wide selection history and formal study-level risk-of-bias appraisal are unavailable. The synthesis therefore identifies defensible relationships and research priorities without claiming exhaustive systematic coverage.