ARTIFICIAL INTELLIGENCE ADOPTION AND PERFORMANCEEFFICIENCY IN ACCOUNTING SYSTEMS OF EMERGINGECONOMIES: AN ANALYTICS MATURITY PERSPECTIVE
Keywords:
Artificial Intelligence; Data Analytics Maturity; Accounting Systems; Performance Efficiency; Mediation Analysis; Emerging Economies; TAM; RBVAbstract
This study examines the association between Artificial Intelligence (AI) adoption and performance efficiency in accounting systems of emerging economies, with analytics maturity as a mediating variable. The study uses the Technology Acceptance Model (TAM) and Resource-Based View (RBV) as supporting lenses. Analytics maturity is operationalized using a composite measurement index (Data Analytics Maturity Indicators – DAMI). A cross-sectional descriptive and explanatory survey design was adopted. Primary data were collected from 300 accounting and finance professionals across banking, manufacturing, telecommunications, and public sector organizations in Lagos, Abuja, Port Harcourt, and Ibadan. Findings indicate that AI adoption is positively associated with performance efficiency (β = 0.36, p < .001). Analytics maturity shows a statistically significant indirect association (indirect effect = 0.32, 95% CI [0.24, 0.40]), indicating evidence of partial indirect association. The full model shows 68% of variance explained in the model sample (R² = 0.68). Reported constraints include data interoperability issues (86.2%), cloud latency (83.5%), API incompatibility (81.7%), algorithm transparency gaps (79.8%), and data governance fragmentation (77.4%). This study contributes to literature by integrating AI adoption with analytics maturity as a mediating variable in emerging economy accounting systems. The findings may inform policy discussions and organizational strategies for analytics capability development.
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