open access

Journal of Artificial Intelligence and Digital Health

P e e r - R e v i e w e d  
Bi-Annual (Two issues per year)

ISSN: 3139-6267 (Online)
DOI Prefix (Crossref): 10.67238

Ai-Driven Digital Transformation and Performance Efficiency in Accounting Information Systems
Research Article - Volume: 1, Issue: 2, 2026 (August)
Ai-Driven Digital Transformation and Performance Efficiency in Accounting Information Systems Download PDF
David Sunday Araoti* ORCID

Department of Research, Policy and AI Governance, Independent Researcher, Ogbomosho, Nigeria

*Correspondence to: David Sunday Araoti, Department of Research, Policy and AI Governance, Independent Researcher, Ogbomosho, Nigeria, E-Mail:
Received: May 22, 2026; Manuscript No: JAID-26-9814; Editor Assigned: May 26, 2026; PreQc No: JAID-26-9814(PQ); Reviewed: June 05, 2026; Revised: July 23, 2026; Manuscript No: JAID-26-9814(R); Published: August 13, 2026

ABSTRACT

This study investigates the impact of Artificial Intelligence (AI)-driven digital transformation on performance efficiency in Accounting Information Systems (AIS) within emerging economies, with Nigeria as the focal context. The study is anchored on the Technology Acceptance Model (TAM), Diffusion of Innovation (DOI), and Resource-Based View (RBV), which collectively explain technology adoption behavior, diffusion patterns, and performance outcomes.

A cross-sectional descriptive and explanatory survey design was adopted. Primary data were collected from 300 accounting and finance professionals drawn from banking, manufacturing, telecommunications, and public sector organizations across Lagos, Abuja, Port Harcourt, and Ibadan. Data were obtained through a structured Likert-scale questionnaire and analyzed using SPSS version 27.

The findings reveal that AI-driven digital transformation significantly enhances accounting system performance efficiency, particularly in processing speed (β = 0.47, p < .001), reporting accuracy (β = 0.43, p < .001), and real-time financial decision support (β = 0.45, p < .001). Results further indicate that AI integration improves automation of financial workflows, strengthens data consistency, and enhances system responsiveness.

However, the study identifies key barriers including high implementation costs (86.9%), inadequate technical skills (84.1%), cybersecurity risks (82.3%), and infrastructural limitations (75.6%), which collectively slow full-scale AIS transformation.

The study concludes that AI-driven digital transformation is a significant predictor of accounting information system performance efficiency in emerging economies. Theoretically, the study extends TAM and DOI by demonstrating their relevance in AIS transformation, while RBV explains how AI enhances organizational capability. Practically, the study provides actionable insights for policymakers, system developers, and organizational leaders on optimizing AI integration in accounting systems. 

Keywords: Artificial Intelligence; Digital Transformation; Accounting Information Systems; Performance Efficiency; Nigeria; TAM; DOI; RBV; Emerging Economies

Citation: Araoti DS (2026). Ai-Driven Digital Transformation and Performance Efficiency in Accounting Information Systems. J. Artif. Intell. Digit. Health. Vol.1 Iss.2, August (2026), pp:131-136.
Copyright: © 2026 David Sunday Araoti. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.