Advances in Management and Applied Economics
Critical Success Factors for AI Training Robot Adoption in Accounting SMEs: An Integrated Delphi–DEMATEL–ANP Approach
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Abstract
Artificial Intelligence (AI) and Robotic Process Automation (RPA) are transforming accounting services toward intelligent, data-driven professional services. However, small and medium-sized accounting firms (SMEs) face barriers to AI adoption, including limited resources, technological capabilities, employee skills, and regulatory uncertainty. This study identifies and prioritizes the critical success factors (CSFs) influencing AI training robot adoption in Taiwanese accounting SMEs. The framework integrates the Technology–Organization–Environment (TOE) framework, Task–Technology Fit (TTF), Technology Acceptance Model (TAM), Human–Computer Trust (HCT), and Explainable Artificial Intelligence (XAI). We used a two-round Delphi process with 15 experts to refine the CSFs, followed by DEMATEL to identify causal relationships and ANP to assess their relative priorities. The DEMATEL results indicate that the Technological dimension is the strongest causal driver (D−R = 1.355), followed by the Organizational dimension (D−R = 0.435), whereas Decision Making is the principal effect dimension (D−R = −1.781). The findings further emphasize task–technology alignment, AI maturity, regulatory conditions, top management support, employee AI competence, and human–computer trust. Overall, AI adoption represents an integrated organizational transformation rather than merely a technological investment. The proposed Delphi–DEMATEL–ANP framework provides systematic decision support for resource prioritization, organizational readiness, capability development, and sustainable AI-enabled digital transformation in accounting SMEs.
JEL classification numbers: M15, M41, O33, C44.
Keywords: Artificial Intelligence, AI Training Robots, Accounting SMEs, Task-Technology Fit, DEMATEL, Analytic Network Process, Digital Transformation.
