Trust over ease? Examining the mediated effects of profitability on AI adoption in accounting

Abstract

Purpose This study investigates the individual-level determinants influencing the adoption of Artificial Intelligence (AI) in the accounting profession within an emerging economy context. It explores how perceptions such as usefulness, ease of use, trust, threat, and susceptibility shape AI adoption, and examines the mediating role of accounting profit. The research is grounded in an extended Technology Acceptance Model and contextualized for Bangladesh to address the gap in AI adoption literature in developing countries. Design/methodology/approach A structured online survey was administered to 478 accounting professionals across various sectors in Bangladesh. The questionnaire included established measures adapted from prior studies and was analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The model assessed both direct and mediated paths from individual perceptions to AI adoption, with accounting profit as the mediating variable. Bias testing, robustness checks, and validity assessments were also conducted to ensure reliability of the findings. Findings Perceived usefulness, trust in AI, and perceived threat significantly influenced AI adoption. Perceived ease of use and perceived susceptibility did not show direct significance. Accounting profit was found to mediate the relationships between perceived usefulness, perceived threat, and trust with AI adoption. These results indicate that while individual perceptions matter, financial feasibility plays a critical role in actual adoption decisions within accounting contexts in emerging economies. Practical implications Accounting firms and policymakers in emerging markets must prioritize financial readiness alongside technology training. To enhance AI adoption, strategies should focus on building trust, communicating the tangible value of AI, and ensuring that AI investments align with profit goals. The findings also suggest firms should promote perceived usefulness and address risk concerns when introducing AI into accounting systems. Social implications The study highlights the socio-economic barriers that affect technology diffusion in emerging economies. As accounting professionals face trust and threat perceptions, along with resource limitations, the integration of AI requires institutional support, inclusive digital training, and clear cost-benefit communication. Broader AI adoption could enhance transparency, efficiency, and job transformation in financial services if these conditions are addressed. Originality/value This study offers a novel integration of individual-level behavioural constructs and financial performance (accounting profit) to explain AI adoption in accounting. By focussing on Bangladesh, it extends Technology Acceptance Model literature into a highly relevant yet underexplored emerging market context. The research also contributes to accounting technology literature by showing how strategic perceptions and profitability jointly shape innovation decisions in the profession.

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