Unlocking AI's potential in accounting: A study on adoption barriers and drivers

Accountants play a vital role in driving the implementation of Artificial Intelligence (AI) to improve financial analysis and performance measurement, but their readiness to adopt the technology is uneven. Drawing on the dual-factor model, this research examines the barriers and drivers to AI adoption. Barriers include knowledge and use of Excel-based data analytics (DA). Drivers include AI training, adoption of DA tools, and accountants' initiatives aimed at reducing resistance to technological change. These factors explain how accountants can suffer from status quo bias that prevents them from adopting AI and how the bias can be alleviated by organizational efforts. We conducted a survey on 271 accounting professionals and used descriptive analysis and Poisson regression to empirically test the effects of the factors. The results demonstrate the significant impacts of these factors on AI adoption. This study advances the literature on AI adoption by providing new insights into the barriers and drivers regarding its adoption in corporate environments.