Artificial intelligence (AI), business intelligence (BI) and analytics are increasingly used in hotel accounting, financial reporting and performance management. Existing research, however, has concentrated mainly on prediction, automation and operational optimisation. Their integration with the critical interpretation of accounting information and human judgement remains less clearly developed.
This study provides a structured review and bibliometric mapping of research on AI-supported accounting and financial reporting in the hospitality industry. It adopts a structured bibliometric review combining science mapping with qualitative content-oriented interpretation.
The review comprises three complementary search streams addressing: (i) AI, BI and analytics in hotel accounting; (ii) AI-supported reporting, dashboards and decision-support systems; and (iii) the broader contextual literature on human judgement and the interpretation of accounting information.
The results identify machine learning, revenue management, forecasting and dynamic pricing as the most prominent and structurally influential areas within the retrieved literature. Research on reporting interpretation, dashboard-based judgement, anomaly detection and human validation is more fragmented and remains weakly integrated across the mapped literature.
The principal research gap therefore concerns the limited connection between AI-supported technologies, reporting outputs and human interpretive judgement, rather than the absence of relevant research in these areas.
The study proposes a human-centred perspective on AI in hotel accounting and identifies future research directions in which AI supports critical interpretation, professional judgement and responsible managerial decision-making.