Abstract:

This study examines the relationship between artificial intelligence, revenue management, management accounting information and short-term rental management in an SME context. It investigates how AI-supported information processes are embedded in revenue-management and management accounting practices and analyses selected performance indicators against external market benchmarks. The research uses an exploratory quantitative embedded single-case study supplemented by documentary evidence from an anonymised Polish SME. The primary occupancy analysis covers July and August 2026 and includes 18 matched location-month observations; the average daily rate (ADR) analysis covers August 2026 and includes nine matched locations. Mean case-company occupancy was 75.89%, compared with 72.13% for the market, a gap of +3.76 percentage points; the case company was above market in 13 of 18 observations. Mean case-company ADR was 435.88 PLN, compared with 567.06 PLN for the market, a gap of -131.18 PLN; the case company was below market in eight of nine observations. The coexistence of above-market occupancy and below-market ADR highlights the need to evaluate revenue-management performance through multiple indicators rather than occupancy alone. Documentary evidence confirms AI-supported pricing, demand monitoring, forecasting, booking-pace analysis, market monitoring and managerial decision support, but the design does not identify a causal effect of AI on occupancy, ADR or revenue. The paper integrates AI-supported information processing, revenue management, management accounting information, external benchmarking and revenue-related performance while emphasising managerial judgement.