The Role of AI and Big Data in Digital Accounting for Tourism Businesses: Opportunities, Challenges, and Future Trends

Georgios Kampiotis, Leonidas Theodorakopoulos and Christos Pierrakeas ()
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Georgios Kampiotis: University of Patras, Department of Management Science and Technology
Leonidas Theodorakopoulos: University of Patras, Department of Management Science and Technology
Christos Pierrakeas: University of Patras, Department of Management Science and Technology

A chapter in Synergizing Management, Culture, and Arts for Tourism Development - Vol. 2, 2026, pp 217-284 from Springer

Abstract: Abstract The convergence of Artificial Intelligence (AI) and Big Data is radically transforming digital accounting in the tourism industry, enabling unprecedented levels of automation, precision, and strategic insight. This paper examines how AI-driven accounting systems—integrated with Big Data analytics—are redefining financial operations across tourism enterprises, from revenue forecasting and fraud detection to regulatory compliance and ESG reporting. By processing vast, heterogeneous datasets from booking platforms, social media, IoT devices, and global financial systems, AI models enhance predictive accuracy, facilitate dynamic pricing, and support real-time decision-making. The study highlights how machine learning algorithms automate routine bookkeeping, identify anomalous transactions, and personalize financial interventions, while Big Data provides the informational substrate for granular forecasting and risk modeling. Yet, despite these advances, the paper underscores critical barriers—such as algorithmic opacity, data privacy regulations, and cybersecurity vulnerabilities—that particularly affect small- and medium-sized tourism businesses. Through a multidisciplinary analysis, this research offers both theoretical insight and practical guidance on how tourism enterprises can harness AI and Big Data to build resilient, adaptive, and ethically responsible financial ecosystems.

Keywords: Real-time Decision-making; ESG Reporting; Revenue Forecasting; Fraud Detection; Disruptive Technologies (search for similar items in EconPapers)
JEL-codes: L86 M31 O32 O33 Z32 Z33 (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-17534-2_6

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