Current Volume 8
This paper presents a systematic review of the applications of artificial intelligence (AI) and machine learning (ML) in advancing sustainable tourism. The study categorizes technological innovations across key sustainability dimensions, including environmental optimization, predictive demand modeling, personalized visitor experiences, and smart hotel systems. Findings reveal that AI and ML have played critical roles in enabling energy efficiency, managing tourist flows to prevent over-tourism, and enhancing cultural sensitivity through personalized and accessible travel services. The review also identifies 2021 as a pivotal year, during which the COVID-19 recovery accelerated digital transformation in tourism, compelling operators to adopt intelligent systems for resilience and sustainability. Furthermore, the paper explores emerging ethical debates around data governance, algorithmic bias, and regulatory oversight, emphasizing the need for inclusive and transparent AI frameworks. The study concludes with strategic implications for tourism development and offers recommendations for future research and policy integration to support ethical, data-driven, and environmentally responsible tourism systems.
Sustainable tourism, Artificial intelligence, Machine learning, Predictive analytics, Digital transformation, Tourism governance
IRE Journals:
Ifeoluwa Oreofe Oluwafemi , Tosin Clement , Oluwasanmi Segun Adanigbo , Toluwase Peter Gbenle , Bolaji Iyanu Adekunle
"Artificial Intelligence and Machine Learning in Sustainable Tourism: A Systematic Review of Trends and Impacts" Iconic Research And Engineering Journals Volume 4 Issue 11 2021 Page 468-477
IEEE:
Ifeoluwa Oreofe Oluwafemi , Tosin Clement , Oluwasanmi Segun Adanigbo , Toluwase Peter Gbenle , Bolaji Iyanu Adekunle
"Artificial Intelligence and Machine Learning in Sustainable Tourism: A Systematic Review of Trends and Impacts" Iconic Research And Engineering Journals, 4(11)