Manuscript Number : SHISRRJ236912
A Conceptual Framework for AI-Driven Sustainability in Tourism Ecosystems
Authors(5) :-Ifeoluwa Oreofe Oluwafemi, Tosin Clement, Oluwasanmi Segun Adanigbo, Toluwase Peter Gbenle, Bolaji Iyanu Adekunle This conceptual paper introduces a comprehensive four-layer framework designed to elucidate how artificial intelligence technologies can drive sustainability across tourism ecosystems. Grounded in contemporary technological paradigms and sustainability theory, the model integrates the technological, operational, behavioral, and governance dimensions to capture AI’s multifaceted role in enhancing energy efficiency, personalizing visitor experiences, optimizing resource use, and supporting adaptive governance. The framework addresses critical gaps in current tourism innovation discourse by positioning AI not merely as a tool for marketing or logistics, but as a systemic agent facilitating sustainable development across the tourism value chain. By outlining pathways for AI-readiness assessment, strategic intervention design, and real-time monitoring, the study offers actionable guidance for researchers, policymakers, and destination planners aiming to harness AI’s potential responsibly. The paper concludes with strategic and policy implications and identifies future research directions to validate and refine the framework in diverse tourism contexts empirically.
Ifeoluwa Oreofe Oluwafemi Artificial Intelligence, Sustainable Tourism, Tourism Ecosystems, AI Governance, Behavioral Adaptation, Smart Tourism Infrastructure Publication Details Published in : Volume 6 | Issue 3 | May-June 2023 Article Preview
Ministry of Art, Culture and Tourism, Ekiti, Nigeria
Tosin Clement
University of Louisville, Louisville, KY USA
Oluwasanmi Segun Adanigbo
Remis Limited, Lagos, Nigeria
Toluwase Peter Gbenle
Soft Switch, Roswell, Georgia, USA
Bolaji Iyanu Adekunle
Data Scientist, GSFEN Limited, Nigeria
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Date of Publication : 2023-06-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 124-135
Manuscript Number : SHISRRJ236912
Publisher : Shauryam Research Institute
URL : https://shisrrj.com/SHISRRJ236912