Akuntansi

Artificial Intelligence (AI) in Improving Sustainable Development Goals (SDGs) for Smart Tourism Program

Oleh: Yustin Nur Faizah S.Tr.Ak.,M.Ak.,Ak.

Sumber: Freepik

Smart tourism is a modern approach that utilizes digital technology to improve the tourism experience, operations, and sustainability of the tourism sector(Pencarelli, 2020). One technology that is increasingly dominant in smart tourism programs is Artificial Intelligence (AI). (Y. N. Faizah, 2024)The use of AI in tourism not only helps improve operational efficiency and service quality, but also has great potential in supporting the achievement of Sustainable Development Goals (SDGs)(Y. nur Faizah, 2024).

  • Improving Energy Efficiency and Natural Resource Management (SDG 7 and 12).

AI can be used to optimize energy use and natural resource management in tourist destinations. For example, AI can predict energy consumption patterns in hotels or other tourist facilities(Casteleiro-Roca et al., 2019), thereby reducing excessive energy use. In addition, AI can monitor water usage and waste, helping tourist destinations manage resources more efficiently and environmentally friendly(Khan et al., 2024).

  • Reducing Carbon Footprint and Pollution (SDG 13)

AI can also play an important role in minimizing the environmental impact of tourism activities. AI technologies, such as data analytics and machine learning, can be used to predict air pollution levels and optimize transportation routes to reduce carbon emissions(Masood & Ahmad, 2021). In addition, AI can assist in monitoring environmental quality such as water and air quality (Zhang et al., 2021), and provide early warning of potential environmental damage(Lamsal & Kumar, 2020).

  • Improved Quality and Accessibility of Tourism for All (SDGs 10 and 11)

AI can also improve inclusivity in tourism by making destinations more accessible to everyone, including individuals with special needs. For example, AI systems can be used to translate information in multiple languages(Kolhar & Alameen, 2021), provide automated translation services for foreign travelers, or create more detailed digital maps to assist travelers with disabilities(Ali et al., 2023).

  • Strengthening Local Economies and Community Empowerment (SDG 8)

By utilizing AI, tourist destinations can improve their competitiveness and support the local economy. AI can help micro, small, and medium enterprises (MSMEs) in the tourism sector by providing data analysis on traveler trends, customer preferences, and consumer behavior (Sulaiman et al., 2020). This information allows MSMEs to make better business decisions and customize their offerings to better suit market needs.

  • Advancing Sustainability Education and Knowledge (SDG 4)

AI can support education and knowledge about sustainability in tourism by providing travelers with relevant information and recommendations on how to travel responsibly. For example, AI-based apps can provide suggestions on local eco-friendly eateries (Bakshi & Singh, 2024), events or activities that focus on nature conservation, and ways to reduce carbon footprint during travel(Grofelnik et al., 2023).

  • Protecting and Sustaining Cultural and Natural Heritage (SDG 11)

AI can help protect cultural and natural heritage by facilitating the monitoring and management of historic sites and conservation areas. Through the use of AI technologies, such as computer vision and image analysis(Kakani et al., 2020), destination managers can monitor possible damage to historic buildings or the natural environment and take necessary precautions(Becken & Hughey, 2013).

Conclusion

The integration of AI in smart tourism programs has great potential to support the achievement of the SDGs. By improving energy efficiency, reducing carbon footprints, strengthening inclusivity, advancing local economies, and protecting cultural heritage, AI not only helps to improve tourist experiences, but also creates more sustainable and responsible tourism. In this digital age, collaboration between technology and the tourism sector is key to a better future.

Reference

Ali, F., Cain, L., Legendre, T. S., & Wu, L. (2023). The Intersection of Technology, Accessible Tourism and Tourists With Intellectual Disabilities: Proposing a Novel Conceptual Framework. Journal of Hospitality & Tourism Research, 47(4), NP76–NP90. https://doi.org/10.1177/10963480221142499

Bakshi, N., & Singh, A. K. (2024). AI-Enabled Smart Buildings Reducing the Carbon Footprint and Enhancing Guest Experiences in Eco-Friendly Hotels (pp. 79–98). https://doi.org/10.4018/979-8-3693-7898-4.ch005

Becken, S., & Hughey, K. F. D. (2013). Linking tourism into emergency management structures to enhance disaster risk reduction. Tourism Management, 36, 77–85. https://doi.org/10.1016/j.tourman.2012.11.006

Casteleiro-Roca, J.-L., Gómez-González, J., Calvo-Rolle, J., Jove, E., Quintián, H., Gonzalez Diaz, B., & Mendez Perez, J. (2019). Short-Term Energy Demand Forecast in Hotels Using Hybrid Intelligent Modeling. Sensors, 19(11), 2485. https://doi.org/10.3390/s19112485

Faizah, Y. N. (2024, January). Accountant VS Artificial Intelligence. Buletin NSC. https://buletin.nscpolteksby.ac.id/accountant-vs-artificial-intelligence/

Faizah, Y. nur. (2024, May). Memahami Sustainable Development Goals (SDGs). Buletin Politeknik NSC, 37–39. https://buletin.nscpolteksby.ac.id/memahami-sustainable-development-goals-sdgs/

Grofelnik, H., Perić, M., & Wise, N. (2023). Evaluating the travel carbon footprint of outdoor sports tourists. Journal of Outdoor Recreation and Tourism, 43, 100678. https://doi.org/10.1016/j.jort.2023.100678

Kakani, V., Nguyen, V. H., Kumar, B. P., Kim, H., & Pasupuleti, V. R. (2020). A critical review on computer vision and artificial intelligence in food industry. Journal of Agriculture and Food Research, 2, 100033. https://doi.org/10.1016/j.jafr.2020.100033

Khan, N., Khan, W., Humayun, M., & Naz, A. (2024). Unlocking the Potential: Artificial Intelligence Applications in Sustainable Tourism. In The Role of Artificial Intelligence in Regenerative Tourism and Green Destinations (pp. 303–316). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-746-420241020

Kolhar, M., & Alameen, A. (2021). Artificial Intelligence Based Language Translation Platform. Intelligent Automation & Soft Computing, 28(1), 1–9. https://doi.org/10.32604/iasc.2021.014995

Lamsal, R., & Kumar, T. V. V. (2020). Artificial Intelligence and Early Warning Systems (pp. 13–32). https://doi.org/10.1007/978-981-15-4291-6_2

Masood, A., & Ahmad, K. (2021). A review on emerging artificial intelligence (AI) techniques for air pollution forecasting: Fundamentals, application and performance. Journal of Cleaner Production, 322, 129072. https://doi.org/10.1016/j.jclepro.2021.129072

Pencarelli, T. (2020). The digital revolution in the travel and tourism industry. Information Technology & Tourism, 22(3), 455–476. https://doi.org/10.1007/s40558-019-00160-3

Sulaiman, E., Derbani, A., & Adawiyah, W. (2020). Digital Marketing in Culinary Tourism : A Case of Micro, Small and Medium Enterprises (MSMEs) in Indonesia. Proceedings of the 2nd International Conference of Business, Accounting and Economics, ICBAE 2020,  5 – 6 August 2020, Purwokerto, Indonesia. https://doi.org/10.4108/eai.5-8-2020.2301123

Zhang, X., Shu, K., Rajkumar, S., & Sivakumar, V. (2021). Research on deep integration of application of artificial intelligence in environmental monitoring system and real economy. Environmental Impact Assessment Review, 86, 106499. https://doi.org/10.1016/j.eiar.2020.106499

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