AI in Tourism: Case Studies on ChatGPT and Amazon Web Services – Part 5 of 8

Circuit board and AI micro processor by By MegiasD

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This is Part 5 of a 8-blog posts series “Exploring the Intersection of Artificial Intelligence and Tourist Experiences: Insights into AI-Driven Customization and Its Impact on Tourism”.

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3.3 ChatGPT: A Game-Changer for e-Tourism

The digital age has ushered in a new era for the tourism industry, with AI and conversational systems like ChatGPT leading the transformation. Drawing from the insights of Luisa Mich & Roberto Garigliano (Mich. L. et al., 2023), this case study delves into ChatGPT’s potential in e-tourism.

While traditional chatbots have their limitations, ChatGPT, developed by OpenAI, offers a fresh perspective. Its capabilities range from writing and translating to creating multimedia content. In e-tourism, its applications span from identifying new markets to innovating business processes.

Implementation Highlights:

  • Integration with existing databases and digital technologies.
  • Specialization for specific domains.
  • Leveraging OpenAI resources and other AI tools.
  • Developing new use cases for a competitive edge.

Results & Evaluation:

While ChatGPT’s integration in e-tourism is nascent, its potential is undeniable. Its human-like content creation capability offers avenues for innovation in tourism.

Challenges & Limitations:

  • Semantic understanding limitations.
  • Potential for inaccurate outputs.
  • Lack of transparency in results.
  • Ethical concerns.

In essence, ChatGPT’s role in e-tourism is transformative, offering unparalleled personalization and efficiency. However, its ethical and operational challenges necessitate careful implementation.


3.4 Amazon Web Services: Pioneering AI-Driven Hyper-Personalization in Travel

The travel industry is undergoing a seismic shift towards hyper-personalization, with AI as the catalyst. Amazon Web Services (AWS) is spearheading this change, partnering with major players in the travel sector.

AWS’s vision for AI in travel is clear: a revolution in hyper-personalized customer service. Their collaboration with Hyatt exemplifies this, resulting in a staggering $40 million revenue boost within half a year (Dawes, 2023).

The industry’s trajectory is towards abundant hyper-personalized content, tailored to individual customer data. Greg Land of AWS envisions this as the norm by year-end (Dawes, 2023).

However, the challenge lies in data quality. Many companies grapple with inconsistent data. AWS’s solution? A dedicated platform for hospitality companies to capture high-quality data (Dawes, 2023).

In conclusion, AWS’s foray into AI-driven hyper-personalization paints a promising picture for the future of travel. Their collaboration with the travel sector promises a new age of travel experiences, tailored to every individual’s unique preferences.

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Previous posts:

AI in Tourism: Revolutionizing Personalized Experiences and Operational Efficiency – Part 1 of 8:
https://www.andrearossi.it/en/ai-tourism-personalized-experiences-operational-efficiency/

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AI-Powered Personalization: Elevating Tourist Experiences – Part 2 of 8:
https://www.andrearossi.it/en/ai-powered-personalization-elevating-tourist-experiences/

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AI’s Role in Crafting Personalized Tourist Experiences: A Literature Review – Part 3 of 8:
https://www.andrearossi.it/en/ai-tourist-experiences-literature-review/

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Revolutionizing Tourism with AI: Case Studies on Hotel Recommendations and Smart City Experiences – Part 4 of 8

https://www.andrearossi.it/en/tourism-ai-case-studies-hotel-smart-city-experiences/

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#TourismTech #ChatGPT #AmazonWebServices #AIinTourism #HyperPersonalization #eTourism #TravelInnovation #CaseStudies #DigitalTransformation #FutureOfTravel

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References

  • AIFinesse. (2023). AI in Tourism: 2023 and Beyond. Retrieved from https://www.aifinesse.com/ai-in-tourism-2023-and-beyond/
  • Amadeus. (2023). Artificial Intelligence | Amadeus. https://amadeus.com/en/solutions/airlines/artificial-intelligence
  • Booking.com. (2018). Booking.com reveals the top travel predictions for 2019. Retrieved from https://globalnews.booking.com/bookingcom-reveals-the-top-travel-predictions-for-2019/
  • Buhalis, D. (2020). Technology in tourism-from information communication technologies to eTourism and smart tourism towards ambient intelligence tourism: a perspective article. Tourism Review.
  • Buhalis, D., & Leung, R. (2020). Smart hospitality—Interconnectivity and interoperability towards an ecosystem. International Journal of Hospitality Management, 85, 102433.
  • Buhalis, D., & Moldavska, A. (2022). Smart tourism and competitive advantage for stakeholders. Tourism Review.
  • Chan, N. L., & Guillet, B. D. (2018). Investigation of social media marketing: how does the hotel industry in Hong Kong perform in marketing on social media websites? Journal of Travel & Tourism Marketing, 31(8), 961-972.
  • Chen, Y., Xu, Z., & Gretzel, U. (2020). The impact of artificial intelligence-powered personalization on tourist satisfaction: A large-scale field experiment. Tourism Management, 80, 104170.
  • Chunduri, P. K. (2020). Effects of Use of Personalised Artificial Intelligence and Robot Application on Customer Service in the Tourism Industry. International Journal of Advanced Science and Technology, 29(12), 1594-1600.
  • Dataconomy. (2023). Is AI Technology The Future Of Travel? Retrieved from https://dataconomy.com/2023/08/03/is-ai-technology-the-future-of-travel/
  • Dawes, J. (2023). Amazon Web Services Execs on AI ‘Hyper-Personalization’ in Travel. Skift. Retrieved from https://skift.com/2023/06/27/amazon-web-services-execs-on-ai-hyper-personalization-in-travel/
  • Dunne, D. (2022). The Future Of Personalization In The Travel Industry. Forbes. Retrieved from https://www.forbes.com/sites/danadunne/2022/01/27/the-future-of-personalisation-in-the-travel-industry/
  • Dwivedi, Y. K., Hughes, D. L., Coombs, C., Constantiou, I., Duan, Y., Edwards, J. S., … & Upadhyay, N. (2023). Impact of COVID-19 pandemic on information management research and practice: Transforming education, work and life. International Journal of Information Management, 55, 102211.
  • Forbes Advisor. (2023). 25 Astonishing AI Statistics for 2023. Retrieved from https://www.forbes.com/advisor/business/ai-statistics/
  • GlobeNewswire. (2023). Artificial Intelligence (AI) in Travel and Tourism Thematic Intelligence Report 2023. Retrieved from https://www.globenewswire.com/news-release/2023/08/03/2718144/0/en/Artificial-Intelligence-AI-in-Travel-and-Tourism-Thematic-Intelligence-Report-2023.html
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
  • Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2018). Smart tourism: Foundations and developments. Cham: Springer International Publishing.
  • Gupta, S., Modgil, S., Lee, CK. et al. The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry. Inf Syst Front 25, 1179–1195 (2023). https://doi.org/10.1007/s10796-022-10271-8
  • Gursoy, D., Chi, C. G. Q., Lu, L., & Nunkoo, R. (2019). Antecedents and outcomes of travelers’ information-seeking behavior in the context of AI. Journal of Travel Research, 0047287519868314.
  • Inanc-Demir, L., & Kozak, M. (2019). The role of artificial intelligence in tourism. In Tourism in the City (pp. 221-232). Springer.
  • Koegler, S. (2023). AI Technology in Tourism: Personalized Experiences. AI & Machine Learning Tech Brief. Retrieved from https://www.aimltechbrief.com/index.php/bigdata/item/7561-ai-technology-in-tourism-personalized-experiences
  • Kong, H., Wang, L., & Fu, X. (2022). Artificial intelligence in tourism: state of the art and future research directions. Journal of Travel Research, 0047287520962792.
  • Leung, R. (2020). Developing a conceptual model for smart tourism research: a sustainability perspective. Sustainability, 12(9), 3832.
  • Li, X., Law, R., Vu, H. Q., Rong, J., & Zhao, X. (2018). Identifying emerging hotel preferences using Emerging Pattern Mining technique. Tourism Management, 67, 370-383.
  • Li, X., Wang, D., Andergassen, R., Huang, Y., & Zeng, B. (2020). Personalized travel recommendation: integrating the strengths of content-based and collaborative filtering. Information Technology & Tourism, 22, 555–573.
  • Li, X., Wang, D., Liang, X., Huang, D. (2020). China’s smart tourism destination initiative: A taste of the service-dominant logic. Journal of Travel Research, 0047287520913410.
  • Lv, Z., Song, H., Basiri, A., Jackson, M., & Kitchin, R. (2022). Recommender systems in tourism: state of the art and future directions. Tourism Review.
  • McCartney, G., & McCartney, A. (2020). The impact of artificial intelligence on the future of tourism. International Journal of Tourism Cities.
  • McKinsey & Company. (2018). An AI nation: Harnessing the opportunity of artificial intelligence in Denmark. Retrieved from https://www.mckinsey.com/~/media/McKinsey/Featured%20Insights/Europe/Harnessing%20the%20opportunity%20of%20artificial%20intelligence%20in%20Denmark/An-AI-nation-Harnessing-the-opportunity-of-AI-in-Denmark.pdf
  • Mich, L., Garigliano, R. ChatGPT for e-Tourism: a technological perspective. Inf Technol Tourism 25, 1–12 (2023). https://doi.org/10.1007/s40558-023-00248-x
  • Mileva, G. (2023). Top 10 AI Trends That Will Transform Businesses in 2023. Influencer Marketing Hub. Retrieved from https://influencermarketinghub.com/ai-trends/
  • O’Flaherty, K. (2023). 3 tech trends that will dominate the travel industry in 2023. The Next Web. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Pang, B., Chen, Y., & Zhang, X. (2020). The impact of AI-powered personalization on tourist experiences: A review of literature. Tourism Management, 79, 104064.
  • Philip L. Pearce, Mao-Ying Wu, Manuela De Carlo, Andrea Rossi “Contemporary experiences of Chinese tourists in Italy: An on-site analysis in Milan” nella rivista internazionale “Tourism Management Perspectives” 7 (2013) 34–37, Ed. Elsevier ltd (retrieved from https://www.academia.edu/4027130/Contemporary_experiences_of_Chinese_tourists_in_Italy)
  • Petar. (2023). The Future of AI in Tourism: Analyzing the Potential for Personalization and Experience Enhancement. Medium. Retrieved from https://medium.com/@peco4312/the-future-of-ai-in-tourism-analyzing-the-potential-for-personalization-and-experience-enhancement-b676e7ac58a8?source=rss——-1
  • PR Newswire. (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Ramzan, B., Bajwa, I.S., Jamil, N., & Mirza, F. (2019). An Intelligent Data Analysis for Hotel Recommendation Systems using Machine Learning. ArXiv, abs/1910.06669.
  • Research and Markets (2023). Global Artificial Intelligence (AI) in Travel and Tourism Intelligence Report 2023: AI-Driven Technologies Disrupting Travel, Enhancing Efficiency and Personalization. Retrieved from https://www.prnewswire.com/news-releases/global-artificial-intelligence-ai-in-travel-and-tourism-intelligence-report-2023-ai-driven-technologies-disrupting-travel-enhancing-efficiency-and-personalization-301891840.html
  • Revfine. (2023). 13 Key Technology Trends Emerging in the Travel & Tourism Industry. Retrieved from https://www.revfine.com/technology-trends-travel-industry/
  • Roh, S., Park, D., & Kim, J. (2020). The role of AI-powered personalization in tourism: A case study of a major South Korean travel agency. Journal of Travel Research, 59(2), 270-284.
  • Rossi Andrea (2020) “La comunicazione del turismo ai tempi del coronavirus” inserito nel fascicolo monografico del “Semestrale di studi e ricerche di Geografia”, dedicato all’impatto socio-territoriale della pandemia, “Epidemia, spazio e società. Idee e analisi per il dibattito e le politiche pubbliche” a cura di Angelo Turco, ISSN 1125-5218, pp. 57-71, XXXII, Fascicolo 2, luglio-dicembre 2020 (retrieved from https://www.semestrale-geografia.uniroma1.it/index.php/semestrale-geografia/article/view/17032/16354)
  • Rossi Andrea (2022), “Comunicazione Digitale per il Turismo”, Self-Publishing, Vercelli, 2022 – ISBN 9791221004175
  • Rossi Andrea (2023). “Il Buono, il Brutto e il Cattivo: Il “Triello” Del Metaverso”. Documenti geografici, 0(2), 673-678. doi:http://dx.doi.org/10.19246/DOCUGEO2281-7549/202302_47 (retrieved from https://www.documentigeografici.it/index.php/docugeo/article/view/478)
  • Rossi Andrea, Goetz Maurizio (2011) “Creare offerte turistiche vincenti con Tourist Experience Design”, ed. Hoepli, Milano, 2011
  • Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson.
  • Saha, T. (2019). AI is Reimagining Travel Personalisation. Towards Data Science. Retrieved from https://towardsdatascience.com/ai-is-reimagining-travel-personalisation-c72685faa378
  • Samara, E., Tsimitakis, E., & Vasilakis, C. (2020). Artificial intelligence (AI) applied in Tourism: A Bibliometric review. In Proceedings of the 2nd International Conference on Tourism Research (pp. 1-10).
  • Stylos, N., Vassiliadis, C. A., Bellou, V., & Andronikidis, A. (2021). Destination images, holistic images and personal normative beliefs: Predictors of intention to revisit a destination. Tourism Management, 31(5), 525-545.
  • TheNextWeb. (2023). 3 tech trends that will revolutionize the travel industry in 2023. Retrieved from https://thenextweb.com/news/3-tech-trends-travel-industry-2023
  • Wang, Y., & Li, S. (2020). The impact of AI-powered personalization on tourist satisfaction: A case study of a Chinese travel website. International Journal of Tourism Research, 22(5), 721-732.
  • Xiang, Z., & Gretzel, U. (2019). Artificial intelligence in tourism: A review of recent research. Tourism Management, 70, 304-326.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51-65.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2020). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 77, 104041.
  • Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2022). Artificial intelligence in tourism and hospitality: Bibliometric analysis and research agenda. Journal of Hospitality and Tourism Technology, 13(1), 1-20.
  • Yue, X., Li, X., & Li, Y. (2021). The future of tourism experience: A review of AI technology. Journal of Hospitality and Tourism Technology, 12(2), 244-259.
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