Big Data and Artificial Intelligence Application in Travel Industry

This investigative report highlights the significant impact of big data and artificial intelligence within the travel industry. It details the roles of both technologies, emphasizing how big data analytics and AI enhance customer experiences, optimize pricing, and improve operational efficiency. The report discusses the progress of these technologies over the years, including advancements in data storage and customer behavior analysis. Furthermore, it outlines a two-phase implementation plan for incorporating these technologies, starting with a single business unit before expanding across the entire organization, ensuring a strategic and resource-efficient adoption process. The report concludes by underscoring the transformative potential of AI and big data in creating more intelligent, personalized, and competitive travel services.

Running head: APPLICATION OF BIG DATA AND ARTIFICIAL INTELLIGENCE
Application of Big Data and Artificial Intelligence
Name of the Student
Name of the University
Author Note:

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Executive Summary
The foremost adjective of the investigative report is to highlight the impact of big data and
artificial intelligence in the travel industry. The two technology and their role in the travel
industry will be professional described in this investigative report. The role of the big data
analytics and artificial intelligence will be presented separately in this report. The progress of the
two technologies over the years in the travel industry will be stated in the paper along with that
the report will be concluding with a successful implementation plan which are currently being
used in the global travel organizations.

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Table of Contents
1. Introduction..................................................................................................................................3
2. Role of Big data in travel industry...............................................................................................3
3. Role of AI in travel industry........................................................................................................3
4. Progress of the two technologies.................................................................................................3
5. Incorporation procedure of the two technologies........................................................................3
6. Conclusion...................................................................................................................................3
7. Reference.....................................................................................................................................3

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1. Introduction
The foremost determination of the investigative report is examining the application of the
big data in the tourism industry. The paper will be focussing on the detailed role of the big data
analytics in the travel industry as well as the role of artificial intelligence in the same industry
(Najafabadi et al., 2015). The progress of this technology over the years will be stated in the
paper with primary importance, along with that the investigative report will be also be focussing
in the incorporation procedure of the two stated technologies.
2. Role of Big data in travel industry
The extensive development in the field of information technology has resulted in the
growth of the big data in wide range of industries such as the travel industry (Alaei, Becken &
Stantic, 2017). Cloud based analytical techniques are increasingly been used in the travel
industry where data are present in both structured and unstructured manner. Important business
decisions can be taken by the management team of the organization with the help of big data
technologies such as Hadoop. The needs and requirements of the customers of the travel industry
are always changing with time the application of the big data can be successfully implemented in
the business environment of the travel industries (Loebbecke & Picot, 2015). The searching of
the destinations arranging local cuisines and personalized customer experience in the trips are the
primary contribution of this technology in this industry. Better marketing strategies can be
chosen by this governmental organization to deal with the robust environments (Bowen &
Whalen, 2017). The application of improved technologies such as the big data analytics is very
much beneficial for the travel industry as it provides them a competitive advantage over the other
similar rival organizations (Mariani et al., 2018). The operations efficiency among the internal

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stakeholders of this business such as the social; media team or customer satisfaction team can be
successfully enhanced with AI and big data (Helbing et al., 2019). Optimization of the price of
the good and services offered by the travel organizations can be revised based upon the data
which are managed using the big data analytics (Zou et al., 2016). The inaccuracies of the data
management in this industry can be solved effectively with the help of this advanced technology.
3. Role of AI in travel industry
Customer engagement and communication with the customers are the two most important
business aspect of the travel industry which are carefully managed with the help of the advanced
machine learning techniques used in artificial intelligence. The interactions with the customers
can be enhanced with the application of the intelligent agents (Chen, Huang & Huang, 2016).
The future directions of the organizations considering the current market trends can be evaluated
with the help of artificially intelligent systems. The existing conventions sales and marketing
strategies are constantly being revised by artificially intelligent bots in the global business
organizations of the travel industry. Automated personalized travel mechanisms systems are used
in the vehicles used in the travel industries (Pieroni et al., 2018). Delivery of the products and
services in time is a challenge for most of the travel organizations which can be resolved quite
effectively with the help of the language processing specification of artificial intelligent systems
(Baggio, 2016). The application of the chatbots have been hugely successful in the travel
industry where it is capable enough to understand the needs and requirements of the customers.
Decision making is a significant aspect of the travel industry which can be improved more
intelligent systems are installed in the travel industry. The online customer service can be
significantly improved with the help of artificial intelligence techniques (Hurwitz, Kaufman &
Bowles, 2015). Data analysis and data processing can be dome in a more useful way with the

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help of artificial intelligent machines. The incorporation of the virtual reality and the augmented
reality is the other trending aspect of artificial intelligence in the travel industry.
4. Progress of the two technologies
The application of artificial intelligence and big data in the travel industry has improved
over the year. The progress of big data analytics started after the year 2005 and since then it is
constantly being used in different industries as well. The two technologies have seen many ups
and down over the years. The bigger volume of data is managed in a better way using big data
and artificial intelligence. The application of the big data analytics changed after the
incorporation of the second version of the big data analytics. Storage of the data are much more
secure these days due to the progress of big data analytics. The raw data of the travel industry
can be managed effectively with the help of the big data (Klous, 2016). Traditional data sets of
the travel industries are also managed professionally using big data analytics. Understanding the
behaviours of the clients are the other important business aspect of this industry which are solved
with the help of the advanced mechanisms of artificial intelligence. The development in IT has
resulted in the growth of many new technologies and the subcategories if artificial intelligence
systems are one of them, these includes artificial general intelligence, artificial super intelligence
and artificial narrow intelligence.
5. Incorporation procedure of the two technologies.
Incorporation of the machine learning technique are very much useful for the travel
industries as it helps in improving the profit percentage of this industry. Data governance plan
can be implemented as it helps in minimising all the risks and challenges associated with the
technology. The incorporation of the new technology requires the support from the lawsuits.

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Security breaches and the other data related risks are the main concern in the implementation of
the two discussed technologies.
The implementation of artificial intelligence in the travel industry has to be done very
carefully as it helps in minimising the workload of the organization. The efficient recruitment
policy of the organization is very much needed for the incorporation of AI based systems in the
travel industry. Effective training sessions can be very much useful for the implementation of
artificial intelligence in travel industry (Xiang & Fesenmaier, 2017). The limitations of the
technology can be well understood with the help of the training sessions. Considering both the
two technologies the implementation procedure is as followings:
Phase 1: The technology can be implemented in a single business unit of the travel
industry such as the online customer experience department. A report should be developed by the
project manager of that unit of the organization.
Phase 2: Based on the report, the entire business area can be considered for the
implementation of the two technology.
6. Conclusion
The investigative report was very much useful to understand the impact of artificial
intelligence and big data in the travel industry. The role of the big data along with its
specifications it provides which are used in the travel industry is stated clearly in this paper. The
impact of technologies such as Hadoop can be understood with the help of the paper. The paper
also concludes the different categories of artificial intelligence which are being used in the travel
industries for a long period of time. The business aspects which are categorically improved with
the help of these two technologies such as the improved customer engagement and better

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communication service has been stated in the paper. The progress of the two technologies have
been presented in the paper as well. The incorporation of the two technologies in the travel
industry has been stated in the paper as well. The implementation procedure of the two
technologies can also be concluded from this investigative report. The two-phase plan is
described in the later stages of the report helps in understanding the importance of the available
utilization of the resources in the travel industry.

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7. Reference
Alaei, A. R., Becken, S., & Stantic, B. (2017). Sentiment Analysis in Tourism: Capitalizing on
Big Data. Journal of Travel Research, 0047287517747753.
Baggio, R. (2016). Big Data, Business Intelligence and Tourism: a brief analysis of the literature.
IFITTtalk@ Östersund: Big Data & Business Intelligence in the Travel & Tourism
Domain.
Bowen, J., & Whalen, E. (2017). Trends that are changing travel and tourism. Worldwide
Hospitality and Tourism Themes, 9(6), 592-602.
Chen, S., Huang, Y., & Huang, W. (2016, March). Big data analytics on aviation social media:
The case of china southern airlines on sina weibo. In Big Data Computing Service and
Applications (BigDataService), 2016 IEEE Second International Conference on (pp. 152-
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Helbing, D., Frey, B. S., Gigerenzer, G., Hafen, E., Hagner, M., Hofstetter, Y., ... & Zwitter, A.
(2019). Will democracy survive big data and artificial intelligence?. In Towards Digital
Enlightenment (pp. 73-98). Springer, Cham.
Hurwitz, J. S., Kaufman, M., & Bowles, A. (2015). Cognitive computing and big data analytics.
John Wiley & Sons.
Klous, S. (2016). Sustainable harvesting of the big data potential. Exploring the Boundaries of
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Loebbecke, C., & Picot, A. (2015). Reflections on societal and business model transformation
arising from digitization and big data analytics: A research agenda. The Journal of
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Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business intelligence and big data
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Zou, L., Liu, Q., Zhang, C., & Yang, H. (2016, September). An approach to applying creative
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