Hilton Hotels is one of the world’s leading hospitality companies, with over 5,000 properties in over 100 countries (Jiang and en, 2020). Hilton Hotels offers guests various accommodations, from luxury suites to budget-friendly rooms. Hilton Hotels also offers catering, event planning, and concierge services. Hilton Hotels is committed to providing guests with an exceptional experience and strives to be a leader in the hospitality industry (Cameroon and green,2019).
The hospitality and event industry has been significantly impacted by the economic changes resulting from the COVID-19 pandemic and the UK’s exit from the European Union. COVID-19 greatly affected hospitality, as many businesses had to close or reduce their operations. Additionally, the restrictions imposed by governments worldwide have resulted in a significant decrease in travel and tourism, further impacting the hospitality industry (Kaushi and Guleria, 2020). As such, Hilton hotels have had to find new ways to remain competitive and profitable. One potential solution to this challenge is artificial intelligence (AI) technology, a software innovation. AI technology can automate various processes, improve customer engagement, and create virtual customer experiences. This report will discuss the potential benefits of using AI technology in Hilton hotels’ hospitality and event industry and the operational and management issues hotels may face in adopting and implementing these innovations. The role of change management models in helping the Hotel to overcome these issues and successfully adopt AI technology will also be discussed.
2.0 Evaluation of artificial intelligence
Artificial intelligence (AI) is a term used to describe the use of computer systems to complete tasks that usually require human intelligence (Chen and Biswas, 2021). Firstly, AI technology automates various processes, such as customer service, event scheduling, and data analysis. This can lead to cost savings, as organizations can reduce their reliance on manual labor and increase operational efficiency. AI technology can also be used to improve customer engagement, as it can be used to analyze customer behavior and provide tailored services and experiences. Finally, AI technology can also create virtual experiences for customers, allowing them to experience events remotely (Sodhi et al., 2022).
Before AI can be successfully integrated into Hilton Hotels’ systems, several considerations need to be considered. First, the AI-based systems must be compatible with the existing systems of Hilton Hotels. This includes ensuring that the existing systems are compatible with the AI-based systems and that the AI-based systems can integrate with the existing systems (Nam et al., 2021). Additionally, the AI-based systems must be able to connect to the existing databases and APIs of Hilton Hotels. Second, AI-based systems must be able to be easily configured and managed. This includes ensuring that the AI-based systems can be easily configured to meet the specific needs of Hilton Hotels and that there are adequate tools for managing and monitoring the AI-based systems (Jabeen et al., 2022).
Additionally, AI-based systems must be able to be easily updated and maintained. Third, the AI-based systems must be able to be integrated into the existing customer service processes of Hilton Hotels. This includes ensuring that the AI-based systems can be integrated into the existing customer service processes and that the AI-based systems can be used to automate customer service tasks such as responding to customer inquiries, providing product recommendations, and resolving customer complaints. Operational and management issues (Campbell, Coldicott, and Kinsella, 2018)
3.0 Operational and management issues
The artificial intelligence model will assist the Hilton Hotel in many ways to minimize costs due to reducing manual labor. However, there are also some potential issues that the Hotel may face when attempting to adopt and implement AI technology. For example, there may be resistance from employees or customers due to concerns about privacy or the perceived loss of jobs (Agarwal, Swami, and Mulihotra, 2022). Additionally, there may be organizational barriers, such as a lack of resources or knowledge, as well as resistance to change due to a lack of leadership or a lack of understanding of the benefits of AI technology. One potential issue that Hilton may need help with when attempting to adopt and implement AI technology in the hospitality and event industry is employee resistance. This resistance may be based on concerns about job loss due to the automation of various processes. For example, AI technology can automate customer service tasks such as responding to customer queries or booking events. This could lead to job losses, as the Hotel may no longer need staff to perform these tasks (Khan, 2021).
Additionally, employees may need more understanding of the technology and its potential benefits to adopt AI technology. Another potential issue that Hilton may need is resistance from customers. This resistance may be based on concerns about privacy and security, as customers may be reluctant to share their data with an AI system (Anshari et al., 2022).
Moreover, Hilton Hotels may need more resources or knowledge to implement AI technology, thus leading to adverse outcomes successfully. In this case, the Hotel may need help to provide the resources required for employee training on using and applying artificial intelligence in their systems (Prentice et al., 2020). Additionally, the Hotel may face a lack of leadership or a lack of understanding of the potential benefits of AI technology, leading to resistance to change. Also, the management personalities may lack the required knowledge and understanding of what is the artificial intelligence model, how it is integrated into their websites and systems, and how it can be used to enhance their day-to-day operations, which will further lead to increased profitability levels (Huang et al., 2022). Lastly, many people need to learn about the developments coming up with the developing technology. This includes the customers who may resist the new technology the Hotel is developing for its day-to-day activities due to a need for more information.
4.0 Change management models
To overcome the abovementioned issues, Hilton hotels may need to utilize change management models to successfully adopt and implement AI technology (Hayes,2022). One such model is Lewin’s Unfreeze-Change-Refreeze Model, which includes several steps, such as the unfreezing stage, where Hilton can create an understanding of the need for change and identify potential resistance to prepare for the change and ensure that all stakeholders are aware of the potential resistance they may face (Koo, Curtis and Ryan,2021). During this stage, the management can assess their current resources and capabilities and identify areas needing improvement to implement AI technology, such as providing employees with the necessary training and support. In the refreezing stage, Hilton can stabilize the change by reinforcing the new behaviors and addressing any remaining resistance (Solakis et al., 2022). This helps ensure the change is successfully implemented and that any resistance is addressed. Additionally, Hilton can use this stage to assess the success of the change and identify any areas that may need to be improved to ensure the technology’s successful implementation (Popesku,2019).
Kotter’s 8-Step Change Model is another model of change that Hilton Hotels can you to overcome all that is related to artificial implementation. In the first step, Hilton can create a sense of urgency for change by highlighting the potential benefits of AI technology (Chan, Hogaboam Cao,2022). This helps ensure all stakeholders know the potential benefits and are motivated to act. In the second step, forming a powerful guiding coalition, Hilton can form a powerful guiding coalition to lead the change process. This can ensure that all stakeholders know the potential benefits and are guided in performing various activities (Berezina et al., 2019).
Moreover, in the third step, creating a vision for change, Hilton can create a vision for change by outlining the long-term economic benefits of AI technology to the Hotel and ensuring that all the project members and stakeholders are aware and they are convinced of the same. In the fifth step, empowering employees for broad-based action, organizations can provide employees with the necessary resources and support to successfully implement the change. This helps ensure that all stakeholders know the potential benefits and are motivated to take action (Stouten et al., 2018). Another step includes the generation of short-term wins where Hilton can generate short-term wins to generate momentum for the change (Solakis et al., 2022). Moreover, Hilton Hotels’ management can apply this model to institutionalize new approaches, such as providing feedback, rewards, and recognition. This can help ensure the change is successfully implemented and that any resistance is addressed (Davenport and Ronanki,2018).
The ADKAR Model also helps organizations to withstand various obstacles in their project implementations, and it consists of various stages such as the creation of awareness where; after Hilton hotel was immensely affected by covid 19 concerning several rules and guidelines that governments imposed, there was a need for change among employees and customers and that where the artificial intelligence model is coming in (Hussain et al., 2018). To successfully implement it, the hotel management should ensure that the employees, the customers, and all the organization’s stakeholders are aware of the new technology that will be incorporated into their systems and its advantages. This will motivate them to participate in the implementation, easing the activity. In the desired stage, the management should organize and cater for the employee training to equip them with the skills required to operate the artificial intelligence model. This will further give the employees the desire and urge to have the model in the hotel systems (Hayes, 2022).
Therefore, the ADKAR model is the most preferable for adoption, providing a comprehensive framework for successful change management. The ADKAR model consists of five stages: creating awareness, creating a desire, knowledge, ability, and reinforcement. Each stage of the model is designed to help organizations successfully implement change by providing employees with the necessary resources and support and addressing any resistance. The model is also designed to ensure the change is successfully implemented and that any resistance is addressed. Ultimately, by utilizing the ADKAR model, Hilton Hotels will ensure that the change is successfully implemented and that any resistance is addressed.
In summary, integrating AI technology into the hospitality and event industry can provide many benefits, such as cost savings, improved customer engagement, and virtual experiences. However, there are also potential operational and management issues that Hilton Hotels must address when attempting to adopt and implement AI technology. To successfully implement AI technology, Hilton Hotels must utilize change management models, such as Lewin’s Unfreeze-Change-Refreeze Model, Kotter’s 8-Step Change Model, and the ADKAR model. These models can help Hilton Hotels understand the need for change, form a powerful guiding coalition, create a vision for change, provide employees with the necessary resources and support, and generate short-term wins. By utilizing these change management models, Hilton Hotels can ensure that the change is successfully implemented and that any resistance is addressed. Ultimately, with the successful implementation of AI technology, Hilton Hotels can remain competitive and profitable in the hospitality and event industry.
Agarwal, P., Swami, S. and Malhotra, S.K., 2022. Artificial intelligence adoption in the post-COVID-19 new-normal and role of intelligent technologies in transforming business: a review. Journal of Science and Technology Policy Management.
Anshari, M., Hamdan, M., Ahmad, N., Ali, E. and Haidi, H., 2022. COVID-19, artificial intelligence, ethical challenges, and policy implications. Ai & Society, pp.1-14.
Berezina, K., Ciftci, O. and Cobanoglu, C., 2019. Robots, artificial intelligence, and service automation in restaurants. In Robots, artificial intelligence, and service automation in travel, tourism, and hospitality. Emerald Publishing Limited.
Cameron, E. and Green, M., 2019. Making sense of change management: A complete guide to the models, tools, and techniques of organizational change. Kogan Page Publishers.
Campbell, D., Coldicott, T. and Kinsella, K., 2018. Systemic work with organizations: A new model for managers and change agents. Routledge.
Chan, L., Hogaboam, L. and Cao, R., 2022. Artificial Intelligence in Tourism and Hospitality. In Applied Artificial Intelligence in Business: Concepts and Cases (pp. 213-229). Cham: Springer International Publishing.
Chen, Y. and Biswas, M.I., 2021. It turned crisis into opportunities: how a firm can enrich its business operations using artificial intelligence and big data during COVID-19—sustainability, 13(22), p.12656.
Davenport, T.H. and Ronanki, R., 2018. Artificial intelligence for the real world. Harvard business review, 96(1), pp.108-116.
Gerwe, O., 2021. The Covid-19 pandemic and the accommodation sharing sector: Effects and prospects for recovery. Technological Forecasting and Social Change, 167, p.120733.
Hayes, J., 2022. The theory and practice of change management. Bloomsbury Publishing.
Huang, A., Chao, Y., de la Mora Velasco, E., Bilgihan, A. and Wei, W., 2022. When artificial intelligence meets the hospitality and tourism industry: an assessment framework to inform theory and management. Journal of Hospitality and Tourism Insights, 5(5), pp.1080-1100.
Hussain, S.T., Lei, S., Akram, T., Haider, M.J., Hussain, S.H. and Ali, M., 2018. Kurt Lewin’s change model: A critical review of the role of leadership and employee involvement in organizational change. Journal of Innovation & Knowledge, 3(3), pp.123-127.
Jabeen, F., Al Zaidi, S. and Al Dhaheri, M.H., 2022. Automation and artificial intelligence in hospitality and tourism. Tourism Review, 77(4), pp.1043-1061.
Jiang, Y. and Wen, J., 2020. Effects of COVID-19 on hotel marketing and management: a perspective article. International journal of contemporary hospitality management, 32(8), pp.2563-2573.
Kaushik, M. and Guleria, N., 2020. The impact of the COVID-19 pandemic in the workplace. European Journal of Business and Management, 12(15), pp.1-10.
Kazak, A.N., Chetyrbok, P.V. and Oleinikov, N.N., 2020. Artificial intelligence in the tourism sphere. In IOP Conference Series: Earth and Environmental Science (Vol. 421, No. 4, p. 042020). IOP Publishing.
Kenny, J. and Dutt, C.S., 2022. The long-term impacts of Hotel’s strategic responses to COVID-19: The case of Dubai. Tourism and hospitality Research, 22(1), pp.71-85.
Khan, M.A., 2021. Artificial intelligence in commerce and business to deal with the COVID-19 pandemic. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(13), pp.1748-1760.
Koo, B., Curtis, C. and Ryan, B., 2021. We are examining the impact of artificial intelligence on hotel employees through job insecurity perspectives—International Journal of Hospitality Management, 95, p.102763.
Lukanova, G. and Ilieva, G., 2019. Robots, artificial intelligence, and service automation in hotels. Robots, artificial intelligence, and service automation in travel, tourism, and hospitality (pp. 157-183). Emerald Publishing Limited.
Nam, K., Dutt, C.S., Chathoth, P., Daghfous, A. and Khan, M.S., 2021. Adopting artificial intelligence and robotics in the hotel industry: Prospects and challenges. Electronic Markets, 31, pp.553-574.
Popesku, J., 2019. Current applications of artificial intelligence in tourism and hospitality. In Sinteza 2019-International Scientific Conference on Information Technology and Data Related Research (pp. 84-90). Singidunum University.
Portugal, I., Alencar, P. and Cowan, D., 2018. The use of machine learning algorithms in recommender systems: A systematic review. Expert Systems with Applications, 97, pp.205-227.
Prentice, C., Dominique Lopes, S. and Wang, X., 2020. Emotional intelligence or artificial intelligence–an employee perspective. Journal of Hospitality Marketing & Management, 29(4), pp.377-403.
Sodhi, G.K., Kaur, S., Gaba, G.S., Kansal, L., Sharma, A. and Dhiman, G., 2022. COVID-19: Role of robotics, artificial intelligence, and machine learning during the pandemic. Current Medical Imaging, 18(2), pp.124-134.
Solakis, K., Katsoni, V., Mahmoud, A.B. and Grigoriou, N., 2022. Factors affecting value co-creation through artificial intelligence in tourism: a general literature review. Journal of Tourism Futures, (ahead-of-print).
Stouten, J., Rousseau, D.M. and De Cremer, D., 2018. Successful organizational change: Integrating the management practice and scholarly literature. Academy of Management Annals, 12(2), pp.752-788.
Zhang, C. and Lu, Y., 2021. Study on artificial intelligence: The state of the art and prospects. Journal of Industrial Information Integration, 23, p.100224.