AI-Driven Hyper-Personalization in Hospitality: Application, Present and Future Opportunities, Challenges, and Guest Trust Issues

AI-Driven Hyper-Personalization in Hospitality: Application, Present and Future Opportunities, Challenges, and Guest Trust Issues

Raihana Akter Nira

Department of Nutrition and Hospitality Management, The University of Mississippi, P.O. Box 1848, University, MS, 38677, USA

DOI: https://dx.doi.org/10.47772/IJRISS.2025.90400397

Received: 11 April 2025; Accepted: 14 April 2025; Published: 19 May 2025

ABSTRACT

Artificial intelligence (AI) has significantly transformed the hospitality industry by enabling hyper-personalized guest experiences, enhancing customer satisfaction, loyalty, and overall brand perception, and enhancing operational efficiency. However, its deployment presents a dichotomy of opportunities and challenges, often framed within paradoxes such as the Personalization-Privacy Paradox. While AI-driven personalization fosters value co-creation through tailored services and convenience, it also raises concerns regarding privacy, technology anxiety, reduced human interaction, and loss of control of personal data, leading to potential value co-destruction and consumer trust issues. This review examines the future direction of AI-driven personalization in hospitality by analyzing existing literature and industry trends. It identifies key benefits, ethical considerations, and trust-related challenges, offering insights into strategies that balance AI’s advantages while mitigating risks. The paper concludes with recommendations for future research and industry practices to optimize AI’s role in hospitality.

Keywords: AI in hospitality, Hyper-personalization, Artificial intelligence applications, Personalized guest experience, Hospitality technology.

INTRODUCTION

The hospitality industry is a sector that heavily relies on delivering satisfying customer experiences, where personalized services and relevance to individual preferences are critical to success(Monteiro et al., 2023). With advancements in technology, particularly in AI, opportunities to provide more personalized experiences have grown, significantly impacting how customers interact with service providers. Personalization in the hospitality industry typically involves offering services tailored to the unique needs and preferences of each customer, from destination recommendations to accommodations and more immersive travel experiences. Previous research indicates that personalized experiences can enhance customer satisfaction, loyalty, and potential revenue growth for companies (Casaca & Miguel, 2024). AI technology enables companies to design contextually relevant experiences that dynamically adapt to changing customer preferences over time.

Consumer experience plays a decisive role in determining the success of a business, directly impacting consumer satisfaction, loyalty, and overall brand perception. In today’s fiercely competitive business environment, organizations are increasingly turning to technology to bolster their customer service capabilities. Artificial intelligence (AI) has been transformative in this realm, offering innovative solutions to meet the ever-changing expectations of customers. AI-powered customer service is fundamentally transforming how businesses engage with their clientele by delivering efficient, personalized, and proactive support (Inavolu, 2024). AI enables companies to personalize advertisements and promotions based on customer profiles, reducing wastage in marketing efforts and increasing conversion rates (Gao et al., 2023). Therefore, implementing AI to design and optimize personalization strategies presents a significant value proposition for the tourism industry. AI has demonstrated its capabilities in analyzing big data, understanding consumer behavior patterns, and delivering highly relevant recommendations to customers. Utilizing machine learning algorithms, AI processes data from various sources, such as customer search histories, personal preferences, and digital behavior, to create more connected and relevant experiences (Chaitanya et al., 2023).

However, while the benefits are substantial, the implementation of AI-driven personalization faces significant challenges, particularly regarding consumer trust and privacy concerns. Despite its potential, the hospitality industry faces significant challenges in integrating AI with consumer trust issues. While AI can provide highly specific recommendations, there are challenges in maintaining consumer trust while ensuring privacy. When users feel that their privacy (Chin et al., 2012) might be compromised, they become more cautious and selective about the information they disclose. Consequently, users may choose to withhold certain details and avoid engaging with features that require extensive personal information or even opt out of using platforms that expose them to risk. AI-driven personalization heavily relies on data (Amil, 2024).

Guest beliefs and behaviors toward technology solutions are often mirrored by their level of trust in the associated technologies (Mcknight et al., 2011). However, establishing guest trust with technology solutions can be fundamentally challenging (Lin et al., 2014), and trust could be adversely impacted by a variety of negative encounters, such as credit card fraud and data breaches (Chen, 2021). Balancing guest anticipation for transformative technologies, such as services supported by artificial intelligence (AI), with consumer expectations for personal information privacy could be a major dilemma for many businesses, including hospitality (West & Allen, 2020). This study seeks to investigate the application of AI in designing personalization strategies to enhance the quality of customer experiences and examine the opportunities, challenges, and consumer trust issues in the hospitality industry. In the era of digital technology, the adoption of artificial intelligence (AI) is crucial. It has presented a lot of possibilities and challenges to a variety of industries, including the hotel sector, since its start. Similarly, when converting invention into a global economy, AI must be considered. The development of numerous AI-powered technologies has the potential to boost the economy by improving people’s quality of life (Khalid et al., 2024; Limna et al., 2021; Siddiqui, 2023). The modern hospitality sector is characterized by intense competition, a plethora of new technology, consumers who want exceptional service, a major source of innovation, and ongoing difficulty due to growing expenses.  In order to improve consumer service and experience, the hospitality and tourism sector is utilizing cutting-edge technology like artificial intelligence and robotics (AIR). These technological innovations are being utilized to enhance the user experience and have been converted into intelligent instruments for customer service (Goel et al., 2024). According to (Limna et al., 2021) and  (Tong-On et al., 2021), a number of firms use AI-powered technologies, like Facebook Ads, LINE Ads, and point of sale (POS), to improve business performance and preserve a competitive edge. In order to optimize daily operations and ensure their guests receive high-quality service, tourism, and hospitality enterprises can benefit greatly from AI and automation technologies (Drexler & Lapré, 2019; S. Kumar et al., 2021).

Artificial Intelligence (AI)

Artificial intelligence (AI) is defined as a thinking capability generated by humans. The term AI is derived from two words: artificial, which means something created by humans, and intelligence, which means the capacity to think for oneself (Limna et al., 2021). Artificial Intelligence (AI) is the ability of computers or machines to simulate human intelligence in information processing, problem solving, and decision making (Harahap et al., 2024). AI is the process by which machines, especially computer systems, mimic human intellect (Wang et al., 2020). Artificial intelligence appears to be excellent at certain activities. By empowering computers to make intelligent choices that lead to more effective operations, it also revolutionizes practically every area of a nation’s economy (Holzinger et al., 2021; S. Kumar et al., 2021). In the same vein, A collection of technologies that can mimic human ability in problem-solving is commonly referred to as artificial intelligence (Lai & Hung, 2018). From early conceptualizations in which AI was defined as possessing some sort of intelligence to more recent definitions and conceptualizations in which AI is defined as having the capacity to act independently on vast amounts of data (Sterne, 2017), the idea of AI has changed over time (Buhalis et al., 2019).

Artificial Intelligence in the Hospitality Industry

According to Rosário and Dias (Rosário & Dias, 2022), technological advancements like artificial intelligence (AI)-powered tools are anticipated to help companies in the digital economy shift to more digital methods of managing, coordinating, and functioning as well as facilitating transformation in a number of organizational processes. Because of the potential impacts on customer satisfaction and service quality, research in the hospitality and tourism sectors is keen to understand how AI technologies impact employee engagement, retention, and productivity levels (Ruel & Njoku, 2021). Technology advancements in AI, robotics, and big data are helping the hotel sector change quickly (Reis et al., 2020). AI-enhanced hotel and tourist operations and management systems, for example, apply intelligence to the hospitality sector, making it an intelligent hotel and tourism sector (Ruel & Njoku, 2021). As AI-powered smart services and robots, such AI-based chatbot technologies, are utilized to support human intelligence and physical capabilities, AI is also employed to enable service innovation in the individualized service delivery sector of the hospitality industry (Chi et al., 2020).  The productivity of employees is significantly impacted when AI technologies are used to provide services in the hospitality sector. A deeper comprehension of how AI technologies can impact service quality, customer satisfaction, and loyalty through employee-related outcomes like employee engagement, productivity, and service quality is necessary because AI service quality significantly contributes to overall service quality in the hospitality industry through employee service quality (Prentice et al., 2020). Thus, in many respects, artificial intelligence is essential to the hotel sector. Hotel, tourist, food and beverage, and meeting and event enterprises are among the industries that heavily rely on modern technological applications like artificial intelligence (AI) and robotics (Drexler & Lapré, 2019; Yan, 2020). Applications for artificial intelligence systems in hospitality are numerous. From a consumer standpoint, artificial intelligence (AI) enhances decision-making, increases mobility, helps consumers locate better and more pertinent information, and, in the end, improves the travel experience (Gretzel, 2011; I. Tussyadiah & Miller, 2019).

Different types of AI in Hospitality

The majority of businesses, including the travel and hospitality sector, now embrace artificial intelligence technologies in this era of digitization. The industry is able to provide guests with a novel experience due to the artificial intelligence technology (Samala et al., 2020). Language translators, chatbots, virtual assistants, AI-powered site search, self-service screens and kiosks, virtual and augmented reality, booking systems, biometric data recognition, QR codes, drones, and robots are a few examples of AI technologies (Bulchand-Gidumal, 2022a; Sousa et al., 2024a).

Types of AI in the Hospitality Industry and Their Applications

AI-Driven Hyper-Personalization in Hospitality

In the hospitality sector, hyper-personalization uses AI and big data to deliver experiences that are specifically catered to each guest’s preferences, prior actions, and current requirements. This strategy, in contrast to conventional segmentation techniques, gathers and examines information from multiple sources, such as direct reservations, social media exchanges, and prior visits, in order to automatically generate tailored suggestions. Hotels can improve customer happiness through personalized services, incentives, and experiences by forecasting visitors’ behavior (Triquell, n.d.). In addition to helping visitors plan their vacations, book flights, and reserve hotel rooms without having to wait for a response from a travel agent, online travel agency (OTA), or hotel receptionist, artificial intelligence (AI) technology is being used to create personalized products and services everywhere (Londhe et al., 2024).

Opportunities of AI-Driven Personalization in Hospitality

A unique aspect of AI technology, artificial intelligence (AI) aims to give robots human-like cognitive and behavioral capacities (Obrenovic et al., 2024). It becomes increasingly clear in this environment how essential data is to improving consumer experiences. Deeper insights into the preferences and habits of customers can be obtained by utilizing data collected from online activities, surveys, and digital interactions. Building extremely detailed consumer profiles with AI-driven big data processing helps businesses provide more specialized offerings that are tailored to particular customer demands (Haleem et al., 2022). Integrating generative AI into the hospitality sector is crucial for improving customer relations and service effectiveness  (Wong et al., 2023). According to (Carvalho & Ivanov, 2024) chatbots and virtual concierges offer immediate support, providing an ongoing and seamless interaction with guests. For example, they can provide information, take orders, confirm bookings (checking in and out), and handle complaints. It serves as an extension of the human element, enabling employees to focus on providing in-person interactions. Personalized experiences can also be developed with generative AI. Their algorithms are able to produce tailored recommendations for dining alternatives, activities, and even room arrangements by analyzing past interactions and individual preferences. This allows them to customize each experience to each guest’s unique interests (Wong et al., 2023). In order to improve the pre-booking and on-site experiences, they can also produce comprehensive virtual reality tours of hotel amenities and the immediate surroundings (I. P. Tussyadiah et al., 2018). These developments allow hotels an advantage over their competitors while maximizing profits through upselling and tailored promotions.

Through the optimization of different company procedures, AI-enabled service operations have shown significant enhancements in customer satisfaction and service delivery (Vijayakumar, 2023). This proactive strategy is made possible by the implementation of AI into customer support operations, which anticipates and resolves problems before they arise. By offering proactive solutions, this capacity for forecasting serves to prevent issues and improve customer satisfaction (Vijayakumar, 2023). AI is essential for improving the accumulation and processing of data from consumer interactions, which provides insightful information about the preferences and activities of customers. These insights are essential to assisting businesses enhance their overall client experience, improve their offerings and services, and refine their plans. According to (Abousaber & Abdalla, 2023), companies can use AI-driven analytics to find emerging trends and patterns that help them make better decisions and manage their customer relationships more successfully. Businesses might gain a deeper understanding of the needs and preferences of their customers by using artificial intelligence’s capacity to process and analyze broad datasets. This leads to more effective marketing and service initiatives (Coelho et al., 2023). Anxiety and anticipation that travelers frequently experience can be minimized by using AI as it guides them through unfamiliar situations (Amil, 2024).

Figure 1 Opportunities of AI-Driven Personalization Challenges of AI-Driven Personalization

Artificial intelligence has and will continue to impact the hospitality industry significantly. Although some challenges and risks need to be resolved. One major obstacle with AI is guests’ thoughts, attitudes, and perceptions of these technologies. Similar to other innovations, guests can be categorized into groups identified by (Rogers, 2010) innovators, early adopters, early majority, late majority, and laggards. (I. Tussyadiah & Miller, 2019) distinguished three user types based on the risks and benefits of artificial intelligence: slow learners, who see high risks and low benefits from AI; enthusiasts, who see high benefits and low risks; and those who see both the potential advantages and risks of AI. According to their research, people who never used AI are the ones who have negative opinions about it  (I. Tussyadiah & Miller, 2019).

A significant and relevant risk associated with the widespread application of AI concerns bias. Even those who develop AI systems have biases, which might be related to race, gender, age, and socioeconomic characteristics. The potential for AI to magnify the biases already in algorithms is the problem (Smith, 2019). This suggests that AI could replicate biased structures as it learns. It has been suggested that AI systems be transparent, robust enough to prevent manipulation, and reliable in order to relieve this worry (Bostrom & Yudkowsky, 2018). Artificial intelligence (AI) systems must constantly make alternatives, so they should be built to make balanced recommendations that optimize advantages for all parties involved. The issue for the future will be to make sure that technological developments enhance rather than replace the human component, which is essential to the hospitality industry (Murphy et al., 2017). By offering ease and customization while maintaining the friendliness and connection that characterize the sector, AI should improve the guest experience. But there are drawbacks to incorporating AI into the hotel sector, such as job loss, burnout, intention to leave, data privacy, and consumer adoption of technology (Nam et al., 2021; Wirtz et al., 2018).  Researchers and business leaders acknowledge that automation systems driven by AI have the capacity to displace human labor, which would limit opportunities for employment (Pillai et al., 2021). Multiple positions in the hospitality industry, including front desk, cleaning, and food service, need an abundance of repetitive work that can be automated, making it one of the sectors most vulnerable to job displacement from automation (Manyika et al., 2017). Another significant challenge associated with AI implementation is data privacy. AI systems rely on vast amounts of data to function effectively, often including sensitive guest information such as personal and financial details. If guests’ data is not used appropriately and ethically, privacy could be violated, and personal details might be leaked to other service providers. (Wirtz et al., 2018) summarized that technology, such as service robots, will introduce ethical and societal challenges for consumers, markets, organizations, and society at large. Recent scholars have voiced concerns about AI’s role in collecting guest data. Ethical issues and possible technological discontent highlight the significance of implementing AI in a balanced manner(Seifert et al., 2022). Current AI ethical principles were examined and criticized by (Jobin et al., 2019) and (Hagendorff, 2020) from a number of points of view, including responsibility, transparency, fairness, and non-maleficence.

Another important privacy concern related to AI recommendation systems is the consent factor. Data privacy rules strongly emphasize getting people’s informed consent before utilizing their data and informing them of how it will be used (Amaya et al., 2021). Nonetheless, it is standard procedure to refuse requests for consent from some users or not disclose information regarding the gathering of personal data from them. In the nations in which they operate, AI recommendation systems that gather personal data are subject to local data protection laws. According to (Ribeiro-Navarrete et al., 2021), these rules are designed to protect people’s privacy with regard to the collection, processing, storing, and use of personal data. The consent factor significantly influences an AI user’s privacy calculus (Shi et al., 2023). Users are concerned about whether their consent was properly obtained and if they completely understand and agree with the usage of their data when they perceive a high consent risk (Pickering, 2021). Information withholding, a lack of transparency, and a refusal to comply with requests for consent are among the issues that raise worries about privacy and can cause users to lose faith in AI systems.

Consumer Trust Issues in AI-Driven Personalization

Building consumer trust is essential for the success of AI-driven personalization (Ingriana & Rolando, 2025). Privacy assurances are crucial for developing consumer trust (Bansal et al., 2015). E-commerce platforms can increase clients’ trust when disclosing personal information by providing them with accurate information about how it is gathered, stored, and utilized (Ozturk et al., 2017). By personalizing consumer experiences, it can strengthen confidence through tailored, meaningful interactions that demonstrate an understanding of consumer needs. Nonetheless, there are concerns that trust can be easily dissolved if consumers believe they have limited authority over their personal information (Holm et al., 2021).

According to a study (Manzini et al., 2024), competence and alignment are two essential components that allow consumers to trust AI. A fundamental component of appropriate trust is competence. It pertains to the trust of users that the AI system can successfully carry out its intended tasks. The user’s desire to trust an AI system’s recommendations is directly impacted by capability (Ryan, 2020). Users perceive the AI system can precisely assess their tastes and provide tailored recommendations when they believe it is competent. Manzini et al., (2024) further highlight that alignment between the interests, values, or incentives of AI assistants, developers, and users is critical for fostering trust. Users’ expectations may be violated as a result of misalignment, which can be extremely harmful.

METHODOLOGY

This literature review was systematically conducted to gather and analyze relevant academic and industry sources on smart hotel technologies, with a focus on innovations like smart mirrors. A structured methodology was employed, involving comprehensive database searches, defined inclusion/exclusion criteria, and narrative synthesis. The search spanned reputable academic platforms, including ScienceDirect, Google Scholar, Scopus, Web of Science, and library databases such as ProQuest and EBSCOhost, to ensure inclusion of peer-reviewed journals and pertinent industry reports. Search terms were strategically chosen to encompass a broad range of literature, including “smart hotel technology,” “smart mirrors,” “artificial intelligence,” “personalization,” “hospitality technology,” “guest experience,” “privacy concern,” “trust,” “technology adoption,” and “opportunities and challenges in hospitality innovation.” Boolean operators (AND/OR) and truncation were applied to refine results. To maintain relevance in the fast-evolving field of hospitality technology, only studies published between 2010 and 2024 were included. Inclusion criteria prioritized peer-reviewed articles and credible industry reports published in English, focusing on smart technologies in hotels or related hospitality contexts. Emphasis was placed on studies exploring guest interaction, user experience, or the adoption of technologies like smart mirrors and AI. Exclusions comprised studies outside the hospitality sector or lacking full-text access, ensuring high-quality and relevant sources.

The selection process adhered to a structured approach, guided by PRISMA guidelines. Titles and abstracts were screened initially, followed by full-text evaluations based on the established criteria. Any selection ambiguities were resolved through discussion or consultation with a second reviewer. As part of the research method, literature analysis and narrative synthesis were conducted using the framework that was used by (Popay et al., 2006). This allowed for the integration of diverse types of evidence—quantitative findings, qualitative insights, and conceptual discussions—into a coherent analysis of the current state of smart hotel technologies.

DISCUSSION AND FUTURE DIRECTIONS

The expanding adoption of AI-powered hyper-personalization in the hospitality industry has shown enormous potential for enhancing loyalty among clients, increasing productivity, and improving the guest experience. However, in order to ensure long-term success and guest satisfaction, its implementation faces challenges that need to be resolved. Establishing the right balance between hyper-personalization and user privacy is one of the key subjects that needs additional investigation. AI-driven solutions improve service adaptability but raise concerns with user control and data security. Future studies ought to examine how AI-driven personalization could incorporate privacy-enhancing technologies like blockchain and federated learning without reducing service quality. The use of AI-powered personalization in the hospitality industry has great potential to improve guest loyalty, make hotel operations more efficient, and offer more personalized experiences. Tools like machine learning for recommendations, chatbots that use natural language, and smart mirrors with computer vision help hotels meet guests’ individual needs more accurately than ever before. However, using these technologies also brings some important challenges. These include how they affect the guest experience, the changing roles of hotel staff, how trust is built or lost, and the risk of making mistakes in personalization. These issues need to be carefully considered. While AI helps make services more flexible, relying too much on data-based personalization can cause problems. If AI systems focus too much on past guest preferences, they might keep offering the same options over and over. This can make experiences feel boring and too predictable, taking away the surprise and excitement that often make hotel stays special. For example, if a guest is always given the same room or restaurant suggestion, they might feel stuck in a “filter bubble.” AI can also reduce the chance of guests doing something unexpected. Systems that follow set rules—like supervised learning models—often stick to pre-planned results instead of allowing for creative or personal touches. For instance, an AI concierge might keep ordering the same meals based on past behaviour, even if the guest wants to try something new and different. This kind of routine lacks the warm, flexible service that human staff usually provide, and it raises the question of whether AI can truly match the natural instincts of people in hospitality.

Furthermore, a major barrier to the deployment of AI is guest trust. Users prefer personalized experiences, but they may also be concerned about the extent of data gathering and AI-driven decision-making. Future research needs to look at approaches to improving transparency, including explainable AI (XAI) models that let users know how their data is utilized for personalization. Likewise, the significance of AI in addressing cultural personalization should be examined in future studies. From the industry standpoint, AI-driven personalization needs to change in order to accommodate emerging ethical and sustainable AI trends. AI can be used by hotels and travel agencies to optimize utilization of resources, minimize waste, and enhance environmentally conscious travel. Future AI developments in the hospitality industry should prioritize ethical AI techniques that promote social responsibility in the workplace.

CONCLUSION

This study demonstrates the groundbreaking impacts of hyper-personalization powered by AI on guest experiences in the hospitality sector. Hotels and tourism businesses can offer increasingly customized services that boost customer happiness, brand loyalty, and operational efficiency by utilizing innovative. These findings show that AI-powered customer interactions, dynamic pricing strategies, and personalized advice all impact how consumers perceive and behave. Looking to the future, we are presented with several challenges. These include protecting the privacy and security of data, effectively responding to complicated inquires, preserving a human component in automated interactions, resolving biases in AI algorithms, and accomplishing seamless integration with current technology. Efficiency and individualization need to be balanced. Despite these advantages, there are drawbacks of achieving hyper-personalization, such as issues with data privacy, ethical choices, and technological integration. Several important challenges need to be tackled to ensure AI in hospitality is used responsibly and sustainably. These include protecting guest privacy, handling complex guest requests, keeping a human element in automated services, preventing biased algorithms, and integrating AI smoothly with existing hotel systems. The increasing use of hyper-personalization requires balancing efficiency with genuine emotional engagement.

These advancements have wider societal effects beyond individual hotels. Ethical AI standards—such as clarity, fairness, and responsibility—should guide personalization technologies to prevent unfair treatment or exclusion. Additionally, the hospitality industry should adopt AI in ways that support global sustainability goals. For example, AI can enable smarter resource use and energy-saving operations to lessen environmental harm, while inclusive design can ensure personalization promotes accessibility and fairness for all guests. Overall, AI-powered hyper-personalization represents a significant advancement in hospitality management, offering businesses opportunities to differentiate themselves in an increasingly competitive market. Continued advancements in AI technologies, combined with strategic application, will be essential for maximizing the benefits of hyper-personalization while reducing risks. As AI continues to grow, its influence on the future of customer service is expected to expand, bringing new opportunities and challenges for businesses operating globally.

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