1 Introduction
The hospitality industry has been slow to adopt artificial intelligence (AI) and digital technologies [1‐3] despite their potential to revolutionize the sector by improving operational efficiency, enhancing customer experiences, and enabling strategic decision-making. This reluctance is particularly pronounced among small and medium-sized hotel enterprises (SMEs), which have been identified as late adopters of digital technology solutions [4, 5]. The COVID-19 pandemic accelerated the digital transformation of various aspects of the hospitality sector, from hotel websites and mobile applications to customer relationship management (CRM) systems and AI applications [2, 6]. However, despite this progress, the industry's interest in AI technologies remains relatively low, with a small percentage of companies actively using them [3, 6, 7]. Several factors contribute to the slow adoption rate of AI in the hospitality sector, including a lack of knowledge and understanding of AI's real benefits, insufficient human and financial resources, and the desire to maintain a human element in hotel operations [4, 5]. These challenges highlight the need for a more comprehensive approach to understanding the benefits and challenges of AI adoption. This approach should encompass not only the technological aspects but also the strategic, operational, and financial implications of AI integration. A thorough understanding of these factors is crucial for the successful integration and utilization of AI technologies in the hospitality industry. This study aims to illuminate these issues by examining the perceptions and attitudes of both experts and hoteliers towards AI adoption in the hospitality sector.
2 Literature Review
The term “Artificial Intelligence” officially appeared in 1956 at the Dartmouth College Conference where John McCarthy proposed the following definition [8]:
‘‘AI is a multidisciplinary technology, which has the ability to integrate cognition, machine learning, emotion recognition, human-machine interaction, data storage, and decision making.”
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As determined in the definition above, AI is multidisciplinary and includes scientific domains such as machine learning, text and speech synthesis, natural language processing, computer vision, planning, robotics and expert systems [9]. Most AI applications are built on the basis of machine learning, thus using different algorithms and methods to obtain the best results in the different scientific domains mentioned above [9]. AI can be divided into two categories: weak AI and strong AI. Weak AI focuses on performing specific tasks, such as voice control of virtual assistants like Apple's Siri or Amazon's Alexa. Strong AI is said to be capable of performing all the tasks that humans are capable of. However, despite significant advances in the field, strong AI is currently only a theory and its realisation remains hypothetical [10]. Nevertheless, thanks to the relatively advanced maturity of technical conditions, AI is currently undergoing rapid development and is being applied in many fields [11], as it is now capable of efficiently solving real-world problems and generating economic benefits.
2.1 Artificial Intelligence and the Travel Field
In June 2017, McKinsey Global Institute published a working paper presenting the level of adoption of AI in various industrial sectors, the common characteristics of companies that have adopted this technology faster, as well as the future demand for AI [1]. According to this paper, the level of adoption of AI in Travel and Tourism was low, as well as their digital maturity. Digital maturity is one of the six common characteristics of AI early adopters: several studies have demonstrated the beneficial impact of digital technologies on business operations and performance, as well as on customer and employee satisfaction, thereby contributing to customer loyalty [12]. In addition, digital transformation enables companies to grow their business and transform their business models [12].
The hospitality sector has also shown some reluctance to integrate and use digital technologies, and hotel SMEs were considered late adopters of digital technology solutions [2, 4, 12]. The study by Calvino et al. [13] analysing data from 2001–2003 and 2013–2015 shows that the digital intensity of sectors varies. The study examined various factors such as the technological components of digitisation, the human capital required and the technological impact on online sales. The result reveals that accommodation and catering activities are considered to have low digital intensity. However, digitalisation is now playing an important role in the hotel sector. For example, according to a quantitative study [12] of 110 small and medium-sized hotels (2–3 stars) in Poland, digitalisation has a significantly positive effect on hotel performance, growth and market performance. In addition, digitalisation plays an intermediary role in the impact of entrepreneurial behaviour on performance. In particular, digitalisation is a determining factor in the impact of proactivity on business growth and in the impact of innovation on market performance. The COVID-19 pandemic has accelerated the digital transformation of the hotel sector, particularly in the areas of websites, mobile applications, social networks, advanced software such as CRM, and AI [2]. Despite progress in digitisation, a study by Telekom and Techconsult in Germany [6] found that the level of digitisation has not changed significantly compared to 2020. Websites have become crucial for information, direct bookings and brand awareness. Digital solutions have enabled contactless check-in, bill payment and access to hotel information and services [2]. Social networks, chatbots and conversation centralisation applications have facilitated direct communication with customers, resulting in operational savings and improved loyalty. CRM is now essential for building lasting relationships and driving innovation. Ivanov [14] emphasises that AI and automation will bring significant changes, which require preparation from both managers and employees. Companies need to assess the costs and benefits of these technologies, provide the necessary training and overcome the knowledge gap, which is a major challenge for hotel SMEs in identifying opportunities to adopt digital technologies [4]. However, according to Telekom Deutschland & Techconsult [6] the hotel industry's interest in AI technologies is lagging behind. According to the study, 54% of companies consider AI applications to be relevant to their business. Of these companies, 7% are already using them, mainly for text (24%) and speech (16%) processing, while 21% have concrete plans to introduce AI-based technologies. Nevertheless, it is imperative for employees to be proactive in improving their skills, as the willingness to use technology in the hospitality and tourism sector is influenced by individual characteristics. As the study by Ciftci, Berezina & Kang [15] shows, the propensity to use technology is associated with personal characteristics such as innovativeness, which defines an individual's openness to new ideas and ability to make independent innovation decisions without relying on the experience of others.
2.2 Artificial Intelligence in the Hospitality Sector
The use of AI technologies in hotels, as detailed in a study by Nam & al. [3], was primarily informed by interviews with senior hotel asset managers overseeing more than 40 hotels in Dubai. The adoption of these technologies was aimed at improving customer experience, reducing costs, increasing revenue, personalising customer service and increasing productivity. The findings of this study identified 11 factors influencing the adoption of AI in the hotel sector and categorized AI applications into four groups based on their types and characteristics. Bulchand-Gidumal [16] categorised the impact of AI into two main areas: operations and marketing. Operationally, AI enables the automation and customisation of various hotel processes, such as room and resource allocation, preventative management, inventory optimisation and energy management. On the marketing front, AI improves forecasting, CRM systems and intelligent marketing strategies, including dynamic pricing, personalised services and experiences, predictive analytics and real-time offers. Additionnaly, according to Tuomi [17], generative AI for SMEs in the hospitality and tourism industry can offer an increased autonomy and more internal control over their creative initiatives in generating contents for social media, facilitating in-house project management. Nonetheless, according to one of the latest report from Skift and AWS [18], the use of data, automation, and AI has the potential to humanize hospitality both on the customer facing and operations side braking down departmental silos.
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3 Research Objectives and Methodology
The hospitality sector appears to be a suitable and promising domain for the integration of AI, yet its adoption in the industry is notably lagging [2]. To understand the underlying reasons for this discrepancy and to develop a critical perspective, this research involves two sets of interviews designed to illuminate the key issues at hand. Additionally, this study aims to bridge the gap between technology companies and hoteliers by identifying common ground that could facilitate the adoption of AI. By fostering a better understanding and collaboration between these two key stakeholders, it is hoped that the barriers to AI adoption in the hospitality sector can be overcome, ultimately leading to enhanced operational efficiency, customer satisfaction, and overall competitiveness in the industry. In order to reach this aim, hospitality technology consultants and hoteliers have been interviewed to tackle the following research objectives: (i) from the experts’ point of view, the research aims at understanding the view on hotels’ adoption on AI, the reason why adoption would be recommended and the main obstacles; (ii) from hoteliers’ point of view, the research aims at understanding the importance of AI for hotels’ operations and what are the factors facilitating adoption.
3.1 Data Collection
80 interview requests were sent, mostly via LinkedIn.com, using purposive and snowball sampling resulting in 7 positive responses from hotel managers in Switzerland and 6 positive responses from experts in the field of AI (Austria, Germany, Switzerland, France, Spain). The description of the participants is presented in the tables below.
Table 1.
Description of experts interviewed
Role/Position | Product/Experience | |
|---|---|---|
E1 | CEO | Platform that integrates communications between hotels and customers from various sources and applications, and can respond through instant messaging (ChatBot) |
E2 | Senior Customer Success Manager | Real-time revenue management system |
E3 | Director of Client Services and Customer Success | Real-time revenue management system |
E4 | CTO | Customer relationship and hotel operations platform (CRM, GuestApp, messaging, operations) |
E5 | Consultant | Consultant in the hotel/technology industry (21 years of experience in technical, commercial, marketing, consulting, and business leadership roles) |
E6 | Co-Founder | AI based guest experience management solutions for hotels |
Table 1 presents the experts who agreed in taking part to the study; while Table 2 presents the hospitality companies involved. In order to ensure that hotel managers had relevant experience with AI, all interviews started with a soft assessment of the hoteliers’ understanding of AI and a brief discussion of the AI solutions used in their respective properties. All the interviews tool place between March 2023 and June 2023.
Table 2.
Description of accommodations
# | Accommodation type | Location | Hotel type | Star-level | Number of staff | Number of rooms | Independent | AI usage |
|---|---|---|---|---|---|---|---|---|
H1 | Hotel | City | Business/Seminar | 5 | ~70 | 60 | Yes | No |
H2 | Small group of hotels | Multiple locations | Depends on hotel | Luxury segment | 1400 permanent staff (~1800 in season) | From 14 to 200 | No | Yes |
H3 | Tourist residence (apartment hotel) | Mountain | Leisure | 3 | 4 | 85 | No | No |
H4 | Hotel | Mountain | Leisure | 3 | 9 | 60 | Yes | No |
H5 | Hotel | City | Business | 4 | ~30 | 136 | No | Yes |
H6 | Hotel | City | Business/Leisure | 3 | ~35 | 71 | Yes | No |
H7 | Tourist residence | Mountain | Leisure | – | ~8 | 200 | Yes | No |
3.2 Data Analysis
The analysis of the data was conducted using deductive coding, which was informed by the literature review. The analysis of the interviews was conducted using MAXQDA 2022 software, significantly enhancing the coding of text segments and their hierarchical organization. The results were categorized and interpreted using the Technology-Organization-Environment (TOE) framework. The TOE framework identifies three categories of factors that influence a company's ability and decision to adopt new technologies [3].
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Technological factors refer to all factors, both internal and external, that are relevant to the business. Internal factors include technologies that are already adopted by the business, and external factors include technologies that are available on the market [19]. This therefore allows us to consider and understand how the characteristics of the technology already adopted may impact on the adoption of new technologies.
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Organizational factors include organizational characteristics and available resources that can impact the adoption of new technologies. SMEs often lack the financial and human resources that can facilitate the adoption process. Financial, technical, and human resources are the key factors when we talk about the adoption of new technologies by SMEs and hotels. They refer to the availability of all these resources for use in integrating new technologies into business processes.
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Environmental factors refer to external elements that impact the company's business activities such as industry, competitors, customers, as well as the legal context, and which influence the decision to adopt new technologies. Competitive pressure has been extensively studied as a characteristic that has an impact on the adoption of new technologies, particularly in the hotel sector [3].
4 Results and Discussions
4.1 Expert Interviews
Initially – as a warm up question - the interviewees were asked about their perception of IT and AI adoption in small and medium-sized hotel enterprises (SMEs). Several respondents noted that that COVID-19 pandemic accelerated technology adoption especially for tools related to guest safety and compliance with new health requirements; however, hoteliers are increasingly aware of technology's importance and understand that they can't do without it as E5 maintains: “Today's hoteliers are well aware that they can't do without technology. […] Technology has become an inescapable subject for them, they may vary in their degree of adoption, but all of them have understood that they have no choice”.
Hotel groups and chains are generally more inclined to adopt technology, however E4 explained that high-end independent hotels, driven by a commitment to exceptional guest experiences, are often leaders in technology adoption, while, perceptions of AI adoption among SME hotels also vary based on owners, managers, and generations as described by E6: “If you're considering small and medium-sized hotels, it depends a little bit on the owner and the manager. There's also likely to be a generational difference in their approach. […] the younger generation recognizes the value of the data, but they struggle with managing it effectively because it's dispersed across multiple systems”.
The hotel sector faces challenges like fragmented technologies, hoteliers’ lack of knowledge about market-available solutions, and integration of diverse data sources. E1, E2, E3 and E6 affirmed that many hotels store data in silos, hindering communication, global data analysis, and the use of outdated software like PMS because as E1 maintains: “[in the hotel business] digitalization is not at the center of hoteliers’ concern […] you do not have specific training and the only way to get new technology is trade show or consultants”.
Advantages of Adopting AI Technologies in the Hotel Industry. The experts were asked about the benefits that small and medium-sized hotels could gain from adopting advanced technologies like AI. Here are the key points from their responses:
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Replacement of Repetitive Tasks. Experts E1, E2, E3, E4, E5 and E6 noted that AI technologies can reduce time spent on repetitive tasks, particularly administrative ones that consume time without adding value. This reduction allows hotel owners and staff to focus on more important tasks. Additionally, AI-based technologies enable hotels to handle huge amounts of data within a short timeframe, to remain competitive and react more quickly to market changes;
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Operational Efficiency in Marketing and Maintenance. AI can enhance operational efficiency by automating tasks such as marketing and predictive maintenance (E1, E2, E3, E4 and E6). AI techniques help personalize offers and rates based on user behavior on hotel websites, optimizing revenue streams (E1, E2). The creation of unified customer profiles means that communication can be based not only on customer profiles (E1, E3 E4, E6), but also on the most appropriate pricing policy. As a result, AI-powered Revenue Management Systems (RMS) can offer accurate demand forecasts, assist in setting optimal pricing strategies, and ensure quick reactions to market changes (E1, E2, E3).
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Customer Experience Personalization: AI enables hotels to better understand customer preferences and desires, offering more personalized experiences (E1, E3). AI-driven communication tools automate interactions, enhancing customer satisfaction (E3). AI can assist in analyzing data to provide personalized services, improving overall guest experience and fostering loyalty (E3 and E6).
Factors influencing AI adoption. When asked about the factors influencing the advantages of AI-based systems, experts mentioned the following one, which have been classified following the TOE framework:
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Technological Factors. (i) Quality of integration with old – and still working technologies (e.g. PMS) (E1, E4, E6). This can cause dissatisfaction which could eventually lead to a decrease in their collaboration with the system. (ii) Quantity and quality of data (E1, E3, E5, E6): data plays an essential role for systems based on artificial intelligence. The number of software applications adopted by a hotel can have a considerable impact, as they constitute a source of digital data.
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Organizational Factors: (i) Willingness of managers or owners to invest the necessary extra effort (E2, E6): Decision-makers must be willing to invest time and resources to reap the medium- and long-term benefits offered by software and services, including in ongoing training. (ii) Hotel strategy and goals (E1, E3): Depending on the customer experience or staff experience hoteliers want to offer, they need to choose the software that matches the hotel's expectations. (iii) Hotel typology (E2, E4, E6): this is an important factor to consider because customers’ expectations may differ depending on their travel purpose. For example, hotels geared towards business travel focus more on administrative efficiency than individualisation and may therefore be less demanding in terms of content quality. Furthermore, the requirements of various types of hotels can vary. Therefore, it is important to determine whether AI models can be adapted to meet specific requirements. (iv) Hotel classification (E1, E4, E6): according to E1, 5-star hotels prefer to build a relationship with their customers based on human contact. E6 maintained that personalisation is more significant in the luxury segment compared to lower category hotels. (v) Hotel size (E1, E2, E3, E5): hotel size can affect the benefits of products based on AI technologies. This is mainly linked to the amount of data held, which can influence the relevance and accuracy of the recommendations and forecasts generated by the software. The larger and more visited the hotel, the easier it is to optimise AI technologies. (vi) Resilience and usability (E1, E3, E6): AI-based software can perform different tasks, but the interaction is often hybrid and also involves a human factor. So, it's essential for employees using a system to have a good understanding of how it works and how it interacts with other systems. If employees are reluctant to try something new, implementing this software can be extremely difficult.
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Environmental Factors: (i) Belonging to a group/network (small or large) or independent establishment (E2, E6) influences the software's ability to meet the different expectations of hotels. Hotels that are part of a group or a network have more standardised processes, which makes it easier to implement the software. (ii) Number of direct competitors (E2, E3): the presence of several direct competitors can improve system performance. This allows a better comparison of prices and a more accurate adaptation to market conditions. Other mentioned factors can be linked to the environment, such as client preferences (E1), AI algorithms (E1), system capacity (E1 and E6), and installation moment (E6), as various establishments have specific needs, for example, those related to different seasons.
4.2 Hoteliers Interviews
The participants’ understanding of AI varied: H2 and H4 summarize the current understanding of AI in the industry in the following way respectively: “[AI] it's still something new […] well, we've been talking about it for quite some time, but it doesn't really affect our industry at the moment […]”, and then H4: “I don't know of any other hotels that have implemented it. Of all the contacts I've had through the [Local Hotel Association] and others, so far none have told me that they use these solutions”.
Most frequently mentioned ideas included (i) personalizing customer experiences, (ii) communication for commercial purposes (customer profiling, recommendations, personalized offers), (iii) revenue management in real-time, chatbots and ChatGPT.
Subsequently, H2 and H5 mentioned several solutions they are currently using or plan to integrate. These include an intelligent video surveillance system that records only upon motion detection (and also using object search), an energy optimization system, an AI-driven electrical backup system, predictive maintenance tools, and a table management system that automatically assigns seating to customers. Surprisingly, the participants did not perceive these solutions as AI-related, or some participants expressed uncertainty about the specific technologies used behind them.
However, what become apparent during the conversation was the need of hoteliers to maintain the ‘human side of the business’ as maintained by H5: “In my opinion, it's still important to retain a human element in the hotel business. The human element remains crucial in this field. […] Customers are often also looking for an exchange with someone who creates an experience, and not just pure technology […]”.
A significant aspect highlighted by hotel managers is the management and support associated with the use of external software and IT service providers. Participants expressed that the quality of support did not always meet their expectations, and some noted a transition from personalized support to automated systems. Several participants mentioned that they often had to complete system configurations themselves (H5) or assume the role of a project manager (H6). Ultimately, multiple participants indicated that while the hotel industry has access to numerous tools, hotels are not always equipped to develop, maintain, install, or configure these tools independently. This underscores a critical gap in the industry's ability to fully leverage available technologies without external assistance. When it comes to obstacles, and challenges in adopting AI, participants highlighted potential use cases for AI in hotel operations, such as reservation management, housekeeping planning, waste monitoring, personalized customer interactions, revenue management, and more. The personnel will be freed to do other tasks, however the current level of knowledge is insufficient, and the actual economic benefit is not clear: H7: “[…] on the one hand, digitalisation [and AI] would free up our staff's time to carry out other tasks”. H2: “[…] in terms of productivity, but not just productivity in terms of quantity, but also productivity in terms of quality. How many distortions, how many values we can make up… Yes, a gain in time, a gain in strategy based on more relevant points, on information that is better analysed, better centralised”. H4: “We haven't taken any courses on this [AI]. Personally, I've never had any courses, so I don't know how it works… Yes, especially in terms of knowledge, and what I could gain from it, what advantages it could bring”.
Hoteliers also called for a more detailed explanations of AI benefits, seeking advice and consultation, ensuring data protection, remaining open to new opportunities, finding reliable partners, and staying updated on evolving technology trends.
TOE factors and AI Adoption. The adoption of AI in hotels is influenced by a variety of factors including technological ease, client preferences, AI product development, competition, human and financial resources, company strategy, hotel characteristics, and accountability considerations. These collectively determine the integration and success of AI technologies in the hospitality industry. Specifically:
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Technological factors. Benefits include operational efficiency (H1, H2, H3, H6, H7), improved customer experience (H1, H2, H3, H5, H6), empowered employees (H1, H2, H6, H7), competitive advantage (H1, H2, H5, H6) and improved overall performance (H1, H2, H5, H6, H7). AI achieves this through automation, personalisation and strategic insight. Compatibility (H2, H3) and simplicity (H1, H2, H5, H7) are critical for successful integration.
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Organizational Factors. Challenges in terms of skills, technical knowledge and time hinder the readiness of human resources (H2, H3, H4, H6, H7). Adequate budgeting and accurate cost estimation are critical financial factors (H1, H2, H3, H5, H6, H7). Corporate strategy and management priorities determine the pace of implementation (H1, H2, H3, H4, H6). Hotel size and type dictate resource availability and requirements to be met (H1, H2, H6). In addition, star rating is important in determining whether or not to implement robotic technologies in luxury hotels, given the importance of providing customers with personalised service and human interaction (H2). In addition, H1 mentioned another factor during the interview, which is responsibility in terms of incorrect chatbot responses. Responsibility should be clearly defined between the service provider and the hotel.
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Environmental Factors. Different customer expectations drive adoption, with some prioritising human interaction and others seeking digital convenience (H1, H3, H4, H5). The development of AI products varies, with potential for different deployments (H1, H3, H4). Competition may drive uptake, particularly in city hotels (H3, H4, H5), but is not currently considered a significant factor influencing uptake (H1, H3, H4, H5, H7). However, it should be considered in relation to supply, higher visibility and pricing (H5). Other factors such as external support, risks, ethics and trust also play a role, but are not the key factors to consider when deciding to adopt AI technologies (H2, H3, H4, H5, H6, H7).
5 Discussion and Conclusions
This research has highlighted the nuanced differences in the understanding of AI between experts and hoteliers within the hospitality industry. While the adoption of standardized technology is more straightforward for chain hotels, the fragmented nature of the industry poses significant challenges to the integration of artificial intelligence. It is important to note that the current discourse on this topic is often framed within the broader context of digitisation and IT adoption. However, AI in the hospitality sector presents unique challenges and opportunities that go beyond general IT adoption.
Experts continue to highlight the multiple benefits of AI, ranging from automating mundane tasks and increasing operational efficiency to refining the guest experience. However, a deeper dive into our findings reveals that many hoteliers, especially those from older generations, are not simply reluctant to adopt the technology. Their reluctance stems from a lack of fundamental understanding of the tangible benefits of AI, which are specific to the hospitality industry. The challenges posed by the digital transformation of tourism, as highlighted in reports [4, 5], parallel the need for a specialised educational approach tailored to hoteliers. Hoteliers need a detailed understanding of the value proposition of AI, including its potential ROI, the impact on human resources and the technological infrastructure required. This education should not be a cursory overview, but a deep dive into the strategic and operational implications of AI specific to the hospitality industry. Equally important is the demystification of the costs associated with AI integration, accompanied by a pragmatic roadmap for integrating AI into existing frameworks. Humanizing the AI transition: The transition to AI is not just a technological change, it's a human one. Resistance to change, particularly among older hoteliers, isn't just about technology - it's about redefining age-old operational paradigms. Recognizing this, it is imperative to formulate change management strategies that are holistic. These should not only include training modules, but also address the innate human resistance to change to ensure a smoother AI integration journey. Forge collaborative pathways: There's an undeniable need for technology vendors to be more than just solution providers - they need to be partners. This research underscores the critical role of technology providers in understanding the complex challenges hoteliers face, which require bespoke AI solutions tailored to individual needs. Beyond the initial integration, ongoing support, training and iterative feedback mechanisms will be critical to the successful deployment and optimization of AI technologies. The intersection of AI and hospitality is full of potential, but realising this potential requires a multi-faceted approach. While the benefits of integrating AI are clear, the challenges, both technological and human, are significant. To realise the full potential of AI in hospitality, a harmonised effort that includes targeted education, comprehensive change management and a symbiotic relationship between technology providers and hoteliers is paramount.
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