1. Introduction
Implementing digital technologies, such as artificial intelligence (AI), digital twins (DTs), the metaverse, and blockchain, amongst many others, in the tourism and travel sectors helps us to achieve high sustainability and resilience levels [1]. Indeed, AI is redefining the essence of travel in cities and commercial airlines because this technological tool provides immediate (understood as ubiquity) customised services and itineraries for consumers when they are planning a trip to London or want to book a round-trip flight between Tokyo and Sidney [2]. The World Economic Forum (WEF) notes that AI offers ubiquity information for consumers about their travel planning and swiftly provides them with detailed itinerary planning, flight bookings, and personalised recommendations that would otherwise take hours or days to plan manually [3]. The future of the AI tool in the tourism and aviation sectors has immense potential for consumers (efficiency of leisure time) and companies (reduction in operational costs). AI applications will outstrip human performance by offering a wide range of information and travel and tourism services tailored to tourists’ needs and preferences in no time [4].
For instance, Carvalho and Ivanov [5] suggest that the ChatGPT tool improves tourists’ experiences because this digital tool helps customers resolve their queries, take orders, customise tours, and compare the facilities offered by hotels or airlines, among many others. Most AI services are being applied in airports, hotels, airlines, theme parks, museums, and restaurants to enhance tourists’ experiences and reduce operational costs [6,7]. Indeed, chatbots linked to AI algorithms are increasingly being deployed by hotels, airlines, and online travel agencies (OTAs) to provide instant customer support and assistance [8,9].
Destination marketing organisations (DMOs) and public and private organisations are using AI technologies in management and marketing activities in order to increase productivity and predict future outcomes by analysing available data [10,11]. AI algorithms learn from the data and obtain patterns that are used to predict and detect events in tourism and travel activities [12]. Buhalis et al. [13] note that the innovative metaverse tool supported by AI algorithms offers new and creative opportunities for tourists through promoting and empowering the products and services of hotels and airlines. However, the use of this AI tool raises concerns about privacy, bias, and transparency in the tourism and air transport sectors, particularly in relation to users’ privacy information [14].
Kılıçarslan et al. [15] argue that AI and metaverse technologies provide instant on-site data regarding users’ experiences and preferences [15]. Bhuiyan et al. [16] found that hotel customers’ willingness to use AI devices is influenced by social influence and consumers’ emotions. In the aviation sector, airport and airline operators are implementing AI techniques in their processes to serve and improve passengers’ needs and satisfaction [17]. In the same vein, Soliman et al. [18] revealed that EgyptAir airlines developed marketing strategies using AI algorithms to provide tailor-made recommendations for passengers that match their preferences and motivations. In 2024, Fiji Airways invested in AI technology to enhance its operational efficiency and provide seamless passengers’ experience.
The adoption of AI techniques in the travel and tourism sector has been slow, and its performance potential for both sectors is at an early stage of development [19,20,21,22,23]. Given that AI is substantially transforming organisations, it is imperative to analyse how AI will change the future of tourism and travel activities [24,25,26]. Therefore, having a global view of the use of AI in the tourism and air transport sectors will help researchers, DMOs, and companies better understand the types of usage of AI, their new opportunities, and the implications for the future of this disruptive tool. The main objective of this review is to illustrate the use of AI in the tourism and air transport industries to improve tourists’ experiences, as well as provide a definition of the AI concept closest to both sectors. Dwivedi et al. [27] note that the use of AI tools will have a positive transformative impact on the travel and tourism industry in order to maximise firms’ benefits and improve the digital interaction between consumers and companies. AI technology could unlock between USD 2 trillion and USD 4 trillion in annual value across industries [28].
2. Methodology
In order to address the main goal of this research and establish the AI concept in a tourism context, this study used a systematic review technique to examine and show the literature already available on the subject of artificial intelligence and how it may be used to improve the travel and aviation industries. This methodology helps us to visualise a future AI scenario in travel and tourist activities by looking at how AI can contribute to the social, environmental, and economic value and condition of the visited area. Encouraging sustainable behaviours using AI technologies can help to improve the travel experience [29]. Additionally, this systematic review really aided us in offering many perspectives on the definitions of AI in this research. Based on this theoretical framework, we were able to create a new AI concept to advance this subject in the literature on travel and tourism. To carry out our methodology, we also followed the established guidelines defined in preferred reporting items for systematic reviews and meta-analyses (PRISMA) [30], which are very useful in tourism and technology research [31].
Due to the recent usage of AI technology by travel and tourist organisations and DMOs, this study primarily focused on studies conducted between 2015 and 30 September 2024, in order to present and assess the most recent data on this topic [17,32]. The most pertinent data about AI and travel and tourism activities were gathered and obtained for this manuscript using the Web of Science (WoS) database [33]. Researchers who study tourism and technology activities rank WoS as one of the most significant datasets in both the travel and tourism literature [34]. Also, we selected WoS because this database is one of the most-used databases in socio-economic disciplines; it has content comparable in size to Scopus and requires fewer data-cleaning operations [35].
The research criteria were based on the following string of words: “artificial intelligence AND tourism” (763 documents) or “artificial intelligence AND air transport” (125 documents). These were used to search against the title, abstract, and keywords of documents to produce initial insights, only in the English language, including books, book chapters, conference proceedings, and review articles that provide viewpoints on the challenges, uses, and theoretical advancements of AI in the travel and tourism industry [36,37]. We would like to highlight that initially, our results were 829 documents for “AI and tourism” and 216 documents for “AI and air transport”. Articles that were not related to AI in a tourism and travel context were excluded, which resulted in the removal of a total of 157 documents for further analysis, according to our criteria applied in the WoS search.
Therefore, the related documents were reduced to 888 documents. From 2020 to September 2024, the average annual growth of “AI” and “tourism” publications and citations was up by 39% and 141.7%, respectively. While the average annual growth of “AI” and “air transport” publications and citations grew by 24.5% and 54.1%, respectively. Indeed, as we can see in Figure 1, the number of documents and citations increased exponentially from the year 2020, that is, after the pandemic crisis. For example, AI-enabled chatbots, virtual assistants, drones, and robots have also been utilised in tourism activities in the post-COVID-19 era to enhance customer service, reduce expenses, and address challenging consumer questions [38].
Another point worth highlighting is that China, with 224 documents published during the established period (AI and tourism search), ranks first, followed by the USA (99), Spain (67), England (64), India (61), Portugal (40), South Korea (32), Turkey (30), Italy (29), and Taiwan with 26 documents. These results are not pure coincidence because AI technology is part of the fabric of Chinese production and includes the most prominent technology-advanced companies of the country [39]. The best university positions in terms of “artificial intelligence AND tourism” are the Hong Kong Polytechnic University with 28 documents, followed by the State University System of Florida (24), the University of Macau (18), the Vama University of Management (15), and the rest of the universities listed in the table below (12 documents) (Table 1).
However, China, with 22 documents published during the established period (AI and air transport search), is the first country worldwide, followed by the USA (21), England (10), South Korea and Spain (9), respectively, Germany, India, and Iran (8), respectively, Italy (7), and finally, France with 6 documents. From a university point of view, the best university positions in terms of the “AI and air transport” search are the Chinese Academy of Sciences and the University of Chinese Academy of Science Cas with 5 documents, respectively; followed by the Changzhou Institute of Technology, the Indian Institute of Technology System IIT System, the Shahid Beheshti University, the University of Tabriz, and the University of Texas System with 3, respectively; and the Beihang University, the Chongqing Jiaotong University, and the Hong Kong Polytechnic University with 2 documents, respectively (see Table 2). As they compete to become the top AI nations in the world, China and the US have conflicting objectives. The evidence primarily focusses on the existing political structure of each country, current geopolitical issues, and the ability to compete in terms of efficiency and production [40].
To further demonstrate AI’s potential for use in travel and tourism activities to improve tourism experiences, this paper also includes contemporary examples of AI’s application in travel and tourism organisations. Consequently, the adoption of digital technology in tourism activities is a complex and multifaceted issue that necessitates collaboration from a variety of stakeholders, including local communities, politicians, tourism operators, and technology providers [4,41].
3. A Global Vision of the Concept of AI Technology in the Tourism and Air Transport Sectors
In reality, AI technology is a disruptive tool in tourism and travel activities that require a lot of investment and dedication to be able to better visualise their benefits and weaknesses for consumers and companies. Indeed, it would be advisable to develop more research projects on the AI concept and its future applications in tourism and travel activities [42,43]. The term AI was coined by John McCarthy in 1956, who defined AI as a family of technologies that may recognise, analyse, act, learn, and demonstrate enhanced features of human intelligence [44], which is why this study includes a new conceptualisation of AI in the tourism and travel context. Nevertheless, this manuscript proposes a revised concept of AI to empower this innovative technology in the tourism and travel context. Based on Table 3, which shows different definitions of AI in the travel and tourism sector, we defined AI as an immersive and technological tool that has the capacity to create individualised information and to satisfy tourists’ wants and needs in real-time and without delay, as well as a sophisticated prediction and efficiency tool that helps the managers of tourism and travel companies to make better decisions to optimise operational performance. For example, chatbots engage with customers in their native tongues and encourage constructive behavioural changes, notably enhancing customers’ experience [45,46].
For example, authors such as Florido-Benítez and del Alcázar [4], Doğan and Niyet [8], Zaoui et al. [17], Soliman et al. [18], Tuo et al. [24], Grundner and Neuhofer [47], Chakraborty et al. [48], Ogunsina and DeLaurentis [49], and Dangwal et al. [50] note that AI technology is being used in the tourism and travel industries to improve consumers’ experience and satisfaction. Notwithstanding, Filieri et al. [19], Dwivedi et al. [51], Khan and Efthymiou [52], Bulchand-Gidumal [53], Wamba et al. [54], Knani et al. [55], García-Madurga and Grilló-Méndez [56], and Merlo [57], among many others, argue that implementing AI techniques in tourism and air transport activities helps to improve and optimise operational efficiency; develop customised products and services for tourists in real-time; resolve immediate tourist queries; predict future problems, progress, costs, income, and unexpected expenditures; and design new tasks and operational processes that can help DMOs, managers of companies, and government organisations to make better decisions in tourist destinations.
Table 3AI definitions.
| Authors | Different Points of View of AI Definitions | Sector |
|---|---|---|
| McCarthy [44] | AI is a technological tool that analyses, resolves, and demonstrates enhanced features of human intelligence. | Technology |
| Shankar [58]; Dwivedi et al. [51] | AI refers to programmes, algorithms, and machines that demonstrate intelligence to improve the operational efficiency of companies. | Tourism and air transport |
| Tsaih and Hsu [59] | AI refers to human intelligence technology realised by sophisticated computer programmes. | Smart tourism destinations |
| Li et al. [43]; Akerkar [60]; Lifelo et al. [61] | AI is a technological tool that thinks independently and conducts autonomous tasks. | Hospitality and tourism |
| Kaplan and Haenlein [62]; Ivanov and Webster [63] | AI is a computer system that has the ability to correctly interpret external data and to use those learnings to achieve specific goals and tasks. | Tourism and air transport |
| Tussyadiah [64]; Li and Di [65] | AI is defined as a system that thinks as humans do, acts humanly, thinks rationally, or acts rationally. | Tourism and air transport |
| Grundner and Neuhofer [47] | AI is a technological tool that helps create individualised offers that satisfy tourists’ wants and needs, providing hyper-personalised information within specific contexts and in real-time. | Tourist destinations |
| Tuo et al. [24] | AI is an innovative technology that can offer a more customised buyer experience to consumers, as well as sharper prediction tools that ensure better decisions by managers’ companies. | Tourism |
| De Carlo et al. [66] | AI is an analytical tool that may help tackle new challenges in complex, multi-stakeholder, and competitive settings such as tourist destinations. | Urban destinations |
| Khan and Efthymiou [52]; Loureiro et al. [67] | AI is a technological tool that provides immediate results in continuous learning and problem-solving. | Air transport and companies |
| Chakraborty et al. [48] | AI is an immersive computer system that is used by airport and airline operators to enhance passengers’ experiences. | Air transport |
| Filieri et al. [19] | AI is an innovative and digital tool that identifies and predicts the entrepreneurial characteristics and performance outcomes of people, teams, and organisations. | Hospitality and tourism |
| Samala et al. [68] | AI is defined as the development of computer systems that can perform tasks and activities that require human intelligence. | Tourism and air transport |
| Doborjeh et al. [12] | AI is an emerging technology that solves problems in all areas. | Hospitality and tourism |
| Bulchand-Gidumal [53]; Wamba et al. [54]; Knani et al. [55] | AI is based on the analysis of historical data by powerful algorithms to generate new knowledge, such as predictions and classifications. | Air transport, tourism, hospitality, and supply chain management |
| Huang et al. [69] | AI is a computer or software that obtains and analyses real-time data. | Hospitality and tourism |
| Ogunsina and DeLaurentis [49] | AI is the field that studies and applies interdisciplinary principles to achieve computationally intelligent agents that can directly assist humans with their day-to-day functions. | Air transport |
| García-Madurga and Grilló-Méndez [56] | AI is a computer system that formulates algorithms and methodologies that seek auto-learning, reasoning, and understanding to resolve problems and improve operational efficiency. | Tourism and air transport |
| Dangwal et al. [50] | AI is a digital tool used to improve the speed, creativity, and knowledge of service, leading to enhanced customer satisfaction. | Tourism |
| Merlo [57] | AI is a computer system that predicts potential process failures and optimises operational performance. | Air transport |
| Kim et al. [25] | AI is a computational agent endowed with humanlike cognitive, perceptual, and conversational abilities. | Hospitality and tourism |
| Florido-Benítez and del Alcázar [4] | AI is a disruptive technology that is being used by smart tourist destinations (STDs) to develop new business models and marketing services to increase tourists’ experiences and sales, revenue, productivity, efficiency, and STDs. | Tourism |
| Doğan and Niyet [8]; Wang and Uysal [70] | AI is a digital tool that offers personalised experiences to tourists and speeds up and improves operational efficiency in tourism companies. | Tourism |
| Zaoui et al. [17]; Zafar [71] | AI is the science and engineering of making intelligent computer programmes. | Air transport |
| Soliman et al. [18] | AI is a technology that involves programming computers and intelligent devices to perform tasks that require independent thinking, learning, and decision-making. | Air transport |
Technologies like the metaverse and AI have permeated the tourism and travel industry, and they are being used to gain a competitive advantage in a changing global market that demands a view of the bigger picture and the future of smart tourist destinations (STDs) [72]. Seoul, Santa Monica, Dubai, London, Tokyo, New York, or Shanghai are a true examples of this type of market, where AI, metaverse, augmented reality (AR), virtual reality (VR), machine learning (ML), blockchains, extended reality (XR), and internet of things (IoT) technologies are complemented to offer better services and experiences to tourists. The implementation of all of these technologies empowers STDs by allowing them to analyse tourists’ behaviours, preferences, motivations, and trends to design and deliver tailored recommendations, elevate the tourist experience, and optimise resource allocation [59,73].
From an efficiency and operational point of view, AI enables hospitality, tourism, and travel organisations to streamline their operations, offer quality tourist services, and lower costs [25]. Technologies based on IoT and AI algorithms have greatly accelerated the development of STDs and enhanced tourists’ experiences [74]. As proof of this, DMOs’ websites are implementing AI algorithms to forecast tourist arrivals [75]; AI techniques are also used in tourism planning in urban areas to adapt tourism and travel services to user demands [76].
However, AI technology has potential negative aspects such as job loss, privacy concerns, machine ethics, security issues, and negative developments in superintelligence [47]. For instance, Rostami and Navabinejad [77] found that chatbots supported by AI need to understand and adapt to consumers’ emotional states and learn empathy, as well as enhance privacy and data security. Indeed, there is a huge gap in the use, adoption, and perception of AI technologies by people with disabilities, older adults, racial and ethnic minorities, gender, and low-income populations [78]. Because important decisions that impact people’s lives are involved, resolving ethical issues is essential when using AI for social justice. AI technologies must be created and applied in a transparent, equitable, and responsible way to ensure their positive effects [79]. The potential for AI decision-making algorithms to unintentionally reinforce discriminatory practises raises questions about bias and justice. Furthermore, the way AI affects human autonomy begs important questions regarding where the lines are drawn between technology influence and human agency. As a result, organisations must guarantee informed consent, data anonymisation, and strict data protection procedures in order to utilise data in a responsible and ethical manner [80].
4. The Adoption of AI Methods and Applications in Travel and Tourism Activities
Tourism and travel activities are highly dependent on technological solutions, as we have seen during the period of the COVID-19 pandemic. The adoption of AI in tourism and travel companies can increase tourists’ experiences as a moderating element of their satisfaction, perceptions, scepticism, expectations, and technological anxiety [81]. Most large airports are using AI technologies to speed up security control procedures, such as airport security scanning devices, facial recognition, monitoring and scanning of baggage, or even chatbots and robots that provide specific information to passengers. Therefore, consumers’ awareness and knowledge about technology are crucial factors for the implementation of AI applications in the tourism, hospitality, and air transport sectors [21,82].
For instance, blind people, people with reduced mobility, and people with other disabilities require different services and needs in terms of access to information and travel when they travel; thus, public transport and DMOs’ websites linked to AI and GPS applications improve the quality of information and services for these groups [83,84] and contribute to empowering inclusive and accessible tourism [85]. The Airports Council International (ACI) recognises that people with disabilities and reduced mobility require specific information about the accessibility of airport infrastructure and that AI applications can provide ubiquitous information about airlines and airports’ services and amenities ahead of travel, which helps to reduce the anxiety of this group and ensure that they are well prepared in advance [86].
Izchak [87] notes that AI has made great advances in the tourism and air transport industries because, thanks to the implementation of this technology in both sectors, chatbots and AI assistants are allowing travellers to book flights and accommodations and hire vehicles online. Possibly, these new advantages that provide AI technology for consumers will be the beginning of a promising future with regard to the development and creation of new opportunities for organisations and consumers. For example, AI and ML techniques have achieved great success in resolving Saudi Arabian airlines’ flight delays and reducing air traffic congestion at airports to improve passengers’ experiences [26].
When consumers plan their trips, an AI assistant can help them perform everything, from booking their hotel to adding the dates to their calendar. We must be aware that an AI travel assistant acts as a travel agent, but without an actual human on the other end. Ivanov and Webster [88] suggest that adopting AI and service automation in travel and tourism activities through chatbots, robots, self-service information/check-in/check-out kiosks, or a robot concierge changes consumers’ experiences and the workforce of organisations [89]. A total of 68% of business travellers and 56% of leisure travellers value personalised recommendations from AI applications, and 64.8% of travel and hospitality professionals already use chatbots [90]. Pillai and Sivathanu [91] revealed that chatbots provide useful and trustworthy information to plan tours and create travel itineraries for tourists. The AI-enabled tourism and transport services help to evolve the trip into a unique experience for tourists, and they feel more self-sufficient [92].
Tourists are more demanding than ever, expecting immediate responses from DMO, airline, and OTA platforms, and AI allows them to deliver response times to tourists that would be impossible for humans. The adoption of AI methods and applications (e.g., ML, Alexa, GitHub, Google Gemini, ChatGPT, Elicit, Microsoft Copilot, Guidegeek, GPT-4, and Perplexity.AI, amongst many others) in hospitality and transportation spaces facilitates the experience of co-creation and consumer service delivery. Indeed, a variety of AI methods and applications have been adopted by hospitality operators, transportation, theme parks, and museums to enhance service quality, provide novel experiences, and improve marketing and promotion strategies [93]. Moreover, AI methods and applications enable the personalisation of the tourism offered in cities, as well as the improvement of companies’ operations and increased productivity [94].
Figure 2 illustrates the main AI methods applied in the tourism and air transport industries, supported by the authors and organisations. AI provides added value in travel and tourism activities because of data and interconnections between companies and consumers [95]. For instance, the airline industry is one of the most prominent industries for business as well as leisure, using AI technology applied to chatbots, robots, IoT, booking engines, ML, AR, VR, and neurolinguistic processing to provide better-valued services for passengers [47,96]. According to the International Air Transport Association (IATA), passengers require their smartphones that are linked to AI technology to receive notifications of flight disruptions or changes. In-flight entertainment, bag tracking, a smoother experience at customs, and security processes are all monitored and run by AI technology [97]. This leads us to think that tourism and travel companies need to rethink the interaction between the adoption of AI technology and new customers who demand new technological processes in the planning and purchasing of products and services.
Indeed, Florido-Benítez [14] argues that tourism and travel companies and DMOs must implement cybersecurity and AI technologies to prevent possible vulnerabilities and future cyberattacks and guarantee the operability of their communication as well as information systems in STDs and airports [98,99]. On the contrary, Demertzi et al. [100] note that AI, AR, VR, XR, and IoT technologies provide new vulnerabilities and cyberthreats to STDs and companies. Furthermore, it is important to point out that one of AI technology’s greatest strengths lies in the immediacy of response and advice that swiftly help tourists plan their trips, tours, detailed itineraries, and flight bookings at the same time. A total of 85% of leisure travellers decide on activities only after having arrived at the destination [101]. AI technology in DMOs, STDs, airports, airlines, and hotels can also be used to analyse tourist requirements and help in increasing brand awareness, sales, and revenues for the companies and tourist destinations. However, there are still problems with AI products and services that need to be designed and improved by DMOs and travel and tourism companies to complete the tourist’s experience [65].
Figure 2The adoption of AI methods and applications in travel and tourism activities. Source: Own elaboration according to the authors as shown in the figure [1,2,3,4,5,6,7,8,9,10,12,13,14,16,17,18,19,21,22,26,27,42,43,48,49,51,52,56,57,62,63,64,68,69,73,74,76,83,84,85,91,92,94,95,98,99,102,103,104,105,106,107,108].
[Figure omitted. See PDF]
5. The Management of Passengers and Tourists’ Experiences at Airports and Cities Through AI
The World Tourism Organisation (UNWTO) reported that the management of data and AI algorithms is helping destinations better manage tourist flows to develop and apply new COVID-19 health and safety protocols [104]. Tourists receiving precise information about the city or tours is of the utmost importance, and without delay, through AI applications. Rai and Rai [109] note that most DMOs’ websites provide a wealth of information about different cities and tourist attractions that sometimes makes it impossible for tourists to collect and rearrange accurate and immediate information about a particular city or tourist attraction. Thus, AI technology is actually the best solution to this problem for tourists and travel and tourism companies [55,109].
In addition, AI applications and algorithms are able to segment tourists based on a specific motivation and preference (e.g., tourists like to visit theme parks) or even segment one tourist, known as hyper-segmentation. For example, for a tourist who visits the same destination every year or has a second residence in a foreign destination, AI applications can offer them different products and services every year. AI methods and applications have the capacity of achieving the hyper-personalisation of a tourist’s travel plans to generate a customised offer adapted to them according to their motivations, needs, behaviours, and preferences. For this reason, tourist destinations, DMOs, and travel and tourism companies are adopting an ongoing AI test-and-learn approach to ensure that their offers and marketing and promotion campaigns are aligned with tourists’ preferences and expectations.
Tourist destinations, airports, airlines, and OTAs should use AI technology in the initial phases of a trip, during the trip, and after it to improve the tourist experience throughout their journey. For instance, social media and AI applications have a notable influence on travel decisions. These platforms allow travellers to access shared experiences, directly influencing their choices by providing opinions and recommendations from the online community. Wong et al. [110] emphasise that the ChatGPT tool facilitates planning and considerably reduces the search time for travellers searching relevant information, improving the traveller’s decision-making process in the pre-trip, en route, and post-trip stages. In the same vein, Basset [111] notes that the best uses of AI for travel are located in the planning and purchasing phases because this digital tool provides multiple flights and suggests destinations based on certain parameters and algorithms.
Furthermore, to improve passengers or tourists’ experiences, they can narrow their search by choosing where they want to travel with this useful tool. AI technology is skilled at responding immediately and without delay to specific interests, whether they are looking for the most recognised local restaurants in the city or designing a four-day itinerary to visit French cathedrals, dives at the coral reefs, or private tours. AI applications can even provide the price of ticketed music concerts around the globe and also book a private jet for individuals to see their favourite singer in New York. Therefore, AI technology-empowered tourism experiences increasingly support and encourage tourists to expand on the notion of co-creation and AI throughout all stages of travel [108]. Hence, the management and analysis of users’ preferences and experiences also allows DMOs and tourism and travel companies to identify patterns and trends in traveller behaviour, thus improving marketing strategies and the offer of products and services according to changing market needs.
De Carlo et al. [66] suggest that AI methods help DMOs design destination strategies in urban cities to improve tourist experiences. A study carried out in Lanzarote (Canary Islands, Spain) by Ferràs et al. [112] showed that it is possible to increase tourist satisfaction by offering a set of customised activities and experiences through AI technology according to their personal characteristics and motivations. According to the World Travel and Tourism Council (WTTC), the crucial importance of AI in revolutionising the tourism and travel industries is that for tourists, the ability to have immediately personalised offers at booking or while in destination enhances their travel experiences via the engagement and process automation of DMOs and companies [113]. Wamba et al. [54] found that AI’s main strengths in supporting organisations concern its improvement in the performance of administrative, marketing, and financial departments. For instance, chatbots and robots linked to AI technology are replacing people, and they have also become a requirement for future tourism and travel services [114].
Viewed as a key growth factor for tourism and travel activities, Kim et al. [115] revealed that ChatGPT provides a positive experience for users to plan for future travel, and DMOs and travel and tourism companies should leverage AI technology’s strength through various communication channels to promote their products and services. The development of AI methods and applications has become an important factor in the competitiveness of tourist destinations, as that is a differentiating factor between destinations, especially in STDs [116]. It is not a question of simply thinking about AI technology and its benefits; mainly, it is about enhancing the tourists’ experiences, which ultimately enables them to consume more tourist and travel products and services to increase the sustainability of the tourism industry in cities. For instance, the concept of “aerotainment” created by Florido-Benítez, Morrison, and Coca-Stefaniak [117] refers to improving tourism experiences, environmental sustainability, and local economies in urban destinations within close proximity of airports and tourist attractions, which must be supported by new technologies to provide segmented and personalised products and services.
It cannot be denied that the combination of open innovation and AI generates new opportunities and synergies in tourist destinations. Furthermore, tourist destinations and organisations do not have the economic resources to implement AI in their operating systems and processes to improve operational efficiency, tourist experiences, sustainability, and the development of the destination. In the more immediate future, tourist destinations and tourism and travel organisations may be motivated to invest in AI methods and applications if they improve financial performance by reducing costs, generating revenues, enhancing the competitiveness of the destination and the tourist experience, and providing value for tourists and passengers. However, the management of passengers and tourists’ experiences at tourist destinations and airports through AI should be tackled from the perspective of technology and economic resources, tourism supply, and cultural characteristics of each city and airport.
6. Conclusions
The main purpose of our study was to illustrate the use of AI in the tourism and air transport industries to improve tourists’ experiences, as well as provide a definition of the AI concept that is the closest to both sectors. Initially, this paper shows how AI technology has helped to outline travel planning for tourists, made it easier to discover new experiences, and streamlined the booking process. In addition, AI methods and applications are providing new changes for travel and tourism companies and tourists. However, it is important to emphasise that one of AI technology’s greatest strengths lies in the immediacy of response and advice that swiftly help tourists plan their trips, tours, detailed itineraries, flight bookings, and resolve unexpected disruptions at the same time. AI has revealed its ability to boost organisations’ efficiency as well as enhance the tourist experience and create new business opportunities in the travel and tourism industry. For instance, chatbots interact with consumers through native languages and promote positive changes in consumer behaviour.
Indeed, AI applications are enhancing tourists’ experiences because they help tourists resolve their queries immediately, customise tours, and compare the facilities offered by hotels or airlines. For instance, robots and chatbots linked to AI algorithms are being introduced by airports, airlines, hotels, DMOs, and OTAs to offer instant customer support and assistance. In brief, AI simplifies the processes and time of tourists when they want to book or buy a vacation trip, a flight, or a personalised service. AI technology is vital for the management and marketing strategies of cities because this digital tool boosts the sustainability and efficiency of the travel and tourism industry. The sustainability of tourist destinations and public and private transport through AI technology can help with mobility and zero-emission issues, and it is an open debate that governments and companies will have to address in concrete terms. If we add to this that AI is capable of developing traveller hyper-segmentation by providing tailored services to travellers through hyper-personalisation, as well as adjusting prices according to future demand and supply in order to maximise hotel occupancy levels and tourism services in cities, then we are possibly at the forefront of one of the biggest digital tools ever created in the tourism industry.
The tourism and travel industry is highly competitive, and tourists’ experience and satisfaction are the main factors in conducting business, so generating a tourism supply depending upon the tourists’ behaviours is a new strategy applied to AI technology by companies. This is one of the main reasons why this study has developed a new concept of AI in a tourism and travel context, which has been insufficiently analysed in the tourism and travel scientific literature. Thus, this manuscript defines AI as an immersive and technological tool that has the capacity to create individualised information and offers that satisfy tourists’ wants and needs in real-time and without delay, as well as a sophisticated prediction and efficiency tool that helps us to make better decisions for managers’ tourism and travel companies to optimise operational performance. This new concept of AI is useful and a reference point for future research, where AI technology can be analysed in a tourism and travel context and can focus on the tourist’s experience and the efficiency and sustainability of both sectors. This paper has emphasised the need to apply cybersecurity and AI technologies in tourism and travel companies to prevent possible vulnerabilities and future cyberattacks, so future research should analyse how AI and cybersecurity technologies could guarantee communication and operations between tourism and travel companies and tourist destinations. Indeed, according to our results, we suggest that future research focus on the use of AI algorithms to manage companies’ operations and the privacy of user data and information, as those are their main weaknesses.
7. Theoretical Implications
The contribution of the current manuscript is twofold. First, this study provides a new conceptualisation of AI that may help future academics and researchers develop their literature review and variables depending on their tourism and travel trends and their relationship with AI methods and applications. We argue that to encourage AI methods and applications in the scientific community, the tourism and travel sector requires a multidisciplinary perspective and different points of view on the AI concept to understand the relevance of this disruptive tool in the immediate future. AI technology makes it easier for companies and researchers to analyse, interpret, respond, and use data through better visualisation and transparency to solve issues and forecast future events. Second, our structured and defined analysis illustrates how AI technology is emerging strongly in tourism and travel activities because it resolves immediate consumers’ queries and provides them with recommendations and personalised offers to improve their experiences and satisfaction.
Although there is a lack of understanding of AI technology to create business value, specific proposals and implementing AI in personalised products and services will boost operational efficiency in firms [118]; in fact, there is a recent need to evaluate the use of AI technology and its impact on decision-making and its benefits. The innovation of AI and its rapid integration across multiple disciplines have prompted questions regarding the subjectivity of this disruptive tool and how the scientific community and organisations are using it to improve the environment, climate change, population quality of life, and operational efficiency of companies. Hence, researchers and travel and tourism companies should be aware that AI technology will completely change the research and sales paradigm and that this emergent tool will remotely manage and control most environmental, sustainability, climate, scientific, and commercial processes.
8. Managerial Implications
From a practical perspective, innovative knowledge and AI technologies are generating relevant changes in tourism and travel activities, making some commercial processes and other technologies obsolete. We should not forget that tourism and travel are two of the most competitive industries on earth, making it necessary for firms to innovate and constantly reinvent themselves to maintain their economic activity and profitability. For this reason, DMOs and companies should adopt AI methods and applications in their commercial activities to enhance their tourism supply, increase their productivity and efficiency in terms of time and cost, make better decisions, and, most importantly, maximise sales through digital channels.
On the other hand, from the tourist’s point of view, AI provides ubiquitous offers and recommendations to tourists related to their preferences and needs due to AI algorithms analysing and leveraging the antecedents of tourists’ information, purchases, queries, and searches. For instance, Amazon serves personalised product and service suggestions through personalised messages and emails. Puntoni et al. [119] note that given the growing ubiquity of AI in consumers’ lives, DMOs and companies are obsessed with creating valued consumer experiences through AI algorithms as a differentiating factor against their main competitors, even though this commercial strategy may undermine consumers’ experiences with AI. This manuscript also stresses the escalation of privacy concerns among individuals and AI applications regarding the utilisation of their personal data, especially in terms of vulnerabilities and cyberattacks. Therefore, travel and tourism organisations need to reinforce these weaknesses to secure commercial transactions and guarantee the privacy of consumers.
The adoption of AI into commercial activities and their legal practises also raises concerns for consumers and organisations. The European Commission (EC) proposes national liability rules for AI, making it easier for victims of AI technology-related damage to receive compensation [120], covering breaches of privacy or damages caused by safety issues. The US, UK, and EU hold pivotal positions around the future of global AI governance in setting standards for AI risk management. Although a US or UK company has customers in the EU and operates with partners across European countries, it will need to play by the EU AI Act rules [121]. To address these new and emergent challenges, the importance of human oversight in AI-driven algorithmic processes and its decision-making have to be continuously monitored and adjusted by legal professionals and government bodies.
9. Limitations of the Study
This research project used a systematic review technique to illustrate the literature review on AI technology. Nevertheless, this manuscript also has certain limitations because it is limited to an exploratory investigation of the use of AI in the travel and aviation industries. In addition, this study is based on a systematic literature review using only the WoS database and 888 documents, which provides one limitation in terms of database and documents. Therefore, this paper did not collect and analyse data and information from other databases, such as Scopus, Google Scholar, PubMed, and EBSCO, amongst many others, and there is a possibility that the authors might have missed some relevant studies and expert authors in this topic from other databases. Another limitation is that this study does not provide relevant information and opinions from tourism and travel operators, which could help to have a better global vision of how AI technology is being used by companies and customers nowadays. Lastly, the adoption of AI by companies offers great advantages for travellers and urban cities; however, this manuscript did not include real data related to the problem of loss of human interaction and experience (e.g., empathy and emotion) amidst countless automatisms (e.g., chatbots and robots supported by AI) that might discriminate against people, for example, with special needs and low income, who have no literacy in information and communication technology (ICT) and the side product of job replacement by automatic services. These and other hurdles to IA must, as well, be addressed in future studies.
10. Avenues for Future Research and Recommendations
This study gives guidance for further research as well as insights into the body of knowledge regarding AI in travel and tourism. The results underline the need for further scholarly attention and the expanding importance of this field of study to improve tourism experiences in tourist destinations and air transport. For instance, future studies should analyse the multifunctionality of AI technology in cities and airports and which factors can help to improve personalised products and services for travellers, reducing costs for organisations and being more efficient in marketing and promotion campaigns. Moreover, future work should tackle questions about AI utilisation by companies in terms of customers’ private information and cybersecurity to protect sensible information that can be used by hackers and companies with spurious interest to subsequently sell on the dark web. Building public trust and ensuring appropriate data management in AI development and implementation depend heavily on transparency and accountability.
Hence, the knowledge needed to plan an attack is in high demand among cybercriminals due to the growth of the cybercrime-as-a-service business model. In 2022, the Kaspersky company examined around 200 posts on the dark web that offered to purchase information in order to gain initial access to businesses’ systems. When compared to the possible harm it could cause to targeted businesses, the typical cost of gaining access to a large company’s systems is between USD 2000 and USD 4000. Ransomware operators are particularly interested in these services since they have the potential to make up to USD 40 million annually [122]. Additionally, findings of the current study suggest that AI can be the perfect tool to enhance the tourist experience and create new business opportunities in travel and tourism activities. However, future research should examine and analyse other new technologies like quantum computing and DTs to boost tourism demand in urban cities and airports, as well as prevent future cyberattacks by cybercriminals and hackers.
Conceptualisation, L.F.-B. and B.d.A.M.; validation, L.F.-B. and B.d.A.M.; formal analysis, L.F.-B. and B.d.A.M.; investigation, L.F.-B. and B.d.A.M.; resources, L.F.-B. and B.d.A.M.; writing—original draft preparation, L.F.-B.; writing—review and editing, L.F.-B. and B.d.A.M.; visualisation, L.F.-B. and B.d.A.M.; supervision, L.F.-B. and B.d.A.M.; project administration, L.F.-B. and B.d.A.M. All authors have read and agreed to the published version of the manuscript.
No new data were created or analyzed in this study. Data sharing is not applicable to this article.
The authors would like to thank the anonymous reviewers and editors for providing valuable suggestions and comments.
The authors declare no conflicts of interest.
Footnotes
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![View Image - Figure 1. Number of publications and citations on “AI” and “tourism”; and “AI” and “air transport” terms between 2015 and 30 September 2024. Source: Own elaboration from WoS [33].](https://media.proquest.com/media/hms/THUM/2/t3Z9b?_a=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%3D%3D&_s=9rYOLqwjJz76QLeky24PCT1ktgs%3D "View Image - Figure 1. Number of publications and citations on “AI” and “tourism”; and “AI” and “air transport” terms between 2015 and 30 September 2024. Source: Own elaboration from WoS [33].")
Enlarge this image.Figure 1. Number of publications and citations on “AI” and “tourism”; and “AI” and “air transport” terms between 2015 and 30 September 2024. Source: Own elaboration from WoS [33].
The top ten countries and universities by number of “AI” and “tourism” documents published between 2015 and 30 September 2024.
| The Top Ten Countries by AI and Tourism | Nº Documents | |
| 1 | China | 224 |
| 2 | USA | 99 |
| 3 | Spain | 67 |
| 4 | England | 64 |
| 5 | India | 61 |
| 6 | Portugal | 40 |
| 7 | South Korea | 32 |
| 8 | Turkey | 30 |
| 9 | Italy | 29 |
| 10 | Taiwan | 26 |
| The top Ten Universities by AI and Tourism | Nº Documents | |
| 1 | Hong Kong Polytechnic University (China) | 28 |
| 2 | State University System of Florida (USA) | 24 |
| 3 | University of Macau (Macau) | 18 |
| 4 | Varna University of Management (Bulgaria) | 15 |
| 5 | Bournemouth University (UK) | 11 |
| 6 | Kyung Hee University (South Korea) | 11 |
| 7 | Nankai University (China) | 10 |
| 8 | University of Surrey (UK) | 10 |
| 9 | Ball State University (USA) | 9 |
| 10 | Egyptian Knowledge Bank Ekb (Egypt) | 9 |
Source: Own elaboration from WoS [
The top ten countries and universities by number of “AI” and “air transport” documents published between 2015 and 30 September 2024.
| The Top Ten Countries by AI and Air Transport | Nº Documents | |
| 1 | China | 22 |
| 2 | USA | 21 |
| 3 | England | 10 |
| 4 | South Korea | 9 |
| 5 | Spain | 9 |
| 6 | Germany | 8 |
| 7 | India | 8 |
| 8 | Iran | 8 |
| 9 | Italy | 7 |
| 10 | France | 6 |
| The Top Ten Universities and by AI and Air Transport | Nº Documents | |
| 1 | Chinese Academy of Sciences (China) | 5 |
| 2 | University of Chinese Academy of Science Cas (China) | 5 |
| 3 | Changzhou Institute of Technology (China) | 3 |
| 4 | Indian Institute of Technology System IIT System (India) | 3 |
| 5 | Shahid Beheshti University (Iran) | 3 |
| 6 | University of Tabriz (Iran) | 3 |
| 7 | University of Texas System (USA) | 3 |
| 8 | Beihang University (China) | 2 |
| 9 | Chongqing Jiaotong University (China) | 2 |
| 10 | Hong Kong Polytechnic University (China) | 2 |
Source: Own elaboration from WoS [
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