How Generative AI Is Transforming Travel and Hospitality Post-COVID

Generative AI and Online Collaboration in the Post-COVID Travel and Hospitality Industry: A Social Construction of Technology (SCOT) and Actor–Network Theory (ANT) Analysis 

The COVID-19 pandemic triggered an urgent digital reckoning across the travel and hospitality sectors, compelling organisations to rethink their operational models in the face of lockdowns, travel restrictions, and shifting consumer expectations. As physical presence became limited, online collaboration tools and digital platforms emerged not only as survival mechanisms but as integral components of post-pandemic innovation. Among these, generative artificial intelligence (AI) has proven especially transformative, not merely assisting processes but actively reshaping how collaboration, service, and strategic decisions are designed and delivered (Abbas et al., 2021). 

This essay argues that post-COVID, generative AI is more than just a useful tool. Instead, it is an active force co-creating fresh kinds of online cooperation and innovation across the travel and hospitality sectors. Using Social Construction of Technology (SCOT) and the Actor-Network Theory (ANT), the study demonstrates how artificial intelligence-driven systems in customer service, marketing, and strategic management have evolved through sociotechnical interactions, reflecting both human intentions and the agency of machines. This is done through a critical analysis of three case studies. They include Airbnb's Online Experiences, AI-enhanced customer service, and AI-powered marketing strategies, examining how generative AI redefines roles, mediates stakeholder relationships, and transforms networks of power, trust, and knowledge. It also highlights three primary challenges, worker displacement, data privacy concerns, and opposition to technological change, thereby stressing the need for treating artificial intelligence in the travel and hospitality sector carefully, ethically, and with full awareness of its social embeddedness. 

Applying theoretical models that combine human agency with technological mediation can help critically evaluate how generative AI has changed online cooperation and innovation in the travel and hotel sectors. As Dwivedi et al., (2023) propose, understanding the interaction between technology capabilities and social dynamics is essential for evaluating how generative AI transforms operational practices, cooperation models, and service innovation within hospitality ecosystems.  

Advanced by Bijker (2009) and colleagues, the Social Construction of Technology (SCOT) suggests that the interpretations, agreements, and power relations of different social groups affect technology more than it is autonomous or self-determining. SCOT underlines how much the shape, acceptance, and development of various technologies depend on relevant social groups, including engineers, legislators, and consumers. "Interpretive flexibility," a fundamental idea in SCOT, holds that depending on the viewpoints of users, designers, and legislators, technologies can have several meanings. 

Developed by Latour (2005), Actor–Network Theory (ANT) conceptualises technologies not as passive tools but as active participants, or "actors," within sociotechnical networks, providing a critical lens for examining the role of generative AI in this study. As demonstrated by Chitanana (2021) in the context of Web 2.0-based educational collaboration, generative AI not only facilitates interaction but actively shape it. Applying this perspective to tourism and hospitality, generative AI must be recognised not merely as infrastructure, but as an active mediator of experiences, connections, and shared values within digital tourism and hospitality environments. 

ANT argues that the agency of technologies such as generative AI arises from their entanglement with policies, infrastructure, algorithms, and users, therefore transcending the difference between human and non-human actors. AI-driven solutions, such as recommendation engines, customer service bots, or automated pricing algorithms, do not just support operations in the tourism and hospitality sector. They actively help to define business plans, decision-making procedures, and visitor experiences. 

Apart from SCOT and ANT, Castells' (2007) concept of the "network society" is rather pertinent. Castells contends that, instead of institutions, power is used in digitally linked societies through communication networks. He presents the idea of "mass self-communication," in which people and companies use digital technologies to create new kinds of cooperation, change perceptions, and shape stories. Generative artificial intelligence amplifies this dynamic by enabling automated, hyper-personalised communication at scale, a trend evident in guest engagement strategies and post-pandemic hotel marketing. 

By showing how digital technologies are ingrained in current social logics and institutional frameworks, Sassen (2002, 2005) sharpens the analytical lens even more. Sassen argues that whereas digitisation permeates social institutions rather than replaces them, it reinforces some hierarchies while undermining others. The adoption of generative AI in the hotel sector could reinforce inequality (e.g., through biased recommendation algorithms or unequal data access), even as it offers efficiency and creativity. 

Taken together, SCOT, ANT, and the complementary viewpoints of Castells (2007) and Sassen (2002, 2005) enable us to question and examine case studies, to discover, not just what AI does but also how it becomes legitimised, challenged, or changed via group human action and institutional arrangements. They offer the framework for examining the sociotechnical co-evolution of generative AI inside the post-COVID digital revolution of the travel and hotel sectors.  

Starting with Airbnb's release of "Online Experiences" amid the height of the COVID-19 epidemic is a striking illustration of sociotechnical convergence. Airbnb responded by developing virtual experiences, ranging from remote cooking courses to cultural excursions via Zoom, while international travel was on pause and traditional bookings declined. From a SCOT standpoint, this quick change emphasises the impact of social groups, hosts looking for other income sources, guests longing for cultural interaction, and investors pushing innovation, all of which help to accept and stabilise this digital pivot. These players saw the "experience" differently, and closure was achieved when some forms became standardised and financially viable via ongoing feedback and platform changes (Bijker, 2009). 

Complementing this reading, ANT charts the actor-network behind these turning points. All engaging inside a dynamic network, this includes human hosts, AI-powered recommendation systems, video conferencing tools, smartphone apps, and guest gadgets. While AI-enhanced technologies choose content visibility and helped translating, Airbnb's algorithms affected user exposure. Essential participants in the co-creation of guest enjoyment and perceived value, generative AI systems such ChatGPT enable customisation and scalability in tourism, hence improving their relevance. 

Technology changed what an experience meant, how it was co-created, and how it would be monetised at scale within a disrupted global market — not just enabling isolated events. Running linguistic adaptations and recommendation engines, artificial intelligence systems have become more important centres within more general socio-technical networks. Faster feedback loops, efficient scaling, and more cross-cultural interaction made possible by artificial intelligence help ANT's view of dispersed agency among human and non-human players (Latour, 2005). Building on the role of generative AI in shaping online experiences, we now turn to examine how these technologies are also transforming front-line service delivery and operational standards across travel and hospitality ecosystems. 

As we widen our analysis of post-COVID generative AI distribution, the development of AI-powered customer service also shows how these technologies are transforming front-line hospitality operations and redefining cooperative standards throughout service ecosystems. Sophisticated chatbots nowadays, thanks to generative AI, can control guest bookings, offer real-time information, and address problems in several languages and platforms. From a SCOT standpoint, this change shows a convergence of social dynamics, including economic pressures such as staff shortages, growing consumer expectations for responsiveness, and operational needs of companies wanting 24/7 service provision. Here, the idea of interpretive flexibility is evident. Although some guests perceive a lack of human warmth or authenticity, others view AI-driven services as efficient, responsive, and helpful (Bijker, 2009). 

By putting artificial intelligence as a completely integrated part of the hotel chain's business operations, ANT offers still more knowledge. These tools link digital marketing infrastructure, CRM systems, and customer databases rather than acting as one-sided remedies. Their existence changes the way value is co-created across departments, distributes decision-making power, and reallocates human jobs, therefore influencing organisational processes. As Ling et al. (2023) underline, AI-powered assistants are now crucial in handling multilingual communication, service personalisation, and operational decision processes in hotel settings. Moreover, ChatGPT and other technologies are progressively included into hotel recommender systems, producing very personalised guest experiences that change service ecosystems (Remountakis et al., 2023). This helps ANT's emphasis on technology as relational actors that affect and are affected by the systems in which they operate (Latour, 2005). 

Recent studies highlight even more the transforming possibilities of generative AI in the hospitality industry. For example, Fui-Hoon Nah et al. (2023) underline how increasingly AI-driven service systems are utilised to reduce customer-service friction, personalise interactions, and forecast guest expectations, so promoting more cooperative service experiences. By means of repeated learning and behaviour recalibration, these tools co-produce services, therefore embodying the adaptive, actor-driven networks imagined by ANT. The degree of these benefits, though, mostly relies on how businesses define artificial intelligence—as a front-stage ambassador for guest involvement or a behind-the-scenes operational booster. Building on the changing function of artificial intelligence in customer service, it is also crucial to investigate how generative artificial intelligence changes more general strategic domains, especially marketing techniques and organisational decision-making across the hotel sector. 

For marketing teams trying to drive brand uniqueness and customise guest communications in the hotel industry, generative AI is becoming ever more important. These technologies help newsletters to be created, generate social media content, and personalise advertising offers depending on real-time behavioural data. Recent research show how technologies like ChatGPT improve the scalability and personalising of marketing efforts, consequently improving visitor involvement and conversion rates (Remountakis et al., 2023). From a SCOT perspective, these actions show how customer demand for tailored experiences, competitive brand positioning, and scalable content creation helps to accept artificial intelligence under societal and business pressures. Different hotel actors understand and use artificial intelligence in different ways depending on their needs and limits, therefore supporting the interpretive flexibility concept (Bijker, 2009). 

Rather than operating just as technical tools, AI-generated content platforms work with human marketers, social media channels, and analytics dashboards to co-create brand narratives. These outputs affect the frequency, timing, and tone of messages, therefore forming guest impressions and expectations. From the managerial standpoint, generative AI also powers systems for seasonal demand analysis, price strategy optimisation, and loyalty program enhancement. By doing this, artificial intelligence not only serves as a support system but also becomes a co-strategist influencing decisions all throughout the company (Latour, 2005). 

Recent research supports these findings. Not only for enhancing operational efficiency but also for their transforming effect on how hospitality companies understand and interact with consumers, generative AI technologies are increasingly prized (Dwivedi et al., 2023). These tools help to discover microsegments, modify content strategies, and mass synthesise guest comments. Complementing data analysts, marketing teams, artificial intelligence providers, and platform algorithms, generative AI tools create complex actor-networks driving engagement and improving conversion rates. 

Therefore, by both SCOT and ANT points of view, the integration of generative artificial intelligence into marketing and strategic management techniques shows even more how AI technologies reflect changing organisational values and actively transform industry standards in a very competitive post-COVID world. 

Generative AI has brought a new set of challenges even as it has sped innovation and changed collaborating in the travel and hospitality industries. These challenges cut into very political, moral, and social spheres, transcending simply technological ones. Recent research points to three important issues resulting from the spread of artificial intelligence: concerns on data privacy, concerns of worker displacement, and opposition to technological change (Dwivedi et al., 2023; Abbas et al., 2021; Fui-Hoon Nah et al., 2023). These challenges draw attention to the intricate socio-technical terrain that generative AI keeps changing. 

Many jobs formerly occupied by humans are being made redundant as generative artificial intelligence systems take over tasks, including visitor check-in, customer assistance, and even housekeeping operations. AI presents operational stability and cost savings, but SCOT reminds us that these technological changes are socially produced. Choosing to automate instead of creating jobs reflects business aims and power dynamics rather than inevitable advancement (Bijker, 2009). Among these challenges, workforce redundancy becomes especially important since artificial intelligence technologies' automation of service functions threatens to replace human labour in many spheres of the travel and hospitality business.  ANT supports this by stressing how workers kicked off the actor-network lose visibility and power inside the system (Latour, 2005). Their absence changes the service dynamic, lessens the chances for tailored visitor experiences, and disrupts accepted processes. Although some hotel chains have tried hybrid approaches, retraining people to oversee AI systems or manage more complicated client needs, research indicates that such initiatives remain erratic and underfunded (Ivanov & Webster, 2019). Furthermore, influencing opposition to workforce automation are more general mental health and resilience issues for displaced workers, as discussed by Abbas et al. (2021) in relation to COVID-era technical developments. Beyond the risks of human redundancy, generative artificial intelligence also raises profound ethical challenges related to the handling and governance of personal data in hospitality environments. 

Likewise, urgent are the data ethics issues raised by generative AI. To offer tailored services, these technologies depend on massive amounts of personal data, including voice commands, location tracking, and behavioural analytics. This datafication of hospitality introduces new vulnerabilities and power asymmetries. From a SCOT standpoint, customer confidence, cultural standards, and legal pressures all help to define the legality of data use (Bijker, 2009). 

ANT reveals even more the inherent weaknesses in the systems enabling artificial intelligence. Whether via a third-party distributor, a cloud database, or an under-regulated algorithm, a compromise at any level can undermine the entire service network and destroy visitor confidence and organisational reputation (Latour, 2005). Digital trust is becoming a major asset in smart hotel ecosystems, as Kandampully et al. (2022) note; once broken, it is somewhat difficult to rebuild. In this regard, as Houston et al. (2015) have shown, crisis response and the recovery of confidence relies mostly on the purposeful and disciplined use of social media and digital communication platforms. 

Ultimately, not every interested party welcomes the inclusion of artificial intelligence into tourism and hospitality. Resistance brings different challenges among employees, and guests. Some employees object to technology that compromises conventional service standards or jeopardises their employment stability. Guests accustomed to personal interaction may object to automated check-ins or chatbot-based communication. SCOT recognises resistance as evidence that technical closure has not yet occurred, and that AI's influence is still debatable and subject to negotiation (Bijker, 2009). 

ANT shows how this resistance shapes the network itself. Disengaged actors can cause delays or disruptions in implementation. Hence, companies have started using hybrid service models that combine optional human interaction with automation. As Fui-Hoon Nah et al. (2023) observe, effective AI adoption in hospitality typically hinges on establishing a balance between automation and empathy, allowing technology to improve, rather than replace, the human touch. Research by Martín-Rojas et al. (2023) also supports the idea that social media use and entrepreneurial adaptability are main causes of organisational resilience in post-COVID digital transitions, implying that hospitality companies must not only adopt technology but also cultivate cultures of collaborative innovation. 

These three challenges, taken together, emphasise the need to see artificial intelligence from perspectives that take equity, agency, and ethics into account, in addition to a prism of invention and efficiency. Reminding us that technology is always a social project and its path depends on the values we create in its networks, SCOT and ANT provide strong tools for negotiating these tensions. 

It is a fundamental actor who shapes the changes in strategic operations, services, and teamwork. Based on stakeholder needs, this paper explores, through the analytical lenses of SCOT and ANT, that artificial intelligence technologies are socially constructed, interpreted, and embedded in dynamic networks of influence and co-dependence. From Airbnb's digital shift to the reconfiguration of customer service and marketing, generative artificial intelligence not only shows up as a tool but also as a catalyst for redesigning standards, procedures, and relationships inside the organisation. 

Still, unresolved ethical issues obscure the transforming power of artificial intelligence. Data privacy questions, worker dislocation, and opposition to technological progress expose the sociopolitical problems caught in technology acceptance. These active elements of the networks artificial intelligence interacts with are not only side effects but also natural components of their socio-technical development. If innovation is to be sustainable and inclusive, leaders in tourism and hospitality have to go beyond efficiency measures to solve the engrained social logics of AI deployment. 

The design, control, and interpretation of generative AI will ultimately decide its future in the travel and hospitality industry. As SCOT reminds us and ANT shows, the meaning and effect of technology are always socially negotiated, relational, and dispersed. Accepting these viewpoints guarantees that we view artificial intelligence not only for its computing capability but also for its great possibility to fundamentally change how systems and people interact and adapt. The road forward must combine technical innovation with human-centric values to make sure AI not only generates but also significantly improves travel and hospitality experiences for everyone. 

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