The artificial intelligence enabled customer experience in tourism: a systematic literature review

Artificial intelligence (AI) is fundamentally changing the customer journey in tourism settings (Grunder & Neuhofer, 2021). From augmented reality (AR), mobile apps and virtual reality (VR) assistants, to chatbots, and service robots, the range and scope of interactions grow rapidly (Beck et al.,2019; Belanche et al., 2020; Pillai and Sivathanu, 2020; Serravalle et al., 2019). In tourism marketing literature, AI is viewed as key to transforming customer experiences (CX) (Hoyer et al., 2020). Indeed, new forms of CX with AI playing an influential role in experience formation are emerging (Buhalis, 2019) and are expected to significantly enhance the CX (Anaya & Lehto, 2020).

Literature on CX and its new AI-enabled forms is, however, fragmented and this adds an additional layer of complexity to already divergent perceptions on CX definition, dimensions, foundations, antecedents, and consequences (De Keyser et al., 2015; Waqas et al., 2021). Furthermore, the contextuality of CX and its role in CX formation, alongside the potential transformational role of technology are now more frequently discussed (Becker & Jaakkola, 2020). The AI-enabled CX (AICX) is thus a promising experiential context that calls for further research and exploration.
The aim of this study is to provide a comprehensive review of academic research related to customer facing AI technologies and CX in tourism. Accordingly, a systematic literature review (SLR) on the AICX in tourism was carried out in May 2021. Additionally, an updated database search took place in March 2022. To fulfil the research aim, the SLR put forward four questions: 1)What are the identified customer-facing AI technologies in the tourism context? 2)What are the methodologies used to study the AICX in the tourism context? 3)What are the theories used to study the AICX in the tourism context? 4)What are the research gaps in AI research on CX in the tourism context? Accordingly, five online databases were searched for peer-reviewed articles from journals listed in the CABS AJG 2021 guide. In total, 99 articles matched the eligibility criteria and were included in the review.
Following the TCCM framework (Paul et al., 2021), the analysis reveals that a wide range of theoretical frameworks are utilized with technology acceptance and adoption as well as consumer behaviour theories being most common. Methodologically speaking, the findings show that quantitative work is widely adopted where a reliance on questionnaires and scenarios is evident. The outcomes also identified AI-technologies across various tourism sectors and an emphasis on the encounter stage. Uncertainty still exists about the notion of the AICX, its antecedents, and its consequences. It pinpoints intriguing areas for research that remain unclear like the effect of AI effect on experience outcomes and consumer behaviour. The demand side is still understudied, for instance, consumer concerns about, motivations to accept, and perceptions on the AICX. Additionally, studies that explore the emotional aspect of AICX are needed. There are also repeated calls to examine theoretical frameworks in real-life settings where comparisons between different contexts, types of services, regions, and stakeholder groups would bring valuable insights on the AICX in tourism.