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1. Introduction
Artificial intelligence (AI) has become a buzzword across society. AI studies focus on creating intelligent machines (Nilsson, 2010; Stone et al., 2016) and include the study of tools with human-like abilities such as sensing, learning, reasoning and acting (PwC, 2018a). AI is receiving worldwide attention for its power to drive economic growth and transform industries. It was forecasted that AI might boost the regional gross domestic product (GDP) by 26% in China, 14% in North America and 11% in Europe (PwC, 2018b, p. 21). In a survey distributed to employees in nine industries in 2018, 47% of all participants indicated that their companies utilized one AI technology at the minimum, and 30% reported their companies were piloting AI projects (McKinsey and Company, 2018).
The hospitality and tourism industry has witnessed exponential growth in its adoption of AI. Around 20% of transportation firms had adopted one or more AI technologies at scale in 2016, with a projected growth rate of 8% (McKinsey Global Institute, 2017). About 12% of other travel and tourism businesses (e.g. hospitality and entertainment) have embraced AI at scale with an annual growth rate of 6.5%. AI has been primarily used in service operations, with projected growth in product development, marketing and sales (McKinsey Global Institute, 2017). Previous research has identified the benefits of AI in the hospitality and tourism industry (e.g. Kong et al., 2021; Cain et al., 2019). AI technologies can offer various advantages for both suppliers (e.g. improved productivity, efficiency and profitability) and consumers (e.g. convenient and personalized tourist experiences) (Samara et al., 2020). However, there is less understanding of a theoretical framework for evaluating the adoption of AI in the hospitality and tourism industry. The McKinsey Global Institute (2017) calls for further research that examines the nature of the specific AI applications and assesses the susceptibility of adoption. To this end, this paper develops a framework for evaluating the adoption of AI in the hospitality and tourism industry using the diffusion innovation theory (Rogers, 2003) as the theoretical underpinning. The diffusion of innovation theory (Rogers, 2003) investigates variables that affect organizations and individuals in adopting innovative technologies.
The remainder of this article is organized as follows. Section 2 defines the subfields of AI...