Investigating customer service and engagement levels in the lodging industry: high-touch to high-tech conversational AI

Abstract

Purpose Considering the need for operational efficiency and personalized guest experiences, this study aims to investigate the adoption of conversational artificial intelligence (AI) among practitioners and potential guests. Design/methodology/approach This study adopted a three-phase mixed-methods approach, combining qualitative data from industry focus groups with quantitative surveys of practitioners and prospective guests. Sentiment analysis was used to assess emotional authenticity, privacy/trust concerns, guest satisfaction and intentions to use conversational AI. Findings Findings indicate that emotional authenticity is the primary barrier to conversational AI adoption, as guests strongly prefer human-centric interactions. Despite technological maturity, privacy and trust concerns remain salient, especially in public/voice contexts. Guests showed mixed acceptance, while practitioners were significantly more positive, emphasizing the relief from workload. Originality The study examined the benefits and barriers to customer service and engagement levels, considering factors such as service interaction type, service complexity, customer personalization and service availability. This study offers new insights into intelligent virtual assistant (IVA) based conversational AI usage trends, platform choices and adoption among industry practitioners and potential guests. Practical implications The hospitality sector relies heavily on high-touch guest service and experiences. Most lodging sectors have adopted interactive voice response (IVR) based systems. Still, with the emergence of IVA-based conversational AI, the industry is shifting from conventional, high-touch service to high-tech service models and solutions for the entire guest journey.

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