Technology and Stereotype Mitigation: The Role of Artificial Intelligence and Machine Learning in Personalizing Hotel Service Encounters

Abstract

Delivering equitable, tailored, and high-quality services has historically been a major challenge for the hospitality industry, with human staff relying on subjective judgment and limited foresight to anticipate guest needs. The emergence of artificial intelligence (AI) and machine learning (ML) technologies is transforming this landscape by enabling hotels to provide personalized, bias-mitigating services at scale. This article examines the potential of AI- and ML-driven tools—including chatbots, virtual assistants, and fair algorithmic systems—to enhance customer interactions, improve operational efficiency, and dismantle long-standing stereotypes embedded in traditional hospitality practices. Drawing upon recent studies, it explores how transparent and ethically designed AI systems can rival or surpass human-delivered services by predicting guest preferences with greater accuracy, facilitating real-time personalization, and promoting inclusivity across diverse customer segments. Furthermore, the paper investigates consumers’ perceptions of trust, privacy, and autonomy when interacting with automated services compared to human staff, emphasizing the importance of ethical governance, data security, and robust countermeasures to prevent unintended discrimination. By balancing technological innovation with strong ethical frameworks, hotels can redefine industry benchmarks, foster socially responsible and guest-centric service models, and contribute to the creation of a fairer, more adaptive, and customer-oriented hospitality environment.