Abstract

The hospitality industry is undergoing a paradigm shift driven by the integration of Artificial Intelligence (AI) and
Machine Learning (ML), particularly in the realms of sustainability and customer-centric innovation. This study
investigates the potential of AI and ML technologies in promoting sustainable food management and enhancing
customer satisfaction within selected restaurants in Hamirpur district, Himachal Pradesh. As a region characterized
by rising tourism and increasing environmental concerns, Hamirpur provides a unique context to explore the
intersection of technology, sustainability, and service quality in food and beverage operations.
The research employs a mixed-methods approach, incorporating structured interviews with restaurant
stakeholders, AI-driven data analysis of inventory and sales patterns, and customer feedback surveys. Specific focus
areas include the implementation of ML algorithms for predictive demand forecasting, intelligent inventory
optimization to reduce food waste, and AI-enabled personalization of menu offerings based on dietary preferences
and consumption trends.
Through empirical analysis, the study aims to uncover how AI-supported systems contribute to both operational
efficiency and improved customer satisfaction, while simultaneously aligning with sustainable development goals.
The research also explores barriers to AI adoption in small and medium-sized food establishments and proposes a
scalable model for integrating intelligent systems into resource-conscious hospitality practices. The outcomes are
expected to offer valuable insights for policymakers, restaurateurs, and technology developers working towards a
greener and more guest-focused future in the Indian hospitality sector.