Introduction

Before the application of AI and ML in hospitality facilities, operations could only be controlled manually, utilizing control mechanisms and pre-set schedules, which only promoted wastage. Waste management has become less efficient due to challenges in segregating waste and monitoring the waste stream, hence more landfills and less recycling. In addition, concepts related to sustainability and providing attentive and personalized guest care were less efficient. The hospitality industry is adopting a technological innovation that will transform sustainability for hotels and resorts. This is being driven by new solutions from Machine learning (ML) and Artificial intelligence (AI) that do not waste energy and have been designed to be environmentally friendly. These technologies have a positive impact on increasing organization efficiency, decreasing organizational costs and satisfying guests by providing opportunities for individualized services and responsibility for the environment. In this opinion piece, the question of how these advanced technologies help sustain or create value is addressed.

Smart Energy Management Systems

Waste in hotels has been growing, with research showing that hotels waste around one-third of their food1. This translates into wasting energy used to grow, package, and transport it, begging for a solution. Hotels use diverse approaches, encouraging customers to waste less and reuse ingredients that otherwise go to waste. However, AI and ML are the most effective in creating smart energy management systems that help track and control energy usage over time. They can anticipate high load demands, control the temperature, and manage lights to prevent electricity waste. This area has seen increased use of smart thermostats and lighting, which automatically adjust temperature and light based on environmental and occupancy conditions. For the food wasted, hotels are striving to

Predictive Analytics: The forecast of energy requirements is done using machine learning, and hotels can make tweaks based on previous data.

Automated Controls: Smart sensors and controllers use AI to regulate HVACs based on occupancy and weather patterns.

Energy efficiency optimization: AI tools provide insights on how much energy is required for specific operations, resulting in maximum utilization of available energy and overall cost savings.

Case Study: Hilton makes use of Energy Optimization.

Hilton Worldwide has also utilized artificial intelligence to control energy consumption and minimize its carbon footprint. Hilton has implemented predictive analytics and automated control for energy saving, leading to a reduction in energy use by 36%2.

Reducing Waste

AI-Powered Waste Management

Current developments in AI and ML are helping the waste management process because it is easier to identify and categorize waste. AI waste bins can sort out recyclable materials, compost, and landfill waste, helping to reduce contamination and increase recycling efficiency. Additionally, AI has allowed calculating how much is required to cook, reducing the incidences of food thrown away. When this food rots, it generates greenhouse gases such as methane, 25 times more potent than carbon dioxide3. This has contributed to around 8% of human-caused emissions in the long run.

Smart Bins: These devices apply artificial intelligence to sort and manage waste to avoid dumping it together4. As a result, recycling streams are not contaminated, and proper disposal is done.

Waste Tracking: It is possible to train machine learning algorithms that recognize patterns in waste generation and suggest opportunities for hotel optimization in the use of resources. For instance, hotels can learn how much they emit and develop strategies to reduce waste.

Implementing Sustainable Practices

Green Building Designs

Artificial intelligence and machine learning are used to develop and manage environmentally friendly sustainable structures. These technologies can improve building layouts, materials, and systems to improve energy efficiency, thus minimizing environmental effects.

Sustainable Materials: AI suggests various environmentally friendly materials and ways to build that would reduce carbon footprint.

Energy-Efficient Designs: Machine learning models allow for comparing different design options and identifying the ones with the lowest energy consumption.

Case Study: Proximity Hotel

One of the most notable examples of AI and ML is the Proximity Hotel in Greensboro, North Carolina. The hotel's energy systems are managed and optimized through AI and has acquired LEED Platinum status. It also includes using sustainable building materials and practices and has minimized energy use by 39 percent compared to other hotels5.

The Future

The future of AI and machine learning in the hospitality industry holds much more change that benefits the industry. Since the advancement of these technologies is ongoing, one can only imagine more improvements in energy efficiency, waste disposal, and sustainable methods. The major areas in the hotels and resorts will be able to improve efficiency and decrease operational expenses by adopting smart technologies, including resource management and maintenance. Further, smart guest experiences promoted by artificial intelligence will enhance customer satisfaction and loyalty; on the other hand, sustainability innovations will enable the industry to achieve environmental objectives and attract environmentally conscious clients. Overall, AI and machine learning shall remain key enablers in improving the hospitality industry's efficiency, sustainability, and guest satisfaction.

Conclusion

AI and machine learning applications in the hospitality industry are changing sustainable management and development by providing chances to enhance energy efficiency, waste reduction, and green building integration. As these technologies develop further, their impact on sustainability will expand, aiding hotel and resort establishments across the United States. For this reason, adopting AI and ML is key to the long-term sustainability of the hospitality industry.


1.  Loschen. (2023, April 25). IBB Hotel Collection says no to food waste - IBB Hotels. IBB Hotels. https://www.ibbhotels.com/ibb-hotel-collection-says-no-to-food-waste/ 

2. 36% energy reduction at Hilton Hotel in APAC. Grundfos. https://www.grundfos.com/about-us/cases/energy-reduction-at-hilton-hotel-in-apac 

3.  Pearce, A. (2022, April 20). Earth Day 2022: How hotels are using AI to reduce waste. inews.co.uk. https://inews.co.uk/inews-lifestyle/travel/earth-day-2022-hotels-ai-tech-reduce-waste-1583498 

4.  Soliman, A., Akkad, M. Z., & Alloush, R. (2020). Smart bin monitoring system for smart waste management. Multidiszciplináris Tudományok, 10(2), 402–412. https://doi.org/10.35925/j.multi.2020.2.45 
5. Sustainable practices at the Proximity Hotel in Greensboro, NC. (n.d.). https://www.proximityhotel.com/features/sustainable-practices/