By Caroline Thomas, Technology Editor: Future possibilities from AI and ML in hospitality and catering.
The use of technology in the hospitality and catering industry has been a gradual process over several decades, transforming the way in which operators and customers interact. Since the introduction of computerised point-of-sale (POS) systems in the 1980’s, adoption has accelerated directly in line with ROI.
Further advancing the use of technology in hospitality and catering will be influenced through the integration of existing applications with Artificial Intelligence (AI) and Machine Learning (ML). These cutting-edge technologies have the potential to revolutionise the industry, bringing increased efficiency, better customer experiences, and cost savings. So, let’s explore some of the most promising future possibilities of AI and ML on the hospitality and catering horizon.
Intelligent Customer Service: AI-powered virtual assistants could be used to provide customers with 24/7 assistance, handling tasks such as booking reservations, answering questions, and providing recommendations. This will not only improve the overall customer experience but also increase operational efficiency. Customers groups like Gen Z will quickly migrate to such services.
Predictive Analytics: AI and ML can analyse data from multiple sources integrated to make predictions about customer behaviour, market trends, and sales patterns. This information can be used to optimise pricing, marketing strategies, and inventory management.
Personalised Recommendations: AI can analyse customer data to provide personalised recommendations for food, drinks, and other offerings. This will lead to increased customer satisfaction and loyalty, as well as increased sales.
Improved Supply Chain Management: AI can be used to optimise the supply chain, reducing waste, increasing efficiency, and reducing costs. For example, AI can analyse data from suppliers, logistics companies, and customers to identify bottlenecks and optimise delivery times. All having a positive impact on improvements in sustainability.
Automated Kitchen Operations: We are already seeing the deployment of front of house waiting robots, AI-powered kitchen robots could be used to automate routine tasks such as some food preparation and warewashing. This will free up people to focus on higher value tasks, increasing efficiency and reducing labour costs.
Food Safety Monitoring: AI can be used to monitor food safety, identifying potential problems before they occur. For example, AI-powered sensors can monitor temperature and humidity levels in food storage areas, ensuring that food is stored at the correct temperature. This is already being done by technology applications, AI will greatly accelerate accuracy and wider adoption.
Employee Training: AI can be used to provide employees with training, improving their skills and increasing their overall effectiveness. This can lead to increased productivity, better customer service, and improved job satisfaction. As with some of the other examples above this is already being achieved, AI and ML will greatly widen the scope of such training, and the complexity of what’s possible.
Environmental Sustainability: As we have already seen, AI and ML has great potential to improve sustainability, this will be even more pronounced in areas such as monitoring and optimising energy use, reducing waste and increasing efficiency . For example, AI-powered systems can monitor lighting, heating, and cooling systems to increase the performance of existing building management systems, ensuring they are running ever more efficiently.
Improved Marketing: AI can be used to analyse customer data to develop targeted marketing campaigns, increasing customer engagement, and sales. For example, AI can be used to analyse customer behaviour and preferences to develop personalised promotions and discounts. There are a myriad of existing digital marketing channels that will be greatly enhanced in terms of ROI through being integrated with AI and ML technology, learning from every campaign and improving the next, automatically.
Predictive Maintenance: Everyone in hospitality and catering knows the cost of breakdowns, AI can be used to predict equipment failures and other issues before they occur, reducing downtime and maintenance costs. This is relevant to almost every part of hospitality and catering real estate, commercial kitchens especially. The adoption of AI and ML will lead to increased efficiency, lower operating costs, and improved customer experiences.
In conclusion, I have only touched on some of the very apparent applications of AI and ML to the industry currently. The future of the hospitality and catering industry will benefit significantly through existing systems and networks being integrated with, and enhanced through AI and ML. These technologies have the potential to truly revolutionise the industry. However, it is important to approach the implementation of AI and ML in a holistic manner to ensure that the realisation of benefit of all stakeholders.