Early adopters are already turning to machine learning today for automation and hoteliers who aren ’ t taking steps to prepare for the next generation of AI-driven hospitality risk being left behind .

Over the past few years , we ’ ve seen early adoption of AI and machine learning , primarily in guest communication . Web chatbots , trip planners , automated call centers , for example , are already transforming the way hotels interact with guests .

Much of this technology is machine-learning based and will get exponentially better as more advanced AI features are adopted . As we look ahead , teams managing back-office tasks and revenue management strategies will see opportunities

in automated rapid decisionmaking open , but only if steps are taken to centralize their data and focus on building the right framework for innovation .

At its foundation , AI relies on the centralization of data used to train a model to make predictions and responses . In hospitality , there is an abundance of data that we can use to train AI models , ingesting information from our property management system , accounting system , point-of-sale system , central reservations system , booking

engine and more .

While we look toward a future where AI is informing all our business decisions , taking steps to centralize this data today is critical to ensure we are building the right framework for innovation .

AI IN BI The ability of today ’ s businessintelligence tools to centralize data from all areas of the business and serve it up in a user-friendly format to inform decisions is incredibly powerful . Moving our data

40 hotelsmag . com July / August 2024