How AI is changing revenue management

The big-data movement, machine learning and artificial intelligence have been great for revenue management. Historically, revenue management has relied on previous trends to predict the future—but today’s hotelier is faced with a number of industry challenges from changing consumer behavior to shift in business and leisure travel patterns to pop culture influencing travel like never before, said Chris Crowley, chief revenue officer, Duetto.

Artificial intelligence allows hoteliers to solve for those industry challenges, including using AI and machine learning to optimize pricing algorithms for maximum profitability. “The more intriguing aspect is how hotel revenue teams employ AI,” Crowley said. “The primary focus often involves organizing promotional or profile-oriented activities with their guests—for instance, using AI for targeted marketing campaigns. AI can help you determine who you are targeting, what you will say to them, and how you will say it.”

Big data has been great for revenue management, but it also increased the need to find relevant data in these new data sources, said Stan van Roij, vice president, product strategy at Infor Hospitality. “AI is helping us do exactly that and separate the chatter from those elements that are relevant to revenue management,” he said. “Once relevant data has been identified, AI is essential in modeling guest behavior; this used to be done with machine-learning techniques and more and more is performed through deep learning AI that functions like a human brain and is able to make complex connections in guest-behavior patterns.”

AI also allows for greater margin optimization, said Geert Mol, senior manager of product management at Infor Hospitality, as AI can not only used for traditional revenue management but also to incorporate venue spaces, restaurants and other revenue centers. AI or generative intelligence also makes it possible to optimize operational aspects—such as duty rosters—based on forecasted guest presence (arriving and departing and mix of clients, as well as use of restaurant and others) and assign rooms to arriving guests based on guest preferences, taking into account expected arrival and departure times and customer segments.

“After forecasting and optimization improvements through AI, we are also able to generate better insights in what drives best revenue and margin,” he said. “All of this allows a revenue manager to focus on strategic decisions and directions, rather than on the mundane tasks of data gathering.”

IDeaS has applied AI beyond its modeling and revenue science in the areas of configuration to enabling the above property-revenue management capabilities at scale to allow a central revenue manager to manage a large portfolio of hotels, said Klaus Kohlmayr, IDeaS chief evangelist.

Machine-learning models power analytics that learn from past data and predict future performance such as a demand forecast, said Tess McGoldrick, vice president, travel and hospitality at Revenue Analytics. “An accurate demand forecast is crucial to the quality of decisions from downstream optimizations like price recommendations, inventory restrictions and others,” she said.

One of the biggest impacts AI and machine learning has had on revenue management is the ability to make real-time offers to guests, said Jason Bryant, vice president of Nor1, part of Oracle Hospitality.

“At that moment in time, we are looking at inventory, we are looking at guests and a whole host of buyer behaviors,” he said. “In 70 milliseconds, we are deciding what to give the guests, what the price is and also the actual offer set."


Approximately 72 percent of business leaders believe that AI will be a significant business advantage in the future. PwC’s research also shows that 45 percent of total economic gains by 2030 will come from product enhancements, stimulating consumer demand. This is because AI will drive greater product variety, with increased personalization, attractiveness and affordability over time. Source: PwC


Approximately 74 percent of people are interested in hotels using AI to deliver more relevant offers and 73 percent of people want hotels to offer tech that minimizes contact with the staff and other guests. Source: Hospitality in 2025: Automated, Intelligent . . . and More Personal


Travelers are interested in using automated messaging or chatbots for customer service requests at hotels. Approximately 39 percent of guests want to order room service from their phone or using a chatbot. Source: Hospitality in 2025: Automated, Intelligent . . . and More Personal


Travelers, 87 percent of them, are more likely to book a hotel that allows them to pay for only the amenities they use. Source: Hospitality in 2025: Automated, Intelligent . . . and More Personal