Generative artificial intelligence has been a constant headline-maker in the travel tech world through the past year. So, it’s no surprise many industry experts believe the technology has the power to change processes on the whole, including in how hotels strategize – and maximize – their opportunities to drive revenue. 

While the full potential of generative AI remains to be seen, many industry experts expect change of some kind whether it involves increased efficiency, a bridge between revenue management and other hospitality operations or new capabilities for revenue managers.

Ally Northfield, managing director of Revenue by Design, described generative AI’s impact on revenue management as almost a guiding force.

Generative AI has the capability to bring these functions forward, she said, removing them from the “dark windowless room” in which they have traditionally lived, into a new light. And the strategy can become about more than just managing elements like room revenue – it can manage the “entire proposition” with the help of generative AI, said Northfield.

Predicting generative AI’s impact on revenue management

Álvaro Ponte, vice president of data for BEONx, believes generative AI will play a revolutionary role in how hotels manage distribution and pricing. “The impact of generative AI on revenue management processes is deep and multifaceted, promising to revolutionize how hotels optimize their revenue strategies.”

And technology for revenue management is likely to become more conversational, according to Klaus Kohlmayr, chief evangelist and development officer at IDeaS. He likened the experience to working with a personal assistant.

“Everything from asking questions, troubleshooting support issues, forecasting, pricing decisions and more will be more conversational than they have been previously,” Kohlmayr said.

Kevin Duncan, vice president of product management at Cendyn said the impact of generative AI will depend on the speed of adoption – and the technology’s progression.

Generative AI, Duncan said, could make it easier for pricing and distribution decisions to be based on predictive modeling – using historical data to predict future outcomes.

Chris Crowley, chief revenue officer at hotel revenue management company Duetto, had a similar outlook. He said revenue managers should be able to make decisions more efficiently with the advent of generative AI. 

“Generative AI has the potential to offer innovative solutions to optimize pricing strategies with market intelligence, enhance demand forecasting and improve overall revenue generation,” Crowley said.

Crowley believes machine learning will continue to do the “heavy lifting” for revenue management, such as data analysis, while generative AI could be implemented to help guide scenario planning, help with proactive adaptation as market conditions shift and personalization opportunities evolve.

BEONx’s Ponte agreed, noting generative AI could provide unprecedented insights and capabilities that will be able to facilitate the development of more precise algorithms to benefit revenue managers.

“These advancements will not only improve the accuracy of predictions and decision-making but also enhance the adaptability of revenue management systems to rapidly changing market conditions,” Ponte said.

Ponte sees a number of changes happening in the day-to-day for managers, too, he said, pointing to the use of ChatGPT and other tools and improvements.

“The biggest disruption will be related with revenue managers’ routines, having more time for other important aspects within the hotel’s management the more they start trusting AI,” said Ponte.

Duncan used the finance sector as an example of how generative AI could play out in hospitality. He said finance players use generative AI to simulate scenarios in an effort to proactively manage risk in instances such as credit applications. He believes revenue management can take a similar proactive approach using generative AI.

“It has the potential to greatly speed up the process of setting rates based on a wide variety of factors,” Duncan said, pointing to local events, weather, competition, targets and more. Having that intel, Duncan added, could help revenue managers reviewing forward bookings allowing hotels to update room rates to ensure optimized sales.


The impact of generative AI on revenue management processes is deep and multifaceted, promising to revolutionize how hotels optimize their revenue strategies.

Álvaro Ponte


Duncan also believes generative AI could help to foster a deeper understanding of the hospitality business. Right now, he said, revenue managers must process data to understand it and make decisions. In the future, he predicts generative AI may be able to summarize inputs and outputs to form a narrative or critique – he believes it could impact demand generation, content creation and personalization aspects that could attract new business.

Similarly, Northfield foresees generative AI could break down silos and serve as a kind of bridge between marketing and revenue management, for example by facilitating ideation for strategies to appeal to customers based on their spending patterns.

But other experts point out the benefits are coming broadly from artificial intelligence – not the subset of generative AI. 

“What I would say is that AI will have a massive impact,” said Jens Munch, CEO of Flyr for Hospitality.

“Maybe I’m just being overly semantic here, but generative AI is kind of used [for] something else so if you think that if you think that revenue management is largely quantitative and has to do with numbers and how to make decisions… demand is going up and source supply is going down and things are changing in the market, then you should respond to that in some appropriate way you’re using an AI to do that – it’s just not generative AI.”

Will AI replace humans in revenue management?

There have been mixed predictions across the industry on how generative AI will alter staffing structures in various sectors across the travel world. 

While structure could change –  many believe humans will still need to be involved in revenue management. 

“There will still be a need for human factors, specifically with what inputs to the AI will be,” said Duncan.

In fact, Kohlmayr said he believes humans will be “more important than ever” as stratification of revenue management roles is likely to occur from commercially strategic to tactical.

Meanwhile, Crowley said the ideal scenario is always a combination of humans and machines. 

“We need experienced revenue leaders to not only test the accuracy of the AI-driven results, but also roll out the overall strategy,” said Crowley. “These are people who understand the market, the goals of the hotel, the specific circumstances of the property and even gut feelings.”

What about five years from now?

Looking ahead, Duncan echoed Northfield’s idea that AI could act as a bridge between revenue and marketing operations, but he took it a step further, envisioning an even greater convergence.

“If generative AI can compose and orchestrate personalized content for individuals which in turn creates a shift in where a hotel’s direct business is coming from, I could envisage the possibility of marketing and revenue manager roles becoming one, broader, commercial role,” said Duncan.

Kohlmayr was on the same page about hospitality processes combining with generative AI’s help. “I also see the commercial stack that hotels use to target, sell, price and convert their business to consolidate.”

But Kohlmayr also said he believes all technology could become conversational in the next five years – including the systems for managing distribution, pricing and revenue strategies.

And Crowley anticipates an overarching shift, thanks to AI, too, in the coming years: “In five years, generative AI tools will be the ‘norm’ and more accessible, which could lead to the ‘democratization’ of revenue management where everyone will benefit from revenue management tools regardless of skill or experience.”

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