For hotel general managers, revenue management is no longer just about adjusting prices and tracking RevPAR. It’s evolving into a dynamic blend of strategy, experimentation, and technology – with artificial intelligence (AI) playing an increasingly pivotal role.
In our latest industry conversation, with Veit Meier of berner+becker, one of our Expert Partners, and Thibault Catala of Catala Consulting we ask 3 questions: Should hotels still rely on historical data for forecasting? Will AI level the playing field and How is the role of the revenue manager evolving (if it is at all)?
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The Evolution of Forecasting: Beyond the Past (@4m 54s)
Traditionally, forecasting relied heavily on historical data – tracking trends, seasonality, and booking patterns. But the post-COVID world has disrupted those models. Traveler behavior has shifted; bookings are now more spontaneous, influenced by flexible work, geopolitical factors, and economic uncertainty.
So, is historical data obsolete? Not quite.
Our guests advocate for a blended approach. Historical data still offers context – “history doesn’t repeat, but it rhymes” – but real-time data, on-the-books figures, and pace are now critical. The goal is to balance what has happened with what is happening and what might happen.
AI and the Democratization of Revenue Management (@14m 03s)
One of the most exciting developments is how AI is leveling the playing field between large corporate hotel chains and smaller independent properties. In the past, sophisticated revenue management systems (RMS) were only accessible to the big players. Today, affordable and user-friendly RMS tools powered by AI allow even small boutique hotels to adopt dynamic pricing, monitor trends, and respond to demand in real time.
AI not only enhances forecasting but also enables scenario planning, testing different strategies before making pricing or distribution decisions. These tools reduce manual work, such as setting up rates across systems, allowing teams to focus on strategy rather than administration.
Yet, as powerful as AI is, it lacks the human gut instinct, contextual understanding, and storytelling skills that experienced revenue professionals bring. The ideal model? AI + Human Expertise – using machines to handle data processing while humans guide strategic direction and influence decision-making.
Redefining the Role: From Tactical to Strategic – and Beyond (@28m 44s)
Revenue management is evolving beyond tactics like pricing changes and daily pickup reports. The new role is strategic – building long-term plans, experimenting with new ideas, and influencing cross-functional teams.
And the next frontier? Experimentation. Revenue managers are adopting a scientific mindset: test hypotheses, analyze outcomes, and refine strategies. This requires a comfort with ambiguity, a data-driven approach, and, importantly, support from leadership.
The Challenge: Talent and Perception (@36m 06s)
Despite these advancements, a surprising 90% of hotels still don’t use a revenue management system. The role itself, once seen as high-impact and exciting, now suffers from burnout and a lack of visibility.
To address this, the industry must:
- Modernize education around revenue management
- Make the role more appealing to new talent
- Update job titles and descriptions to reflect strategic and analytical responsibilities
Final Thoughts
AI is not replacing revenue managers – it’s transforming what they do and how they do it. The most successful GMs will be those who recognize the value of revenue management as a strategic function, invest in technology, and empower their teams to blend human insight with machine intelligence.
After all, in the fast-changing landscape of hospitality, those who adapt fastest – and smartest – will win.
Timestamps
00:00 – Welcome & Intro
00:15 – Quick soundbites from the discussion
04:54 – Should hotels still rely on historical data?
14:03 – How AI is changing access for smaller hotels
28:44 – Revenue management: Tactical vs Strategic vs Experimental
36:06 – What skills will tomorrow’s revenue managers need?
43:13 – Who wants to be a Revenue Manager
46:44 – Wrapping up
47:35 – Link to other videos, playlists and subscribe
