The hotel industry faces a paradox: while the adoption rate of artificial intelligence (AI) in revenue management systems (RMS) is rising rapidly, confidence in the technology’s decisions often remains low.
NB: This is an article from Hotellistat, one of our Expert Partners
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Many hoteliers use AI but are not willing to release full control. The reason is simple: there is a lack of transparency.
The “black box” is blocking progress
AI systems often operate as so-called “black boxes.” They take in large amounts of data and spit out an optimized price without explaining how they got there. For the revenue manager, whose responsibility is at stake with every pricing error, this is an unacceptable situation: they have to implement decisions that they do not understand or cannot explain. The consequence of this lack of transparency is that the systems are often only operated at a low level of automation or merely serve as expensive data aggregators instead of exploiting their full potential for profit maximization.
This lack of accountability leads to three key problems:
- Lack of trust: The user intervenes manually because they cannot understand the recommendation. This often happens out of fear of unforeseen losses or a feeling of losing control over their own pricing strategy. Constant manual corrections undermine the efficiency and usefulness of AI.
- Missed opportunities: Automation is throttled or switched off. This prevents hotels from responding quickly enough to real-time market changes. Especially in times of strong demand shocks (such as major events or sudden weather changes), these hotels lose valuable revenue to their more agile competitors.
- Lack of learning: The revenue manager cannot use the logic of the system to improve his own strategic skills. The black box prevents understanding of complex relationships and hinders staff development in dealing with modern data-driven strategies.
Transparency creates trust
A modern, future-proof RMS must close this trust gap. At Hotellistat, it was clear from the very beginning that AI must not only recommend prices, but also explain them. Only then can technology become a reliable “right-hand man.” ARIS, Hotellistat’s Automatic Revenue Intelligent System, reveals the basis for decision-making. The AI analyzes over 1,000 relevant data points and filters out the five most important factors for each individual price recommendation. In addition, hoteliers can adjust the weighting of the influencing factors themselves in the settings and decide whether the AI should focus more on market developments or internal PMS data.
