AI in Revenue Management isn't some distant future - it's already reshaping hotel performance worldwide. The catch is that the shift isn't landing evenly. Global chains and premium hotels are pulling ahead fast, while much of the Polish market - independent hotels in particular - hasn't moved. And this isn't a technology problem. It's a mindset problem.
The data tells a consistent story. According to the Wyndham Owner Trends Report (January 2026), 98% of hotel owners have begun using AI in some form - yet only 32% have embedded it across most of their operations, and 73% say they want to do more but feel overwhelmed or unsure where to begin. Amperity's 2025 report captures the other half of the picture: while 96% of travel professionals plan to maintain or grow their AI investment, just 12.5% feel ready to scale it. The appetite is there. The execution isn't.
Marriott International reports that advanced AI pricing algorithms dynamically adjusting room rates and availability in real time contributed to a 6.2% increase in global RevPAR in the first quarter of 2026. This is part of a broader technological transformation under the Project Catalyst initiative. (Source: Marriott International data, Q1 2026)
Marriott has spent years building its own Revenue Management ecosystem - with One Yield at its core - and is now layering advanced AI pricing on top of it. This sits within Project Catalyst, a multi-year initiative replacing legacy reservation and property-management systems with modern cloud infrastructure. It points to where the whole industry is heading: AI doesn't replace proven systems, it adds a smarter decision-making layer above them.
Marriott itself is the clearest proof. In Q1 2026 the chain reported that AI algorithms adjusting room rates and availability in real time were among the drivers of its global RevPAR growth. The real edge is speed: the system reprices in response to shifting demand faster than any human updating rates by hand ever could.
In Europe the picture is more nuanced. Chains run smoothly - they have the technology, the resources and centralised revenue teams. The challenge sits almost entirely with independent hotels, and research on technology adoption across European hospitality keeps surfacing the same three barriers:
The three barriers cited most often when European hoteliers talk about AI and digital technology are the cost of implementation, the complexity of integrating with existing systems, and a shortage of technical skills in the team. The same obstacles resurface report after report - from Wyndham Owner Trends to studies published by hotel-tech vendors.
In the Polish context, one further barrier looms especially large: unease about data security and a reluctance to hand decisions over to external systems. Layered on top of the pan-European cost and skills concerns, it acts as an extra brake on adoption.
To grasp the scale of the problem, start with one fact: most independent Polish hotels run no RMS at all today. Not for lack of options - there are plenty. The barrier to entry, financial, technical and psychological alike, simply remains too high.
Professional RMS platforms such as IDeaS, Duetto and Atomize are standard fare in Western Europe and the US, yet in Poland they are virtually absent outside the large chain properties.
What do hotels without an RMS lose? Day after day they price on gut feel, a glance at the competition and a spreadsheet. With no real data on pickup, booking pace or segment behaviour, they either sell too cheap and leave RevPAR on the table, or price too high and lose occupancy. Either way they lose money - they just can't see how much, because there's nothing to measure it against.
Polish hospitality is still ruled by an owner's mindset: "we have our regulars," "our market is different," "it won't pay off." Meanwhile the ground is shifting - OTAs keep gaining power, guests compare prices in seconds, and fully tooled-up chain hotels are increasingly direct competitors to independents, even in regional markets.
The most common excuse - and the easiest to dismantle. A basic dynamic-pricing tool for a 50-100 room hotel runs to a few hundred zloty a month. The real question isn't "can I afford it," but "how much am I losing every month without it." Hotels that adopt even entry-level pricing tools routinely report a clear lift in ADR and RevPAR within the first few quarters - often enough for the tool to pay for itself in a matter of months.
A more serious barrier - and an honest one. Industry surveys repeatedly find a shortage of technical skills near the top of the list of obstacles. In Poland the gap runs deeper still, because Revenue Management as a discipline is relatively young here. Many hotel directors still wear the GM and RM hats at once - and do the revenue work after hours, with no tools, no training and no benchmarks.
Ironically, the healthiest reason of the three - when it's stated openly. The trouble is that most hoteliers who distrust algorithms have never actually looked at what those algorithms do. The fear of "handing control to the machine" is understandable but misplaced: no RMS runs on its own. It recommends and optimises. The final call always stays with a human.
"Over 80% of hotels still spend up to two full working days a week just producing reports. AI doesn't replace the Revenue Manager - it frees them from work they should never have been doing by hand in the first place."
- HFTP, The AI Revolution in Hotel Revenue Management, 2025There's one more dimension to this debate that rarely gets aired publicly in Poland - though anyone working in the industry knows it intimately. The problem doesn't lie only with hoteliers who resist adoption. Just as often, it lies with the vendors who can't actually deliver the implementation.
Implementing an RMS is never just buying software. It's a complex integration project that begins with a set of questions: which PMS does the hotel run? What does its reservation data look like? Which Channel Manager is it wired into? How is segmentation structured in its operating system? Only once those are answered can you even begin to assess whether a given RMS will work at all.
A typical chain of dependencies for an RMS implementation in a Polish hotel: The PMS system (e.g. OPERA, Protel, Sihot) → integration with a Channel Manager (e.g. Profitroom, YieldPlanet) → integration with OTAs and GDS → only then is synchronisation with the RMS possible. Every link must have a compatible API. One missing connector - and the whole project stalls.
Polish hospitality runs on a highly fragmented tech stack - frequently older, local or heavily customised. Many hotels operate PMS platforms with no off-the-shelf integrations to the leading RMS systems. And those systems - IDeaS, Duetto, Atomize - are built for Western European and Nordic markets, where integration standards are far more uniform. In Poland they hit a wall.
The upshot? RMS vendors that tried to enter the Polish market have often pulled back out. Not because demand was lacking, but because the cost of adapting the product to Polish technical realities outweighed the return. From the vendor's side, the logic is simple: it's easier to chase markets where integration works straight out of the box.
An 80-room independent hotel wants to roll out dynamic pricing. It runs a local PMS with no API compatible with the leading RMS systems. Its Channel Manager handles only basic connections. The RMS vendor sends a proposal - but flags that integration would need custom development on both sides, doubling or tripling the cost. The project dies at the quotation stage. The hotel goes back to Excel.
This is the lived experience of many Polish hoteliers who set out to adopt modern tools and ran straight into a technical wall they could neither afford nor justify. And it's hard to blame them. The market can't move forward while the technology on both sides - hotels and vendors alike - isn't ready to meet in the middle.
What can be done about it? A few directions:
Modern AI systems already forecast demand far more accurately than traditional models built on historical data alone. For a hotel, that means planning staffing, purchasing and sales with far greater precision, a week or even a month out. By 2030, forecasts will be generated in real time, drawing simultaneously on flight data, events, social media and competitor activity.
This is already underway in the global chains. By 2030, pricing personalised to booking history, channel, device and behavioural profile will be standard in the premium segment. Analysts expect that, in the coming years, a growing share of bookings will involve AI agents acting for the guest - assistants that search, compare and negotiate terms directly with hotel systems.
AI will fold rooms, F&B, spa, events and parking into a single optimisation model. Hotels that still manage these in silos will lose ground to those that see the whole picture. Pre-bookable add-ons - breakfast, parking, late check-out, spa - already deliver measurable results: hotels that surface them during the online booking flow capture a markedly higher share of non-room revenue than those selling rooms alone.
The trend is unmistakable: luxury and upper-upscale consistently outperform the economy segment. Marriott reported luxury RevPAR up roughly 4% in Q3 2025, well ahead of the chain-wide average. The market is splitting in two, and the gap is widening. Premium hotels that invest in technology and revenue management pull away from the rest - not because their guests are wealthier, but because they manage what they have better.
And here we reach the heart of it. Every conversation about AI in Revenue Management eventually lands on the same question: "will the algorithm replace the Revenue Manager?" The short answer is no. The sharper answer is this: the algorithm will replace the Revenue Manager who can't use the algorithm.
I've seen hotels with the best tools on the market deliver mediocre results - because no one understood the system's recommendations, no one questioned the forecast assumptions, and no one had the nerve to override the algorithm when the market called for a different move. And I've seen Revenue Managers armed with only basic tools who, through a deep read of the market, analytical discipline and the courage to hold price, delivered results no algorithm would have produced on its own.
AI makes the Revenue Manager's job more strategic. Less time building reports, more time interpreting them. Less time updating rates by hand, more time understanding why the market is behaving as it is. Less firefighting - more building advantage.
By 2030, AI in Revenue Management won't be a competitive edge - it will be table stakes. The hotels that start building the capability now - rolling out tools, training teams, growing a culture of data-driven decisions - will be ready. The ones that wait until "it feels safer" will spend years playing catch-up.
Polish hospitality has the potential. It has a growing number of switched-on owners and directors. It has Revenue Managers who read the market and want to grow. One thing is still missing: the courage to invest both in the tools and in the people who know how to use them. The two together - a good system and a good person - are the only combination that truly works.