AI Agents: The 20% Gross Operating Profit boost hotels are sleeping on

The financial pressure on hotel operators is mounting. Recently, Sircle Hotels, operator of the W Hotel Amsterdam and multiple Park Hotel locations, has been unable to meet its rental obligations to landlords. In Germany, Revo Hospitality filed for bankruptcy. These incidents underscore a wider pattern of operational and financial stress across the hotel sector. Even financially healthy operators are feeling the squeeze, as unfavorable and uncapped indexation clauses in lease contracts collide with stagnating RevPAR growth. Previous comfortable margins are now turning into a genuine strategic concern. 

To make matters worse, the headwinds are not just on revenue level, but also on expense level. Across many regions, labour costs are rising sharply due to collective labour agreement increases and tight job markets. Food and beverage procurement has become more expensive as a result of inflation and supply chain disruptions have become more frequent and impactful due to increasing geopolitical instability. Furthermore, this instability has been fuelling (pun intended) higher energy and raw material prices. 

Governments are also looking at where to apply higher taxes to deal with higher government spending (on defence for example). In the Netherlands, for instance, the VAT rate on hotel stays was raised from 9% to 21% in 2026. Additionally, tourist taxes in cities across Europe have repeatedly been increased by local authorities to makes ends meet. These are extra costs that the operators cannot simply pass on to guests without risking a decline in occupancy. The combined effect of these trends is increasing pressure on Gross Operating Profit (GOP) margins. Many hotel operators are now approaching the minimum required GOP margin to sustain healthy operations. 

The instinctive response of further reducing headcount and cutting other operational costs has reached its limits. Beyond a certain point, staff reductions degrade service quality, generate negative reviews and ultimately costs more due to lost revenue than it saves in payroll. 

A promising approach lies in the deployment of AI agents that can reduce operating costs and grow revenue simultaneously without compromising the guest experience. In an industry still largely focused on Revenue per available room (RevPAR), GOP is the actual value driver. 

The Compelling Math

Consider a typical 150-room upscale hotel generating €10 million in annual revenue with a 37% GOP margin (€3.7 million GOP).

• A 5% revenue increase (through better personalization, higher conversion, dynamic pricing, and upselling) brings revenue to €10.5 million.

• A 3 percentage point reduction in operating expenses (from automation of admin tasks, optimized staffing, predictive maintenance, and smarter procurement) increases GOP by more than 700K.

The combined effect would push GOP well above €4.4 million,a 19–25% uplift depending on starting efficiency. This is transformative for both independent hotels and chains fighting margin pressure.

How could AI agents make this possible? Not through one single chatbot, but through networks of combined, specialized, autonomous agents that handle repetitive work while empowering staff to deliver genuine hospitality. Modern AI agents go far beyond basic chatbots. They think, act, and adapt across systems, learn from your standard operating procedures, and coordinate with each other and human teams.

The effects of AI agents (acting alone or in concert) could be profound in many crucial areas and certainly on GOP. 

While the previously mentioned 5% revenue boost and 3 percentage point increase in GOP margin sound aggressive, the below six examples of where AI agents can add value indicate the potential effect could actually be much larger. 

1) Personnel Management, Retention & Effectiveness  

AI agents handle administrative burdens so staff can focus on what they do best: being hospitable. Agents manage shift scheduling, time-off requests, payroll queries, training modules, onboarding, and real-time KPI tracking. 

One AI supplier, Oxmaint, claims that by using role-specific agents reported housekeeping teams gaining 45 min to 1,5 hours a day for genuine guest interaction instead of admin work on scheduling alone. It also increases the quality of the planning, thus impacting costs directly. All of this directly improves employee satisfaction, and boosts retention; critical in an industry plagued by high staff churn. Agents even help managers formulate relevant, individualized KPIs and deliver real-time coaching suggestions. 

2) Customer Satisfaction

And also on customer satisfaction which should be treated as a 24/7 and personalized & seamless activity, AI agents can unlock a lot of value:   

• Check-in/out: Fully automated via WhatsApp, app or voice; digital key issuance, room assignment, and folio review in seconds.

• Billing & data management: Real-time transparency with one-click dispute resolution and automated accurate invoicing.

• Up-to-date info & convenience: Instant answers on amenities, policies, restaurant hours, or pool temperatures; no more “let me check with the front desk.”

• Proactive service: Agents detect issues (e.g., delayed flight + late arrival) and offer solutions before the guest even asks.

• Personalized recommendations: “Based on your previous stays and love for local wine, would you like to book our vineyard tour?”; driving higher satisfaction and ancillary spend.

• Concierge-level convenience: Seamless booking of excursions, taxis, museum tickets, restaurants, or local activities with real-time availability and commissions back to the hotel.

The positive effect this has on net promoter scores, and reviews, should translate into increased repeat/direct business.

3) Response Rates & Marketing 

Agents achieve near-100% response rates within seconds across channels. They also power smarter marketing by analyzing guest data to create targeted campaigns, improve online visibility, and match preferences perfectly. This will— lift conversion rates on direct bookings and packages.

4) Revenue Management

Continuous analysis of booking curves, competitor rates, events, and demand forecasts enables dynamic pricing far beyond traditional tools. Upsell opportunities during the stay (spa, F&B, experiences) are suggested automatically.

5) Facility, Cost & Cash Management 

Predictive maintenance agents monitor HVAC, energy use, and equipment to prevent breakdowns. Inventory and procurement agents reduce waste and optimize purchasing. Cash-flow forecasting agents provide real-time visibility and scenario modeling, supporting smarter investment decisions on renovations or expansions.

6) Investment Decisions & External Connections  

Agents can quickly analyse any proposed investments by calculating return on invested capital, compare it to the risk (WACC) and point to the most value adding investments options.

Two Examples Of Companies Making It Real Today

www.inhotel.io  has built a sophisticated agentic platform specifically for hospitality. Their AI agents handle complex workflows across PMS systems, coordinate between departments, and power both guest-facing assistants (Reservations and Guest Relations) and back-of-house orchestration. Hotels using their solution (including properties like Hermitage Hotel Prague) report significantly faster response times, reduced coordination friction, and staff freed from admin tasks. The platform’s A2A (agent-to-agent) capabilities let hotel agents talk directly to traveler agents for instant booking confirmations and custom requests.

Another emerging player is SOUS, an Amsterdam-based startup specializing in AI-driven software for the hospitality sector, with a strong emphasis on restaurants and food service operations. In a recent seed funding round, SOUS secured €2.75 million from investors. The company's AI agent acts as a digital "co-pilot" for independent restaurant entrepreneurs, helping them manage and grow their businesses digitally without the need for large teams or high budgets. It allows operators to consolidate multiple tools (such as review monitoring, competitor tracking, and visibility optimization) into a single system while building their own ordering and delivery infrastructure to eliminate high commissions from platforms like Uber Eats or Thuisbezorgd. By providing fixed monthly pricing (around €100+), SOUS empowers smaller venues to compete more effectively with major chains, handling aspects like direct customer contact, revenue growth through better digital presence, and operational efficiency in a way that mimics the capabilities of large players. While SOUS focuses on mostly independent restaurants, hotels with F&B operations can also use the same set-up to improve results. 

The Adoption Paradox: Why So Few Hotels Are Moving

Despite the compelling economics, AI adoption in hospitality remains surprisingly low compared to other industries. In fact, in the recently published Yearly Outlook for 2026  “The AI Power Gap: Hospitality Lags Behind as Value Shifts to Tech Giants” by Hotelschool The Hague’s research department, the Dutch hospitality sector is next to last on AI adoption rates (only beaten by the construction sector, based on 2024 data).

According to the March 2026 Canary Technologies report surveying 400+ hotel technology decision-makers globally, while 82% of hotels expect their AI usage to increase in 2026 and 85% plan to allocate at least 5% of their IT budget to AI. Yet despite this momentum, deep implementation continues to lag behind Broader studies show that although nearly 98% of hotels have experimented with AI, only about 32% have embedded it meaningfully across operations. This puts hospitality well behind sectors like retail, banking, and technology, where McKinsey reports 78–88% of organizations now use AI in at least one business function.

Why Are Hotels Moving So Slowly?

Research published in journals such as the International Journal of Hospitality Management and Emerald’s EuroMed Journal of Business also consistently highlights issues like high employee turnover, conservative organizational culture, skills gaps, and lack of digital talent as primary inhibitors of digital transformation in hospitality. Most of these inhibitors presented in academic literature and industry analyses can be summarized by four types of adoption inhibitors:

1. Chronic Understaffing and Firefighting Mode 

   Many general managers are so consumed with daily operations and staffing shortages that they lack the bandwidth to evaluate, test, and implement new systems. The “we’re too busy to improve” paradox is real.

2. Cultural and Traditional Resistance  

   Hospitality has long prided itself on human connection. There is a genuine fear that technology will erode the personal touch that defines great hotels. Legacy mindsets of “this is how we’ve always done it” remain powerful.

3. Fragmented Technology Landscape and Legacy Systems  

   Many properties still run on outdated PMS and siloed software that is expensive and risky to integrate. 

4. Risk Aversion and ROI Uncertainty  

   High staff turnover discourages investment in training. Past technology projects that failed to deliver promised returns have created skepticism. Smaller independent operators, in particular, struggle to see clear payback periods.

The Opportunity of the Century?

But as is often the case, proper execution is essential; the hospitality sector has enough software in place (see point 3 above), but the promised returns often disappoint. Some rightfully claim that the industry has too many software packages and that this is exactly the reason benefits have not materialized, as the different software systems do not properly interoperate, leading to extra manual work, mistakes and bad financial outcomes. While this has kept many new and smaller software providers out the door, here too, AI agents can prove to be a boon, as these can allow all these different systems to properly communicate with each other, thus unlocking the value of software packages and IT systems that are already in place.  

One could argue the gap between what is possible and what is currently happening creates a huge asymmetric opportunity in hospitality.

Hotels that move decisively with well-designed AI agent systems will not only protect margins in a challenging cost environment.  They will create structural competitive advantages in guest experience, operational efficiency, and talent attraction. While 100% simultaneous AI adoption by the sector would negate most competitive advantages at revenue level (mind you, it will still have positive effects on cost control), it also means that there is a first mover advantage. Or put differently, there could be severe negative consequences for those hotels that lag in AI implementation. Hence the statement that AI will have a STRUCTURAL competitive advantage, but only for those who dare to move first. Being proactive rather than reactive looks especially apt in this case. 

The winners of the next decade in hospitality will not necessarily be the hotels with the nicest real estate in the best locations; it will be the ones that intelligently combine human hospitality with AI-powered operational excellence.

The 20% GOP opportunity is waiting. The agents are ready. The only thing missing is action.

Disclaimer:

1. The co-author A. Sassen has a consultancy firm, Sassen Research, which is operationally involved with one of the mentioned companies (inhotel.io), but A. Sassen nor Sassen Research is a shareholder in inhotel.io, nor is paid by inhotel.io for this publication.

2. While most of the content and set-up has been developed by the authors, AI has been used for content suggestions, sources, grammar and structuring, not doing so, would be like ignoring what we have written above!