Hotels across the APAC region are looking to AI to help improve their commercial effectiveness, better engage with guests and relieve staff of unnecessary administrative burden. However, despite this widespread interest, many hoteliers are still facing challenges in implementing AI effectively.
A major Massachusetts Institute of Technology (MIT) study recently found that 95% of generative AI pilots fail to deliver meaningful return on investment (ROI) or scale effectively. And although the AI market in the travel and hospitality sectors is projected to reach a value of USD$8.3 billion by 2030, many hotels are not yet realising the full benefits of AI due to poor data quality, misaligned use cases and a limited understanding of the technology.
Many hotels make the mistake of approaching AI as a plug-in or a marketing accessory, expecting unrealistic outcomes. They are adopting AI in a piecemeal fashion, essentially adding tools to solve isolated tactical problems without a clear understanding of how different types of AI strategically align to distinct business outcomes. True transformation begins when hotel leaders understand what kind of AI they’re using, what problem it’s solving and how it fits into a broader commercial strategy.
A major barrier to successful AI implementation today is the misconception that “AI” is a single technology. It isn’t. AI encompasses several distinct forms, each with its own purpose and limitations. When these differences are ignored, technology is often applied in ways that add little value or even create new inefficiencies.
To begin to understand AI and what value it can add in a commercial hospitality environment, hotel owners, investors and managers first need clarity on the three forms of AI that exist today: mathematical AI, generative AI and agentic AI.
Mathematical AI Powers Modern Revenue Management
Mathematical AI is the science behind modern revenue management. These are the proven, tailored algorithms that forecast demand, determine availability restrictions and recommend the right price at the right time. Over the years, these algorithms have become increasingly refined, delivering precise recommendations for every segment, room type and stay length for holistic revenue optimisation. This form of AI has quietly delivered reliable revenue optimisation for years and for many hotels, it’s already the cornerstone of their commercial AI strategies.
In the context of commercial strategy, revenue management is where mathematical AI currently proves its value most consistently. While many emerging AI tools promise to streamline operations or personalise guest interactions, mathematical AI has long provided measurable financial impact like RevPAR growth. It transforms raw demand signals into accurate forecasts and powers intelligent pricing. Increasingly, these systems also enable real-time decision-making on sharp demand shifts, helping hotels adapt to fast changing market conditions. And with scenario simulation capabilities, teams can test marketing and revenue strategies before implementation, avoiding costly missteps and aligning decisions with business goals.
In an environment defined by cost pressures and shifting traveller behaviour, this form of AI gives hotels the confidence to make profit focused decisions rather than rely on static budgets or intuition.
Where Generative AI Helps (and Where It Should Not Be Used)
Generative AI use sophisticated large language models (LLMs) to help hotel teams quickly write, summarise and analyse text, images and data. This application of AI can help staff save time and communicate more effectively. In a hotel environment, this can support content based activity like drafting marketing copy or personalising pre-arrival messages to welcome guests. It can also turn large datasets into simple summaries for managers, assist with multilingual guest communication and help frontline teams access information instantly without searching through manuals or document libraries. When used well, it improves productivity across marketing, operations and reporting by removing repetitive work that adds little value.
However, generative AI does have limitations and should only be used in defined areas of hotel operations. While generative AI outputs can seem a bit like magic, it is not built to make precise pricing or forecasting recommendations, nor does it contain the specialised logic needed for accurate performance analysis. It predicts likely words or images rather than calculating the best commercial decision based on demand patterns or business rules. As a result, it works best as a support layer that enhances human output rather than replaces it.
How Agentic AI Can Deliver Autonomy to Hotel Decision Making
Agentic AI is an emerging category that can autonomously act on information rather than simply present it. It can take inputs, interpret what they mean for the business and complete tasks without waiting for a human prompt. At their most sophisticated, these AI agents can plan, decide, carry out and evaluate entire sequences with minimal human oversight, making them more like digital teammates that automate workflows and free up key hotel personnel.
In a hospitality setting, this could mean adjusting pricing or rate restriction guidelines when forecasted demand shifts, launching targeted marketing offers to fill shoulder nights, or reallocating inventory across channels when certain room types begin to pace ahead. It could also support operations by triggering housekeeping schedules based on actual occupancy rather than static plans, or by notifying maintenance teams when sensor data suggests a room is at risk of a guest complaint.
The potential is a more connected and adaptive commercial engine where departments respond to the same real time signals and routine decisions are automated. However, few hotels today are tapping into the full potential of agentic AI as it requires significant prerequisites. Clean, centralised data, consistent business rules and clear governance frameworks are essential to determine what can be automated and what must remain under human control. Agentic AI should only be introduced once these data foundations and clear governance frameworks are firmly in place.
AI Success Begins with Understanding
AI will shape hospitality in profound ways over the coming years. But real progress depends on understanding, not hype. Technology that is designed for creativity or communication cannot deliver the precision needed for pricing or forecasting. At the same time, AI also delivers value only when it is powered by accurate, connected data and clearly defined business rules. Without that foundation, hotels risk automating poor decisions rather than improving performance.
The hotels that succeed with AI start with clarity. They know exactly what they are trying to achieve and choose the appropriate type of AI to meet that goal. They strengthen rather than replace human decision making and connect their data, so all commercial functions move together to help the hotel operate more efficiently and make better decisions with confidence. When people provide strategic direction and AI provides the analytical muscle, hotels create a commercial engine that is both adaptive and resilient.
For more information on how mathematical AI can power your commercial operations, please visit: www.ideas.com
