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Your hotel chain launched AI chatbots. You tried dynamic pricing. You tested personalisation features. But are you seeing tangible evidence of the promised transformation and even more importantly a measurable ROI?
The findings?
78% of chains are live with AI and 89% are queuing up new tools, yet most remain stuck in pilots or leaning on ChatGPT. The sector is rich with ambition but starved for strategy, integration, and proof.
The numbers reveal the core problem. Hoteliers trust AI at 6.6 out of 10. But when asked how much they actually rely on AI, that number drops to 4.7.
That gap between trust and reality is costing the industry billions.
Top 3 takeaways for hospitality & payments technology leaders
Trust outpaces reliance. Payment fraud detection AI lags potential
- Trust in AI sits at 6.6/10, but actual reliance is just 4.7/10. In payments, only 16% use AI for fraud protection today (with 28% planning) despite 63% citing data security as a top investment driver. The gap screams opportunity: proven, integrated fraud-AI could close the trust-reliance chasm and unlock budget.
Data silos and poor integration kill personalisation and upsell potential
- 41% flag "barriers to effective data usage" and 32% cite cross-departmental sharing blocks. Without unified guest profiles, AI-driven upselling (54% planned) and personalised booking (49% planned) stall at the gate. For hospitality tech, this means friction in dynamic pricing, one-click upsell, and frictionless checkout. Fix the data plumbing first.
ROI blind spot threatens scale; guest-facing AI is the fastest mover
- 42% of chains don't track AI ROI at all. Meanwhile, chatbots (40% planning) and personalised IBE offers (59% planning) surge ahead. Payment platforms that bundle embedded upsell and measurable revenue lift will win the next wave. Early movers who quantify every cent of AI impact will set the benchmark.
Why only 8% have real AI strategies
Only 8% of hotel chains have an actual company-wide AI strategy with senior leadership involved and bought in as champions. Without leadership alignment, AI spending goes nowhere fast. Marketing tries one chatbot platform. Revenue management picks a different pricing tool. Operations automates something else entirely. Nothing connects. Nothing scales.
What's blocking success? Top of the list is insufficient AI expertise (62%), followed by no clear strategy or cohesive program management (51%). Notice what's not at the top? Technology problems. Integration headaches come in at 45%, budget issues at 39%. These are people problems, not tech problems.
Your data problem is killing your AI
Even the smartest AI can't work with messy, disconnected data. The study shows why projects fail: data quality problems hit 41% of hotels, another 32% can't share data between departments or integrated systems, and only 22% have built centralised data systems and established clear system of record for data ownership that properly feed AI.
Think about what this means. Your PMS holds guest information. Your payments platform sees spending patterns. Your CRM tracks preferences. If these systems don't talk to each other, AI works in the dark.
Integration sits at the very top of factors driving AI investment decisions. 70% of hotels say easy integration with existing systems is critical. The lesson is simple: unify your tech stack and clarify which system owns what data at each step in the guest journey before worrying about which AI tools to buy.
How to actually get started
First 90 days: Get the basics right
Pick one person to own this with real authority. Engage leadership to align on the business objectives. Set up a dashboard tracking AI projects against business results. Clean up your data, focusing on matching guest identities across systems.
Months 3-6: Connect your systems
Make your PMS, payments, booking engine, and customer data work in real-time. Automate mindless tasks: reconciliations, reports, data entry. The study found 28% of hotels expect innovation in Robotic Process Automation for good reason; these tasks eat staff time without adding guest value.
Months 6-12: Start making money
Put AI in front of guests. 54% plan AI-driven upselling in the next 12-24 months. 49% are targeting personalised bookings. 40% are adding chatbots. Bundle these features together a chatbot that has access to guest history, books directly, suggests upgrades, works in multiple languages and has clear visibility on availability, rates and occupancy becomes a revenue engine.
Build what guests actually want
For chatbots, guests prioritise booking help (85% say it's essential), multilingual support (82%), and direct booking capability (71%). Build these first.
For booking engines, personalisation jumped to the top with 59% of hotels planning implementation, a 14-point increase year over year. Real-time chatbot assistance hit 43%, up 13 points.
Revenue managers are cautiously optimistic, rating their comfort with AI pricing at 6.4 out of 10. They're open to AI but need evidence it works without losing control. Hotels see AI helping most with cutting manual workload (63%), identifying guest behaviour patterns (62%), and better forecasting (61%).
You have about 18 months
With 89% of chains planning more AI and chatbot adoption heading past 70%, hotels moving fast have maybe 12-18 months to build real advantages. After that, AI capabilities become table stakes.
The hotels making real money from AI stopped doing pilots and started building platforms. They unified their tech stack, wrote clear governance, and measure everything through dashboards tracking task reduction, revenue growth, and customer experience improvements.
The path from hype to ROI isn't mysterious. It's methodical. Establish objectives that support business objectives. Set up AI governance, unify your technology stack, deploy proven use cases systematically, and measure everything rigorously.
Hotels that execute this plan won't just implement AI, they'll transform how they operate in ways that keep compounding value over time.
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