We are promised that AI will “transform” our operations overnight. AI is definitely transforming, but I'm not sure about it “overnight.” The reality uncovered by h2c's 2025 Global AI and Automation Survey is far more practical. Most hotel groups remain in disarray automation and A.I.and this disruption is slowing returns, hindering adoption, and slowing down the efficiency gains that can be achieved today.
To make AI a trusted and valuable partner, it is important to understand one fact: true efficiency does not start with intelligence. It starts with automation.
Industry issue: Hotels trust AI more than they use it
h2c's research highlights a surprising 1.9 percentage point gap between trust and confidence. AI scores 6.6/10 for hotel reliability, but only 4.7/10 for actual reliability.
This gap is not due to lack of interest. That's because of a lack of clarity.
- 78% of hotel chains already use some form of AI (mostly chatbots)
- But 70% say integration challenges are hindering adoption
- 62% cited lack of AI expertise as the biggest barrier, twice as many as concerns about staff resistance
- And 42% don’t track the ROI of their AI initiatives at all
This represents a simple diagram. Hotels want the benefits of automation and AI, but don't have the operational infrastructure needed to ensure intelligent systems work.
And automation is the foundation of this.
Automation ≠ AI: The difference hotels need to understand
Workflow automation
It is structured, rule-based, predictable and reproducible. works with your system As is.
An example of an active RobosizeME deployment is:
- OTA payment posting
- Billing to travel partners
- Profile quality check
- Daily cash register adjustment
These are high-volume, low-profit tasks that hotels perform every day. Yet, automation allows them to run with over 99% reliability. Automation doesn't “think”. It happens every time.
AI (LLM, agents, predictive systems)
AI, on the other hand, interprets data, generates text, predicts outcomes, and recommends actions. AI is powerful, but:
- Prone to hallucinations (confidently conveys false information)
- Shaped by cognitive biases in the data being trained on
- Relies on data quality, overwhelmingly cited by hotels as an issue (41% cite data quality/accessibility issues)
Let's look at some definitions.
LLM (Large-Scale Language Model)
A machine learning model trained on a large text dataset to predict the next word in a sequence. Great for conversations and content, but not for financial workflows or performing precise operational tasks.
hallucination
When the AI confidently produces inaccurate or fabricated outputs due to a lack of appropriate data or because the task exceeds the limits of inference.
cognitive bias
AI reflects the biases present in the training data, resulting in skewed decisions and unbalanced recommendations.
(For more information about LLM, please visit: https://www.digitalnative.tech/p/llms-for-dummies)
When hotel teams misunderstand the difference between automation and AI, they expect AI to perform automation tasks and vice versa. That's where the failure begins.
The data is clear: Automation delivers today, AI powers tomorrow.
According to h2c research:
- 69% of hotel groups want technology to reduce repetitive tasks. This is the core strength of automation.
- 63% want reporting automation in revenue management – one of the most common use cases for RobosizeME
- 70% cite “ease of integration” as a top investment criterion – automation works even with traditional PMSs and fragmented stacks
- Meanwhile, only 11% currently use AI agents and only 1% say AI is central to their business model.
This highlights an important truth. That means hotels can't scale AI until their processes are automated, stable, and measurable.
Because if automation doesn’t collect data consistently, AI won’t be able to clean it up. AI cannot predict accurately if the underlying reports are manually combined. Additionally, AI cannot personalize the guest journey if half of the customer profiles are duplicated.
Automation then lays the foundation first.
A Practical Framework for Hotel Leaders: An Automation-First Roadmap
1. Start with low-complexity, high-repetition tasks
These provide immediate ROI and build trust in your organization. This is also confirmed by industry leaders: simple, repetitive tasks result in the fastest deployments.
2. Track operational KPIs long before implementing AI
Automation inherently provides measurable output.
- success rate
- processing time
- Reduce errors
- time saving
Without these baselines, it is impossible to measure the ROI of AI.
3. Use automation to correct data before using AI to interpret it
Given that 41% of chains face data quality issues, automation becomes a necessary cleaning and hardening layer.
4. Deploy AI only when inference is required rather than repetition.
Examples where AI is applied addnot replaced, value:
- Demand forecast
- Content generation
- Email triage
- personalized messaging
- Guest sentiment analysis
Conclusion Hotel Leaders Should Hear
There are no AI issues in the hotel. They have an automation gap.
h2c research confirms that while trust in AI is growing, it is not operationally ready. The fastest path to efficiency, guest satisfaction, and scalable innovation is:
👉 Start by automating your workflow.
👉 Improve data quality.
👉 Next, layer in AI that can truly enhance decision-making.
At RobosizeME, we see this every day across thousands of live workflow automations. Once the fundamentals are automated with 99% reliability, AI is not only safe to deploy, but exponentially more valuable.
If your hotel group wants to prepare for the next decade of hospitality technology, this is the right order.
📩 Ready to identify your first workflow automation candidate?
Contact us to schedule a free discovery session with a hotel automation expert.
About RobosizeME
RobosizeME is a leading provider of AI-enabled process automation solutions for the global hotel industry. By combining digital workers with deep expertise in hotel API, RPA, IPA, and AI development, RobosizeME helps hospitality groups streamline critical workflows in reservations, finance, delivery, and front office to operate faster, more accurately, and more efficiently. Backed by advanced security certifications (ISO 27001, GDPR, PCI-DSS), RobosizeME's industry-specific automation solutions ensure the highest level of data protection, compliance, and data sovereignty. Trusted by prominent hotel companies such as Design Hotels, Dorchester Collection, GHA, Kempinski, Loews Hotels, Louvre Hotel Group, and Radisson Hotel Group, RobosizeME continues to set the standard for large-scale, secure and professional automation in the hospitality sector. For more information, please visit www.robosize.me.
Zuzana Jakesova
marketing consultant
Robo Size ME
